Sample records for identifying cancer genes

  1. Identifying Cancer Driver Genes Using Replication-Incompetent Retroviral Vectors

    PubMed Central

    Bii, Victor M.; Trobridge, Grant D.

    2016-01-01

    Identifying novel genes that drive tumor metastasis and drug resistance has significant potential to improve patient outcomes. High-throughput sequencing approaches have identified cancer genes, but distinguishing driver genes from passengers remains challenging. Insertional mutagenesis screens using replication-incompetent retroviral vectors have emerged as a powerful tool to identify cancer genes. Unlike replicating retroviruses and transposons, replication-incompetent retroviral vectors lack additional mutagenesis events that can complicate the identification of driver mutations from passenger mutations. They can also be used for almost any human cancer due to the broad tropism of the vectors. Replication-incompetent retroviral vectors have the ability to dysregulate nearby cancer genes via several mechanisms including enhancer-mediated activation of gene promoters. The integrated provirus acts as a unique molecular tag for nearby candidate driver genes which can be rapidly identified using well established methods that utilize next generation sequencing and bioinformatics programs. Recently, retroviral vector screens have been used to efficiently identify candidate driver genes in prostate, breast, liver and pancreatic cancers. Validated driver genes can be potential therapeutic targets and biomarkers. In this review, we describe the emergence of retroviral insertional mutagenesis screens using replication-incompetent retroviral vectors as a novel tool to identify cancer driver genes in different cancer types. PMID:27792127

  2. Gene Signature in Sessile Serrated Polyps Identifies Colon Cancer Subtype

    PubMed Central

    Kanth, Priyanka; Bronner, Mary P.; Boucher, Kenneth M.; Burt, Randall W.; Neklason, Deborah W.; Hagedorn, Curt H.; Delker, Don A.

    2016-01-01

    Sessile serrated colon adenoma/polyps (SSA/Ps) are found during routine screening colonoscopy and may account for 20–30% of colon cancers. However, differentiating SSA/Ps from hyperplastic polyps (HP) with little risk of cancer is challenging and complementary molecular markers are needed. Additionally, the molecular mechanisms of colon cancer development from SSA/Ps are poorly understood. RNA sequencing was performed on 21 SSA/Ps, 10 HPs, 10 adenomas, 21 uninvolved colon and 20 control colon specimens. Differential expression and leave-one-out cross validation methods were used to define a unique gene signature of SSA/Ps. Our SSA/P gene signature was evaluated in colon cancer RNA-Seq data from The Cancer Genome Atlas (TCGA) to identify a subtype of colon cancers that may develop from SSA/Ps. A total of 1422 differentially expressed genes were found in SSA/Ps relative to controls. Serrated polyposis syndrome (n=12) and sporadic SSA/Ps (n=9) exhibited almost complete (96%) gene overlap. A 51-gene panel in SSA/P showed similar expression in a subset of TCGA colon cancers with high microsatellite instability (MSI-H). A smaller seven-gene panel showed high sensitivity and specificity in identifying BRAF mutant, CpG island methylator phenotype high (CIMP-H) and MLH1 silenced colon cancers. We describe a unique gene signature in SSA/Ps that identifies a subset of colon cancers likely to develop through the serrated pathway. These gene panels may be utilized for improved differentiation of SSA/Ps from HPs and provide insights into novel molecular pathways altered in colon cancer arising from the serrated pathway. PMID:27026680

  3. A recellularized human colon model identifies cancer driver genes

    PubMed Central

    Chen, Huanhuan Joyce; Wei, Zhubo; Sun, Jian; Bhattacharya, Asmita; Savage, David J; Serda, Rita; Mackeyev, Yuri; Curley, Steven A.; Bu, Pengcheng; Wang, Lihua; Chen, Shuibing; Cohen-Gould, Leona; Huang, Emina; Shen, Xiling; Lipkin, Steven M.; Copeland, Neal G.; Jenkins, Nancy A.; Shuler, Michael L.

    2016-01-01

    Refined cancer models are needed to bridge the gap between cell-line, animal and clinical research. Here we describe the engineering of an organotypic colon cancer model by recellularization of a native human matrix that contains cell-populated mucosa and an intact muscularis mucosa layer. This ex vivo system recapitulates the pathophysiological progression from APC-mutant neoplasia to submucosal invasive tumor. We used it to perform a Sleeping Beauty transposon mutagenesis screen to identify genes that cooperate with mutant APC in driving invasive neoplasia. 38 candidate invasion driver genes were identified, 17 of which have been previously implicated in colorectal cancer progression, including TCF7L2, TWIST2, MSH2, DCC and EPHB1/2. Six invasion driver genes that to our knowledge have not been previously described were validated in vitro using cell proliferation, migration and invasion assays, and ex vivo using recellularized human colon. These results demonstrate the utility of our organoid model for studying cancer biology. PMID:27398792

  4. ICan: an integrated co-alteration network to identify ovarian cancer-related genes.

    PubMed

    Zhou, Yuanshuai; Liu, Yongjing; Li, Kening; Zhang, Rui; Qiu, Fujun; Zhao, Ning; Xu, Yan

    2015-01-01

    Over the last decade, an increasing number of integrative studies on cancer-related genes have been published. Integrative analyses aim to overcome the limitation of a single data type, and provide a more complete view of carcinogenesis. The vast majority of these studies used sample-matched data of gene expression and copy number to investigate the impact of copy number alteration on gene expression, and to predict and prioritize candidate oncogenes and tumor suppressor genes. However, correlations between genes were neglected in these studies. Our work aimed to evaluate the co-alteration of copy number, methylation and expression, allowing us to identify cancer-related genes and essential functional modules in cancer. We built the Integrated Co-alteration network (ICan) based on multi-omics data, and analyzed the network to uncover cancer-related genes. After comparison with random networks, we identified 155 ovarian cancer-related genes, including well-known (TP53, BRCA1, RB1 and PTEN) and also novel cancer-related genes, such as PDPN and EphA2. We compared the results with a conventional method: CNAmet, and obtained a significantly better area under the curve value (ICan: 0.8179, CNAmet: 0.5183). In this paper, we describe a framework to find cancer-related genes based on an Integrated Co-alteration network. Our results proved that ICan could precisely identify candidate cancer genes and provide increased mechanistic understanding of carcinogenesis. This work suggested a new research direction for biological network analyses involving multi-omics data.

  5. ICan: An Integrated Co-Alteration Network to Identify Ovarian Cancer-Related Genes

    PubMed Central

    Zhou, Yuanshuai; Liu, Yongjing; Li, Kening; Zhang, Rui; Qiu, Fujun; Zhao, Ning; Xu, Yan

    2015-01-01

    Background Over the last decade, an increasing number of integrative studies on cancer-related genes have been published. Integrative analyses aim to overcome the limitation of a single data type, and provide a more complete view of carcinogenesis. The vast majority of these studies used sample-matched data of gene expression and copy number to investigate the impact of copy number alteration on gene expression, and to predict and prioritize candidate oncogenes and tumor suppressor genes. However, correlations between genes were neglected in these studies. Our work aimed to evaluate the co-alteration of copy number, methylation and expression, allowing us to identify cancer-related genes and essential functional modules in cancer. Results We built the Integrated Co-alteration network (ICan) based on multi-omics data, and analyzed the network to uncover cancer-related genes. After comparison with random networks, we identified 155 ovarian cancer-related genes, including well-known (TP53, BRCA1, RB1 and PTEN) and also novel cancer-related genes, such as PDPN and EphA2. We compared the results with a conventional method: CNAmet, and obtained a significantly better area under the curve value (ICan: 0.8179, CNAmet: 0.5183). Conclusion In this paper, we describe a framework to find cancer-related genes based on an Integrated Co-alteration network. Our results proved that ICan could precisely identify candidate cancer genes and provide increased mechanistic understanding of carcinogenesis. This work suggested a new research direction for biological network analyses involving multi-omics data. PMID:25803614

  6. A Functional Genomics Approach to Identify Novel Breast Cancer Gene Targets in Yeast

    DTIC Science & Technology

    2004-05-01

    AD Award Number: DAMD17-03-1-0232 TITLE: A Functional Genomics Approach to Identify Novel Breast Cancer Gene Targets in Yeast PRINCIPAL INVESTIGATOR...Approach to Identify Novel Breast DAMD17-03-1-0232 Cancer Gene Targets in Yeast 6. A UTHOR(S) Craig Bennett, Ph.D. 7. PERFORMING ORGANIZA TION NAME(S...Unlimited 13. ABSTRACT (Maximum 200 Words) We are using the yeast Saccharomyces cerevisiae to identify new cancer gene targets that interact with the

  7. A Novel Yeast Genomics Method for Identifying New Breast Cancer Susceptibility Genes

    DTIC Science & Technology

    2007-05-01

    find new candidate genes for breast cancer susceptibility in women and identifying these human genes can further improve monitoring and treatment...breast cancer susceptibility genes in humans that are currently unknown and not deducible from current methodologies. It is a fundamental...template to faithfully repair the broken strand. In human cancer it is loss of HR, rather than NHEJ, that is more important in increasing cancer

  8. MMTV insertional mutagenesis identifies genes, gene families and pathways involved in mammary cancer.

    PubMed

    Theodorou, Vassiliki; Kimm, Melanie A; Boer, Mandy; Wessels, Lodewyk; Theelen, Wendy; Jonkers, Jos; Hilkens, John

    2007-06-01

    We performed a high-throughput retroviral insertional mutagenesis screen in mouse mammary tumor virus (MMTV)-induced mammary tumors and identified 33 common insertion sites, of which 17 genes were previously not known to be associated with mammary cancer and 13 had not previously been linked to cancer in general. Although members of the Wnt and fibroblast growth factors (Fgf) families were frequently tagged, our exhaustive screening for MMTV insertion sites uncovered a new repertoire of candidate breast cancer oncogenes. We validated one of these genes, Rspo3, as an oncogene by overexpression in a p53-deficient mammary epithelial cell line. The human orthologs of the candidate oncogenes were frequently deregulated in human breast cancers and associated with several tumor parameters. Computational analysis of all MMTV-tagged genes uncovered specific gene families not previously associated with cancer and showed a significant overrepresentation of protein domains and signaling pathways mainly associated with development and growth factor signaling. Comparison of all tagged genes in MMTV and Moloney murine leukemia virus-induced malignancies showed that both viruses target mostly different genes that act predominantly in distinct pathways.

  9. Lentiviral vector-based insertional mutagenesis identifies genes associated with liver cancer

    PubMed Central

    Ranzani, Marco; Cesana, Daniela; Bartholomae, Cynthia C.; Sanvito, Francesca; Pala, Mauro; Benedicenti, Fabrizio; Gallina, Pierangela; Sergi, Lucia Sergi; Merella, Stefania; Bulfone, Alessandro; Doglioni, Claudio; von Kalle, Christof; Kim, Yoon Jun; Schmidt, Manfred; Tonon, Giovanni; Naldini, Luigi; Montini, Eugenio

    2013-01-01

    Transposons and γ-retroviruses have been efficiently used as insertional mutagens in different tissues to identify molecular culprits of cancer. However, these systems are characterized by recurring integrations that accumulate in tumor cells, hampering the identification of early cancer-driving events amongst bystander and progression-related events. We developed an insertional mutagenesis platform based on lentiviral vectors (LVV) by which we could efficiently induce hepatocellular carcinoma (HCC) in 3 different mouse models. By virtue of LVV’s replication-deficient nature and broad genome-wide integration pattern, LVV-based insertional mutagenesis allowed identification of 4 new liver cancer genes from a limited number of integrations. We validated the oncogenic potential of all the identified genes in vivo, with different levels of penetrance. Our newly identified cancer genes are likely to play a role in human disease, since they are upregulated and/or amplified/deleted in human HCCs and can predict clinical outcome of patients. PMID:23314173

  10. Gene expression meta-analysis identifies chromosomal regions and candidate genes involved in breast cancer metastasis.

    PubMed

    Thomassen, Mads; Tan, Qihua; Kruse, Torben A

    2009-01-01

    Breast cancer cells exhibit complex karyotypic alterations causing deregulation of numerous genes. Some of these genes are probably causal for cancer formation and local growth whereas others are causal for the various steps of metastasis. In a fraction of tumors deregulation of the same genes might be caused by epigenetic modulations, point mutations or the influence of other genes. We have investigated the relation of gene expression and chromosomal position, using eight datasets including more than 1200 breast tumors, to identify chromosomal regions and candidate genes possibly causal for breast cancer metastasis. By use of "Gene Set Enrichment Analysis" we have ranked chromosomal regions according to their relation to metastasis. Overrepresentation analysis identified regions with increased expression for chromosome 1q41-42, 8q24, 12q14, 16q22, 16q24, 17q12-21.2, 17q21-23, 17q25, 20q11, and 20q13 among metastasizing tumors and reduced gene expression at 1p31-21, 8p22-21, and 14q24. By analysis of genes with extremely imbalanced expression in these regions we identified DIRAS3 at 1p31, PSD3, LPL, EPHX2 at 8p21-22, and FOS at 14q24 as candidate metastasis suppressor genes. Potential metastasis promoting genes includes RECQL4 at 8q24, PRMT7 at 16q22, GINS2 at 16q24, and AURKA at 20q13.

  11. Identifying novel genes and chemicals related to nasopharyngeal cancer in a heterogeneous network.

    PubMed

    Li, Zhandong; An, Lifeng; Li, Hao; Wang, ShaoPeng; Zhou, You; Yuan, Fei; Li, Lin

    2016-05-05

    Nasopharyngeal cancer or nasopharyngeal carcinoma (NPC) is the most common cancer originating in the nasopharynx. The factors that induce nasopharyngeal cancer are still not clear. Additional information about the chemicals or genes related to nasopharyngeal cancer will promote a better understanding of the pathogenesis of this cancer and the factors that induce it. Thus, a computational method NPC-RGCP was proposed in this study to identify the possible relevant chemicals and genes based on the presently known chemicals and genes related to nasopharyngeal cancer. To extensively utilize the functional associations between proteins and chemicals, a heterogeneous network was constructed based on interactions of proteins and chemicals. The NPC-RGCP included two stages: the searching stage and the screening stage. The former stage is for finding new possible genes and chemicals in the heterogeneous network, while the latter stage is for screening and removing false discoveries and selecting the core genes and chemicals. As a result, five putative genes, CXCR3, IRF1, CDK1, GSTP1, and CDH2, and seven putative chemicals, iron, propionic acid, dimethyl sulfoxide, isopropanol, erythrose 4-phosphate, β-D-Fructose 6-phosphate, and flavin adenine dinucleotide, were identified by NPC-RGCP. Extensive analyses provided confirmation that the putative genes and chemicals have significant associations with nasopharyngeal cancer.

  12. Identifying novel genes and chemicals related to nasopharyngeal cancer in a heterogeneous network

    PubMed Central

    Li, Zhandong; An, Lifeng; Li, Hao; Wang, ShaoPeng; Zhou, You; Yuan, Fei; Li, Lin

    2016-01-01

    Nasopharyngeal cancer or nasopharyngeal carcinoma (NPC) is the most common cancer originating in the nasopharynx. The factors that induce nasopharyngeal cancer are still not clear. Additional information about the chemicals or genes related to nasopharyngeal cancer will promote a better understanding of the pathogenesis of this cancer and the factors that induce it. Thus, a computational method NPC-RGCP was proposed in this study to identify the possible relevant chemicals and genes based on the presently known chemicals and genes related to nasopharyngeal cancer. To extensively utilize the functional associations between proteins and chemicals, a heterogeneous network was constructed based on interactions of proteins and chemicals. The NPC-RGCP included two stages: the searching stage and the screening stage. The former stage is for finding new possible genes and chemicals in the heterogeneous network, while the latter stage is for screening and removing false discoveries and selecting the core genes and chemicals. As a result, five putative genes, CXCR3, IRF1, CDK1, GSTP1, and CDH2, and seven putative chemicals, iron, propionic acid, dimethyl sulfoxide, isopropanol, erythrose 4-phosphate, β-D-Fructose 6-phosphate, and flavin adenine dinucleotide, were identified by NPC-RGCP. Extensive analyses provided confirmation that the putative genes and chemicals have significant associations with nasopharyngeal cancer. PMID:27149165

  13. Similarity of markers identified from cancer gene expression studies: observations from GEO.

    PubMed

    Shi, Xingjie; Shen, Shihao; Liu, Jin; Huang, Jian; Zhou, Yong; Ma, Shuangge

    2014-09-01

    Gene expression profiling has been extensively conducted in cancer research. The analysis of multiple independent cancer gene expression datasets may provide additional information and complement single-dataset analysis. In this study, we conduct multi-dataset analysis and are interested in evaluating the similarity of cancer-associated genes identified from different datasets. The first objective of this study is to briefly review some statistical methods that can be used for such evaluation. Both marginal analysis and joint analysis methods are reviewed. The second objective is to apply those methods to 26 Gene Expression Omnibus (GEO) datasets on five types of cancers. Our analysis suggests that for the same cancer, the marker identification results may vary significantly across datasets, and different datasets share few common genes. In addition, datasets on different cancers share few common genes. The shared genetic basis of datasets on the same or different cancers, which has been suggested in the literature, is not observed in the analysis of GEO data. © The Author 2013. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

  14. Identifying candidate driver genes by integrative ovarian cancer genomics data

    NASA Astrophysics Data System (ADS)

    Lu, Xinguo; Lu, Jibo

    2017-08-01

    Integrative analysis of molecular mechanics underlying cancer can distinguish interactions that cannot be revealed based on one kind of data for the appropriate diagnosis and treatment of cancer patients. Tumor samples exhibit heterogeneity in omics data, such as somatic mutations, Copy Number Variations CNVs), gene expression profiles and so on. In this paper we combined gene co-expression modules and mutation modulators separately in tumor patients to obtain the candidate driver genes for resistant and sensitive tumor from the heterogeneous data. The final list of modulators identified are well known in biological processes associated with ovarian cancer, such as CCL17, CACTIN, CCL16, CCL22, APOB, KDF1, CCL11, HNF1B, LRG1, MED1 and so on, which can help to facilitate the discovery of biomarkers, molecular diagnostics, and drug discovery.

  15. Sleeping Beauty transposon mutagenesis identifies genes that cooperate with mutant Smad4 in gastric cancer development

    PubMed Central

    Takeda, Haruna; Rust, Alistair G.; Ward, Jerrold M.; Yew, Christopher Chin Kuan; Jenkins, Nancy A.; Copeland, Neal G.

    2016-01-01

    Mutations in SMAD4 predispose to the development of gastrointestinal cancer, which is the third leading cause of cancer-related deaths. To identify genes driving gastric cancer (GC) development, we performed a Sleeping Beauty (SB) transposon mutagenesis screen in the stomach of Smad4+/− mutant mice. This screen identified 59 candidate GC trunk drivers and a much larger number of candidate GC progression genes. Strikingly, 22 SB-identified trunk drivers are known or candidate cancer genes, whereas four SB-identified trunk drivers, including PTEN, SMAD4, RNF43, and NF1, are known human GC trunk drivers. Similar to human GC, pathway analyses identified WNT, TGF-β, and PI3K-PTEN signaling, ubiquitin-mediated proteolysis, adherens junctions, and RNA degradation in addition to genes involved in chromatin modification and organization as highly deregulated pathways in GC. Comparative oncogenomic filtering of the complete list of SB-identified genes showed that they are highly enriched for genes mutated in human GC and identified many candidate human GC genes. Finally, by comparing our complete list of SB-identified genes against the list of mutated genes identified in five large-scale human GC sequencing studies, we identified LDL receptor-related protein 1B (LRP1B) as a previously unidentified human candidate GC tumor suppressor gene. In LRP1B, 129 mutations were found in 462 human GC samples sequenced, and LRP1B is one of the top 10 most deleted genes identified in a panel of 3,312 human cancers. SB mutagenesis has, thus, helped to catalog the cooperative molecular mechanisms driving SMAD4-induced GC growth and discover genes with potential clinical importance in human GC. PMID:27006499

  16. Sleeping Beauty transposon mutagenesis identifies genes that cooperate with mutant Smad4 in gastric cancer development.

    PubMed

    Takeda, Haruna; Rust, Alistair G; Ward, Jerrold M; Yew, Christopher Chin Kuan; Jenkins, Nancy A; Copeland, Neal G

    2016-04-05

    Mutations in SMAD4 predispose to the development of gastrointestinal cancer, which is the third leading cause of cancer-related deaths. To identify genes driving gastric cancer (GC) development, we performed a Sleeping Beauty (SB) transposon mutagenesis screen in the stomach of Smad4(+/-) mutant mice. This screen identified 59 candidate GC trunk drivers and a much larger number of candidate GC progression genes. Strikingly, 22 SB-identified trunk drivers are known or candidate cancer genes, whereas four SB-identified trunk drivers, including PTEN, SMAD4, RNF43, and NF1, are known human GC trunk drivers. Similar to human GC, pathway analyses identified WNT, TGF-β, and PI3K-PTEN signaling, ubiquitin-mediated proteolysis, adherens junctions, and RNA degradation in addition to genes involved in chromatin modification and organization as highly deregulated pathways in GC. Comparative oncogenomic filtering of the complete list of SB-identified genes showed that they are highly enriched for genes mutated in human GC and identified many candidate human GC genes. Finally, by comparing our complete list of SB-identified genes against the list of mutated genes identified in five large-scale human GC sequencing studies, we identified LDL receptor-related protein 1B (LRP1B) as a previously unidentified human candidate GC tumor suppressor gene. In LRP1B, 129 mutations were found in 462 human GC samples sequenced, and LRP1B is one of the top 10 most deleted genes identified in a panel of 3,312 human cancers. SB mutagenesis has, thus, helped to catalog the cooperative molecular mechanisms driving SMAD4-induced GC growth and discover genes with potential clinical importance in human GC.

  17. An Optimal Mean Based Block Robust Feature Extraction Method to Identify Colorectal Cancer Genes with Integrated Data.

    PubMed

    Liu, Jian; Cheng, Yuhu; Wang, Xuesong; Zhang, Lin; Liu, Hui

    2017-08-17

    It is urgent to diagnose colorectal cancer in the early stage. Some feature genes which are important to colorectal cancer development have been identified. However, for the early stage of colorectal cancer, less is known about the identity of specific cancer genes that are associated with advanced clinical stage. In this paper, we conducted a feature extraction method named Optimal Mean based Block Robust Feature Extraction method (OMBRFE) to identify feature genes associated with advanced colorectal cancer in clinical stage by using the integrated colorectal cancer data. Firstly, based on the optimal mean and L 2,1 -norm, a novel feature extraction method called Optimal Mean based Robust Feature Extraction method (OMRFE) is proposed to identify feature genes. Then the OMBRFE method which introduces the block ideology into OMRFE method is put forward to process the colorectal cancer integrated data which includes multiple genomic data: copy number alterations, somatic mutations, methylation expression alteration, as well as gene expression changes. Experimental results demonstrate that the OMBRFE is more effective than previous methods in identifying the feature genes. Moreover, genes identified by OMBRFE are verified to be closely associated with advanced colorectal cancer in clinical stage.

  18. Identifying differentially expressed genes in cancer patients using a non-parameter Ising model.

    PubMed

    Li, Xumeng; Feltus, Frank A; Sun, Xiaoqian; Wang, James Z; Luo, Feng

    2011-10-01

    Identification of genes and pathways involved in diseases and physiological conditions is a major task in systems biology. In this study, we developed a novel non-parameter Ising model to integrate protein-protein interaction network and microarray data for identifying differentially expressed (DE) genes. We also proposed a simulated annealing algorithm to find the optimal configuration of the Ising model. The Ising model was applied to two breast cancer microarray data sets. The results showed that more cancer-related DE sub-networks and genes were identified by the Ising model than those by the Markov random field model. Furthermore, cross-validation experiments showed that DE genes identified by Ising model can improve classification performance compared with DE genes identified by Markov random field model. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  19. Systematic analysis of mutation distribution in three dimensional protein structures identifies cancer driver genes.

    PubMed

    Fujimoto, Akihiro; Okada, Yukinori; Boroevich, Keith A; Tsunoda, Tatsuhiko; Taniguchi, Hiroaki; Nakagawa, Hidewaki

    2016-05-26

    Protein tertiary structure determines molecular function, interaction, and stability of the protein, therefore distribution of mutation in the tertiary structure can facilitate the identification of new driver genes in cancer. To analyze mutation distribution in protein tertiary structures, we applied a novel three dimensional permutation test to the mutation positions. We analyzed somatic mutation datasets of 21 types of cancers obtained from exome sequencing conducted by the TCGA project. Of the 3,622 genes that had ≥3 mutations in the regions with tertiary structure data, 106 genes showed significant skew in mutation distribution. Known tumor suppressors and oncogenes were significantly enriched in these identified cancer gene sets. Physical distances between mutations in known oncogenes were significantly smaller than those of tumor suppressors. Twenty-three genes were detected in multiple cancers. Candidate genes with significant skew of the 3D mutation distribution included kinases (MAPK1, EPHA5, ERBB3, and ERBB4), an apoptosis related gene (APP), an RNA splicing factor (SF1), a miRNA processing factor (DICER1), an E3 ubiquitin ligase (CUL1) and transcription factors (KLF5 and EEF1B2). Our study suggests that systematic analysis of mutation distribution in the tertiary protein structure can help identify cancer driver genes.

  20. Systematic analysis of mutation distribution in three dimensional protein structures identifies cancer driver genes

    PubMed Central

    Fujimoto, Akihiro; Okada, Yukinori; Boroevich, Keith A.; Tsunoda, Tatsuhiko; Taniguchi, Hiroaki; Nakagawa, Hidewaki

    2016-01-01

    Protein tertiary structure determines molecular function, interaction, and stability of the protein, therefore distribution of mutation in the tertiary structure can facilitate the identification of new driver genes in cancer. To analyze mutation distribution in protein tertiary structures, we applied a novel three dimensional permutation test to the mutation positions. We analyzed somatic mutation datasets of 21 types of cancers obtained from exome sequencing conducted by the TCGA project. Of the 3,622 genes that had ≥3 mutations in the regions with tertiary structure data, 106 genes showed significant skew in mutation distribution. Known tumor suppressors and oncogenes were significantly enriched in these identified cancer gene sets. Physical distances between mutations in known oncogenes were significantly smaller than those of tumor suppressors. Twenty-three genes were detected in multiple cancers. Candidate genes with significant skew of the 3D mutation distribution included kinases (MAPK1, EPHA5, ERBB3, and ERBB4), an apoptosis related gene (APP), an RNA splicing factor (SF1), a miRNA processing factor (DICER1), an E3 ubiquitin ligase (CUL1) and transcription factors (KLF5 and EEF1B2). Our study suggests that systematic analysis of mutation distribution in the tertiary protein structure can help identify cancer driver genes. PMID:27225414

  1. MADGiC: a model-based approach for identifying driver genes in cancer

    PubMed Central

    Korthauer, Keegan D.; Kendziorski, Christina

    2015-01-01

    Motivation: Identifying and prioritizing somatic mutations is an important and challenging area of cancer research that can provide new insights into gene function as well as new targets for drug development. Most methods for prioritizing mutations rely primarily on frequency-based criteria, where a gene is identified as having a driver mutation if it is altered in significantly more samples than expected according to a background model. Although useful, frequency-based methods are limited in that all mutations are treated equally. It is well known, however, that some mutations have no functional consequence, while others may have a major deleterious impact. The spatial pattern of mutations within a gene provides further insight into their functional consequence. Properly accounting for these factors improves both the power and accuracy of inference. Also important is an accurate background model. Results: Here, we develop a Model-based Approach for identifying Driver Genes in Cancer (termed MADGiC) that incorporates both frequency and functional impact criteria and accommodates a number of factors to improve the background model. Simulation studies demonstrate advantages of the approach, including a substantial increase in power over competing methods. Further advantages are illustrated in an analysis of ovarian and lung cancer data from The Cancer Genome Atlas (TCGA) project. Availability and implementation: R code to implement this method is available at http://www.biostat.wisc.edu/ kendzior/MADGiC/. Contact: kendzior@biostat.wisc.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:25573922

  2. A transcriptome-wide association study of 229,000 women identifies new candidate susceptibility genes for breast cancer.

    PubMed

    Wu, Lang; Shi, Wei; Long, Jirong; Guo, Xingyi; Michailidou, Kyriaki; Beesley, Jonathan; Bolla, Manjeet K; Shu, Xiao-Ou; Lu, Yingchang; Cai, Qiuyin; Al-Ejeh, Fares; Rozali, Esdy; Wang, Qin; Dennis, Joe; Li, Bingshan; Zeng, Chenjie; Feng, Helian; Gusev, Alexander; Barfield, Richard T; Andrulis, Irene L; Anton-Culver, Hoda; Arndt, Volker; Aronson, Kristan J; Auer, Paul L; Barrdahl, Myrto; Baynes, Caroline; Beckmann, Matthias W; Benitez, Javier; Bermisheva, Marina; Blomqvist, Carl; Bogdanova, Natalia V; Bojesen, Stig E; Brauch, Hiltrud; Brenner, Hermann; Brinton, Louise; Broberg, Per; Brucker, Sara Y; Burwinkel, Barbara; Caldés, Trinidad; Canzian, Federico; Carter, Brian D; Castelao, J Esteban; Chang-Claude, Jenny; Chen, Xiaoqing; Cheng, Ting-Yuan David; Christiansen, Hans; Clarke, Christine L; Collée, Margriet; Cornelissen, Sten; Couch, Fergus J; Cox, David; Cox, Angela; Cross, Simon S; Cunningham, Julie M; Czene, Kamila; Daly, Mary B; Devilee, Peter; Doheny, Kimberly F; Dörk, Thilo; Dos-Santos-Silva, Isabel; Dumont, Martine; Dwek, Miriam; Eccles, Diana M; Eilber, Ursula; Eliassen, A Heather; Engel, Christoph; Eriksson, Mikael; Fachal, Laura; Fasching, Peter A; Figueroa, Jonine; Flesch-Janys, Dieter; Fletcher, Olivia; Flyger, Henrik; Fritschi, Lin; Gabrielson, Marike; Gago-Dominguez, Manuela; Gapstur, Susan M; García-Closas, Montserrat; Gaudet, Mia M; Ghoussaini, Maya; Giles, Graham G; Goldberg, Mark S; Goldgar, David E; González-Neira, Anna; Guénel, Pascal; Hahnen, Eric; Haiman, Christopher A; Håkansson, Niclas; Hall, Per; Hallberg, Emily; Hamann, Ute; Harrington, Patricia; Hein, Alexander; Hicks, Belynda; Hillemanns, Peter; Hollestelle, Antoinette; Hoover, Robert N; Hopper, John L; Huang, Guanmengqian; Humphreys, Keith; Hunter, David J; Jakubowska, Anna; Janni, Wolfgang; John, Esther M; Johnson, Nichola; Jones, Kristine; Jones, Michael E; Jung, Audrey; Kaaks, Rudolf; Kerin, Michael J; Khusnutdinova, Elza; Kosma, Veli-Matti; Kristensen, Vessela N; Lambrechts, Diether; Le Marchand, Loic; Li, Jingmei; Lindström, Sara; Lissowska, Jolanta; Lo, Wing-Yee; Loibl, Sibylle; Lubinski, Jan; Luccarini, Craig; Lux, Michael P; MacInnis, Robert J; Maishman, Tom; Kostovska, Ivana Maleva; Mannermaa, Arto; Manson, JoAnn E; Margolin, Sara; Mavroudis, Dimitrios; Meijers-Heijboer, Hanne; Meindl, Alfons; Menon, Usha; Meyer, Jeffery; Mulligan, Anna Marie; Neuhausen, Susan L; Nevanlinna, Heli; Neven, Patrick; Nielsen, Sune F; Nordestgaard, Børge G; Olopade, Olufunmilayo I; Olson, Janet E; Olsson, Håkan; Peterlongo, Paolo; Peto, Julian; Plaseska-Karanfilska, Dijana; Prentice, Ross; Presneau, Nadege; Pylkäs, Katri; Rack, Brigitte; Radice, Paolo; Rahman, Nazneen; Rennert, Gad; Rennert, Hedy S; Rhenius, Valerie; Romero, Atocha; Romm, Jane; Rudolph, Anja; Saloustros, Emmanouil; Sandler, Dale P; Sawyer, Elinor J; Schmidt, Marjanka K; Schmutzler, Rita K; Schneeweiss, Andreas; Scott, Rodney J; Scott, Christopher G; Seal, Sheila; Shah, Mitul; Shrubsole, Martha J; Smeets, Ann; Southey, Melissa C; Spinelli, John J; Stone, Jennifer; Surowy, Harald; Swerdlow, Anthony J; Tamimi, Rulla M; Tapper, William; Taylor, Jack A; Terry, Mary Beth; Tessier, Daniel C; Thomas, Abigail; Thöne, Kathrin; Tollenaar, Rob A E M; Torres, Diana; Truong, Thérèse; Untch, Michael; Vachon, Celine; Van Den Berg, David; Vincent, Daniel; Waisfisz, Quinten; Weinberg, Clarice R; Wendt, Camilla; Whittemore, Alice S; Wildiers, Hans; Willett, Walter C; Winqvist, Robert; Wolk, Alicja; Xia, Lucy; Yang, Xiaohong R; Ziogas, Argyrios; Ziv, Elad; Dunning, Alison M; Pharoah, Paul D P; Simard, Jacques; Milne, Roger L; Edwards, Stacey L; Kraft, Peter; Easton, Douglas F; Chenevix-Trench, Georgia; Zheng, Wei

    2018-06-18

    The breast cancer risk variants identified in genome-wide association studies explain only a small fraction of the familial relative risk, and the genes responsible for these associations remain largely unknown. To identify novel risk loci and likely causal genes, we performed a transcriptome-wide association study evaluating associations of genetically predicted gene expression with breast cancer risk in 122,977 cases and 105,974 controls of European ancestry. We used data from the Genotype-Tissue Expression Project to establish genetic models to predict gene expression in breast tissue and evaluated model performance using data from The Cancer Genome Atlas. Of the 8,597 genes evaluated, significant associations were identified for 48 at a Bonferroni-corrected threshold of P < 5.82 × 10 -6 , including 14 genes at loci not yet reported for breast cancer. We silenced 13 genes and showed an effect for 11 on cell proliferation and/or colony-forming efficiency. Our study provides new insights into breast cancer genetics and biology.

  3. Gene-environment interaction involving recently identified colorectal cancer susceptibility loci

    PubMed Central

    Kantor, Elizabeth D.; Hutter, Carolyn M.; Minnier, Jessica; Berndt, Sonja I.; Brenner, Hermann; Caan, Bette J.; Campbell, Peter T.; Carlson, Christopher S.; Casey, Graham; Chan, Andrew T.; Chang-Claude, Jenny; Chanock, Stephen J.; Cotterchio, Michelle; Du, Mengmeng; Duggan, David; Fuchs, Charles S.; Giovannucci, Edward L.; Gong, Jian; Harrison, Tabitha A.; Hayes, Richard B.; Henderson, Brian E.; Hoffmeister, Michael; Hopper, John L.; Jenkins, Mark A.; Jiao, Shuo; Kolonel, Laurence N.; Le Marchand, Loic; Lemire, Mathieu; Ma, Jing; Newcomb, Polly A.; Ochs-Balcom, Heather M.; Pflugeisen, Bethann M.; Potter, John D.; Rudolph, Anja; Schoen, Robert E.; Seminara, Daniela; Slattery, Martha L.; Stelling, Deanna L.; Thomas, Fridtjof; Thornquist, Mark; Ulrich, Cornelia M.; Warnick, Greg S.; Zanke, Brent W.; Peters, Ulrike; Hsu, Li; White, Emily

    2014-01-01

    BACKGROUND Genome-wide association studies have identified several single nucleotide polymorphisms (SNPs) that are associated with risk of colorectal cancer (CRC). Prior research has evaluated the presence of gene-environment interaction involving the first 10 identified susceptibility loci, but little work has been conducted on interaction involving SNPs at recently identified susceptibility loci, including: rs10911251, rs6691170, rs6687758, rs11903757, rs10936599, rs647161, rs1321311, rs719725, rs1665650, rs3824999, rs7136702, rs11169552, rs59336, rs3217810, rs4925386, and rs2423279. METHODS Data on 9160 cases and 9280 controls from the Genetics and Epidemiology of Colorectal Cancer Consortium (GECCO) and Colon Cancer Family Registry (CCFR) were used to evaluate the presence of interaction involving the above-listed SNPs and sex, body mass index (BMI), alcohol consumption, smoking, aspirin use, post-menopausal hormone (PMH) use, as well as intake of dietary calcium, dietary fiber, dietary folate, red meat, processed meat, fruit, and vegetables. Interaction was evaluated using a fixed-effects meta-analysis of an efficient Empirical Bayes estimator, and permutation was used to account for multiple comparisons. RESULTS None of the permutation-adjusted p-values reached statistical significance. CONCLUSIONS The associations between recently identified genetic susceptibility loci and CRC are not strongly modified by sex, BMI, alcohol, smoking, aspirin, PMH use, and various dietary factors. IMPACT Results suggest no evidence of strong gene-environment interactions involving the recently identified 16 susceptibility loci for CRC taken one at a time. PMID:24994789

  4. Preferential Allele Expression Analysis Identifies Shared Germline and Somatic Driver Genes in Advanced Ovarian Cancer

    PubMed Central

    Halabi, Najeeb M.; Martinez, Alejandra; Al-Farsi, Halema; Mery, Eliane; Puydenus, Laurence; Pujol, Pascal; Khalak, Hanif G.; McLurcan, Cameron; Ferron, Gwenael; Querleu, Denis; Al-Azwani, Iman; Al-Dous, Eman; Mohamoud, Yasmin A.; Malek, Joel A.; Rafii, Arash

    2016-01-01

    Identifying genes where a variant allele is preferentially expressed in tumors could lead to a better understanding of cancer biology and optimization of targeted therapy. However, tumor sample heterogeneity complicates standard approaches for detecting preferential allele expression. We therefore developed a novel approach combining genome and transcriptome sequencing data from the same sample that corrects for sample heterogeneity and identifies significant preferentially expressed alleles. We applied this analysis to epithelial ovarian cancer samples consisting of matched primary ovary and peritoneum and lymph node metastasis. We find that preferentially expressed variant alleles include germline and somatic variants, are shared at a relatively high frequency between patients, and are in gene networks known to be involved in cancer processes. Analysis at a patient level identifies patient-specific preferentially expressed alleles in genes that are targets for known drugs. Analysis at a site level identifies patterns of site specific preferential allele expression with similar pathways being impacted in the primary and metastasis sites. We conclude that genes with preferentially expressed variant alleles can act as cancer drivers and that targeting those genes could lead to new therapeutic strategies. PMID:26735499

  5. Engineering and Functional Characterization of Fusion Genes Identifies Novel Oncogenic Drivers of Cancer.

    PubMed

    Lu, Hengyu; Villafane, Nicole; Dogruluk, Turgut; Grzeskowiak, Caitlin L; Kong, Kathleen; Tsang, Yiu Huen; Zagorodna, Oksana; Pantazi, Angeliki; Yang, Lixing; Neill, Nicholas J; Kim, Young Won; Creighton, Chad J; Verhaak, Roel G; Mills, Gordon B; Park, Peter J; Kucherlapati, Raju; Scott, Kenneth L

    2017-07-01

    Oncogenic gene fusions drive many human cancers, but tools to more quickly unravel their functional contributions are needed. Here we describe methodology permitting fusion gene construction for functional evaluation. Using this strategy, we engineered the known fusion oncogenes, BCR-ABL1, EML4-ALK , and ETV6-NTRK3, as well as 20 previously uncharacterized fusion genes identified in The Cancer Genome Atlas datasets. In addition to confirming oncogenic activity of the known fusion oncogenes engineered by our construction strategy, we validated five novel fusion genes involving MET, NTRK2 , and BRAF kinases that exhibited potent transforming activity and conferred sensitivity to FDA-approved kinase inhibitors. Our fusion construction strategy also enabled domain-function studies of BRAF fusion genes. Our results confirmed other reports that the transforming activity of BRAF fusions results from truncation-mediated loss of inhibitory domains within the N-terminus of the BRAF protein. BRAF mutations residing within this inhibitory region may provide a means for BRAF activation in cancer, therefore we leveraged the modular design of our fusion gene construction methodology to screen N-terminal domain mutations discovered in tumors that are wild-type at the BRAF mutation hotspot, V600. We identified an oncogenic mutation, F247L, whose expression robustly activated the MAPK pathway and sensitized cells to BRAF and MEK inhibitors. When applied broadly, these tools will facilitate rapid fusion gene construction for subsequent functional characterization and translation into personalized treatment strategies. Cancer Res; 77(13); 3502-12. ©2017 AACR . ©2017 American Association for Cancer Research.

  6. Transposon mutagenesis identifies genes that cooperate with mutant Pten in breast cancer progression

    PubMed Central

    Rangel, Roberto; Lee, Song-Choon; Hon-Kim Ban, Kenneth; Guzman-Rojas, Liliana; Mann, Michael B.; Newberg, Justin Y.; McNoe, Leslie A.; Selvanesan, Luxmanan; Ward, Jerrold M.; Rust, Alistair G.; Chin, Kuan-Yew; Black, Michael A.; Jenkins, Nancy A.; Copeland, Neal G.

    2016-01-01

    Triple-negative breast cancer (TNBC) has the worst prognosis of any breast cancer subtype. To better understand the genetic forces driving TNBC, we performed a transposon mutagenesis screen in a phosphatase and tensin homolog (Pten) mutant mice and identified 12 candidate trunk drivers and a much larger number of progression genes. Validation studies identified eight TNBC tumor suppressor genes, including the GATA-like transcriptional repressor TRPS1. Down-regulation of TRPS1 in TNBC cells promoted epithelial-to-mesenchymal transition (EMT) by deregulating multiple EMT pathway genes, in addition to increasing the expression of SERPINE1 and SERPINB2 and the subsequent migration, invasion, and metastasis of tumor cells. Transposon mutagenesis has thus provided a better understanding of the genetic forces driving TNBC and discovered genes with potential clinical importance in TNBC. PMID:27849608

  7. Use of deep whole-genome sequencing data to identify structure risk variants in breast cancer susceptibility genes.

    PubMed

    Guo, Xingyi; Shi, Jiajun; Cai, Qiuyin; Shu, Xiao-Ou; He, Jing; Wen, Wanqing; Allen, Jamie; Pharoah, Paul; Dunning, Alison; Hunter, David J; Kraft, Peter; Easton, Douglas F; Zheng, Wei; Long, Jirong

    2018-03-01

    Functional disruptions of susceptibility genes by large genomic structure variant (SV) deletions in germlines are known to be associated with cancer risk. However, few studies have been conducted to systematically search for SV deletions in breast cancer susceptibility genes. We analysed deep (> 30x) whole-genome sequencing (WGS) data generated in blood samples from 128 breast cancer patients of Asian and European descent with either a strong family history of breast cancer or early cancer onset disease. To identify SV deletions in known or suspected breast cancer susceptibility genes, we used multiple SV calling tools including Genome STRiP, Delly, Manta, BreakDancer and Pindel. SV deletions were detected by at least three of these bioinformatics tools in five genes. Specifically, we identified heterozygous deletions covering a fraction of the coding regions of BRCA1 (with approximately 80kb in two patients), and TP53 genes (with ∼1.6 kb in two patients), and of intronic regions (∼1 kb) of the PALB2 (one patient), PTEN (three patients) and RAD51C genes (one patient). We confirmed the presence of these deletions using real-time quantitative PCR (qPCR). Our study identified novel SV deletions in breast cancer susceptibility genes and the identification of such SV deletions may improve clinical testing.

  8. Multiscale mutation clustering algorithm identifies pan-cancer mutational clusters associated with pathway-level changes in gene expression

    PubMed Central

    Poole, William; Leinonen, Kalle; Shmulevich, Ilya

    2017-01-01

    Cancer researchers have long recognized that somatic mutations are not uniformly distributed within genes. However, most approaches for identifying cancer mutations focus on either the entire-gene or single amino-acid level. We have bridged these two methodologies with a multiscale mutation clustering algorithm that identifies variable length mutation clusters in cancer genes. We ran our algorithm on 539 genes using the combined mutation data in 23 cancer types from The Cancer Genome Atlas (TCGA) and identified 1295 mutation clusters. The resulting mutation clusters cover a wide range of scales and often overlap with many kinds of protein features including structured domains, phosphorylation sites, and known single nucleotide variants. We statistically associated these multiscale clusters with gene expression and drug response data to illuminate the functional and clinical consequences of mutations in our clusters. Interestingly, we find multiple clusters within individual genes that have differential functional associations: these include PTEN, FUBP1, and CDH1. This methodology has potential implications in identifying protein regions for drug targets, understanding the biological underpinnings of cancer, and personalizing cancer treatments. Toward this end, we have made the mutation clusters and the clustering algorithm available to the public. Clusters and pathway associations can be interactively browsed at m2c.systemsbiology.net. The multiscale mutation clustering algorithm is available at https://github.com/IlyaLab/M2C. PMID:28170390

  9. Multiscale mutation clustering algorithm identifies pan-cancer mutational clusters associated with pathway-level changes in gene expression.

    PubMed

    Poole, William; Leinonen, Kalle; Shmulevich, Ilya; Knijnenburg, Theo A; Bernard, Brady

    2017-02-01

    Cancer researchers have long recognized that somatic mutations are not uniformly distributed within genes. However, most approaches for identifying cancer mutations focus on either the entire-gene or single amino-acid level. We have bridged these two methodologies with a multiscale mutation clustering algorithm that identifies variable length mutation clusters in cancer genes. We ran our algorithm on 539 genes using the combined mutation data in 23 cancer types from The Cancer Genome Atlas (TCGA) and identified 1295 mutation clusters. The resulting mutation clusters cover a wide range of scales and often overlap with many kinds of protein features including structured domains, phosphorylation sites, and known single nucleotide variants. We statistically associated these multiscale clusters with gene expression and drug response data to illuminate the functional and clinical consequences of mutations in our clusters. Interestingly, we find multiple clusters within individual genes that have differential functional associations: these include PTEN, FUBP1, and CDH1. This methodology has potential implications in identifying protein regions for drug targets, understanding the biological underpinnings of cancer, and personalizing cancer treatments. Toward this end, we have made the mutation clusters and the clustering algorithm available to the public. Clusters and pathway associations can be interactively browsed at m2c.systemsbiology.net. The multiscale mutation clustering algorithm is available at https://github.com/IlyaLab/M2C.

  10. Overexpression screens identify conserved dosage chromosome instability genes in yeast and human cancer

    PubMed Central

    Duffy, Supipi; Fam, Hok Khim; Wang, Yi Kan; Styles, Erin B.; Kim, Jung-Hyun; Ang, J. Sidney; Singh, Tejomayee; Larionov, Vladimir; Shah, Sohrab P.; Andrews, Brenda; Boerkoel, Cornelius F.; Hieter, Philip

    2016-01-01

    Somatic copy number amplification and gene overexpression are common features of many cancers. To determine the role of gene overexpression on chromosome instability (CIN), we performed genome-wide screens in the budding yeast for yeast genes that cause CIN when overexpressed, a phenotype we refer to as dosage CIN (dCIN), and identified 245 dCIN genes. This catalog of genes reveals human orthologs known to be recurrently overexpressed and/or amplified in tumors. We show that two genes, TDP1, a tyrosyl-DNA-phosphdiesterase, and TAF12, an RNA polymerase II TATA-box binding factor, cause CIN when overexpressed in human cells. Rhabdomyosarcoma lines with elevated human Tdp1 levels also exhibit CIN that can be partially rescued by siRNA-mediated knockdown of TDP1. Overexpression of dCIN genes represents a genetic vulnerability that could be leveraged for selective killing of cancer cells through targeting of an unlinked synthetic dosage lethal (SDL) partner. Using SDL screens in yeast, we identified a set of genes that when deleted specifically kill cells with high levels of Tdp1. One gene was the histone deacetylase RPD3, for which there are known inhibitors. Both HT1080 cells overexpressing hTDP1 and rhabdomyosarcoma cells with elevated levels of hTdp1 were more sensitive to histone deacetylase inhibitors valproic acid (VPA) and trichostatin A (TSA), recapitulating the SDL interaction in human cells and suggesting VPA and TSA as potential therapeutic agents for tumors with elevated levels of hTdp1. The catalog of dCIN genes presented here provides a candidate list to identify genes that cause CIN when overexpressed in cancer, which can then be leveraged through SDL to selectively target tumors. PMID:27551064

  11. Genomic characterization of biliary tract cancers identifies driver genes and predisposing mutations.

    PubMed

    Wardell, Christopher P; Fujita, Masashi; Yamada, Toru; Simbolo, Michele; Fassan, Matteo; Karlic, Rosa; Polak, Paz; Kim, Jaegil; Hatanaka, Yutaka; Maejima, Kazuhiro; Lawlor, Rita T; Nakanishi, Yoshitsugu; Mitsuhashi, Tomoko; Fujimoto, Akihiro; Furuta, Mayuko; Ruzzenente, Andrea; Conci, Simone; Oosawa, Ayako; Sasaki-Oku, Aya; Nakano, Kaoru; Tanaka, Hiroko; Yamamoto, Yujiro; Michiaki, Kubo; Kawakami, Yoshiiku; Aikata, Hiroshi; Ueno, Masaki; Hayami, Shinya; Gotoh, Kunihito; Ariizumi, Shun-Ichi; Yamamoto, Masakazu; Yamaue, Hiroki; Chayama, Kazuaki; Miyano, Satoru; Getz, Gad; Scarpa, Aldo; Hirano, Satoshi; Nakamura, Toru; Nakagawa, Hidewaki

    2018-05-01

    Biliary tract cancers (BTCs) are clinically and pathologically heterogeneous and respond poorly to treatment. Genomic profiling can offer a clearer understanding of their carcinogenesis, classification and treatment strategy. We performed large-scale genome sequencing analyses on BTCs to investigate their somatic and germline driver events and characterize their genomic landscape. We analyzed 412 BTC samples from Japanese and Italian populations, 107 by whole-exome sequencing (WES), 39 by whole-genome sequencing (WGS), and a further 266 samples by targeted sequencing. The subtypes were 136 intrahepatic cholangiocarcinomas (ICCs), 101 distal cholangiocarcinomas (DCCs), 109 peri-hilar type cholangiocarcinomas (PHCs), and 66 gallbladder or cystic duct cancers (GBCs/CDCs). We identified somatic alterations and searched for driver genes in BTCs, finding pathogenic germline variants of cancer-predisposing genes. We predicted cell-of-origin for BTCs by combining somatic mutation patterns and epigenetic features. We identified 32 significantly and commonly mutated genes including TP53, KRAS, SMAD4, NF1, ARID1A, PBRM1, and ATR, some of which negatively affected patient prognosis. A novel deletion of MUC17 at 7q22.1 affected patient prognosis. Cell-of-origin predictions using WGS and epigenetic features suggest hepatocyte-origin of hepatitis-related ICCs. Deleterious germline mutations of cancer-predisposing genes such as BRCA1, BRCA2, RAD51D, MLH1, or MSH2 were detected in 11% (16/146) of BTC patients. BTCs have distinct genetic features including somatic events and germline predisposition. These findings could be useful to establish treatment and diagnostic strategies for BTCs based on genetic information. We here analyzed genomic features of 412 BTC samples from Japanese and Italian populations. A total of 32 significantly and commonly mutated genes were identified, some of which negatively affected patient prognosis, including a novel deletion of MUC17 at 7q22.1. Cell

  12. Suppression subtractive hybridization identified differentially expressed genes in lung adenocarcinoma: ERGIC3 as a novel lung cancer-related gene

    PubMed Central

    2013-01-01

    Background To understand the carcinogenesis caused by accumulated genetic and epigenetic alterations and seek novel biomarkers for various cancers, studying differentially expressed genes between cancerous and normal tissues is crucial. In the study, two cDNA libraries of lung cancer were constructed and screened for identification of differentially expressed genes. Methods Two cDNA libraries of differentially expressed genes were constructed using lung adenocarcinoma tissue and adjacent nonmalignant lung tissue by suppression subtractive hybridization. The data of the cDNA libraries were then analyzed and compared using bioinformatics analysis. Levels of mRNA and protein were measured by quantitative real-time polymerase chain reaction (q-RT-PCR) and western blot respectively, as well as expression and localization of proteins were determined by immunostaining. Gene functions were investigated using proliferation and migration assays after gene silencing and gene over-expression. Results Two libraries of differentially expressed genes were obtained. The forward-subtracted library (FSL) and the reverse-subtracted library (RSL) contained 177 and 59 genes, respectively. Bioinformatic analysis demonstrated that these genes were involved in a wide range of cellular functions. The vast majority of these genes were newly identified to be abnormally expressed in lung cancer. In the first stage of the screening for 16 genes, we compared lung cancer tissues with their adjacent non-malignant tissues at the mRNA level, and found six genes (ERGIC3, DDR1, HSP90B1, SDC1, RPSA, and LPCAT1) from the FSL were significantly up-regulated while two genes (GPX3 and TIMP3) from the RSL were significantly down-regulated (P < 0.05). The ERGIC3 protein was also over-expressed in lung cancer tissues and cultured cells, and expression of ERGIC3 was correlated with the differentiated degree and histological type of lung cancer. The up-regulation of ERGIC3 could promote cellular migration

  13. Comparing cancer vs normal gene expression profiles identifies new disease entities and common transcriptional programs in AML patients.

    PubMed

    Rapin, Nicolas; Bagger, Frederik Otzen; Jendholm, Johan; Mora-Jensen, Helena; Krogh, Anders; Kohlmann, Alexander; Thiede, Christian; Borregaard, Niels; Bullinger, Lars; Winther, Ole; Theilgaard-Mönch, Kim; Porse, Bo T

    2014-02-06

    Gene expression profiling has been used extensively to characterize cancer, identify novel subtypes, and improve patient stratification. However, it has largely failed to identify transcriptional programs that differ between cancer and corresponding normal cells and has not been efficient in identifying expression changes fundamental to disease etiology. Here we present a method that facilitates the comparison of any cancer sample to its nearest normal cellular counterpart, using acute myeloid leukemia (AML) as a model. We first generated a gene expression-based landscape of the normal hematopoietic hierarchy, using expression profiles from normal stem/progenitor cells, and next mapped the AML patient samples to this landscape. This allowed us to identify the closest normal counterpart of individual AML samples and determine gene expression changes between cancer and normal. We find the cancer vs normal method (CvN method) to be superior to conventional methods in stratifying AML patients with aberrant karyotype and in identifying common aberrant transcriptional programs with potential importance for AML etiology. Moreover, the CvN method uncovered a novel poor-outcome subtype of normal-karyotype AML, which allowed for the generation of a highly prognostic survival signature. Collectively, our CvN method holds great potential as a tool for the analysis of gene expression profiles of cancer patients.

  14. Engineering and Functional Characterization of Fusion Genes Identifies Novel Oncogenic Drivers of Cancer. | Office of Cancer Genomics

    Cancer.gov

    Oncogenic gene fusions drive many human cancers, but tools to more quickly unravel their functional contributions are needed. Here we describe methodology permitting fusion gene construction for functional evaluation. Using this strategy, we engineered the known fusion oncogenes, BCR-ABL1, EML4-ALK, and ETV6-NTRK3, as well as 20 previously uncharacterized fusion genes identified in TCGA datasets.

  15. Comparison of Expression Profiles in Ovarian Epithelium In Vivo and Ovarian Cancer Identifies Novel Candidate Genes Involved in Disease Pathogenesis

    PubMed Central

    Emmanuel, Catherine; Gava, Natalie; Kennedy, Catherine; Balleine, Rosemary L.; Sharma, Raghwa; Wain, Gerard; Brand, Alison; Hogg, Russell; Etemadmoghadam, Dariush; George, Joshy; Birrer, Michael J.; Clarke, Christine L.; Chenevix-Trench, Georgia; Bowtell, David D. L.; Harnett, Paul R.; deFazio, Anna

    2011-01-01

    Molecular events leading to epithelial ovarian cancer are poorly understood but ovulatory hormones and a high number of life-time ovulations with concomitant proliferation, apoptosis, and inflammation, increases risk. We identified genes that are regulated during the estrous cycle in murine ovarian surface epithelium and analysed these profiles to identify genes dysregulated in human ovarian cancer, using publically available datasets. We identified 338 genes that are regulated in murine ovarian surface epithelium during the estrous cycle and dysregulated in ovarian cancer. Six of seven candidates selected for immunohistochemical validation were expressed in serous ovarian cancer, inclusion cysts, ovarian surface epithelium and in fallopian tube epithelium. Most were overexpressed in ovarian cancer compared with ovarian surface epithelium and/or inclusion cysts (EpCAM, EZH2, BIRC5) although BIRC5 and EZH2 were expressed as highly in fallopian tube epithelium as in ovarian cancer. We prioritised the 338 genes for those likely to be important for ovarian cancer development by in silico analyses of copy number aberration and mutation using publically available datasets and identified genes with established roles in ovarian cancer as well as novel genes for which we have evidence for involvement in ovarian cancer. Chromosome segregation emerged as an important process in which genes from our list of 338 were over-represented including two (BUB1, NCAPD2) for which there is evidence of amplification and mutation. NUAK2, upregulated in ovarian surface epithelium in proestrus and predicted to have a driver mutation in ovarian cancer, was examined in a larger cohort of serous ovarian cancer where patients with lower NUAK2 expression had shorter overall survival. In conclusion, defining genes that are activated in normal epithelium in the course of ovulation that are also dysregulated in cancer has identified a number of pathways and novel candidate genes that may contribute

  16. Transcriptional Profiling of Breast Cancer Metastases Identifies Liver Metastasis-Selective Genes Associated with Adverse Outcome in Luminal A Primary Breast Cancer.

    PubMed

    Kimbung, Siker; Johansson, Ida; Danielsson, Anna; Veerla, Srinivas; Egyhazi Brage, Suzanne; Frostvik Stolt, Marianne; Skoog, Lambert; Carlsson, Lena; Einbeigi, Zakaria; Lidbrink, Elisabet; Linderholm, Barbro; Loman, Niklas; Malmström, Per-Olof; Söderberg, Martin; Walz, Thomas M; Fernö, Mårten; Hatschek, Thomas; Hedenfalk, Ingrid

    2016-01-01

    The complete molecular basis of the organ-specificity of metastasis is elusive. This study aimed to provide an independent characterization of the transcriptional landscape of breast cancer metastases with the specific objective to identify liver metastasis-selective genes of prognostic importance following primary tumor diagnosis. A cohort of 304 women with advanced breast cancer was studied. Associations between the site of recurrence and clinicopathologic features were investigated. Fine-needle aspirates of metastases (n = 91) were subjected to whole-genome transcriptional profiling. Liver metastasis-selective genes were identified by significance analysis of microarray (SAM) analyses and independently validated in external datasets. Finally, the prognostic relevance of the liver metastasis-selective genes in primary breast cancer was tested. Liver relapse was associated with estrogen receptor (ER) expression (P = 0.002), luminal B subtype (P = 0.01), and was prognostic for an inferior postrelapse survival (P = 0.01). The major variation in the transcriptional landscape of metastases was also associated with ER expression and molecular subtype. However, liver metastases displayed unique transcriptional fingerprints, characterized by downregulation of extracellular matrix (i.e., stromal) genes. Importantly, we identified a 17-gene liver metastasis-selective signature, which was significantly and independently prognostic for shorter relapse-free (P < 0.001) and overall (P = 0.001) survival in ER-positive tumors. Remarkably, this signature remained independently prognostic for shorter relapse-free survival (P = 0.001) among luminal A tumors. Extracellular matrix (stromal) genes can be used to partition breast cancer by site of relapse and may be used to further refine prognostication in ER positive primary breast cancer. ©2015 American Association for Cancer Research.

  17. Identifying molecular features for prostate cancer with Gleason 7 based on microarray gene expression profiles.

    PubMed

    Bălăcescu, Loredana; Bălăcescu, O; Crişan, N; Fetica, B; Petruţ, B; Bungărdean, Cătălina; Rus, Meda; Tudoran, Oana; Meurice, G; Irimie, Al; Dragoş, N; Berindan-Neagoe, Ioana

    2011-01-01

    Prostate cancer represents the first leading cause of cancer among western male population, with different clinical behavior ranging from indolent to metastatic disease. Although many molecules and deregulated pathways are known, the molecular mechanisms involved in the development of prostate cancer are not fully understood. The aim of this study was to explore the molecular variation underlying the prostate cancer, based on microarray analysis and bioinformatics approaches. Normal and prostate cancer tissues were collected by macrodissection from prostatectomy pieces. All prostate cancer specimens used in our study were Gleason score 7. Gene expression microarray (Agilent Technologies) was used for Whole Human Genome evaluation. The bioinformatics and functional analysis were based on Limma and Ingenuity software. The microarray analysis identified 1119 differentially expressed genes between prostate cancer and normal prostate, which were up- or down-regulated at least 2-fold. P-values were adjusted for multiple testing using Benjamini-Hochberg method with a false discovery rate of 0.01. These genes were analyzed with Ingenuity Pathway Analysis software and were established 23 genetic networks. Our microarray results provide new information regarding the molecular networks in prostate cancer stratified as Gleason 7. These data highlighted gene expression profiles for better understanding of prostate cancer progression.

  18. Gene expression profiling of prostate tissue identifies chromatin regulation as a potential link between obesity and lethal prostate cancer.

    PubMed

    Ebot, Ericka M; Gerke, Travis; Labbé, David P; Sinnott, Jennifer A; Zadra, Giorgia; Rider, Jennifer R; Tyekucheva, Svitlana; Wilson, Kathryn M; Kelly, Rachel S; Shui, Irene M; Loda, Massimo; Kantoff, Philip W; Finn, Stephen; Vander Heiden, Matthew G; Brown, Myles; Giovannucci, Edward L; Mucci, Lorelei A

    2017-11-01

    Obese men are at higher risk of advanced prostate cancer and cancer-specific mortality; however, the biology underlying this association remains unclear. This study examined gene expression profiles of prostate tissue to identify biological processes differentially expressed by obesity status and lethal prostate cancer. Gene expression profiling was performed on tumor (n = 402) and adjacent normal (n = 200) prostate tissue from participants in 2 prospective cohorts who had been diagnosed with prostate cancer from 1982 to 2005. Body mass index (BMI) was calculated from the questionnaire immediately preceding cancer diagnosis. Men were followed for metastases or prostate cancer-specific death (lethal disease) through 2011. Gene Ontology biological processes differentially expressed by BMI were identified using gene set enrichment analysis. Pathway scores were computed by averaging the signal intensities of member genes. Odds ratios (ORs) for lethal prostate cancer were estimated with logistic regression. Among 402 men, 48% were healthy weight, 31% were overweight, and 21% were very overweight/obese. Fifteen gene sets were enriched in tumor tissue, but not normal tissue, of very overweight/obese men versus healthy-weight men; 5 of these were related to chromatin modification and remodeling (false-discovery rate < 0.25). Patients with high tumor expression of chromatin-related genes had worse clinical characteristics (Gleason grade > 7, 41% vs 17%; P = 2 × 10 -4 ) and an increased risk of lethal disease that was independent of grade and stage (OR, 5.26; 95% confidence interval, 2.37-12.25). This study improves our understanding of the biology of aggressive prostate cancer and identifies a potential mechanistic link between obesity and prostate cancer death that warrants further study. Cancer 2017;123:4130-4138. © 2017 American Cancer Society. © 2017 American Cancer Society.

  19. Feature genes in metastatic breast cancer identified by MetaDE and SVM classifier methods.

    PubMed

    Tuo, Youlin; An, Ning; Zhang, Ming

    2018-03-01

    The aim of the present study was to investigate the feature genes in metastatic breast cancer samples. A total of 5 expression profiles of metastatic breast cancer samples were downloaded from the Gene Expression Omnibus database, which were then analyzed using the MetaQC and MetaDE packages in R language. The feature genes between metastasis and non‑metastasis samples were screened under the threshold of P<0.05. Based on the protein‑protein interactions (PPIs) in the Biological General Repository for Interaction Datasets, Human Protein Reference Database and Biomolecular Interaction Network Database, the PPI network of the feature genes was constructed. The feature genes identified by topological characteristics were then used for support vector machine (SVM) classifier training and verification. The accuracy of the SVM classifier was then evaluated using another independent dataset from The Cancer Genome Atlas database. Finally, function and pathway enrichment analyses for genes in the SVM classifier were performed. A total of 541 feature genes were identified between metastatic and non‑metastatic samples. The top 10 genes with the highest betweenness centrality values in the PPI network of feature genes were Nuclear RNA Export Factor 1, cyclin‑dependent kinase 2 (CDK2), myelocytomatosis proto‑oncogene protein (MYC), Cullin 5, SHC Adaptor Protein 1, Clathrin heavy chain, Nucleolin, WD repeat domain 1, proteasome 26S subunit non‑ATPase 2 and telomeric repeat binding factor 2. The cyclin‑dependent kinase inhibitor 1A (CDKN1A), E2F transcription factor 1 (E2F1), and MYC interacted with CDK2. The SVM classifier constructed by the top 30 feature genes was able to distinguish metastatic samples from non‑metastatic samples [correct rate, specificity, positive predictive value and negative predictive value >0.89; sensitivity >0.84; area under the receiver operating characteristic curve (AUROC) >0.96]. The verification of the SVM classifier in an

  20. A transposon-based genetic screen in mice identifies genes altered in colorectal cancer.

    PubMed

    Starr, Timothy K; Allaei, Raha; Silverstein, Kevin A T; Staggs, Rodney A; Sarver, Aaron L; Bergemann, Tracy L; Gupta, Mihir; O'Sullivan, M Gerard; Matise, Ilze; Dupuy, Adam J; Collier, Lara S; Powers, Scott; Oberg, Ann L; Asmann, Yan W; Thibodeau, Stephen N; Tessarollo, Lino; Copeland, Neal G; Jenkins, Nancy A; Cormier, Robert T; Largaespada, David A

    2009-03-27

    Human colorectal cancers (CRCs) display a large number of genetic and epigenetic alterations, some of which are causally involved in tumorigenesis (drivers) and others that have little functional impact (passengers). To help distinguish between these two classes of alterations, we used a transposon-based genetic screen in mice to identify candidate genes for CRC. Mice harboring mutagenic Sleeping Beauty (SB) transposons were crossed with mice expressing SB transposase in gastrointestinal tract epithelium. Most of the offspring developed intestinal lesions, including intraepithelial neoplasia, adenomas, and adenocarcinomas. Analysis of over 16,000 transposon insertions identified 77 candidate CRC genes, 60 of which are mutated and/or dysregulated in human CRC and thus are most likely to drive tumorigenesis. These genes include APC, PTEN, and SMAD4. The screen also identified 17 candidate genes that had not previously been implicated in CRC, including POLI, PTPRK, and RSPO2.

  1. Targeted next generation sequencing identifies functionally deleterious germline mutations in novel genes in early-onset/familial prostate cancer.

    PubMed

    Paulo, Paula; Maia, Sofia; Pinto, Carla; Pinto, Pedro; Monteiro, Augusta; Peixoto, Ana; Teixeira, Manuel R

    2018-04-01

    Considering that mutations in known prostate cancer (PrCa) predisposition genes, including those responsible for hereditary breast/ovarian cancer and Lynch syndromes, explain less than 5% of early-onset/familial PrCa, we have sequenced 94 genes associated with cancer predisposition using next generation sequencing (NGS) in a series of 121 PrCa patients. We found monoallelic truncating/functionally deleterious mutations in seven genes, including ATM and CHEK2, which have previously been associated with PrCa predisposition, and five new candidate PrCa associated genes involved in cancer predisposing recessive disorders, namely RAD51C, FANCD2, FANCI, CEP57 and RECQL4. Furthermore, using in silico pathogenicity prediction of missense variants among 18 genes associated with breast/ovarian cancer and/or Lynch syndrome, followed by KASP genotyping in 710 healthy controls, we identified "likely pathogenic" missense variants in ATM, BRIP1, CHEK2 and TP53. In conclusion, this study has identified putative PrCa predisposing germline mutations in 14.9% of early-onset/familial PrCa patients. Further data will be necessary to confirm the genetic heterogeneity of inherited PrCa predisposition hinted in this study.

  2. Gene expression patterns combined with network analysis identify hub genes associated with bladder cancer.

    PubMed

    Bi, Dongbin; Ning, Hao; Liu, Shuai; Que, Xinxiang; Ding, Kejia

    2015-06-01

    To explore molecular mechanisms of bladder cancer (BC), network strategy was used to find biomarkers for early detection and diagnosis. The differentially expressed genes (DEGs) between bladder carcinoma patients and normal subjects were screened using empirical Bayes method of the linear models for microarray data package. Co-expression networks were constructed by differentially co-expressed genes and links. Regulatory impact factors (RIF) metric was used to identify critical transcription factors (TFs). The protein-protein interaction (PPI) networks were constructed by the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) and clusters were obtained through molecular complex detection (MCODE) algorithm. Centralities analyses for complex networks were performed based on degree, stress and betweenness. Enrichment analyses were performed based on Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. Co-expression networks and TFs (based on expression data of global DEGs and DEGs in different stages and grades) were identified. Hub genes of complex networks, such as UBE2C, ACTA2, FABP4, CKS2, FN1 and TOP2A, were also obtained according to analysis of degree. In gene enrichment analyses of global DEGs, cell adhesion, proteinaceous extracellular matrix and extracellular matrix structural constituent were top three GO terms. ECM-receptor interaction, focal adhesion, and cell cycle were significant pathways. Our results provide some potential underlying biomarkers of BC. However, further validation is required and deep studies are needed to elucidate the pathogenesis of BC. Copyright © 2015 Elsevier Ltd. All rights reserved.

  3. A gene-signature progression approach to identifying candidate small-molecule cancer therapeutics with connectivity mapping.

    PubMed

    Wen, Qing; Kim, Chang-Sik; Hamilton, Peter W; Zhang, Shu-Dong

    2016-05-11

    Gene expression connectivity mapping has gained much popularity recently with a number of successful applications in biomedical research testifying its utility and promise. Previously methodological research in connectivity mapping mainly focused on two of the key components in the framework, namely, the reference gene expression profiles and the connectivity mapping algorithms. The other key component in this framework, the query gene signature, has been left to users to construct without much consensus on how this should be done, albeit it has been an issue most relevant to end users. As a key input to the connectivity mapping process, gene signature is crucially important in returning biologically meaningful and relevant results. This paper intends to formulate a standardized procedure for constructing high quality gene signatures from a user's perspective. We describe a two-stage process for making quality gene signatures using gene expression data as initial inputs. First, a differential gene expression analysis comparing two distinct biological states; only the genes that have passed stringent statistical criteria are considered in the second stage of the process, which involves ranking genes based on statistical as well as biological significance. We introduce a "gene signature progression" method as a standard procedure in connectivity mapping. Starting from the highest ranked gene, we progressively determine the minimum length of the gene signature that allows connections to the reference profiles (drugs) being established with a preset target false discovery rate. We use a lung cancer dataset and a breast cancer dataset as two case studies to demonstrate how this standardized procedure works, and we show that highly relevant and interesting biological connections are returned. Of particular note is gefitinib, identified as among the candidate therapeutics in our lung cancer case study. Our gene signature was based on gene expression data from Taiwan

  4. Transposon mutagenesis identifies chromatin modifiers cooperating with Ras in thyroid tumorigenesis and detects ATXN7 as a cancer gene.

    PubMed

    Montero-Conde, Cristina; Leandro-Garcia, Luis J; Chen, Xu; Oler, Gisele; Ruiz-Llorente, Sergio; Ryder, Mabel; Landa, Iñigo; Sanchez-Vega, Francisco; La, Konnor; Ghossein, Ronald A; Bajorin, Dean F; Knauf, Jeffrey A; Riordan, Jesse D; Dupuy, Adam J; Fagin, James A

    2017-06-20

    Oncogenic RAS mutations are present in 15-30% of thyroid carcinomas. Endogenous expression of mutant Ras is insufficient to initiate thyroid tumorigenesis in murine models, indicating that additional genetic alterations are required. We used Sleeping Beauty (SB) transposon mutagenesis to identify events that cooperate with Hras G12V in thyroid tumor development. Random genomic integration of SB transposons primarily generated loss-of-function events that significantly increased thyroid tumor penetrance in Tpo-Cre/homozygous FR-Hras G12V mice. The thyroid tumors closely phenocopied the histological features of human RAS-driven, poorly differentiated thyroid cancers. Characterization of transposon insertion sites in the SB-induced tumors identified 45 recurrently mutated candidate cancer genes. These mutation profiles were remarkably concordant with mutated cancer genes identified in a large series of human poorly differentiated and anaplastic thyroid cancers screened by next-generation sequencing using the MSK-IMPACT panel of cancer genes, which we modified to include all SB candidates. The disrupted genes primarily clustered in chromatin remodeling functional nodes and in the PI3K pathway. ATXN7 , a component of a multiprotein complex with histone acetylase activity, scored as a significant SB hit. It was recurrently mutated in advanced human cancers and significantly co-occurred with RAS or NF1 mutations. Expression of ATXN7 mutants cooperated with oncogenic RAS to induce thyroid cell proliferation, pointing to ATXN7 as a previously unrecognized cancer gene.

  5. Transposon mutagenesis identifies chromatin modifiers cooperating with Ras in thyroid tumorigenesis and detects ATXN7 as a cancer gene

    PubMed Central

    Montero-Conde, Cristina; Leandro-Garcia, Luis J.; Chen, Xu; Oler, Gisele; Ruiz-Llorente, Sergio; Ryder, Mabel; Landa, Iñigo; Sanchez-Vega, Francisco; La, Konnor; Ghossein, Ronald A.; Bajorin, Dean F.; Knauf, Jeffrey A.; Riordan, Jesse D.; Dupuy, Adam J.; Fagin, James A.

    2017-01-01

    Oncogenic RAS mutations are present in 15–30% of thyroid carcinomas. Endogenous expression of mutant Ras is insufficient to initiate thyroid tumorigenesis in murine models, indicating that additional genetic alterations are required. We used Sleeping Beauty (SB) transposon mutagenesis to identify events that cooperate with HrasG12V in thyroid tumor development. Random genomic integration of SB transposons primarily generated loss-of-function events that significantly increased thyroid tumor penetrance in Tpo-Cre/homozygous FR-HrasG12V mice. The thyroid tumors closely phenocopied the histological features of human RAS-driven, poorly differentiated thyroid cancers. Characterization of transposon insertion sites in the SB-induced tumors identified 45 recurrently mutated candidate cancer genes. These mutation profiles were remarkably concordant with mutated cancer genes identified in a large series of human poorly differentiated and anaplastic thyroid cancers screened by next-generation sequencing using the MSK-IMPACT panel of cancer genes, which we modified to include all SB candidates. The disrupted genes primarily clustered in chromatin remodeling functional nodes and in the PI3K pathway. ATXN7, a component of a multiprotein complex with histone acetylase activity, scored as a significant SB hit. It was recurrently mutated in advanced human cancers and significantly co-occurred with RAS or NF1 mutations. Expression of ATXN7 mutants cooperated with oncogenic RAS to induce thyroid cell proliferation, pointing to ATXN7 as a previously unrecognized cancer gene. PMID:28584132

  6. Identifying prognostic signature in ovarian cancer using DirGenerank

    PubMed Central

    Wang, Jian-Yong; Chen, Ling-Ling; Zhou, Xiong-Hui

    2017-01-01

    Identifying the prognostic genes in cancer is essential not only for the treatment of cancer patients, but also for drug discovery. However, it's still a big challenge to select the prognostic genes that can distinguish the risk of cancer patients across various data sets because of tumor heterogeneity. In this situation, the selected genes whose expression levels are statistically related to prognostic risks may be passengers. In this paper, based on gene expression data and prognostic data of ovarian cancer patients, we used conditional mutual information to construct gene dependency network in which the nodes (genes) with more out-degrees have more chances to be the modulators of cancer prognosis. After that, we proposed DirGenerank (Generank in direct netowrk) algorithm, which concerns both the gene dependency network and genes’ correlations to prognostic risks, to identify the gene signature that can predict the prognostic risks of ovarian cancer patients. Using ovarian cancer data set from TCGA (The Cancer Genome Atlas) as training data set, 40 genes with the highest importance were selected as prognostic signature. Survival analysis of these patients divided by the prognostic signature in testing data set and four independent data sets showed the signature can distinguish the prognostic risks of cancer patients significantly. Enrichment analysis of the signature with curated cancer genes and the drugs selected by CMAP showed the genes in the signature may be drug targets for therapy. In summary, we have proposed a useful pipeline to identify prognostic genes of cancer patients. PMID:28615526

  7. Identifying New Candidate Genes and Chemicals Related to Prostate Cancer Using a Hybrid Network and Shortest Path Approach

    PubMed Central

    Wang, Meng; Wu, Kai; Lu, Changhong; Kong, Xiangyin

    2015-01-01

    Prostate cancer is a type of cancer that occurs in the male prostate, a gland in the male reproductive system. Because prostate cancer cells may spread to other parts of the body and can influence human reproduction, understanding the mechanisms underlying this disease is critical for designing effective treatments. The identification of as many genes and chemicals related to prostate cancer as possible will enhance our understanding of this disease. In this study, we proposed a computational method to identify new candidate genes and chemicals based on currently known genes and chemicals related to prostate cancer by applying a shortest path approach in a hybrid network. The hybrid network was constructed according to information concerning chemical-chemical interactions, chemical-protein interactions, and protein-protein interactions. Many of the obtained genes and chemicals are associated with prostate cancer. PMID:26504486

  8. Genome-wide methylation analysis identifies a core set of hypermethylated genes in CIMP-H colorectal cancer.

    PubMed

    McInnes, Tyler; Zou, Donghui; Rao, Dasari S; Munro, Francesca M; Phillips, Vicky L; McCall, John L; Black, Michael A; Reeve, Anthony E; Guilford, Parry J

    2017-03-28

    Aberrant DNA methylation profiles are a characteristic of all known cancer types, epitomized by the CpG island methylator phenotype (CIMP) in colorectal cancer (CRC). Hypermethylation has been observed at CpG islands throughout the genome, but it is unclear which factors determine whether an individual island becomes methylated in cancer. DNA methylation in CRC was analysed using the Illumina HumanMethylation450K array. Differentially methylated loci were identified using Significance Analysis of Microarrays (SAM) and the Wilcoxon Signed Rank (WSR) test. Unsupervised hierarchical clustering was used to identify methylation subtypes in CRC. In this study we characterized the DNA methylation profiles of 94 CRC tissues and their matched normal counterparts. Consistent with previous studies, unsupervized hierarchical clustering of genome-wide methylation data identified three subtypes within the tumour samples, designated CIMP-H, CIMP-L and CIMP-N, that showed high, low and very low methylation levels, respectively. Differential methylation between normal and tumour samples was analysed at the individual CpG level, and at the gene level. The distribution of hypermethylation in CIMP-N tumours showed high inter-tumour variability and appeared to be highly stochastic in nature, whereas CIMP-H tumours exhibited consistent hypermethylation at a subset of genes, in addition to a highly variable background of hypermethylated genes. EYA4, TFPI2 and TLX1 were hypermethylated in more than 90% of all tumours examined. One-hundred thirty-two genes were hypermethylated in 100% of CIMP-H tumours studied and these were highly enriched for functions relating to skeletal system development (Bonferroni adjusted p value =2.88E-15), segment specification (adjusted p value =9.62E-11), embryonic development (adjusted p value =1.52E-04), mesoderm development (adjusted p value =1.14E-20), and ectoderm development (adjusted p value =7.94E-16). Our genome-wide characterization of DNA

  9. In-Silico Integration Approach to Identify a Key miRNA Regulating a Gene Network in Aggressive Prostate Cancer

    PubMed Central

    Colaprico, Antonio; Bontempi, Gianluca; Castiglioni, Isabella

    2018-01-01

    Like other cancer diseases, prostate cancer (PC) is caused by the accumulation of genetic alterations in the cells that drives malignant growth. These alterations are revealed by gene profiling and copy number alteration (CNA) analysis. Moreover, recent evidence suggests that also microRNAs have an important role in PC development. Despite efforts to profile PC, the alterations (gene, CNA, and miRNA) and biological processes that correlate with disease development and progression remain partially elusive. Many gene signatures proposed as diagnostic or prognostic tools in cancer poorly overlap. The identification of co-expressed genes, that are functionally related, can identify a core network of genes associated with PC with a better reproducibility. By combining different approaches, including the integration of mRNA expression profiles, CNAs, and miRNA expression levels, we identified a gene signature of four genes overlapping with other published gene signatures and able to distinguish, in silico, high Gleason-scored PC from normal human tissue, which was further enriched to 19 genes by gene co-expression analysis. From the analysis of miRNAs possibly regulating this network, we found that hsa-miR-153 was highly connected to the genes in the network. Our results identify a four-gene signature with diagnostic and prognostic value in PC and suggest an interesting gene network that could play a key regulatory role in PC development and progression. Furthermore, hsa-miR-153, controlling this network, could be a potential biomarker for theranostics in high Gleason-scored PC. PMID:29562723

  10. Network-Based Integration of GWAS and Gene Expression Identifies a HOX-Centric Network Associated with Serous Ovarian Cancer Risk.

    PubMed

    Kar, Siddhartha P; Tyrer, Jonathan P; Li, Qiyuan; Lawrenson, Kate; Aben, Katja K H; Anton-Culver, Hoda; Antonenkova, Natalia; Chenevix-Trench, Georgia; Baker, Helen; Bandera, Elisa V; Bean, Yukie T; Beckmann, Matthias W; Berchuck, Andrew; Bisogna, Maria; Bjørge, Line; Bogdanova, Natalia; Brinton, Louise; Brooks-Wilson, Angela; Butzow, Ralf; Campbell, Ian; Carty, Karen; Chang-Claude, Jenny; Chen, Yian Ann; Chen, Zhihua; Cook, Linda S; Cramer, Daniel; Cunningham, Julie M; Cybulski, Cezary; Dansonka-Mieszkowska, Agnieszka; Dennis, Joe; Dicks, Ed; Doherty, Jennifer A; Dörk, Thilo; du Bois, Andreas; Dürst, Matthias; Eccles, Diana; Easton, Douglas F; Edwards, Robert P; Ekici, Arif B; Fasching, Peter A; Fridley, Brooke L; Gao, Yu-Tang; Gentry-Maharaj, Aleksandra; Giles, Graham G; Glasspool, Rosalind; Goode, Ellen L; Goodman, Marc T; Grownwald, Jacek; Harrington, Patricia; Harter, Philipp; Hein, Alexander; Heitz, Florian; Hildebrandt, Michelle A T; Hillemanns, Peter; Hogdall, Estrid; Hogdall, Claus K; Hosono, Satoyo; Iversen, Edwin S; Jakubowska, Anna; Paul, James; Jensen, Allan; Ji, Bu-Tian; Karlan, Beth Y; Kjaer, Susanne K; Kelemen, Linda E; Kellar, Melissa; Kelley, Joseph; Kiemeney, Lambertus A; Krakstad, Camilla; Kupryjanczyk, Jolanta; Lambrechts, Diether; Lambrechts, Sandrina; Le, Nhu D; Lee, Alice W; Lele, Shashi; Leminen, Arto; Lester, Jenny; Levine, Douglas A; Liang, Dong; Lissowska, Jolanta; Lu, Karen; Lubinski, Jan; Lundvall, Lene; Massuger, Leon; Matsuo, Keitaro; McGuire, Valerie; McLaughlin, John R; McNeish, Iain A; Menon, Usha; Modugno, Francesmary; Moysich, Kirsten B; Narod, Steven A; Nedergaard, Lotte; Ness, Roberta B; Nevanlinna, Heli; Odunsi, Kunle; Olson, Sara H; Orlow, Irene; Orsulic, Sandra; Weber, Rachel Palmieri; Pearce, Celeste Leigh; Pejovic, Tanja; Pelttari, Liisa M; Permuth-Wey, Jennifer; Phelan, Catherine M; Pike, Malcolm C; Poole, Elizabeth M; Ramus, Susan J; Risch, Harvey A; Rosen, Barry; Rossing, Mary Anne; Rothstein, Joseph H; Rudolph, Anja; Runnebaum, Ingo B; Rzepecka, Iwona K; Salvesen, Helga B; Schildkraut, Joellen M; Schwaab, Ira; Shu, Xiao-Ou; Shvetsov, Yurii B; Siddiqui, Nadeem; Sieh, Weiva; Song, Honglin; Southey, Melissa C; Sucheston-Campbell, Lara E; Tangen, Ingvild L; Teo, Soo-Hwang; Terry, Kathryn L; Thompson, Pamela J; Timorek, Agnieszka; Tsai, Ya-Yu; Tworoger, Shelley S; van Altena, Anne M; Van Nieuwenhuysen, Els; Vergote, Ignace; Vierkant, Robert A; Wang-Gohrke, Shan; Walsh, Christine; Wentzensen, Nicolas; Whittemore, Alice S; Wicklund, Kristine G; Wilkens, Lynne R; Woo, Yin-Ling; Wu, Xifeng; Wu, Anna; Yang, Hannah; Zheng, Wei; Ziogas, Argyrios; Sellers, Thomas A; Monteiro, Alvaro N A; Freedman, Matthew L; Gayther, Simon A; Pharoah, Paul D P

    2015-10-01

    Genome-wide association studies (GWAS) have so far reported 12 loci associated with serous epithelial ovarian cancer (EOC) risk. We hypothesized that some of these loci function through nearby transcription factor (TF) genes and that putative target genes of these TFs as identified by coexpression may also be enriched for additional EOC risk associations. We selected TF genes within 1 Mb of the top signal at the 12 genome-wide significant risk loci. Mutual information, a form of correlation, was used to build networks of genes strongly coexpressed with each selected TF gene in the unified microarray dataset of 489 serous EOC tumors from The Cancer Genome Atlas. Genes represented in this dataset were subsequently ranked using a gene-level test based on results for germline SNPs from a serous EOC GWAS meta-analysis (2,196 cases/4,396 controls). Gene set enrichment analysis identified six networks centered on TF genes (HOXB2, HOXB5, HOXB6, HOXB7 at 17q21.32 and HOXD1, HOXD3 at 2q31) that were significantly enriched for genes from the risk-associated end of the ranked list (P < 0.05 and FDR < 0.05). These results were replicated (P < 0.05) using an independent association study (7,035 cases/21,693 controls). Genes underlying enrichment in the six networks were pooled into a combined network. We identified a HOX-centric network associated with serous EOC risk containing several genes with known or emerging roles in serous EOC development. Network analysis integrating large, context-specific datasets has the potential to offer mechanistic insights into cancer susceptibility and prioritize genes for experimental characterization. ©2015 American Association for Cancer Research.

  11. Mutations in the Kinase Domain of the HER2/ERBB2 Gene Identified in a Wide Variety of Human Cancers.

    PubMed

    Wen, Wenhsiang; Chen, Wangjuh Sting; Xiao, Nick; Bender, Ryan; Ghazalpour, Anatole; Tan, Zheng; Swensen, Jeffrey; Millis, Sherri Z; Basu, Gargi; Gatalica, Zoran; Press, Michael F

    2015-09-01

    The HER2 (official name ERBB2) gene encodes a membrane receptor in the epidermal growth factor receptor family amplified and overexpressed in adenocarcinoma. Activating mutations also occur in several cancers. We report mutation analyses of the HER2 kinase domain in 7497 histologically diverse cancers. Forty-five genes, including the kinase domain of HER2 with HER2 IHC and dual in situ hybridization, were analyzed in tumors from 7497 patients with cancer, including 850 breast, 770 colorectal, 910 non-small cell lung, 823 uterine or cervical, 1372 ovarian, and 297 pancreatic cancers, as well as 323 melanomas and 2152 other solid tumors. Sixty-nine HER2 kinase domain mutations were identified in tumors from 68 patients (approximately 1% of all cases, ranging from absent in sarcomas to 4% in urothelial cancers), which included previously published activating mutations and 13 novel mutations. Fourteen cases with coexisting HER2 mutation and amplification and/or overexpression were identified. Fifty-two of 68 patients had additional mutations in other analyzed genes, whereas 16 patients (23%) had HER2 mutations identified as the sole driver mutation. HER2 mutations coexisted with HER2 gene amplification and overexpression and with mutations in other functionally important genes. HER2 mutations were identified as the only driver mutation in a significant proportion of solid cancers. Evaluation of anti-HER2 therapies in nonamplified, HER2-mutated cancers is warranted. Copyright © 2015 American Society for Investigative Pathology and the Association for Molecular Pathology. Published by Elsevier Inc. All rights reserved.

  12. Expression screening of cancer/testis genes in prostate cancer identifies NR6A1 as a novel marker of disease progression and aggressiveness.

    PubMed

    Mathieu, Romain; Evrard, Bertrand; Fromont, Gaëlle; Rioux-Leclercq, Nathalie; Godet, Julie; Cathelineau, Xavier; Guillé, François; Primig, Michael; Chalmel, Frédéric

    2013-07-01

    Cancer/Testis (CT) genes are expressed in male gonads, repressed in most healthy somatic tissues and de-repressed in various somatic malignancies including prostate cancers (PCa). Because of their specific expression signature and their associations with tumor aggressiveness and poor outcomes, CT genes are considered to be useful biomarkers and they are also targets for the development of new anti-cancer immunotherapies. The aim of this study was to identify novel CT genes associated with hormone-sensitive prostate cancer (HSPC), and castration-resistant prostate cancer (CRPC). To identify novel CT genes we screened genes for which transcripts were detected by RNA profiling specifically in normal testis and in either HSPC or CRPC as compared to normal prostate and 44 other healthy tissues using GeneChips. The expression and clinicopathological significance of a promising candidate--NR6A1--was examined in HSPC, CRPC, and metastatic site samples using tissue microarrays. We report the identification of 98 genes detected in CRPC, HSPC and testicular samples but not in the normal controls. Among them, cellular levels of NR6A1 were found to be higher in HSPC compared to normal prostate and further increased in metastatic lesions and CRPC. Furthermore, increased NR6A1 immunoreactivity was significantly associated with a high Gleason score, advanced pT stage and cancer cell proliferation. Our results show that cellular levels of NR6A1 are correlated with disease progression in PCa. We suggest that this essential orphan nuclear receptor is a potential therapeutic target as well as a biomarker of PCa aggressiveness. Copyright © 2013 Wiley Periodicals, Inc.

  13. Transcriptome profiling identified differentially expressed genes and pathways associated with tamoxifen resistance in human breast cancer

    PubMed Central

    Men, Xin; Ma, Jun; Wu, Tong; Pu, Junyi; Wen, Shaojia; Shen, Jianfeng; Wang, Xun; Wang, Yamin; Chen, Chao; Dai, Penggao

    2018-01-01

    Tamoxifen (TAM) resistance is an important clinical problem in the treatment of breast cancer. In order to identify the mechanism of TAM resistance for estrogen receptor (ER)-positive breast cancer, we screened the transcriptome using RNA-seq and compared the gene expression profiles between the MCF-7 mamma carcinoma cell line and the TAM-resistant cell line TAMR/MCF-7, 52 significant differential expression genes (DEGs) were identified including SLIT2, ROBO, LHX, KLF, VEGFC, BAMBI, LAMA1, FLT4, PNMT, DHRS2, MAOA and ALDH. The DEGs were annotated in the GO, COG and KEGG databases. Annotation of the function of the DEGs in the KEGG database revealed the top three pathways enriched with the most DEGs, including pathways in cancer, the PI3K-AKT pathway, and focal adhesion. Then we compared the gene expression profiles between the Clinical progressive disease (PD) and the complete response (CR) from the cancer genome altas (TCGA). 10 common DEGs were identified through combining the clinical and cellular analysis results. Protein-protein interaction network was applied to analyze the association of ER signal pathway with the 10 DEGs. 3 significant genes (GFRA3, NPY1R and PTPRN2) were closely related to ER related pathway. These significant DEGs regulated many biological activities such as cell proliferation and survival, motility and migration, and tumor cell invasion. The interactions between these DEGs and drug resistance phenomenon need to be further elucidated at a functional level in further studies. Based on our findings, we believed that these DEGs could be therapeutic targets, which can be explored to develop new treatment options. PMID:29423105

  14. The Candidate Cancer Gene Database: a database of cancer driver genes from forward genetic screens in mice.

    PubMed

    Abbott, Kenneth L; Nyre, Erik T; Abrahante, Juan; Ho, Yen-Yi; Isaksson Vogel, Rachel; Starr, Timothy K

    2015-01-01

    Identification of cancer driver gene mutations is crucial for advancing cancer therapeutics. Due to the overwhelming number of passenger mutations in the human tumor genome, it is difficult to pinpoint causative driver genes. Using transposon mutagenesis in mice many laboratories have conducted forward genetic screens and identified thousands of candidate driver genes that are highly relevant to human cancer. Unfortunately, this information is difficult to access and utilize because it is scattered across multiple publications using different mouse genome builds and strength metrics. To improve access to these findings and facilitate meta-analyses, we developed the Candidate Cancer Gene Database (CCGD, http://ccgd-starrlab.oit.umn.edu/). The CCGD is a manually curated database containing a unified description of all identified candidate driver genes and the genomic location of transposon common insertion sites (CISs) from all currently published transposon-based screens. To demonstrate relevance to human cancer, we performed a modified gene set enrichment analysis using KEGG pathways and show that human cancer pathways are highly enriched in the database. We also used hierarchical clustering to identify pathways enriched in blood cancers compared to solid cancers. The CCGD is a novel resource available to scientists interested in the identification of genetic drivers of cancer. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

  15. A novel gammaretroviral shuttle vector insertional mutagenesis screen identifies SHARPIN as a breast cancer metastasis gene and prognostic biomarker.

    PubMed

    Bii, Victor M; Rae, Dustin T; Trobridge, Grant D

    2015-11-24

    Breast cancer (BC) is the second leading cause of malignancy among U.S. women. Metastasis results in a poor prognosis and increased mortality, but the molecular mechanisms by which metastatic tumors occur are not well understood. Identifying the genes that drive the metastatic process could provide targets for improved therapy and biomarkers to improve BC patient outcomes. Using a forward mutagenesis screen, BC cells mutagenized with a replication-incompetent gammaretroviral vector (γRV) were xenotransplanted into the mammary fat pad of immunodeficient mice. In this approach the vector provirus dysregulates nearby genes, providing a selective advantage to transduced cells to form metastases. Metastatic tumors were analyzed for proviral integration sites to identify nearby candidate metastasis genes. The γRV has a transgene cassette that allows for rescue in bacteria and rapid identification of vector integration sites. Using this approach, we identified the previously described metastasis gene WWTR1 (TAZ), and three other novel candidate metastasis genes including SHARPIN. SHARPIN was independently validated in vivo as a BC metastasis gene. Analysis of patient data showed that SHARPIN expression predicts metastasis-free survival after adjuvant therapy. Our approach has broad potential to identify genes involved in oncogenic processes for BC and other cancers. We show here it can identify both known (WWTR1) and novel (SHARPIN) BC metastasis genes.

  16. Identifying anti-cancer drug response related genes using an integrative analysis of transcriptomic and genomic variations with cell line-based drug perturbations.

    PubMed

    Sun, Yi; Zhang, Wei; Chen, Yunqin; Ma, Qin; Wei, Jia; Liu, Qi

    2016-02-23

    Clinical responses to anti-cancer therapies often only benefit a defined subset of patients. Predicting the best treatment strategy hinges on our ability to effectively translate genomic data into actionable information on drug responses. To achieve this goal, we compiled a comprehensive collection of baseline cancer genome data and drug response information derived from a large panel of cancer cell lines. This data set was applied to identify the signature genes relevant to drug sensitivity and their resistance by integrating CNVs and the gene expression of cell lines with in vitro drug responses. We presented an efficient in-silico pipeline for integrating heterogeneous cell line data sources with the simultaneous modeling of drug response values across all the drugs and cell lines. Potential signature genes correlated with drug response (sensitive or resistant) in different cancer types were identified. Using signature genes, our collaborative filtering-based drug response prediction model outperformed the 44 algorithms submitted to the DREAM competition on breast cancer cells. The functions of the identified drug response related signature genes were carefully analyzed at the pathway level and the synthetic lethality level. Furthermore, we validated these signature genes by applying them to the classification of the different subtypes of the TCGA tumor samples, and further uncovered their in vivo implications using clinical patient data. Our work may have promise in translating genomic data into customized marker genes relevant to the response of specific drugs for a specific cancer type of individual patients.

  17. Identifying clinically relevant drug resistance genes in drug-induced resistant cancer cell lines and post-chemotherapy tissues.

    PubMed

    Tong, Mengsha; Zheng, Weicheng; Lu, Xingrong; Ao, Lu; Li, Xiangyu; Guan, Qingzhou; Cai, Hao; Li, Mengyao; Yan, Haidan; Guo, You; Chi, Pan; Guo, Zheng

    2015-12-01

    Until recently, few molecular signatures of drug resistance identified in drug-induced resistant cancer cell models can be translated into clinical practice. Here, we defined differentially expressed genes (DEGs) between pre-chemotherapy colorectal cancer (CRC) tissue samples of non-responders and responders for 5-fluorouracil and oxaliplatin-based therapy as clinically relevant drug resistance genes (CRG5-FU/L-OHP). Taking CRG5-FU/L-OHP as reference, we evaluated the clinical relevance of several types of genes derived from HCT116 CRC cells with resistance to 5-fluorouracil and oxaliplatin, respectively. The results revealed that DEGs between parental and resistant cells, when both were treated with the corresponding drug for a certain time, were significantly consistent with the CRG5-FU/L-OHP as well as the DEGs between the post-chemotherapy CRC specimens of responders and non-responders. This study suggests a novel strategy to extract clinically relevant drug resistance genes from both drug-induced resistant cell models and post-chemotherapy cancer tissue specimens.

  18. Network-based integration of GWAS and gene expression identifies a HOX-centric network associated with serous ovarian cancer risk

    PubMed Central

    Kar, Siddhartha P.; Tyrer, Jonathan P.; Li, Qiyuan; Lawrenson, Kate; Aben, Katja K.H.; Anton-Culver, Hoda; Antonenkova, Natalia; Chenevix-Trench, Georgia; Baker, Helen; Bandera, Elisa V.; Bean, Yukie T.; Beckmann, Matthias W.; Berchuck, Andrew; Bisogna, Maria; Bjørge, Line; Bogdanova, Natalia; Brinton, Louise; Brooks-Wilson, Angela; Butzow, Ralf; Campbell, Ian; Carty, Karen; Chang-Claude, Jenny; Chen, Yian Ann; Chen, Zhihua; Cook, Linda S.; Cramer, Daniel; Cunningham, Julie M.; Cybulski, Cezary; Dansonka-Mieszkowska, Agnieszka; Dennis, Joe; Dicks, Ed; Doherty, Jennifer A.; Dörk, Thilo; du Bois, Andreas; Dürst, Matthias; Eccles, Diana; Easton, Douglas F.; Edwards, Robert P.; Ekici, Arif B.; Fasching, Peter A.; Fridley, Brooke L.; Gao, Yu-Tang; Gentry-Maharaj, Aleksandra; Giles, Graham G.; Glasspool, Rosalind; Goode, Ellen L.; Goodman, Marc T.; Grownwald, Jacek; Harrington, Patricia; Harter, Philipp; Hein, Alexander; Heitz, Florian; Hildebrandt, Michelle A.T.; Hillemanns, Peter; Hogdall, Estrid; Hogdall, Claus K.; Hosono, Satoyo; Iversen, Edwin S.; Jakubowska, Anna; Paul, James; Jensen, Allan; Ji, Bu-Tian; Karlan, Beth Y; Kjaer, Susanne K.; Kelemen, Linda E.; Kellar, Melissa; Kelley, Joseph; Kiemeney, Lambertus A.; Krakstad, Camilla; Kupryjanczyk, Jolanta; Lambrechts, Diether; Lambrechts, Sandrina; Le, Nhu D.; Lee, Alice W.; Lele, Shashi; Leminen, Arto; Lester, Jenny; Levine, Douglas A.; Liang, Dong; Lissowska, Jolanta; Lu, Karen; Lubinski, Jan; Lundvall, Lene; Massuger, Leon; Matsuo, Keitaro; McGuire, Valerie; McLaughlin, John R.; McNeish, Iain A.; Menon, Usha; Modugno, Francesmary; Moysich, Kirsten B.; Narod, Steven A.; Nedergaard, Lotte; Ness, Roberta B.; Nevanlinna, Heli; Odunsi, Kunle; Olson, Sara H.; Orlow, Irene; Orsulic, Sandra; Weber, Rachel Palmieri; Pearce, Celeste Leigh; Pejovic, Tanja; Pelttari, Liisa M.; Permuth-Wey, Jennifer; Phelan, Catherine M.; Pike, Malcolm C.; Poole, Elizabeth M.; Ramus, Susan J.; Risch, Harvey A.; Rosen, Barry; Rossing, Mary Anne; Rothstein, Joseph H.; Rudolph, Anja; Runnebaum, Ingo B.; Rzepecka, Iwona K.; Salvesen, Helga B.; Schildkraut, Joellen M.; Schwaab, Ira; Shu, Xiao-Ou; Shvetsov, Yurii B; Siddiqui, Nadeem; Sieh, Weiva; Song, Honglin; Southey, Melissa C.; Sucheston-Campbell, Lara E.; Tangen, Ingvild L.; Teo, Soo-Hwang; Terry, Kathryn L.; Thompson, Pamela J; Timorek, Agnieszka; Tsai, Ya-Yu; Tworoger, Shelley S.; van Altena, Anne M.; Van Nieuwenhuysen, Els; Vergote, Ignace; Vierkant, Robert A.; Wang-Gohrke, Shan; Walsh, Christine; Wentzensen, Nicolas; Whittemore, Alice S.; Wicklund, Kristine G.; Wilkens, Lynne R.; Woo, Yin-Ling; Wu, Xifeng; Wu, Anna; Yang, Hannah; Zheng, Wei; Ziogas, Argyrios; Sellers, Thomas A.; Monteiro, Alvaro N. A.; Freedman, Matthew L.; Gayther, Simon A.; Pharoah, Paul D. P.

    2015-01-01

    Background Genome-wide association studies (GWAS) have so far reported 12 loci associated with serous epithelial ovarian cancer (EOC) risk. We hypothesized that some of these loci function through nearby transcription factor (TF) genes and that putative target genes of these TFs as identified by co-expression may also be enriched for additional EOC risk associations. Methods We selected TF genes within 1 Mb of the top signal at the 12 genome-wide significant risk loci. Mutual information, a form of correlation, was used to build networks of genes strongly co-expressed with each selected TF gene in the unified microarray data set of 489 serous EOC tumors from The Cancer Genome Atlas. Genes represented in this data set were subsequently ranked using a gene-level test based on results for germline SNPs from a serous EOC GWAS meta-analysis (2,196 cases/4,396 controls). Results Gene set enrichment analysis identified six networks centered on TF genes (HOXB2, HOXB5, HOXB6, HOXB7 at 17q21.32 and HOXD1, HOXD3 at 2q31) that were significantly enriched for genes from the risk-associated end of the ranked list (P<0.05 and FDR<0.05). These results were replicated (P<0.05) using an independent association study (7,035 cases/21,693 controls). Genes underlying enrichment in the six networks were pooled into a combined network. Conclusion We identified a HOX-centric network associated with serous EOC risk containing several genes with known or emerging roles in serous EOC development. Impact Network analysis integrating large, context-specific data sets has the potential to offer mechanistic insights into cancer susceptibility and prioritize genes for experimental characterization. PMID:26209509

  19. Identifying pathways affected by cancer mutations.

    PubMed

    Iengar, Prathima

    2017-12-16

    Mutations in 15 cancers, sourced from the COSMIC Whole Genomes database, and 297 human pathways, arranged into pathway groups based on the processes they orchestrate, and sourced from the KEGG pathway database, have together been used to identify pathways affected by cancer mutations. Genes studied in ≥15, and mutated in ≥10 samples of a cancer have been considered recurrently mutated, and pathways with recurrently mutated genes have been considered affected in the cancer. Novel doughnut plots have been presented which enable visualization of the extent to which pathways and genes, in each pathway group, are targeted, in each cancer. The 'organismal systems' pathway group (including organism-level pathways; e.g., nervous system) is the most targeted, more than even the well-recognized signal transduction, cell-cycle and apoptosis, and DNA repair pathway groups. The important, yet poorly-recognized, role played by the group merits attention. Pathways affected in ≥7 cancers yielded insights into processes affected. Copyright © 2017 Elsevier Inc. All rights reserved.

  20. Gene panel testing for hereditary breast cancer.

    PubMed

    Winship, Ingrid; Southey, Melissa C

    2016-03-21

    Inherited predisposition to breast cancer is explained only in part by mutations in the BRCA1 and BRCA2 genes. Most families with an apparent familial clustering of breast cancer who are investigated through Australia's network of genetic services and familial cancer centres do not have mutations in either of these genes. More recently, additional breast cancer predisposition genes, such as PALB2, have been identified. New genetic technology allows a panel of multiple genes to be tested for mutations in a single test. This enables more women and their families to have risk assessment and risk management, in a preventive approach to predictable breast cancer. Predictive testing for a known family-specific mutation in a breast cancer predisposition gene provides personalised risk assessment and evidence-based risk management. Breast cancer predisposition gene panel tests have a greater diagnostic yield than conventional testing of only the BRCA1 and BRCA2 genes. The clinical validity and utility of some of the putative breast cancer predisposition genes is not yet clear. Ethical issues warrant consideration, as multiple gene panel testing has the potential to identify secondary findings not originally sought by the test requested. Multiple gene panel tests may provide an affordable and effective way to investigate the heritability of breast cancer.

  1. Metastatic canine mammary carcinomas can be identified by a gene expression profile that partly overlaps with human breast cancer profiles

    PubMed Central

    2010-01-01

    Background Similar to human breast cancer mammary tumors of the female dog are commonly associated with a fatal outcome due to the development of distant metastases. However, the molecular defects leading to metastasis are largely unknown and the value of canine mammary carcinoma as a model for human breast cancer is unclear. In this study, we analyzed the gene expression signatures associated with mammary tumor metastasis and asked for parallels with the human equivalent. Methods Messenger RNA expression profiles of twenty-seven lymph node metastasis positive or negative canine mammary carcinomas were established by microarray analysis. Differentially expressed genes were functionally characterized and associated with molecular pathways. The findings were also correlated with published data on human breast cancer. Results Metastatic canine mammary carcinomas had 1,011 significantly differentially expressed genes when compared to non-metastatic carcinomas. Metastatic carcinomas had a significant up-regulation of genes associated with cell cycle regulation, matrix modulation, protein folding and proteasomal degradation whereas cell differentiation genes, growth factor pathway genes and regulators of actin organization were significantly down-regulated. Interestingly, 265 of the 1,011 differentially expressed canine genes are also related to human breast cancer and, vice versa, parts of a human prognostic gene signature were identified in the expression profiles of the metastatic canine tumors. Conclusions Metastatic canine mammary carcinomas can be discriminated from non-metastatic carcinomas by their gene expression profiles. More than one third of the differentially expressed genes are also described of relevance for human breast cancer. Many of the differentially expressed genes are linked to functions and pathways which appear to be relevant for the induction and maintenance of metastatic progression and may represent new therapeutic targets. Furthermore, dogs

  2. Gene Expression Profiling of Gastric Cancer

    PubMed Central

    Marimuthu, Arivusudar; Jacob, Harrys K.C.; Jakharia, Aniruddha; Subbannayya, Yashwanth; Keerthikumar, Shivakumar; Kashyap, Manoj Kumar; Goel, Renu; Balakrishnan, Lavanya; Dwivedi, Sutopa; Pathare, Swapnali; Dikshit, Jyoti Bajpai; Maharudraiah, Jagadeesha; Singh, Sujay; Sameer Kumar, Ghantasala S; Vijayakumar, M.; Veerendra Kumar, Kariyanakatte Veeraiah; Premalatha, Chennagiri Shrinivasamurthy; Tata, Pramila; Hariharan, Ramesh; Roa, Juan Carlos; Prasad, T.S.K; Chaerkady, Raghothama; Kumar, Rekha Vijay; Pandey, Akhilesh

    2015-01-01

    Gastric cancer is the second leading cause of cancer death worldwide, both in men and women. A genomewide gene expression analysis was carried out to identify differentially expressed genes in gastric adenocarcinoma tissues as compared to adjacent normal tissues. We used Agilent’s whole human genome oligonucleotide microarray platform representing ~41,000 genes to carry out gene expression analysis. Two-color microarray analysis was employed to directly compare the expression of genes between tumor and normal tissues. Through this approach, we identified several previously known candidate genes along with a number of novel candidate genes in gastric cancer. Testican-1 (SPOCK1) was one of the novel molecules that was 10-fold upregulated in tumors. Using tissue microarrays, we validated the expression of testican-1 by immunohistochemical staining. It was overexpressed in 56% (160/282) of the cases tested. Pathway analysis led to the identification of several networks in which SPOCK1 was among the topmost networks of interacting genes. By gene enrichment analysis, we identified several genes involved in cell adhesion and cell proliferation to be significantly upregulated while those corresponding to metabolic pathways were significantly downregulated. The differentially expressed genes identified in this study are candidate biomarkers for gastric adenoacarcinoma. PMID:27030788

  3. GTA: a game theoretic approach to identifying cancer subnetwork markers.

    PubMed

    Farahmand, S; Goliaei, S; Ansari-Pour, N; Razaghi-Moghadam, Z

    2016-03-01

    The identification of genetic markers (e.g. genes, pathways and subnetworks) for cancer has been one of the most challenging research areas in recent years. A subset of these studies attempt to analyze genome-wide expression profiles to identify markers with high reliability and reusability across independent whole-transcriptome microarray datasets. Therefore, the functional relationships of genes are integrated with their expression data. However, for a more accurate representation of the functional relationships among genes, utilization of the protein-protein interaction network (PPIN) seems to be necessary. Herein, a novel game theoretic approach (GTA) is proposed for the identification of cancer subnetwork markers by integrating genome-wide expression profiles and PPIN. The GTA method was applied to three distinct whole-transcriptome breast cancer datasets to identify the subnetwork markers associated with metastasis. To evaluate the performance of our approach, the identified subnetwork markers were compared with gene-based, pathway-based and network-based markers. We show that GTA is not only capable of identifying robust metastatic markers, it also provides a higher classification performance. In addition, based on these GTA-based subnetworks, we identified a new bonafide candidate gene for breast cancer susceptibility.

  4. Identifying clinically relevant drug resistance genes in drug-induced resistant cancer cell lines and post- chemotherapy tissues

    PubMed Central

    Tong, Mengsha; Zheng, Weicheng; Lu, Xingrong; Ao, Lu; Li, Xiangyu; Guan, Qingzhou; Cai, Hao; Li, Mengyao; Yan, Haidan; Guo, You; Chi, Pan; Guo, Zheng

    2015-01-01

    Until recently, few molecular signatures of drug resistance identified in drug-induced resistant cancer cell models can be translated into clinical practice. Here, we defined differentially expressed genes (DEGs) between pre-chemotherapy colorectal cancer (CRC) tissue samples of non-responders and responders for 5-fluorouracil and oxaliplatin-based therapy as clinically relevant drug resistance genes (CRG5-FU/L-OHP). Taking CRG5-FU/L-OHP as reference, we evaluated the clinical relevance of several types of genes derived from HCT116 CRC cells with resistance to 5-fluorouracil and oxaliplatin, respectively. The results revealed that DEGs between parental and resistant cells, when both were treated with the corresponding drug for a certain time, were significantly consistent with the CRG5-FU/L-OHP as well as the DEGs between the post-chemotherapy CRC specimens of responders and non-responders. This study suggests a novel strategy to extract clinically relevant drug resistance genes from both drug-induced resistant cell models and post-chemotherapy cancer tissue specimens. PMID:26515599

  5. Gene panel sequencing in familial breast/ovarian cancer patients identifies multiple novel mutations also in genes others than BRCA1/2.

    PubMed

    Kraus, Cornelia; Hoyer, Juliane; Vasileiou, Georgia; Wunderle, Marius; Lux, Michael P; Fasching, Peter A; Krumbiegel, Mandy; Uebe, Steffen; Reuter, Miriam; Beckmann, Matthias W; Reis, André

    2017-01-01

    Breast and ovarian cancer (BC/OC) predisposition has been attributed to a number of high- and moderate to low-penetrance susceptibility genes. With the advent of next generation sequencing (NGS) simultaneous testing of these genes has become feasible. In this monocentric study, we report results of panel-based screening of 14 BC/OC susceptibility genes (BRCA1, BRCA2, RAD51C, RAD51D, CHEK2, PALB2, ATM, NBN, CDH1, TP53, MLH1, MSH2, MSH6 and PMS2) in a group of 581 consecutive individuals from a German population with BC and/or OC fulfilling diagnostic criteria for BRCA1 and BRCA2 testing including 179 with a triple-negative tumor. Altogether we identified 106 deleterious mutations in 105 (18%) patients in 10 different genes, including seven different exon deletions. Of these 106 mutations, 16 (15%) were novel and only six were found in BRCA1/2. To further characterize mutations located in or nearby splicing consensus sites we performed RT-PCR analysis which allowed confirmation of pathogenicity in 7 of 9 mutations analyzed. In PALB2, we identified a deleterious variant in six cases. All but one were associated with early onset BC and a positive family history indicating that penetrance for PALB2 mutations is comparable to BRCA2. Overall, extended testing beyond BRCA1/2 identified a deleterious mutation in further 6% of patients. As a downside, 89 variants of uncertain significance were identified highlighting the need for comprehensive variant databases. In conclusion, panel testing yields more accurate information on genetic cancer risk than assessing BRCA1/2 alone and wide-spread testing will help improve penetrance assessment of variants in these risk genes. © 2016 UICC.

  6. Germline whole exome sequencing and large-scale replication identifies FANCM as a likely high grade serous ovarian cancer susceptibility gene.

    PubMed

    Dicks, Ed; Song, Honglin; Ramus, Susan J; Oudenhove, Elke Van; Tyrer, Jonathan P; Intermaggio, Maria P; Kar, Siddhartha; Harrington, Patricia; Bowtell, David D; Group, Aocs Study; Cicek, Mine S; Cunningham, Julie M; Fridley, Brooke L; Alsop, Jennifer; Jimenez-Linan, Mercedes; Piskorz, Anna; Goranova, Teodora; Kent, Emma; Siddiqui, Nadeem; Paul, James; Crawford, Robin; Poblete, Samantha; Lele, Shashi; Sucheston-Campbell, Lara; Moysich, Kirsten B; Sieh, Weiva; McGuire, Valerie; Lester, Jenny; Odunsi, Kunle; Whittemore, Alice S; Bogdanova, Natalia; Dürst, Matthias; Hillemanns, Peter; Karlan, Beth Y; Gentry-Maharaj, Aleksandra; Menon, Usha; Tischkowitz, Marc; Levine, Douglas; Brenton, James D; Dörk, Thilo; Goode, Ellen L; Gayther, Simon A; Pharoah, D P Paul

    2017-08-01

    We analyzed whole exome sequencing data in germline DNA from 412 high grade serous ovarian cancer (HGSOC) cases from The Cancer Genome Atlas Project and identified 5,517 genes harboring a predicted deleterious germline coding mutation in at least one HGSOC case. Gene-set enrichment analysis showed enrichment for genes involved in DNA repair (p = 1.8×10 -3 ). Twelve DNA repair genes - APEX1, APLF, ATX, EME1, FANCL, FANCM, MAD2L2, PARP2, PARP3, POLN, RAD54L and SMUG1 - were prioritized for targeted sequencing in up to 3,107 HGSOC cases, 1,491 cases of other epithelial ovarian cancer (EOC) subtypes and 3,368 unaffected controls of European origin. We estimated mutation prevalence for each gene and tested for associations with disease risk. Mutations were identified in both cases and controls in all genes except MAD2L2 , where we found no evidence of mutations in controls. In FANCM we observed a higher mutation frequency in HGSOC cases compared to controls (29/3,107 cases, 0.96 percent; 13/3,368 controls, 0.38 percent; P=0.008) with little evidence for association with other subtypes (6/1,491, 0.40 percent; P=0.82). The relative risk of HGSOC associated with deleterious FANCM mutations was estimated to be 2.5 (95% CI 1.3 - 5.0; P=0.006). In summary, whole exome sequencing of EOC cases with large-scale replication in case-control studies has identified FANCM as a likely novel susceptibility gene for HGSOC, with mutations associated with a moderate increase in risk. These data may have clinical implications for risk prediction and prevention approaches for high-grade serous ovarian cancer in the future and a significant impact on reducing disease mortality.

  7. Functional genomics identifies specific vulnerabilities in PTEN-deficient breast cancer.

    PubMed

    Tang, Yew Chung; Ho, Szu-Chi; Tan, Elisabeth; Ng, Alvin Wei Tian; McPherson, John R; Goh, Germaine Yen Lin; Teh, Bin Tean; Bard, Frederic; Rozen, Steven G

    2018-03-22

    Phosphatase and tensin homolog (PTEN) is one of the most frequently inactivated tumor suppressors in breast cancer. While PTEN itself is not considered a druggable target, PTEN synthetic-sick or synthetic-lethal (PTEN-SSL) genes are potential drug targets in PTEN-deficient breast cancers. Therefore, with the aim of identifying potential targets for precision breast cancer therapy, we sought to discover PTEN-SSL genes present in a broad spectrum of breast cancers. To discover broad-spectrum PTEN-SSL genes in breast cancer, we used a multi-step approach that started with (1) a genome-wide short interfering RNA (siRNA) screen of ~ 21,000 genes in a pair of isogenic human mammary epithelial cell lines, followed by (2) a short hairpin RNA (shRNA) screen of ~ 1200 genes focused on hits from the first screen in a panel of 11 breast cancer cell lines; we then determined reproducibility of hits by (3) identification of overlaps between our results and reanalyzed data from 3 independent gene-essentiality screens, and finally, for selected candidate PTEN-SSL genes we (4) confirmed PTEN-SSL activity using either drug sensitivity experiments in a panel of 19 cell lines or mutual exclusivity analysis of publicly available pan-cancer somatic mutation data. The screens (steps 1 and 2) and the reproducibility analysis (step 3) identified six candidate broad-spectrum PTEN-SSL genes (PIK3CB, ADAMTS20, AP1M2, HMMR, STK11, and NUAK1). PIK3CB was previously identified as PTEN-SSL, while the other five genes represent novel PTEN-SSL candidates. Confirmation studies (step 4) provided additional evidence that NUAK1 and STK11 have PTEN-SSL patterns of activity. Consistent with PTEN-SSL status, inhibition of the NUAK1 protein kinase by the small molecule drug HTH-01-015 selectively impaired viability in multiple PTEN-deficient breast cancer cell lines, while mutations affecting STK11 and PTEN were largely mutually exclusive across large pan-cancer data sets. Six genes showed PTEN

  8. integIRTy: a method to identify genes altered in cancer by accounting for multiple mechanisms of regulation using item response theory.

    PubMed

    Tong, Pan; Coombes, Kevin R

    2012-11-15

    Identifying genes altered in cancer plays a crucial role in both understanding the mechanism of carcinogenesis and developing novel therapeutics. It is known that there are various mechanisms of regulation that can lead to gene dysfunction, including copy number change, methylation, abnormal expression, mutation and so on. Nowadays, all these types of alterations can be simultaneously interrogated by different types of assays. Although many methods have been proposed to identify altered genes from a single assay, there is no method that can deal with multiple assays accounting for different alteration types systematically. In this article, we propose a novel method, integration using item response theory (integIRTy), to identify altered genes by using item response theory that allows integrated analysis of multiple high-throughput assays. When applied to a single assay, the proposed method is more robust and reliable than conventional methods such as Student's t-test or the Wilcoxon rank-sum test. When used to integrate multiple assays, integIRTy can identify novel-altered genes that cannot be found by looking at individual assay separately. We applied integIRTy to three public cancer datasets (ovarian carcinoma, breast cancer, glioblastoma) for cross-assay type integration which all show encouraging results. The R package integIRTy is available at the web site http://bioinformatics.mdanderson.org/main/OOMPA:Overview. kcoombes@mdanderson.org. Supplementary data are available at Bioinformatics online.

  9. Cancer Genes in Lung Cancer

    PubMed Central

    El-Telbany, Ahmed

    2012-01-01

    Cancer is now known as a disease of genomic alterations. Mutational analysis and genomics profiling in recent years have advanced the field of lung cancer genetics/genomics significantly. It is becoming more accepted now that the identification of genomic alterations in lung cancer can impact therapeutics, especially when the alterations represent “oncogenic drivers” in the processes of tumorigenesis and progression. In this review, we will highlight the key driver oncogenic gene mutations and fusions identified in lung cancer. The review will summarize and report the available demographic and clinicopathological data as well as molecular details behind various lung cancer gene alterations in the context of race. We hope to shed some light into the disparities in the incidence of various genetic mutations among lung cancer patients of different racial backgrounds. As molecularly targeted therapy continues to advance in lung cancer, racial differences in specific genetic/genomic alterations can have an important impact in the choices of therapeutics and in our understanding of the drug sensitivity/resistance profile. The most relevant genes in lung cancer described in this review include the following: EGFR, KRAS, MET, LKB1, BRAF, PIK3CA, ALK, RET, and ROS1. Commonly identified genetic/genomic alterations such as missense or nonsense mutations, small insertions or deletions, alternative splicing, and chromosomal fusion rearrangements were discussed. Relevance in current targeted therapeutic drugs was mentioned when appropriate. We also highlighted various targeted therapeutics that are currently under clinical development, such as the MET inhibitors and antibodies. With the advent of next-generation sequencing, the landscape of genomic alterations in lung cancer is expected to be much transformed and detailed in upcoming years. These genomic landscape differences in the context of racial disparities should be emphasized both in tumorigenesis and in drug

  10. LNDriver: identifying driver genes by integrating mutation and expression data based on gene-gene interaction network.

    PubMed

    Wei, Pi-Jing; Zhang, Di; Xia, Junfeng; Zheng, Chun-Hou

    2016-12-23

    Cancer is a complex disease which is characterized by the accumulation of genetic alterations during the patient's lifetime. With the development of the next-generation sequencing technology, multiple omics data, such as cancer genomic, epigenomic and transcriptomic data etc., can be measured from each individual. Correspondingly, one of the key challenges is to pinpoint functional driver mutations or pathways, which contributes to tumorigenesis, from millions of functional neutral passenger mutations. In this paper, in order to identify driver genes effectively, we applied a generalized additive model to mutation profiles to filter genes with long length and constructed a new gene-gene interaction network. Then we integrated the mutation data and expression data into the gene-gene interaction network. Lastly, greedy algorithm was used to prioritize candidate driver genes from the integrated data. We named the proposed method Length-Net-Driver (LNDriver). Experiments on three TCGA datasets, i.e., head and neck squamous cell carcinoma, kidney renal clear cell carcinoma and thyroid carcinoma, demonstrated that the proposed method was effective. Also, it can identify not only frequently mutated drivers, but also rare candidate driver genes.

  11. Identification of druggable cancer driver genes amplified across TCGA datasets.

    PubMed

    Chen, Ying; McGee, Jeremy; Chen, Xianming; Doman, Thompson N; Gong, Xueqian; Zhang, Youyan; Hamm, Nicole; Ma, Xiwen; Higgs, Richard E; Bhagwat, Shripad V; Buchanan, Sean; Peng, Sheng-Bin; Staschke, Kirk A; Yadav, Vipin; Yue, Yong; Kouros-Mehr, Hosein

    2014-01-01

    The Cancer Genome Atlas (TCGA) projects have advanced our understanding of the driver mutations, genetic backgrounds, and key pathways activated across cancer types. Analysis of TCGA datasets have mostly focused on somatic mutations and translocations, with less emphasis placed on gene amplifications. Here we describe a bioinformatics screening strategy to identify putative cancer driver genes amplified across TCGA datasets. We carried out GISTIC2 analysis of TCGA datasets spanning 16 cancer subtypes and identified 486 genes that were amplified in two or more datasets. The list was narrowed to 75 cancer-associated genes with potential "druggable" properties. The majority of the genes were localized to 14 amplicons spread across the genome. To identify potential cancer driver genes, we analyzed gene copy number and mRNA expression data from individual patient samples and identified 42 putative cancer driver genes linked to diverse oncogenic processes. Oncogenic activity was further validated by siRNA/shRNA knockdown and by referencing the Project Achilles datasets. The amplified genes represented a number of gene families, including epigenetic regulators, cell cycle-associated genes, DNA damage response/repair genes, metabolic regulators, and genes linked to the Wnt, Notch, Hedgehog, JAK/STAT, NF-KB and MAPK signaling pathways. Among the 42 putative driver genes were known driver genes, such as EGFR, ERBB2 and PIK3CA. Wild-type KRAS was amplified in several cancer types, and KRAS-amplified cancer cell lines were most sensitive to KRAS shRNA, suggesting that KRAS amplification was an independent oncogenic event. A number of MAP kinase adapters were co-amplified with their receptor tyrosine kinases, such as the FGFR adapter FRS2 and the EGFR family adapters GRB2 and GRB7. The ubiquitin-like ligase DCUN1D1 and the histone methyltransferase NSD3 were also identified as novel putative cancer driver genes. We discuss the patient tailoring implications for existing cancer

  12. Identification of Druggable Cancer Driver Genes Amplified across TCGA Datasets

    PubMed Central

    Chen, Ying; McGee, Jeremy; Chen, Xianming; Doman, Thompson N.; Gong, Xueqian; Zhang, Youyan; Hamm, Nicole; Ma, Xiwen; Higgs, Richard E.; Bhagwat, Shripad V.; Buchanan, Sean; Peng, Sheng-Bin; Staschke, Kirk A.; Yadav, Vipin; Yue, Yong; Kouros-Mehr, Hosein

    2014-01-01

    The Cancer Genome Atlas (TCGA) projects have advanced our understanding of the driver mutations, genetic backgrounds, and key pathways activated across cancer types. Analysis of TCGA datasets have mostly focused on somatic mutations and translocations, with less emphasis placed on gene amplifications. Here we describe a bioinformatics screening strategy to identify putative cancer driver genes amplified across TCGA datasets. We carried out GISTIC2 analysis of TCGA datasets spanning 14 cancer subtypes and identified 461 genes that were amplified in two or more datasets. The list was narrowed to 73 cancer-associated genes with potential “druggable” properties. The majority of the genes were localized to 14 amplicons spread across the genome. To identify potential cancer driver genes, we analyzed gene copy number and mRNA expression data from individual patient samples and identified 40 putative cancer driver genes linked to diverse oncogenic processes. Oncogenic activity was further validated by siRNA/shRNA knockdown and by referencing the Project Achilles datasets. The amplified genes represented a number of gene families, including epigenetic regulators, cell cycle-associated genes, DNA damage response/repair genes, metabolic regulators, and genes linked to the Wnt, Notch, Hedgehog, JAK/STAT, NF-KB and MAPK signaling pathways. Among the 40 putative driver genes were known driver genes, such as EGFR, ERBB2 and PIK3CA. Wild-type KRAS was amplified in several cancer types, and KRAS-amplified cancer cell lines were most sensitive to KRAS shRNA, suggesting that KRAS amplification was an independent oncogenic event. A number of MAP kinase adapters were co-amplified with their receptor tyrosine kinases, such as the FGFR adapter FRS2 and the EGFR family adapter GRB7. The ubiquitin-like ligase DCUN1D1 and the histone methyltransferase NSD3 were also identified as novel putative cancer driver genes. We discuss the patient tailoring implications for existing cancer drug

  13. Cancer gene discovery: exploiting insertional mutagenesis

    PubMed Central

    Ranzani, Marco; Annunziato, Stefano; Adams, David J.; Montini, Eugenio

    2013-01-01

    Insertional mutagenesis has been utilized as a functional forward genetics screen for the identification of novel genes involved in the pathogenesis of human cancers. Different insertional mutagens have been successfully used to reveal new cancer genes. For example, retroviruses (RVs) are integrating viruses with the capacity to induce the deregulation of genes in the neighborhood of the insertion site. RVs have been employed for more than 30 years to identify cancer genes in the hematopoietic system and mammary gland. Similarly, another tool that has revolutionized cancer gene discovery is the cut-and-paste transposons. These DNA elements have been engineered to contain strong promoters and stop cassettes that may function to perturb gene expression upon integration proximal to genes. In addition, complex mouse models characterized by tissue-restricted activity of transposons have been developed to identify oncogenes and tumor suppressor genes that control the development of a wide range of solid tumor types, extending beyond those tissues accessible using RV-based approaches. Most recently, lentiviral vectors (LVs) have appeared on the scene for use in cancer gene screens. LVs are replication defective integrating vectors that have the advantage of being able to infect non-dividing cells, in a wide range of cell types and tissues. In this review, we describe the various insertional mutagens focusing on their advantages/limitations and we discuss the new and promising tools that will improve the insertional mutagenesis screens of the future. PMID:23928056

  14. Identifying module biomarkers from gastric cancer by differential correlation network

    PubMed Central

    Liu, Xiaoping; Chang, Xiao

    2016-01-01

    Gastric cancer (stomach cancer) is a severe disease caused by dysregulation of many functionally correlated genes or pathways instead of the mutation of individual genes. Systematic identification of gastric cancer biomarkers can provide insights into the mechanisms underlying this deadly disease and help in the development of new drugs. In this paper, we present a novel network-based approach to predict module biomarkers of gastric cancer that can effectively distinguish the disease from normal samples. Specifically, by assuming that gastric cancer has mainly resulted from dysfunction of biomolecular networks rather than individual genes in an organism, the genes in the module biomarkers are potentially related to gastric cancer. Finally, we identified a module biomarker with 27 genes, and by comparing the module biomarker with known gastric cancer biomarkers, we found that our module biomarker exhibited a greater ability to diagnose the samples with gastric cancer. PMID:27703371

  15. A large-scale RNA interference screen identifies genes that regulate autophagy at different stages.

    PubMed

    Guo, Sujuan; Pridham, Kevin J; Virbasius, Ching-Man; He, Bin; Zhang, Liqing; Varmark, Hanne; Green, Michael R; Sheng, Zhi

    2018-02-12

    Dysregulated autophagy is central to the pathogenesis and therapeutic development of cancer. However, how autophagy is regulated in cancer is not well understood and genes that modulate cancer autophagy are not fully defined. To gain more insights into autophagy regulation in cancer, we performed a large-scale RNA interference screen in K562 human chronic myeloid leukemia cells using monodansylcadaverine staining, an autophagy-detecting approach equivalent to immunoblotting of the autophagy marker LC3B or fluorescence microscopy of GFP-LC3B. By coupling monodansylcadaverine staining with fluorescence-activated cell sorting, we successfully isolated autophagic K562 cells where we identified 336 short hairpin RNAs. After candidate validation using Cyto-ID fluorescence spectrophotometry, LC3B immunoblotting, and quantitative RT-PCR, 82 genes were identified as autophagy-regulating genes. 20 genes have been reported previously and the remaining 62 candidates are novel autophagy mediators. Bioinformatic analyses revealed that most candidate genes were involved in molecular pathways regulating autophagy, rather than directly participating in the autophagy process. Further autophagy flux assays revealed that 57 autophagy-regulating genes suppressed autophagy initiation, whereas 21 candidates promoted autophagy maturation. Our RNA interference screen identifies identified genes that regulate autophagy at different stages, which helps decode autophagy regulation in cancer and offers novel avenues to develop autophagy-related therapies for cancer.

  16. Applying Multivariate Adaptive Splines to Identify Genes With Expressions Varying After Diagnosis in Microarray Experiments.

    PubMed

    Duan, Fenghai; Xu, Ye

    2017-01-01

    To analyze a microarray experiment to identify the genes with expressions varying after the diagnosis of breast cancer. A total of 44 928 probe sets in an Affymetrix microarray data publicly available on Gene Expression Omnibus from 249 patients with breast cancer were analyzed by the nonparametric multivariate adaptive splines. Then, the identified genes with turning points were grouped by K-means clustering, and their network relationship was subsequently analyzed by the Ingenuity Pathway Analysis. In total, 1640 probe sets (genes) were reliably identified to have turning points along with the age at diagnosis in their expression profiling, of which 927 expressed lower after turning points and 713 expressed higher after the turning points. K-means clustered them into 3 groups with turning points centering at 54, 62.5, and 72, respectively. The pathway analysis showed that the identified genes were actively involved in various cancer-related functions or networks. In this article, we applied the nonparametric multivariate adaptive splines method to a publicly available gene expression data and successfully identified genes with expressions varying before and after breast cancer diagnosis.

  17. Inferring causal genomic alterations in breast cancer using gene expression data

    PubMed Central

    2011-01-01

    Background One of the primary objectives in cancer research is to identify causal genomic alterations, such as somatic copy number variation (CNV) and somatic mutations, during tumor development. Many valuable studies lack genomic data to detect CNV; therefore, methods that are able to infer CNVs from gene expression data would help maximize the value of these studies. Results We developed a framework for identifying recurrent regions of CNV and distinguishing the cancer driver genes from the passenger genes in the regions. By inferring CNV regions across many datasets we were able to identify 109 recurrent amplified/deleted CNV regions. Many of these regions are enriched for genes involved in many important processes associated with tumorigenesis and cancer progression. Genes in these recurrent CNV regions were then examined in the context of gene regulatory networks to prioritize putative cancer driver genes. The cancer driver genes uncovered by the framework include not only well-known oncogenes but also a number of novel cancer susceptibility genes validated via siRNA experiments. Conclusions To our knowledge, this is the first effort to systematically identify and validate drivers for expression based CNV regions in breast cancer. The framework where the wavelet analysis of copy number alteration based on expression coupled with the gene regulatory network analysis, provides a blueprint for leveraging genomic data to identify key regulatory components and gene targets. This integrative approach can be applied to many other large-scale gene expression studies and other novel types of cancer data such as next-generation sequencing based expression (RNA-Seq) as well as CNV data. PMID:21806811

  18. The application of artificial intelligence to microarray data: identification of a novel gene signature to identify bladder cancer progression.

    PubMed

    Catto, James W F; Abbod, Maysam F; Wild, Peter J; Linkens, Derek A; Pilarsky, Christian; Rehman, Ishtiaq; Rosario, Derek J; Denzinger, Stefan; Burger, Maximilian; Stoehr, Robert; Knuechel, Ruth; Hartmann, Arndt; Hamdy, Freddie C

    2010-03-01

    New methods for identifying bladder cancer (BCa) progression are required. Gene expression microarrays can reveal insights into disease biology and identify novel biomarkers. However, these experiments produce large datasets that are difficult to interpret. To develop a novel method of microarray analysis combining two forms of artificial intelligence (AI): neurofuzzy modelling (NFM) and artificial neural networks (ANN) and validate it in a BCa cohort. We used AI and statistical analyses to identify progression-related genes in a microarray dataset (n=66 tumours, n=2800 genes). The AI-selected genes were then investigated in a second cohort (n=262 tumours) using immunohistochemistry. We compared the accuracy of AI and statistical approaches to identify tumour progression. AI identified 11 progression-associated genes (odds ratio [OR]: 0.70; 95% confidence interval [CI], 0.56-0.87; p=0.0004), and these were more discriminate than genes chosen using statistical analyses (OR: 1.24; 95% CI, 0.96-1.60; p=0.09). The expression of six AI-selected genes (LIG3, FAS, KRT18, ICAM1, DSG2, and BRCA2) was determined using commercial antibodies and successfully identified tumour progression (concordance index: 0.66; log-rank test: p=0.01). AI-selected genes were more discriminate than pathologic criteria at determining progression (Cox multivariate analysis: p=0.01). Limitations include the use of statistical correlation to identify 200 genes for AI analysis and that we did not compare regression identified genes with immunohistochemistry. AI and statistical analyses use different techniques of inference to determine gene-phenotype associations and identify distinct prognostic gene signatures that are equally valid. We have identified a prognostic gene signature whose members reflect a variety of carcinogenic pathways that could identify progression in non-muscle-invasive BCa. 2009 European Association of Urology. Published by Elsevier B.V. All rights reserved.

  19. Comprehensive Characterization of Cancer Driver Genes and Mutations.

    PubMed

    Bailey, Matthew H; Tokheim, Collin; Porta-Pardo, Eduard; Sengupta, Sohini; Bertrand, Denis; Weerasinghe, Amila; Colaprico, Antonio; Wendl, Michael C; Kim, Jaegil; Reardon, Brendan; Ng, Patrick Kwok-Shing; Jeong, Kang Jin; Cao, Song; Wang, Zixing; Gao, Jianjiong; Gao, Qingsong; Wang, Fang; Liu, Eric Minwei; Mularoni, Loris; Rubio-Perez, Carlota; Nagarajan, Niranjan; Cortés-Ciriano, Isidro; Zhou, Daniel Cui; Liang, Wen-Wei; Hess, Julian M; Yellapantula, Venkata D; Tamborero, David; Gonzalez-Perez, Abel; Suphavilai, Chayaporn; Ko, Jia Yu; Khurana, Ekta; Park, Peter J; Van Allen, Eliezer M; Liang, Han; Lawrence, Michael S; Godzik, Adam; Lopez-Bigas, Nuria; Stuart, Josh; Wheeler, David; Getz, Gad; Chen, Ken; Lazar, Alexander J; Mills, Gordon B; Karchin, Rachel; Ding, Li

    2018-04-05

    Identifying molecular cancer drivers is critical for precision oncology. Multiple advanced algorithms to identify drivers now exist, but systematic attempts to combine and optimize them on large datasets are few. We report a PanCancer and PanSoftware analysis spanning 9,423 tumor exomes (comprising all 33 of The Cancer Genome Atlas projects) and using 26 computational tools to catalog driver genes and mutations. We identify 299 driver genes with implications regarding their anatomical sites and cancer/cell types. Sequence- and structure-based analyses identified >3,400 putative missense driver mutations supported by multiple lines of evidence. Experimental validation confirmed 60%-85% of predicted mutations as likely drivers. We found that >300 MSI tumors are associated with high PD-1/PD-L1, and 57% of tumors analyzed harbor putative clinically actionable events. Our study represents the most comprehensive discovery of cancer genes and mutations to date and will serve as a blueprint for future biological and clinical endeavors. Published by Elsevier Inc.

  20. A DNA methylation microarray-based study identifies ERG as a gene commonly methylated in prostate cancer.

    PubMed

    Schwartzman, Jacob; Mongoue-Tchokote, Solange; Gibbs, Angela; Gao, Lina; Corless, Christopher L; Jin, Jennifer; Zarour, Luai; Higano, Celestia; True, Lawrence D; Vessella, Robert L; Wilmot, Beth; Bottomly, Daniel; McWeeney, Shannon K; Bova, G Steven; Partin, Alan W; Mori, Motomi; Alumkal, Joshi

    2011-10-01

    DNA methylation of promoter regions is a common event in prostate cancer, one of the most common cancers in men worldwide. Because prior reports demonstrating that DNA methylation is important in prostate cancer studied a limited number of genes, we systematically quantified the DNA methylation status of 1505 CpG dinucleotides for 807 genes in 78 paraffin-embedded prostate cancer samples and three normal prostate samples. The ERG gene, commonly repressed in prostate cells in the absence of an oncogenic fusion to the TMPRSS2 gene, was one of the most commonly methylated genes, occurring in 74% of prostate cancer specimens. In an independent group of patient samples, we confirmed that ERG DNA methylation was common, occurring in 57% of specimens, and cancer-specific. The ERG promoter is marked by repressive chromatin marks mediated by polycomb proteins in both normal prostate cells and prostate cancer cells, which may explain ERG's predisposition to DNA methylation and the fact that tumors with ERG DNA methylation were more methylated, in general. These results demonstrate that bead arrays offer a high-throughput method to discover novel genes with promoter DNA methylation such as ERG, whose measurement may improve our ability to more accurately detect prostate cancer.

  1. Visual gene-network analysis reveals the cancer gene co-expression in human endometrial cancer

    PubMed Central

    2014-01-01

    Background Endometrial cancers (ECs) are the most common form of gynecologic malignancy. Recent studies have reported that ECs reveal distinct markers for molecular pathogenesis, which in turn is linked to the various histological types of ECs. To understand further the molecular events contributing to ECs and endometrial tumorigenesis in general, a more precise identification of cancer-associated molecules and signaling networks would be useful for the detection and monitoring of malignancy, improving clinical cancer therapy, and personalization of treatments. Results ECs-specific gene co-expression networks were constructed by differential expression analysis and weighted gene co-expression network analysis (WGCNA). Important pathways and putative cancer hub genes contribution to tumorigenesis of ECs were identified. An elastic-net regularized classification model was built using the cancer hub gene signatures to predict the phenotypic characteristics of ECs. The 19 cancer hub gene signatures had high predictive power to distinguish among three key principal features of ECs: grade, type, and stage. Intriguingly, these hub gene networks seem to contribute to ECs progression and malignancy via cell-cycle regulation, antigen processing and the citric acid (TCA) cycle. Conclusions The results of this study provide a powerful biomarker discovery platform to better understand the progression of ECs and to uncover potential therapeutic targets in the treatment of ECs. This information might lead to improved monitoring of ECs and resulting improvement of treatment of ECs, the 4th most common of cancer in women. PMID:24758163

  2. Predicting hepatocellular carcinoma through cross-talk genes identified by risk pathways

    PubMed Central

    Shao, Zhuo; Huo, Diwei; Zhang, Denan; Xie, Hongbo; Yang, Jingbo; Liu, Qiuqi; Chen, Xiujie

    2018-01-01

    Hepatocellular carcinoma (HCC) is the most frequent type of liver cancer with poor survival rate and high mortality. Despite efforts on the mechanism of HCC, new molecular markers are needed for exact diagnosis, evaluation and treatment. Here, we combined transcriptome of HCC with networks and pathways to identify reliable molecular markers. Through integrating 249 differentially expressed genes with syncretic protein interaction networks, we constructed a HCC-specific network, from which we further extracted 480 pivotal genes. Based on the cross-talk between the enriched pathways of the pivotal genes, we finally identified a HCC signature of 45 genes, which could accurately distinguish HCC patients with normal individuals and reveal the prognosis of HCC patients. Among these 45 genes, 15 showed dysregulated expression patterns and a part have been reported to be associated with HCC and/or other cancers. These findings suggested that our identified 45 gene signature could be potential and valuable molecular markers for diagnosis and evaluation of HCC. PMID:29765536

  3. Impact of homeobox genes in gastrointestinal cancer.

    PubMed

    Joo, Moon Kyung; Park, Jong-Jae; Chun, Hoon Jai

    2016-10-07

    Homeobox genes, including HOX and non- HOX genes, have been identified to be expressed aberrantly in solid tumors. In gastrointestinal (GI) cancers, most studies have focused on the function of non- HOX genes including caudal-related homeobox transcription factor 1 (CDX1) and CDX2. CDX2 is a crucial factor in the development of pre-cancerous lesions such as Barrett's esophagus or intestinal metaplasia in the stomach, and its tumor suppressive role has been investigated in colorectal cancers. Recently, several HOX genes were reported to have specific roles in GI cancers; for example, HOXA13 in esophageal squamous cell cancer and HOXB7 in stomach and colorectal cancers. HOXD10 is upregulated in colorectal cancer while it is silenced epigenetically in gastric cancer. Thus, it is essential to examine the differential expression pattern of various homeobox genes in specific tumor types or cell lineages, and understand their underlying mechanisms. In this review, we summarize the available research on homeobox genes and present their potential value for the prediction of prognosis in GI cancers.

  4. Targeting gene expression selectively in cancer cells by using the progression-elevated gene-3 promoter.

    PubMed

    Su, Zhao-Zhong; Sarkar, Devanand; Emdad, Luni; Duigou, Gregory J; Young, Charles S H; Ware, Joy; Randolph, Aaron; Valerie, Kristoffer; Fisher, Paul B

    2005-01-25

    One impediment to effective cancer-specific gene therapy is the rarity of regulatory sequences targeting gene expression selectively in tumor cells. Although many tissue-specific promoters are recognized, few cancer-selective gene promoters are available. Progression-elevated gene-3 (PEG-3) is a rodent gene identified by subtraction hybridization that displays elevated expression as a function of transformation by diversely acting oncogenes, DNA damage, and cancer cell progression. The promoter of PEG-3, PEG-Prom, displays robust expression in a broad spectrum of human cancer cell lines with marginal expression in normal cellular counterparts. Whereas GFP expression, when under the control of a CMV promoter, is detected in both normal and cancer cells, when GFP is expressed under the control of the PEG-Prom, cancer-selective expression is evident. Mutational analysis identifies the AP-1 and PEA-3 transcription factors as primary mediators of selective, cancer-specific expression of the PEG-Prom. Synthesis of apoptosis-inducing genes, under the control of the CMV promoter, inhibits the growth of both normal and cancer cells, whereas PEG-Prom-mediated expression of these genes kills only cancer cells and spares normal cells. The efficacy of the PEG-Prom as part of a cancer gene therapeutic regimen is further documented by in vivo experiments in which PEG-Prom-controlled expression of an apoptosis-inducing gene completely inhibited prostate cancer xenograft growth in nude mice. These compelling observations indicate that the PEG-Prom, with its cancer-specific expression, provides a means of selectively delivering genes to cancer cells, thereby providing a crucial component in developing effective cancer gene therapies.

  5. Nearing saturation of cancer driver gene discovery.

    PubMed

    Hsiehchen, David; Hsieh, Antony

    2018-06-15

    Extensive sequencing efforts of cancer genomes such as The Cancer Genome Atlas (TCGA) have been undertaken to uncover bona fide cancer driver genes which has enhanced our understanding of cancer and revealed therapeutic targets. However, the number of driver gene mutations is bounded, indicating that there must be a point when further sequencing efforts will be excessive. We found that there was a significant positive correlation between sample size and identified driver gene mutations across 33 cancers sequenced by the TCGA, which is expected if additional sequencing is still leading to the identification of more driver genes. However, the rate of new cancer driver genes being discovered with larger samples is declining rapidly. Our analysis provides a general guide for determining which cancer types would likely benefit from additional sequencing efforts, particularly those with relatively high rates of cancer driver gene discovery. Our results argue that past strategies of indiscriminately sequencing as many specimens as possible for all cancer types is becoming inefficient. In addition, without significant investments into applying our knowledge of cancer genomes, we risk sequencing more cancer genomes for the sake of sequencing rather than meaningful patient benefit.

  6. Global Gene Expression Profiles Identify Metastasis Regulatory Networks | Center for Cancer Research

    Cancer.gov

    Metastasis is a systemic disease in which cancer cells break away from a tumor and migrate to other parts of the body, usually via the blood or lymphatic systems, to form new tumors. Metastatic tumors are difficult to treat and account for the majority of cancer-related deaths. Susceptibility to metastasis is known to have a genetic component, with some individuals more predisposed than others. However, because of the complex interchange between random genomic and epigenetic events that contribute to the disease, characterization of individual genes or small numbers of genes is not sufficient to understand the processes leading up to metastasis.

  7. Identifying activating mutations in the EGFR gene: prognostic and therapeutic implications in non-small cell lung cancer *

    PubMed Central

    Lopes, Gabriel Lima; Vattimo, Edoardo Filippo de Queiroz; de Castro, Gilberto

    2015-01-01

    Abstract Lung cancer is the leading cause of cancer-related deaths worldwide. Promising new therapies have recently emerged from the development of molecular targeted drugs; particularly promising are those blocking the signal transduction machinery of cancer cells. One of the most widely studied cell signaling pathways is that of EGFR, which leads to uncontrolled cell proliferation, increased cell angiogenesis, and greater cell invasiveness. Activating mutations in the EGFR gene (deletions in exon 19 and mutation L858R in exon 21), first described in 2004, have been detected in approximately 10% of all non-squamous non-small cell lung cancer (NSCLC) patients in Western countries and are the most important predictors of a response to EGFR tyrosine-kinase inhibitors (EGFR-TKIs). Studies of the EGFR-TKIs gefitinib, erlotinib, and afatinib, in comparison with platinum-based regimens, as first-line treatments in chemotherapy-naïve patients have shown that the EGFR-TKIs produce gains in progression-free survival and overall response rates, although only in patients whose tumors harbor activating mutations in the EGFR gene. Clinical trials have also shown EGFR-TKIs to be effective as second- and third-line therapies in advanced NSCLC. Here, we review the main aspects of EGFR pathway activation in NSCLC, underscore the importance of correctly identifying activating mutations in the EGFR gene, and discuss the main outcomes of EGFR-TKI treatment in NSCLC. PMID:26398757

  8. Identifying activating mutations in the EGFR gene: prognostic and therapeutic implications in non-small cell lung cancer.

    PubMed

    Lopes, Gabriel Lima; Vattimo, Edoardo Filippo de Queiroz; Castro Junior, Gilberto de

    2015-01-01

    Lung cancer is the leading cause of cancer-related deaths worldwide. Promising new therapies have recently emerged from the development of molecular targeted drugs; particularly promising are those blocking the signal transduction machinery of cancer cells. One of the most widely studied cell signaling pathways is that of EGFR, which leads to uncontrolled cell proliferation, increased cell angiogenesis, and greater cell invasiveness. Activating mutations in the EGFR gene (deletions in exon 19 and mutation L858R in exon 21), first described in 2004, have been detected in approximately 10% of all non-squamous non-small cell lung cancer (NSCLC) patients in Western countries and are the most important predictors of a response to EGFR tyrosine-kinase inhibitors (EGFR-TKIs). Studies of the EGFR-TKIs gefitinib, erlotinib, and afatinib, in comparison with platinum-based regimens, as first-line treatments in chemotherapy-naïve patients have shown that the EGFR-TKIs produce gains in progression-free survival and overall response rates, although only in patients whose tumors harbor activating mutations in the EGFR gene. Clinical trials have also shown EGFR-TKIs to be effective as second- and third-line therapies in advanced NSCLC. Here, we review the main aspects of EGFR pathway activation in NSCLC, underscore the importance of correctly identifying activating mutations in the EGFR gene, and discuss the main outcomes of EGFR-TKI treatment in NSCLC.

  9. Gene Expression Profiling Predicts the Development of Oral Cancer

    PubMed Central

    Saintigny, Pierre; Zhang, Li; Fan, You-Hong; El-Naggar, Adel K.; Papadimitrakopoulou, Vali; Feng, Lei; Lee, J. Jack; Kim, Edward S.; Hong, Waun Ki; Mao, Li

    2011-01-01

    Patients with oral preneoplastic lesion (OPL) have high risk of developing oral cancer. Although certain risk factors such as smoking status and histology are known, our ability to predict oral cancer risk remains poor. The study objective was to determine the value of gene expression profiling in predicting oral cancer development. Gene expression profile was measured in 86 of 162 OPL patients who were enrolled in a clinical chemoprevention trial that used the incidence of oral cancer development as a prespecified endpoint. The median follow-up time was 6.08 years and 35 of the 86 patients developed oral cancer over the course. Gene expression profiles were associated with oral cancer-free survival and used to develope multivariate predictive models for oral cancer prediction. We developed a 29-transcript predictive model which showed marked improvement in terms of prediction accuracy (with 8% predicting error rate) over the models using previously known clinico-pathological risk factors. Based on the gene expression profile data, we also identified 2182 transcripts significantly associated with oral cancer risk associated genes (P-value<0.01, single variate Cox proportional hazards model). Functional pathway analysis revealed proteasome machinery, MYC, and ribosomes components as the top gene sets associated with oral cancer risk. In multiple independent datasets, the expression profiles of the genes can differentiate head and neck cancer from normal mucosa. Our results show that gene expression profiles may improve the prediction of oral cancer risk in OPL patients and the significant genes identified may serve as potential targets for oral cancer chemoprevention. PMID:21292635

  10. Realising the Promise of Cancer Predisposition Genes

    PubMed Central

    Rahman, Nazneen

    2016-01-01

    Genes in which germline mutations confer high or moderate increased risks of cancer are called cancer predisposition genes (CPG). Over 100 CPGs have been identified providing important scientific insights in many areas, particularly mechanisms of cancer causation. Moreover, clinical utilisation of CPGs has had substantial impact in diagnosis, optimised management and prevention of cancer. The recent transformative advances in DNA sequencing bring the promise of many more CPG discoveries and greater, broader clinical applications. However, there is also considerable potential for incorrect inferences and inappropriate clinical applications. Realising the promise of cancer predisposition genes for science and medicine will thus require careful navigation. PMID:24429628

  11. Inference of cancer-specific gene regulatory networks using soft computing rules.

    PubMed

    Wang, Xiaosheng; Gotoh, Osamu

    2010-03-24

    Perturbations of gene regulatory networks are essentially responsible for oncogenesis. Therefore, inferring the gene regulatory networks is a key step to overcoming cancer. In this work, we propose a method for inferring directed gene regulatory networks based on soft computing rules, which can identify important cause-effect regulatory relations of gene expression. First, we identify important genes associated with a specific cancer (colon cancer) using a supervised learning approach. Next, we reconstruct the gene regulatory networks by inferring the regulatory relations among the identified genes, and their regulated relations by other genes within the genome. We obtain two meaningful findings. One is that upregulated genes are regulated by more genes than downregulated ones, while downregulated genes regulate more genes than upregulated ones. The other one is that tumor suppressors suppress tumor activators and activate other tumor suppressors strongly, while tumor activators activate other tumor activators and suppress tumor suppressors weakly, indicating the robustness of biological systems. These findings provide valuable insights into the pathogenesis of cancer.

  12. A review of NCI's extramural grant portfolio: identifying opportunities for future research in genes and environment in cancer.

    PubMed

    Ghazarian, Armen A; Simonds, Naoko I; Bennett, Kelly; Pimentel, Camilla B; Ellison, Gary L; Gillanders, Elizabeth M; Schully, Sheri D; Mechanic, Leah E

    2013-04-01

    Genetic and environmental factors jointly influence cancer risk. The NIH has made the study of gene-environment (GxE) interactions a research priority since the year 2000. To assess the current status of GxE research in cancer, we analyzed the extramural grant portfolio of the National Cancer Institute (NCI) from Fiscal Years 2007 to 2009. Publications attributed to selected grants were also evaluated. From the 1,106 research grants identified in our portfolio analysis, a random sample of 450 grants (40%) was selected for data abstraction; of these, 147 (33%) were considered relevant. The most common cancer type was breast (20%, n = 29), followed by lymphoproliferative (10%, n = 14), colorectal (9%, n = 13), melanoma/other skin (9%, n = 13), and lung/upper aerodigestive tract (8%, n = 12) cancers. The majority of grants were studies of candidate genes (68%, n = 100) compared with genome-wide association studies (GWAS) (8%, n = 12). Approximately one-third studied environmental exposures categorized as energy balance (37%, n = 54) or drugs/treatment (29%, n = 43). From the 147 relevant grants, 108 publications classified as GxE or pharmacogenomic were identified. These publications were linked to 37 of the 147 grant applications (25%). The findings from our portfolio analysis suggest that GxE studies are concentrated in specific areas. There is room for investments in other aspects of GxE research, including, but not limited to developing alternative approaches to exposure assessment, broadening the spectrum of cancer types investigated, and conducting GxE within GWAS. This portfolio analysis provides a cross-sectional review of NCI support for GxE research in cancer.

  13. Genome-wide association study identifies genes associated with neuropathy in patients with head and neck cancer.

    PubMed

    Reyes-Gibby, Cielito C; Wang, Jian; Yeung, Sai-Ching J; Chaftari, Patrick; Yu, Robert K; Hanna, Ehab Y; Shete, Sanjay

    2018-06-08

    Neuropathic pain (NP), defined as pain initiated or caused by a primary lesion or dysfunction in the nervous system, is a debilitating chronic pain condition often resulting from cancer treatment. Among cancer patients, neuropathy during cancer treatment is a predisposing event for NP. To identify genetic variants influencing the development of NP, we conducted a genome-wide association study in 1,043 patients with squamous cell carcinoma of the head and neck, based on 714,494 tagging single-nucleotide polymorphisms (SNPs) (130 cases, 913 controls). About 12.5% of the patients, who previously had cancer treatment, had neuropathy-associated diagnoses, as defined using the ICD-9/ICD-10 codes. We identified four common SNPs representing four genomic regions: 7q22.3 (rs10950641; SNX8; P = 3.39 × 10 -14 ), 19p13.2 (rs4804217; PCP2; P = 2.95 × 10 -9 ), 3q27.3 (rs6796803; KNG1; P = 6.42 × 10 -9 ) and 15q22.2 (rs4775319; RORA; P = 1.02 × 10 -8 ), suggesting SNX8, PCP2, KNG1 and RORA might be novel target genes for NP in patients with head and neck cancer. Future experimental validation to explore physiological effects of the identified SNPs will provide a better understanding of the biological mechanisms underlying NP and may provide insights into novel therapeutic targets for treatment and management of NP.

  14. Recurrent Targeted Genes of Hepatitis B Virus in the Liver Cancer Genomes Identified by a Next-Generation Sequencing–Based Approach

    PubMed Central

    Ding, Dong; Lou, Xiaoyan; Hua, Dasong; Yu, Wei; Li, Lisha; Wang, Jun; Gao, Feng; Zhao, Na; Ren, Guoping; Li, Lanjuan; Lin, Biaoyang

    2012-01-01

    Integration of the viral DNA into host chromosomes was found in most of the hepatitis B virus (HBV)–related hepatocellular carcinomas (HCCs). Here we devised a massive anchored parallel sequencing (MAPS) method using next-generation sequencing to isolate and sequence HBV integrants. Applying MAPS to 40 pairs of HBV–related HCC tissues (cancer and adjacent tissues), we identified 296 HBV integration events corresponding to 286 unique integration sites (UISs) with precise HBV–Human DNA junctions. HBV integration favored chromosome 17 and preferentially integrated into human transcript units. HBV targeted genes were enriched in GO terms: cAMP metabolic processes, T cell differentiation and activation, TGF beta receptor pathway, ncRNA catabolic process, and dsRNA fragmentation and cellular response to dsRNA. The HBV targeted genes include 7 genes (PTPRJ, CNTN6, IL12B, MYOM1, FNDC3B, LRFN2, FN1) containing IPR003961 (Fibronectin, type III domain), 7 genes (NRG3, MASP2, NELL1, LRP1B, ADAM21, NRXN1, FN1) containing IPR013032 (EGF-like region, conserved site), and three genes (PDE7A, PDE4B, PDE11A) containing IPR002073 (3′, 5′-cyclic-nucleotide phosphodiesterase). Enriched pathways include hsa04512 (ECM-receptor interaction), hsa04510 (Focal adhesion), and hsa04012 (ErbB signaling pathway). Fewer integration events were found in cancers compared to cancer-adjacent tissues, suggesting a clonal expansion model in HCC development. Finally, we identified 8 genes that were recurrent target genes by HBV integration including fibronectin 1 (FN1) and telomerase reverse transcriptase (TERT1), two known recurrent target genes, and additional novel target genes such as SMAD family member 5 (SMAD5), phosphatase and actin regulator 4 (PHACTR4), and RNA binding protein fox-1 homolog (C. elegans) 1 (RBFOX1). Integrating analysis with recently published whole-genome sequencing analysis, we identified 14 additional recurrent HBV target genes, greatly expanding the HBV recurrent

  15. Meta-analysis of cancer gene expression signatures reveals new cancer genes, SAGE tags and tumor associated regions of co-regulation

    PubMed Central

    Kavak, Erşen; Ünlü, Mustafa; Nistér, Monica; Koman, Ahmet

    2010-01-01

    Cancer is among the major causes of human death and its mechanism(s) are not fully understood. We applied a novel meta-analysis approach to multiple sets of merged serial analysis of gene expression and microarray cancer data in order to analyze transcriptome alterations in human cancer. Our methodology, which we denote ‘COgnate Gene Expression patterNing in tumours’ (COGENT), unmasked numerous genes that were differentially expressed in multiple cancers. COGENT detected well-known tumor-associated (TA) genes such as TP53, EGFR and VEGF, as well as many multi-cancer, but not-yet-tumor-associated genes. In addition, we identified 81 co-regulated regions on the human genome (RIDGEs) by using expression data from all cancers. Some RIDGEs (28%) consist of paralog genes while another subset (30%) are specifically dysregulated in tumors but not in normal tissues. Furthermore, a significant number of RIDGEs are associated with GC-rich regions on the genome. All assembled data is freely available online (www.oncoreveal.org) as a tool implementing COGENT analysis of multi-cancer genes and RIDGEs. These findings engender a deeper understanding of cancer biology by demonstrating the existence of a pool of under-studied multi-cancer genes and by highlighting the cancer-specificity of some TA-RIDGEs. PMID:20621981

  16. Association analysis identifies 65 new breast cancer risk loci

    PubMed Central

    Lemaçon, Audrey; Soucy, Penny; Glubb, Dylan; Rostamianfar, Asha; Bolla, Manjeet K.; Wang, Qin; Tyrer, Jonathan; Dicks, Ed; Lee, Andrew; Wang, Zhaoming; Allen, Jamie; Keeman, Renske; Eilber, Ursula; French, Juliet D.; Chen, Xiao Qing; Fachal, Laura; McCue, Karen; McCart Reed, Amy E.; Ghoussaini, Maya; Carroll, Jason; Jiang, Xia; Finucane, Hilary; Adams, Marcia; Adank, Muriel A.; Ahsan, Habibul; Aittomäki, Kristiina; Anton-Culver, Hoda; Antonenkova, Natalia N.; Arndt, Volker; Aronson, Kristan J.; Arun, Banu; Auer, Paul L.; Bacot, François; Barrdahl, Myrto; Baynes, Caroline; Beckmann, Matthias W.; Behrens, Sabine; Benitez, Javier; Bermisheva, Marina; Bernstein, Leslie; Blomqvist, Carl; Bogdanova, Natalia V.; Bojesen, Stig E.; Bonanni, Bernardo; Børresen-Dale, Anne-Lise; Brand, Judith S.; Brauch, Hiltrud; Brennan, Paul; Brenner, Hermann; Brinton, Louise; Broberg, Per; Brock, Ian W.; Broeks, Annegien; Brooks-Wilson, Angela; Brucker, Sara Y.; Brüning, Thomas; Burwinkel, Barbara; Butterbach, Katja; Cai, Qiuyin; Cai, Hui; Caldés, Trinidad; Canzian, Federico; Carracedo, Angel; Carter, Brian D.; Castelao, Jose E.; Chan, Tsun L.; Cheng, Ting-Yuan David; Chia, Kee Seng; Choi, Ji-Yeob; Christiansen, Hans; Clarke, Christine L.; Collée, Margriet; Conroy, Don M.; Cordina-Duverger, Emilie; Cornelissen, Sten; Cox, David G; Cox, Angela; Cross, Simon S.; Cunningham, Julie M.; Czene, Kamila; Daly, Mary B.; Devilee, Peter; Doheny, Kimberly F.; Dörk, Thilo; dos-Santos-Silva, Isabel; Dumont, Martine; Durcan, Lorraine; Dwek, Miriam; Eccles, Diana M.; Ekici, Arif B.; Eliassen, A. Heather; Ellberg, Carolina; Elvira, Mingajeva; Engel, Christoph; Eriksson, Mikael; Fasching, Peter A.; Figueroa, Jonine; Flesch-Janys, Dieter; Fletcher, Olivia; Flyger, Henrik; Fritschi, Lin; Gaborieau, Valerie; Gabrielson, Marike; Gago-Dominguez, Manuela; Gao, Yu-Tang; Gapstur, Susan M.; García-Sáenz, José A.; Gaudet, Mia M.; Georgoulias, Vassilios; Giles, Graham G.; Glendon, Gord; Goldberg, Mark S.; Goldgar, David E.; González-Neira, Anna; Grenaker Alnæs, Grethe I.; Grip, Mervi; Gronwald, Jacek; Grundy, Anne; Guénel, Pascal; Haeberle, Lothar; Hahnen, Eric; Haiman, Christopher A.; Håkansson, Niclas; Hamann, Ute; Hamel, Nathalie; Hankinson, Susan; Harrington, Patricia; Hart, Steven N.; Hartikainen, Jaana M.; Hartman, Mikael; Hein, Alexander; Heyworth, Jane; Hicks, Belynda; Hillemanns, Peter; Ho, Dona N.; Hollestelle, Antoinette; Hooning, Maartje J.; Hoover, Robert N.; Hopper, John L.; Hou, Ming-Feng; Hsiung, Chia-Ni; Huang, Guanmengqian; Humphreys, Keith; Ishiguro, Junko; Ito, Hidemi; Iwasaki, Motoki; Iwata, Hiroji; Jakubowska, Anna; Janni, Wolfgang; John, Esther M.; Johnson, Nichola; Jones, Kristine; Jones, Michael; Jukkola-Vuorinen, Arja; Kaaks, Rudolf; Kabisch, Maria; Kaczmarek, Katarzyna; Kang, Daehee; Kasuga, Yoshio; Kerin, Michael J.; Khan, Sofia; Khusnutdinova, Elza; Kiiski, Johanna I.; Kim, Sung-Won; Knight, Julia A.; Kosma, Veli-Matti; Kristensen, Vessela N.; Krüger, Ute; Kwong, Ava; Lambrechts, Diether; Marchand, Loic Le; Lee, Eunjung; Lee, Min Hyuk; Lee, Jong Won; Lee, Chuen Neng; Lejbkowicz, Flavio; Li, Jingmei; Lilyquist, Jenna; Lindblom, Annika; Lissowska, Jolanta; Lo, Wing-Yee; Loibl, Sibylle; Long, Jirong; Lophatananon, Artitaya; Lubinski, Jan; Luccarini, Craig; Lux, Michael P.; Ma, Edmond S.K.; MacInnis, Robert J.; Maishman, Tom; Makalic, Enes; Malone, Kathleen E; Kostovska, Ivana Maleva; Mannermaa, Arto; Manoukian, Siranoush; Manson, JoAnn E.; Margolin, Sara; Mariapun, Shivaani; Martinez, Maria Elena; Matsuo, Keitaro; Mavroudis, Dimitrios; McKay, James; McLean, Catriona; Meijers-Heijboer, Hanne; Meindl, Alfons; Menéndez, Primitiva; Menon, Usha; Meyer, Jeffery; Miao, Hui; Miller, Nicola; Mohd Taib, Nur Aishah; Muir, Kenneth; Mulligan, Anna Marie; Mulot, Claire; Neuhausen, Susan L.; Nevanlinna, Heli; Neven, Patrick; Nielsen, Sune F.; Noh, Dong-Young; Nordestgaard, Børge G.; Norman, Aaron; Olopade, Olufunmilayo I.; Olson, Janet E.; Olsson, Håkan; Olswold, Curtis; Orr, Nick; Pankratz, V. Shane; Park, Sue K.; Park-Simon, Tjoung-Won; Lloyd, Rachel; Perez, Jose I.A.; Peterlongo, Paolo; Peto, Julian; Phillips, Kelly-Anne; Pinchev, Mila; Plaseska-Karanfilska, Dijana; Prentice, Ross; Presneau, Nadege; Prokofieva, Darya; Pugh, Elizabeth; Pylkäs, Katri; Rack, Brigitte; Radice, Paolo; Rahman, Nazneen; Rennert, Gadi; Rennert, Hedy S.; Rhenius, Valerie; Romero, Atocha; Romm, Jane; Ruddy, Kathryn J; Rüdiger, Thomas; Rudolph, Anja; Ruebner, Matthias; Rutgers, Emiel J. Th.; Saloustros, Emmanouil; Sandler, Dale P.; Sangrajrang, Suleeporn; Sawyer, Elinor J.; Schmidt, Daniel F.; Schmutzler, Rita K.; Schneeweiss, Andreas; Schoemaker, Minouk J.; Schumacher, Fredrick; Schürmann, Peter; Scott, Rodney J.; Scott, Christopher; Seal, Sheila; Seynaeve, Caroline; Shah, Mitul; Sharma, Priyanka; Shen, Chen-Yang; Sheng, Grace; Sherman, Mark E.; Shrubsole, Martha J.; Shu, Xiao-Ou; Smeets, Ann; Sohn, Christof; Southey, Melissa C.; Spinelli, John J.; Stegmaier, Christa; Stewart-Brown, Sarah; Stone, Jennifer; Stram, Daniel O.; Surowy, Harald; Swerdlow, Anthony; Tamimi, Rulla; Taylor, Jack A.; Tengström, Maria; Teo, Soo H.; Terry, Mary Beth; Tessier, Daniel C.; Thanasitthichai, Somchai; Thöne, Kathrin; Tollenaar, Rob A.E.M.; Tomlinson, Ian; Tong, Ling; Torres, Diana; Truong, Thérèse; Tseng, Chiu-chen; Tsugane, Shoichiro; Ulmer, Hans-Ulrich; Ursin, Giske; Untch, Michael; Vachon, Celine; van Asperen, Christi J.; Van Den Berg, David; van den Ouweland, Ans M.W.; van der Kolk, Lizet; van der Luijt, Rob B.; Vincent, Daniel; Vollenweider, Jason; Waisfisz, Quinten; Wang-Gohrke, Shan; Weinberg, Clarice R.; Wendt, Camilla; Whittemore, Alice S.; Wildiers, Hans; Willett, Walter; Winqvist, Robert; Wolk, Alicja; Wu, Anna H.; Xia, Lucy; Yamaji, Taiki; Yang, Xiaohong R.; Yip, Cheng Har; Yoo, Keun-Young; Yu, Jyh-Cherng; Zheng, Wei; Zheng, Ying; Zhu, Bin; Ziogas, Argyrios; Ziv, Elad; Lakhani, Sunil R.; Antoniou, Antonis C.; Droit, Arnaud; Andrulis, Irene L.; Amos, Christopher I.; Couch, Fergus J.; Pharoah, Paul D.P.; Chang-Claude, Jenny; Hall, Per; Hunter, David J.; Milne, Roger L.; García-Closas, Montserrat; Schmidt, Marjanka K.; Chanock, Stephen J.; Dunning, Alison M.; Edwards, Stacey L.; Bader, Gary D.; Chenevix-Trench, Georgia; Simard, Jacques; Kraft, Peter; Easton, Douglas F.

    2017-01-01

    Breast cancer risk is influenced by rare coding variants in susceptibility genes such as BRCA1 and many common, mainly non-coding variants. However, much of the genetic contribution to breast cancer risk remains unknown. We report results from a genome-wide association study (GWAS) of breast cancer in 122,977 cases and 105,974 controls of European ancestry and 14,068 cases and 13,104 controls of East Asian ancestry1. We identified 65 new loci associated with overall breast cancer at p<5x10-8. The majority of credible risk SNPs in the new loci fall in distal regulatory elements, and by integrating in-silico data to predict target genes in breast cells at each locus, we demonstrate a strong overlap between candidate target genes and somatic driver genes in breast tumours. We also find that heritability of breast cancer due to all SNPs in regulatory features was 2-5-fold enriched relative to the genome-wide average, with strong enrichment for particular transcription factor binding sites. These results provide further insight into genetic susceptibility to breast cancer and will improve the utility of genetic risk scores for individualized screening and prevention. PMID:29059683

  17. Systematic Functional Interrogation of Rare Cancer Variants Identifies Oncogenic Alleles | Office of Cancer Genomics

    Cancer.gov

    Cancer genome characterization efforts now provide an initial view of the somatic alterations in primary tumors. However, most point mutations occur at low frequency, and the function of these alleles remains undefined. We have developed a scalable systematic approach to interrogate the function of cancer-associated gene variants. We subjected 474 mutant alleles curated from 5,338 tumors to pooled in vivo tumor formation assays and gene expression profiling. We identified 12 transforming alleles, including two in genes (PIK3CB, POT1) that have not been shown to be tumorigenic.

  18. A Review of NCI’s Extramural Grant Portfolio: Identifying Opportunities for Future Research in Genes and Environment in Cancer

    PubMed Central

    Ghazarian, Armen A.; Simonds, Naoko I.; Bennett, Kelly; Pimentel, Camilla B.; Ellison, Gary L.; Gillanders, Elizabeth M.; Schully, Sheri D.; Mechanic, Leah E.

    2013-01-01

    Background Genetic and environmental factors jointly influence cancer risk. The National Institutes of Health (NIH) has made the study of gene-environment (GxE) interactions a research priority since the year 2000. Methods To assess the current status of GxE research in cancer, we analyzed the extramural grant portfolio of the National Cancer Institute (NCI) from Fiscal Years 2007 to 2009. Publications attributed to selected grants were also evaluated. Results From the 1,106 research grants identified in our portfolio analysis, a random sample of 450 grants (40%) was selected for data abstraction; of these, 147 (33%) were considered relevant. The most common cancer type was breast (20%, n=29), followed by lymphoproliferative (10%, n=14), colorectal (9%, n=13), melanoma/other skin (9%, n=13), and lung/upper aero-digestive tract (8%, n=12) cancers. The majority of grants were studies of candidate genes (68%, n=100) compared to genome-wide association studies (GWAS) (8%, n=12). Approximately one third studied environmental exposures categorized as energy balance (37%, n=54) or drugs/treatment (29%, n=43). From the 147 relevant grants, 108 publications classified as GxE or pharmacogenomic were identified. These publications were linked to 37 of the 147 grant applications (25%). Conclusion The findings from our portfolio analysis suggest that GxE studies are concentrated in specific areas. There is room for investments in other aspects of GxE research, including, but not limited to developing alternative approaches to exposure assessment, broadening the spectrum of cancer types investigated, and performing GxE within GWAS. Impact This portfolio analysis provides a cross-sectional review of NCI support for GxE research in cancer. PMID:23462918

  19. Comparative analysis of protein interactome networks prioritizes candidate genes with cancer signatures.

    PubMed

    Li, Yongsheng; Sahni, Nidhi; Yi, Song

    2016-11-29

    Comprehensive understanding of human cancer mechanisms requires the identification of a thorough list of cancer-associated genes, which could serve as biomarkers for diagnoses and therapies in various types of cancer. Although substantial progress has been made in functional studies to uncover genes involved in cancer, these efforts are often time-consuming and costly. Therefore, it remains challenging to comprehensively identify cancer candidate genes. Network-based methods have accelerated this process through the analysis of complex molecular interactions in the cell. However, the extent to which various interactome networks can contribute to prediction of candidate genes responsible for cancer is still enigmatic. In this study, we evaluated different human protein-protein interactome networks and compared their application to cancer gene prioritization. Our results indicate that network analyses can increase the power to identify novel cancer genes. In particular, such predictive power can be enhanced with the use of unbiased systematic protein interaction maps for cancer gene prioritization. Functional analysis reveals that the top ranked genes from network predictions co-occur often with cancer-related terms in literature, and further, these candidate genes are indeed frequently mutated across cancers. Finally, our study suggests that integrating interactome networks with other omics datasets could provide novel insights into cancer-associated genes and underlying molecular mechanisms.

  20. Global transcriptome analysis of formalin-fixed prostate cancer specimens identifies biomarkers of disease recurrence.

    PubMed

    Long, Qi; Xu, Jianpeng; Osunkoya, Adeboye O; Sannigrahi, Soma; Johnson, Brent A; Zhou, Wei; Gillespie, Theresa; Park, Jong Y; Nam, Robert K; Sugar, Linda; Stanimirovic, Aleksandra; Seth, Arun K; Petros, John A; Moreno, Carlos S

    2014-06-15

    Prostate cancer remains the second leading cause of cancer death in American men and there is an unmet need for biomarkers to identify patients with aggressive disease. In an effort to identify biomarkers of recurrence, we performed global RNA sequencing on 106 formalin-fixed, paraffin-embedded prostatectomy samples from 100 patients at three independent sites, defining a 24-gene signature panel. The 24 genes in this panel function in cell-cycle progression, angiogenesis, hypoxia, apoptosis, PI3K signaling, steroid metabolism, translation, chromatin modification, and transcription. Sixteen genes have been associated with cancer, with five specifically associated with prostate cancer (BTG2, IGFBP3, SIRT1, MXI1, and FDPS). Validation was performed on an independent publicly available dataset of 140 patients, where the new signature panel outperformed markers published previously in terms of predicting biochemical recurrence. Our work also identified differences in gene expression between Gleason pattern 4 + 3 and 3 + 4 tumors, including several genes involved in the epithelial-to-mesenchymal transition and developmental pathways. Overall, this study defines a novel biomarker panel that has the potential to improve the clinical management of prostate cancer. ©2014 American Association for Cancer Research.

  1. The landscape of cancer genes and mutational processes in breast cancer

    PubMed Central

    Stephens, Philip J.; Tarpey, Patrick S.; Davies, Helen; Loo, Peter Van; Greenman, Chris; Wedge, David C.; Nik-Zainal, Serena; Martin, Sancha; Varela, Ignacio; Bignell, Graham R.; Yates, Lucy R.; Papaemmanuil, Elli; Beare, David; Butler, Adam; Cheverton, Angela; Gamble, John; Hinton, Jonathan; Jia, Mingming; Jayakumar, Alagu; Jones, David; Latimer, Calli; Lau, King Wai; McLaren, Stuart; McBride, David J.; Menzies, Andrew; Mudie, Laura; Raine, Keiran; Rad, Roland; Chapman, Michael Spencer; Teague, Jon; Easton, Douglas; Langerød, Anita; OSBREAC; Lee, Ming Ta Michael; Shen, Chen-Yang; Tee, Benita Tan Kiat; Huimin, Bernice Wong; Broeks, Annegien; Vargas, Ana Cristina; Turashvili, Gulisa; Martens, John; Fatima, Aquila; Miron, Penelope; Chin, Suet-Feung; Thomas, Gilles; Boyault, Sandrine; Mariani, Odette; Lakhani, Sunil R.; van de Vijver, Marc; van ’t Veer, Laura; Foekens, John; Desmedt, Christine; Sotiriou, Christos; Tutt, Andrew; Caldas, Carlos; Reis-Filho, Jorge S.; Aparicio, Samuel A. J. R.; Salomon, Anne Vincent; Børresen-Dale, Anne-Lise; Richardson, Andrea L.; Campbell, Peter J.; Futreal, P. Andrew; Stratton, Michael R.

    2012-01-01

    All cancers carry somatic mutations in their genomes. A subset, known as driver mutations, confer clonal selective advantage on cancer cells and are causally implicated in oncogenesis1, and the remainder are passenger mutations. The driver mutations and mutational processes operative in breast cancer have not yet been comprehensively explored. Here we examine the genomes of 100 tumours for somatic copy number changes and mutations in the coding exons of protein-coding genes. The number of somatic mutations varied markedly between individual tumours. We found strong correlations between mutation number, age at which cancer was diagnosed and cancer histological grade, and observed multiple mutational signatures, including one present in about ten per cent of tumours characterized by numerous mutations of cytosine at TpC dinucleotides. Driver mutations were identified in several new cancer genes including AKT2, ARID1B, CASP8, CDKN1B, MAP3K1, MAP3K13, NCOR1, SMARCD1 and TBX3. Among the 100 tumours, we found driver mutations in at least 40 cancer genes and 73 different combinations of mutated cancer genes. The results highlight the substantial genetic diversity underlying this common disease. PMID:22722201

  2. Gene expression profiles of breast biopsies from healthy women identify a group with claudin-low features

    PubMed Central

    2011-01-01

    Background Increased understanding of the variability in normal breast biology will enable us to identify mechanisms of breast cancer initiation and the origin of different subtypes, and to better predict breast cancer risk. Methods Gene expression patterns in breast biopsies from 79 healthy women referred to breast diagnostic centers in Norway were explored by unsupervised hierarchical clustering and supervised analyses, such as gene set enrichment analysis and gene ontology analysis and comparison with previously published genelists and independent datasets. Results Unsupervised hierarchical clustering identified two separate clusters of normal breast tissue based on gene-expression profiling, regardless of clustering algorithm and gene filtering used. Comparison of the expression profile of the two clusters with several published gene lists describing breast cells revealed that the samples in cluster 1 share characteristics with stromal cells and stem cells, and to a certain degree with mesenchymal cells and myoepithelial cells. The samples in cluster 1 also share many features with the newly identified claudin-low breast cancer intrinsic subtype, which also shows characteristics of stromal and stem cells. More women belonging to cluster 1 have a family history of breast cancer and there is a slight overrepresentation of nulliparous women in cluster 1. Similar findings were seen in a separate dataset consisting of histologically normal tissue from both breasts harboring breast cancer and from mammoplasty reductions. Conclusion This is the first study to explore the variability of gene expression patterns in whole biopsies from normal breasts and identified distinct subtypes of normal breast tissue. Further studies are needed to determine the specific cell contribution to the variation in the biology of normal breasts, how the clusters identified relate to breast cancer risk and their possible link to the origin of the different molecular subtypes of breast

  3. Gene expression profiles of breast biopsies from healthy women identify a group with claudin-low features.

    PubMed

    Haakensen, Vilde D; Lingjaerde, Ole Christian; Lüders, Torben; Riis, Margit; Prat, Aleix; Troester, Melissa A; Holmen, Marit M; Frantzen, Jan Ole; Romundstad, Linda; Navjord, Dina; Bukholm, Ida K; Johannesen, Tom B; Perou, Charles M; Ursin, Giske; Kristensen, Vessela N; Børresen-Dale, Anne-Lise; Helland, Aslaug

    2011-11-01

    Increased understanding of the variability in normal breast biology will enable us to identify mechanisms of breast cancer initiation and the origin of different subtypes, and to better predict breast cancer risk. Gene expression patterns in breast biopsies from 79 healthy women referred to breast diagnostic centers in Norway were explored by unsupervised hierarchical clustering and supervised analyses, such as gene set enrichment analysis and gene ontology analysis and comparison with previously published genelists and independent datasets. Unsupervised hierarchical clustering identified two separate clusters of normal breast tissue based on gene-expression profiling, regardless of clustering algorithm and gene filtering used. Comparison of the expression profile of the two clusters with several published gene lists describing breast cells revealed that the samples in cluster 1 share characteristics with stromal cells and stem cells, and to a certain degree with mesenchymal cells and myoepithelial cells. The samples in cluster 1 also share many features with the newly identified claudin-low breast cancer intrinsic subtype, which also shows characteristics of stromal and stem cells. More women belonging to cluster 1 have a family history of breast cancer and there is a slight overrepresentation of nulliparous women in cluster 1. Similar findings were seen in a separate dataset consisting of histologically normal tissue from both breasts harboring breast cancer and from mammoplasty reductions. This is the first study to explore the variability of gene expression patterns in whole biopsies from normal breasts and identified distinct subtypes of normal breast tissue. Further studies are needed to determine the specific cell contribution to the variation in the biology of normal breasts, how the clusters identified relate to breast cancer risk and their possible link to the origin of the different molecular subtypes of breast cancer.

  4. Learning contextual gene set interaction networks of cancer with condition specificity

    PubMed Central

    2013-01-01

    Background Identifying similarities and differences in the molecular constitutions of various types of cancer is one of the key challenges in cancer research. The appearances of a cancer depend on complex molecular interactions, including gene regulatory networks and gene-environment interactions. This complexity makes it challenging to decipher the molecular origin of the cancer. In recent years, many studies reported methods to uncover heterogeneous depictions of complex cancers, which are often categorized into different subtypes. The challenge is to identify diverse molecular contexts within a cancer, to relate them to different subtypes, and to learn underlying molecular interactions specific to molecular contexts so that we can recommend context-specific treatment to patients. Results In this study, we describe a novel method to discern molecular interactions specific to certain molecular contexts. Unlike conventional approaches to build modular networks of individual genes, our focus is to identify cancer-generic and subtype-specific interactions between contextual gene sets, of which each gene set share coherent transcriptional patterns across a subset of samples, termed contextual gene set. We then apply a novel formulation for quantitating the effect of the samples from each subtype on the calculated strength of interactions observed. Two cancer data sets were analyzed to support the validity of condition-specificity of identified interactions. When compared to an existing approach, the proposed method was much more sensitive in identifying condition-specific interactions even in heterogeneous data set. The results also revealed that network components specific to different types of cancer are related to different biological functions than cancer-generic network components. We found not only the results that are consistent with previous studies, but also new hypotheses on the biological mechanisms specific to certain cancer types that warrant further

  5. Machine Learning-Assisted Network Inference Approach to Identify a New Class of Genes that Coordinate the Functionality of Cancer Networks.

    PubMed

    Ghanat Bari, Mehrab; Ung, Choong Yong; Zhang, Cheng; Zhu, Shizhen; Li, Hu

    2017-08-01

    Emerging evidence indicates the existence of a new class of cancer genes that act as "signal linkers" coordinating oncogenic signals between mutated and differentially expressed genes. While frequently mutated oncogenes and differentially expressed genes, which we term Class I cancer genes, are readily detected by most analytical tools, the new class of cancer-related genes, i.e., Class II, escape detection because they are neither mutated nor differentially expressed. Given this hypothesis, we developed a Machine Learning-Assisted Network Inference (MALANI) algorithm, which assesses all genes regardless of expression or mutational status in the context of cancer etiology. We used 8807 expression arrays, corresponding to 9 cancer types, to build more than 2 × 10 8 Support Vector Machine (SVM) models for reconstructing a cancer network. We found that ~3% of ~19,000 not differentially expressed genes are Class II cancer gene candidates. Some Class II genes that we found, such as SLC19A1 and ATAD3B, have been recently reported to associate with cancer outcomes. To our knowledge, this is the first study that utilizes both machine learning and network biology approaches to uncover Class II cancer genes in coordinating functionality in cancer networks and will illuminate our understanding of how genes are modulated in a tissue-specific network contribute to tumorigenesis and therapy development.

  6. Cancer Susceptibility Gene Mutations in Individuals With Colorectal Cancer

    PubMed Central

    Yurgelun, Matthew B.; Kulke, Matthew H.; Fuchs, Charles S.; Allen, Brian A.; Uno, Hajime; Hornick, Jason L.; Ukaegbu, Chinedu I.; Brais, Lauren K.; McNamara, Philip G.; Mayer, Robert J.; Schrag, Deborah; Meyerhardt, Jeffrey A.; Ng, Kimmie; Kidd, John; Singh, Nanda; Hartman, Anne-Renee; Wenstrup, Richard J.

    2017-01-01

    Purpose Hereditary factors play an important role in colorectal cancer (CRC) risk, yet the prevalence of germline cancer susceptibility gene mutations in patients with CRC unselected for high-risk features (eg, early age at diagnosis, personal/family history of cancer or polyps, tumor microsatellite instability [MSI], mismatch repair [MMR] deficiency) is unknown. Patients and Methods We recruited 1,058 participants who received CRC care in a clinic-based setting without preselection for age at diagnosis, personal/family history, or MSI/MMR results. All participants underwent germline testing for mutations in 25 genes associated with inherited cancer risk. Each gene was categorized as high penetrance or moderate penetrance on the basis of published estimates of the lifetime cancer risks conferred by pathogenic germline mutations in that gene. Results One hundred five (9.9%; 95% CI, 8.2% to 11.9%) of 1,058 participants carried one or more pathogenic mutations, including 33 (3.1%) with Lynch syndrome (LS). Twenty-eight (96.6%) of 29 available LS CRCs demonstrated abnormal MSI/MMR results. Seventy-four (7.0%) of 1,058 participants carried non-LS gene mutations, including 23 (2.2%) with mutations in high-penetrance genes (five APC, three biallelic MUTYH, 11 BRCA1/2, two PALB2, one CDKN2A, and one TP53), 15 of whom lacked clinical histories suggestive of their underlying mutation. Thirty-eight (3.6%) participants had moderate-penetrance CRC risk gene mutations (19 monoallelic MUTYH, 17 APC*I1307K, two CHEK2). Neither proband age at CRC diagnosis, family history of CRC, nor personal history of other cancers significantly predicted the presence of pathogenic mutations in non-LS genes. Conclusion Germline cancer susceptibility gene mutations are carried by 9.9% of patients with CRC. MSI/MMR testing reliably identifies LS probands, although 7.0% of patients with CRC carry non-LS mutations, including 1.0% with BRCA1/2 mutations. PMID:28135145

  7. Association analysis identifies 65 new breast cancer risk loci.

    PubMed

    Michailidou, Kyriaki; Lindström, Sara; Dennis, Joe; Beesley, Jonathan; Hui, Shirley; Kar, Siddhartha; Lemaçon, Audrey; Soucy, Penny; Glubb, Dylan; Rostamianfar, Asha; Bolla, Manjeet K; Wang, Qin; Tyrer, Jonathan; Dicks, Ed; Lee, Andrew; Wang, Zhaoming; Allen, Jamie; Keeman, Renske; Eilber, Ursula; French, Juliet D; Qing Chen, Xiao; Fachal, Laura; McCue, Karen; McCart Reed, Amy E; Ghoussaini, Maya; Carroll, Jason S; Jiang, Xia; Finucane, Hilary; Adams, Marcia; Adank, Muriel A; Ahsan, Habibul; Aittomäki, Kristiina; Anton-Culver, Hoda; Antonenkova, Natalia N; Arndt, Volker; Aronson, Kristan J; Arun, Banu; Auer, Paul L; Bacot, François; Barrdahl, Myrto; Baynes, Caroline; Beckmann, Matthias W; Behrens, Sabine; Benitez, Javier; Bermisheva, Marina; Bernstein, Leslie; Blomqvist, Carl; Bogdanova, Natalia V; Bojesen, Stig E; Bonanni, Bernardo; Børresen-Dale, Anne-Lise; Brand, Judith S; Brauch, Hiltrud; Brennan, Paul; Brenner, Hermann; Brinton, Louise; Broberg, Per; Brock, Ian W; Broeks, Annegien; Brooks-Wilson, Angela; Brucker, Sara Y; Brüning, Thomas; Burwinkel, Barbara; Butterbach, Katja; Cai, Qiuyin; Cai, Hui; Caldés, Trinidad; Canzian, Federico; Carracedo, Angel; Carter, Brian D; Castelao, Jose E; Chan, Tsun L; David Cheng, Ting-Yuan; Seng Chia, Kee; Choi, Ji-Yeob; Christiansen, Hans; Clarke, Christine L; Collée, Margriet; Conroy, Don M; Cordina-Duverger, Emilie; Cornelissen, Sten; Cox, David G; Cox, Angela; Cross, Simon S; Cunningham, Julie M; Czene, Kamila; Daly, Mary B; Devilee, Peter; Doheny, Kimberly F; Dörk, Thilo; Dos-Santos-Silva, Isabel; Dumont, Martine; Durcan, Lorraine; Dwek, Miriam; Eccles, Diana M; Ekici, Arif B; Eliassen, A Heather; Ellberg, Carolina; Elvira, Mingajeva; Engel, Christoph; Eriksson, Mikael; Fasching, Peter A; Figueroa, Jonine; Flesch-Janys, Dieter; Fletcher, Olivia; Flyger, Henrik; Fritschi, Lin; Gaborieau, Valerie; Gabrielson, Marike; Gago-Dominguez, Manuela; Gao, Yu-Tang; Gapstur, Susan M; García-Sáenz, José A; Gaudet, Mia M; Georgoulias, Vassilios; Giles, Graham G; Glendon, Gord; Goldberg, Mark S; Goldgar, David E; González-Neira, Anna; Grenaker Alnæs, Grethe I; Grip, Mervi; Gronwald, Jacek; Grundy, Anne; Guénel, Pascal; Haeberle, Lothar; Hahnen, Eric; Haiman, Christopher A; Håkansson, Niclas; Hamann, Ute; Hamel, Nathalie; Hankinson, Susan; Harrington, Patricia; Hart, Steven N; Hartikainen, Jaana M; Hartman, Mikael; Hein, Alexander; Heyworth, Jane; Hicks, Belynda; Hillemanns, Peter; Ho, Dona N; Hollestelle, Antoinette; Hooning, Maartje J; Hoover, Robert N; Hopper, John L; Hou, Ming-Feng; Hsiung, Chia-Ni; Huang, Guanmengqian; Humphreys, Keith; Ishiguro, Junko; Ito, Hidemi; Iwasaki, Motoki; Iwata, Hiroji; Jakubowska, Anna; Janni, Wolfgang; John, Esther M; Johnson, Nichola; Jones, Kristine; Jones, Michael; Jukkola-Vuorinen, Arja; Kaaks, Rudolf; Kabisch, Maria; Kaczmarek, Katarzyna; Kang, Daehee; Kasuga, Yoshio; Kerin, Michael J; Khan, Sofia; Khusnutdinova, Elza; Kiiski, Johanna I; Kim, Sung-Won; Knight, Julia A; Kosma, Veli-Matti; Kristensen, Vessela N; Krüger, Ute; Kwong, Ava; Lambrechts, Diether; Le Marchand, Loic; Lee, Eunjung; Lee, Min Hyuk; Lee, Jong Won; Neng Lee, Chuen; Lejbkowicz, Flavio; Li, Jingmei; Lilyquist, Jenna; Lindblom, Annika; Lissowska, Jolanta; Lo, Wing-Yee; Loibl, Sibylle; Long, Jirong; Lophatananon, Artitaya; Lubinski, Jan; Luccarini, Craig; Lux, Michael P; Ma, Edmond S K; MacInnis, Robert J; Maishman, Tom; Makalic, Enes; Malone, Kathleen E; Kostovska, Ivana Maleva; Mannermaa, Arto; Manoukian, Siranoush; Manson, JoAnn E; Margolin, Sara; Mariapun, Shivaani; Martinez, Maria Elena; Matsuo, Keitaro; Mavroudis, Dimitrios; McKay, James; McLean, Catriona; Meijers-Heijboer, Hanne; Meindl, Alfons; Menéndez, Primitiva; Menon, Usha; Meyer, Jeffery; Miao, Hui; Miller, Nicola; Taib, Nur Aishah Mohd; Muir, Kenneth; Mulligan, Anna Marie; Mulot, Claire; Neuhausen, Susan L; Nevanlinna, Heli; Neven, Patrick; Nielsen, Sune F; Noh, Dong-Young; Nordestgaard, Børge G; Norman, Aaron; Olopade, Olufunmilayo I; Olson, Janet E; Olsson, Håkan; Olswold, Curtis; Orr, Nick; Pankratz, V Shane; Park, Sue K; Park-Simon, Tjoung-Won; Lloyd, Rachel; Perez, Jose I A; Peterlongo, Paolo; Peto, Julian; Phillips, Kelly-Anne; Pinchev, Mila; Plaseska-Karanfilska, Dijana; Prentice, Ross; Presneau, Nadege; Prokofyeva, Darya; Pugh, Elizabeth; Pylkäs, Katri; Rack, Brigitte; Radice, Paolo; Rahman, Nazneen; Rennert, Gadi; Rennert, Hedy S; Rhenius, Valerie; Romero, Atocha; Romm, Jane; Ruddy, Kathryn J; Rüdiger, Thomas; Rudolph, Anja; Ruebner, Matthias; Rutgers, Emiel J T; Saloustros, Emmanouil; Sandler, Dale P; Sangrajrang, Suleeporn; Sawyer, Elinor J; Schmidt, Daniel F; Schmutzler, Rita K; Schneeweiss, Andreas; Schoemaker, Minouk J; Schumacher, Fredrick; Schürmann, Peter; Scott, Rodney J; Scott, Christopher; Seal, Sheila; Seynaeve, Caroline; Shah, Mitul; Sharma, Priyanka; Shen, Chen-Yang; Sheng, Grace; Sherman, Mark E; Shrubsole, Martha J; Shu, Xiao-Ou; Smeets, Ann; Sohn, Christof; Southey, Melissa C; Spinelli, John J; Stegmaier, Christa; Stewart-Brown, Sarah; Stone, Jennifer; Stram, Daniel O; Surowy, Harald; Swerdlow, Anthony; Tamimi, Rulla; Taylor, Jack A; Tengström, Maria; Teo, Soo H; Beth Terry, Mary; Tessier, Daniel C; Thanasitthichai, Somchai; Thöne, Kathrin; Tollenaar, Rob A E M; Tomlinson, Ian; Tong, Ling; Torres, Diana; Truong, Thérèse; Tseng, Chiu-Chen; Tsugane, Shoichiro; Ulmer, Hans-Ulrich; Ursin, Giske; Untch, Michael; Vachon, Celine; van Asperen, Christi J; Van Den Berg, David; van den Ouweland, Ans M W; van der Kolk, Lizet; van der Luijt, Rob B; Vincent, Daniel; Vollenweider, Jason; Waisfisz, Quinten; Wang-Gohrke, Shan; Weinberg, Clarice R; Wendt, Camilla; Whittemore, Alice S; Wildiers, Hans; Willett, Walter; Winqvist, Robert; Wolk, Alicja; Wu, Anna H; Xia, Lucy; Yamaji, Taiki; Yang, Xiaohong R; Har Yip, Cheng; Yoo, Keun-Young; Yu, Jyh-Cherng; Zheng, Wei; Zheng, Ying; Zhu, Bin; Ziogas, Argyrios; Ziv, Elad; Lakhani, Sunil R; Antoniou, Antonis C; Droit, Arnaud; Andrulis, Irene L; Amos, Christopher I; Couch, Fergus J; Pharoah, Paul D P; Chang-Claude, Jenny; Hall, Per; Hunter, David J; Milne, Roger L; García-Closas, Montserrat; Schmidt, Marjanka K; Chanock, Stephen J; Dunning, Alison M; Edwards, Stacey L; Bader, Gary D; Chenevix-Trench, Georgia; Simard, Jacques; Kraft, Peter; Easton, Douglas F

    2017-11-02

    Breast cancer risk is influenced by rare coding variants in susceptibility genes, such as BRCA1, and many common, mostly non-coding variants. However, much of the genetic contribution to breast cancer risk remains unknown. Here we report the results of a genome-wide association study of breast cancer in 122,977 cases and 105,974 controls of European ancestry and 14,068 cases and 13,104 controls of East Asian ancestry. We identified 65 new loci that are associated with overall breast cancer risk at P < 5 × 10 -8 . The majority of credible risk single-nucleotide polymorphisms in these loci fall in distal regulatory elements, and by integrating in silico data to predict target genes in breast cells at each locus, we demonstrate a strong overlap between candidate target genes and somatic driver genes in breast tumours. We also find that heritability of breast cancer due to all single-nucleotide polymorphisms in regulatory features was 2-5-fold enriched relative to the genome-wide average, with strong enrichment for particular transcription factor binding sites. These results provide further insight into genetic susceptibility to breast cancer and will improve the use of genetic risk scores for individualized screening and prevention.

  8. Genes involved in prostate cancer progression determine MRI visibility

    PubMed Central

    Li, Ping; You, Sungyong; Nguyen, Christopher; Wang, Yanping; Kim, Jayoung; Sirohi, Deepika; Ziembiec, Asha; Luthringer, Daniel; Lin, Shih-Chieh; Daskivich, Timothy; Wu, Jonathan; Freeman, Michael R; Saouaf, Rola; Li, Debiao; Kim, Hyung L.

    2018-01-01

    MRI is used to image prostate cancer and target tumors for biopsy or therapeutic ablation. The objective was to understand the biology of tumors not visible on MRI that may go undiagnosed and untreated. Methods: Prostate cancers visible or invisible on multiparametric MRI were macrodissected and examined by RNAseq. Differentially expressed genes (DEGs) based on MRI visibility status were cross-referenced with publicly available gene expression databases to identify genes associated with disease progression. Genes with potential roles in determining MRI visibility and disease progression were knocked down in murine prostate cancer xenografts, and imaged by MRI. Results: RNAseq identified 1,654 DEGs based on MRI visibility status. Comparison of DEGs based on MRI visibility and tumor characteristics revealed that Gleason score (dissimilarity test, p<0.0001) and tumor size (dissimilarity test, p<0.039) did not completely determine MRI visibility. Genes in previously reported prognostic signatures significantly correlated with MRI visibility suggesting that MRI visibility was prognostic. Cross-referencing DEGs with external datasets identified four genes (PHYHD1, CENPF, ALDH2, GDF15) that predict MRI visibility, progression free survival and metastatic deposits. Genetic modification of a human prostate cancer cell line to induce miR-101 and suppress CENPF decreased cell migration and invasion. As prostate cancer xenografts in mice, these cells had decreased visibility on diffusion weighted MRI and decreased perfusion, which correlated with immunostaining showing decreased cell density and proliferation. Conclusions: Genes involved in prostate cancer prognosis and metastasis determine MRI visibility, indicating that MRI visibility has prognostic significance. MRI visibility was associated with genetic features linked to poor prognosis. PMID:29556354

  9. Deregulation of Rab and Rab Effector Genes in Bladder Cancer

    PubMed Central

    Ho, Joel R.; Chapeaublanc, Elodie; Kirkwood, Lisa; Nicolle, Remy; Benhamou, Simone; Lebret, Thierry; Allory, Yves; Southgate, Jennifer; Radvanyi, François; Goud, Bruno

    2012-01-01

    Growing evidence indicates that Rab GTPases, key regulators of intracellular transport in eukaryotic cells, play an important role in cancer. We analysed the deregulation at the transcriptional level of the genes encoding Rab proteins and Rab-interacting proteins in bladder cancer pathogenesis, distinguishing between the two main progression pathways so far identified in bladder cancer: the Ta pathway characterized by a high frequency of FGFR3 mutation and the carcinoma in situ pathway where no or infrequent FGFR3 mutations have been identified. A systematic literature search identified 61 genes encoding Rab proteins and 223 genes encoding Rab-interacting proteins. Transcriptomic data were obtained for normal urothelium samples and for two independent bladder cancer data sets corresponding to 152 and 75 tumors. Gene deregulation was analysed with the SAM (significant analysis of microarray) test or the binomial test. Overall, 30 genes were down-regulated, and 13 were up-regulated in the tumor samples. Five of these deregulated genes (LEPRE1, MICAL2, RAB23, STXBP1, SYTL1) were specifically deregulated in FGFR3-non-mutated muscle-invasive tumors. No gene encoding a Rab or Rab-interacting protein was found to be specifically deregulated in FGFR3-mutated tumors. Cluster analysis showed that the RAB27 gene cluster (comprising the genes encoding RAB27 and its interacting partners) was deregulated and that this deregulation was associated with both pathways of bladder cancer pathogenesis. Finally, we found that the expression of KIF20A and ZWINT was associated with that of proliferation markers and that the expression of MLPH, MYO5B, RAB11A, RAB11FIP1, RAB20 and SYTL2 was associated with that of urothelial cell differentiation markers. This systematic analysis of Rab and Rab effector gene deregulation in bladder cancer, taking relevant tumor subgroups into account, provides insight into the possible roles of Rab proteins and their effectors in bladder cancer pathogenesis

  10. Mutator gene and hereditary non-polyposis colorectal cancer

    DOEpatents

    de la Chapelle, Albert [Helsingfors, FI; Vogelstein, Bert [Baltimore, MD; Kinzler, Kenneth W [Baltimore, MD

    2008-02-05

    The human MSH2 gene, responsible for hereditary non-polyposis colorectal cancer, was identified by virtue of its homology to the MutS class of genes, which are involved in DNA mismatch repair. The sequence of cDNA clones of the human gene are provided, and the sequence of the gene can be used to demonstrate the existence of germ line mutations in hereditary non-polyposis colorectal cancer (HNPCC) kindreds, as well as in replication error.sup.+ (RER.sup.+) tumor cells.

  11. A basal stem cell signature identifies aggressive prostate cancer phenotypes

    PubMed Central

    Smith, Bryan A.; Sokolov, Artem; Uzunangelov, Vladislav; Baertsch, Robert; Newton, Yulia; Graim, Kiley; Mathis, Colleen; Cheng, Donghui; Stuart, Joshua M.; Witte, Owen N.

    2015-01-01

    Evidence from numerous cancers suggests that increased aggressiveness is accompanied by up-regulation of signaling pathways and acquisition of properties common to stem cells. It is unclear if different subtypes of late-stage cancer vary in stemness properties and whether or not these subtypes are transcriptionally similar to normal tissue stem cells. We report a gene signature specific for human prostate basal cells that is differentially enriched in various phenotypes of late-stage metastatic prostate cancer. We FACS-purified and transcriptionally profiled basal and luminal epithelial populations from the benign and cancerous regions of primary human prostates. High-throughput RNA sequencing showed the basal population to be defined by genes associated with stem cell signaling programs and invasiveness. Application of a 91-gene basal signature to gene expression datasets from patients with organ-confined or hormone-refractory metastatic prostate cancer revealed that metastatic small cell neuroendocrine carcinoma was molecularly more stem-like than either metastatic adenocarcinoma or organ-confined adenocarcinoma. Bioinformatic analysis of the basal cell and two human small cell gene signatures identified a set of E2F target genes common between prostate small cell neuroendocrine carcinoma and primary prostate basal cells. Taken together, our data suggest that aggressive prostate cancer shares a conserved transcriptional program with normal adult prostate basal stem cells. PMID:26460041

  12. eMBI: Boosting Gene Expression-based Clustering for Cancer Subtypes.

    PubMed

    Chang, Zheng; Wang, Zhenjia; Ashby, Cody; Zhou, Chuan; Li, Guojun; Zhang, Shuzhong; Huang, Xiuzhen

    2014-01-01

    Identifying clinically relevant subtypes of a cancer using gene expression data is a challenging and important problem in medicine, and is a necessary premise to provide specific and efficient treatments for patients of different subtypes. Matrix factorization provides a solution by finding checker-board patterns in the matrices of gene expression data. In the context of gene expression profiles of cancer patients, these checkerboard patterns correspond to genes that are up- or down-regulated in patients with particular cancer subtypes. Recently, a new matrix factorization framework for biclustering called Maximum Block Improvement (MBI) is proposed; however, it still suffers several problems when applied to cancer gene expression data analysis. In this study, we developed many effective strategies to improve MBI and designed a new program called enhanced MBI (eMBI), which is more effective and efficient to identify cancer subtypes. Our tests on several gene expression profiling datasets of cancer patients consistently indicate that eMBI achieves significant improvements in comparison with MBI, in terms of cancer subtype prediction accuracy, robustness, and running time. In addition, the performance of eMBI is much better than another widely used matrix factorization method called nonnegative matrix factorization (NMF) and the method of hierarchical clustering, which is often the first choice of clinical analysts in practice.

  13. eMBI: Boosting Gene Expression-based Clustering for Cancer Subtypes

    PubMed Central

    Chang, Zheng; Wang, Zhenjia; Ashby, Cody; Zhou, Chuan; Li, Guojun; Zhang, Shuzhong; Huang, Xiuzhen

    2014-01-01

    Identifying clinically relevant subtypes of a cancer using gene expression data is a challenging and important problem in medicine, and is a necessary premise to provide specific and efficient treatments for patients of different subtypes. Matrix factorization provides a solution by finding checker-board patterns in the matrices of gene expression data. In the context of gene expression profiles of cancer patients, these checkerboard patterns correspond to genes that are up- or down-regulated in patients with particular cancer subtypes. Recently, a new matrix factorization framework for biclustering called Maximum Block Improvement (MBI) is proposed; however, it still suffers several problems when applied to cancer gene expression data analysis. In this study, we developed many effective strategies to improve MBI and designed a new program called enhanced MBI (eMBI), which is more effective and efficient to identify cancer subtypes. Our tests on several gene expression profiling datasets of cancer patients consistently indicate that eMBI achieves significant improvements in comparison with MBI, in terms of cancer subtype prediction accuracy, robustness, and running time. In addition, the performance of eMBI is much better than another widely used matrix factorization method called nonnegative matrix factorization (NMF) and the method of hierarchical clustering, which is often the first choice of clinical analysts in practice. PMID:25374455

  14. Differential Connectivity in Colorectal Cancer Gene Expression Network

    PubMed

    Izadi, Fereshteh

    2018-05-30

    Colorectal cancer (CRC) is one of the challenging types of cancers; thus, exploring effective biomarkers related to colorectal could lead to significant progresses toward the treatment of this disease. In the present study, CRC gene expression datasets have been reanalyzed. Mutual differentially expressed genes across 294 normal mucosa and adjacent tumoral samples were then utilized in order to build two independent transcriptional regulatory networks. By analyzing the networks topologically, genes with differential global connectivity related to cancer state were determined for which the potential transcriptional regulators including transcription factors were identified. The majority of differentially connected genes (DCGs) were up-regulated in colorectal transcriptome experiments. Moreover, a number of these genes have been experimentally validated as cancer or CRC-associated genes. The DCGs, including GART, TGFB1, ITGA2, SLC16A5, SOX9, and MMP7, were investigated across 12 cancer types. Functional enrichment analysis followed by detailed data mining exhibited that these candidate genes could be related to CRC by mediating in metastatic cascade in addition to shared pathways with 12 cancer types by triggering the inflammatory events Our study uncovered correlated alterations in gene expression related to CRC susceptibility and progression that the potent candidate biomarkers could provide a link to disease.

  15. Novel Genome-Wide Screening Method Identifies Genes Important to Breast Cancer Metastasis | Center for Cancer Research

    Cancer.gov

    For patients with solid tumors, the primary cause of illness and death is metastasis, a complex process involving multiple steps and cooperation between cancerous and normal cells. Many genes must be involved, but few have been found and characterized.

  16. Gene expression analysis of pancreatic cell lines reveals genes overexpressed in pancreatic cancer.

    PubMed

    Alldinger, Ingo; Dittert, Dag; Peiper, Matthias; Fusco, Alberto; Chiappetta, Gennaro; Staub, Eike; Lohr, Matthias; Jesnowski, Ralf; Baretton, Gustavo; Ockert, Detlef; Saeger, Hans-Detlev; Grützmann, Robert; Pilarsky, Christian

    2005-01-01

    Pancreatic cancer is one of the leading causes of cancer-related death. Using DNA gene expression analysis based on a custom made Affymetrix cancer array, we investigated the expression pattern of both primary and established pancreatic carcinoma cell lines. We analyzed the gene expression of 5 established pancreatic cancer cell lines (AsPC-1, BxPC-3, Capan-1, Capan-2 and HPAF II) and 5 primary isolates, 1 of them derived from benign pancreatic duct cells. Out of 1,540 genes which were expressed in at least 3 experiments, we found 122 genes upregulated and 18 downregulated in tumor cell lines compared to benign cells with a fold change >3. Several of the upregulated genes (like Prefoldin 5, ADAM9 and E-cadherin) have been associated with pancreatic cancer before. The other differentially regulated genes, however, play a so far unknown role in the course of human pancreatic carcinoma. By means of immunohistochemistry we could show that thymosin beta-10 (TMSB10), upregulated in tumor cell lines, is expressed in human pancreatic carcinoma, but not in non-neoplastic pancreatic tissue, suggesting a role for TMSB10 in the carcinogenesis of pancreatic carcinoma. Using gene expression profiling of pancreatic cell lines we were able to identify genes differentially expressed in pancreatic adenocarcinoma, which might contribute to pancreatic cancer development. Copyright 2005 S. Karger AG, Basel.

  17. A Targeted RNAi Screen of the Breast Cancer Genome Identifies KIF14 and TLN1 as Genes That Modulate Docetaxel Chemosensitivity in Triple-Negative Breast Cancer

    PubMed Central

    Singel, Stina Mui; Cornelius, Crystal; Batten, Kimberly; Fasciani, Gail; Wright, Woodring E.; Lum, Lawrence; Shay, Jerry W.

    2015-01-01

    Purpose To identify biomarkers within the breast cancer genome that may predict chemosensitivity in breast cancer. Experimental Design We conducted an RNA interference (RNAi) screen within the breast cancer genome for genes whose loss-of-function enhanced docetaxel chemosensitivity in an estrogen receptor–negative, progesterone receptor–negative, and Her2-negative (ER−, PR−, and Her2−, respectively) breast cancer cell line, MDA-MB-231. Top candidates were tested for their ability to modulate chemosensitivity in 8 breast cancer cell lines and to show in vivo chemosensitivity in a mouse xenograft model. Results From ranking chemosensitivity of 328 short hairpin RNA (shRNA) MDA-MB-231 cell lines (targeting 133 genes with known somatic mutations in breast cancer), we focused on the top two genes, kinesin family member 14 (KIF14) and talin 1 (TLN1). KIF14 and TLN1 loss-of-function significantly enhanced chemosensitivity in four triple-negative breast cancer (TNBC) cell lines (MDA-MB-231, HCC38, HCC1937, and Hs478T) but not in three hormone receptor–positive cell lines (MCF7, T47D, and HCC1428) or normal human mammary epithelial cells (HMEC). Decreased expression of KIF14, but not TLN1, also enhanced docetaxel sensitivity in a Her2-amplified breast cancer cell line, SUM190PT. Higher KIF14 and TLN1 expressions are found in TNBCs compared with the other clinical subtypes. Mammary fat pad xenografts of KIF14- and TLN1-deficient MDA-MB-231 cells revealed reduced tumor mass compared with control MDA-MB-231 cells after chemotherapy. KIF14 expression is also prognostic of relapse-free and overall survival in representative breast cancer expression arrays. Conclusion KIF14 and TLN1 are modulators of response to docetaxel and potential therapeutic targets in TNBC. PMID:23479679

  18. Filling in the Gaps in the Catalog of Cancer Genes - TCGA

    Cancer.gov

    Dr. Gad Getz and his group at the Broad Institute of MIT and Harvard identifies 33 new cancer-causing genes and finds that the catalog of cancer genes is far from complete. Learn more about the current cancer genome landscape in this Case Study.

  19. Evaluating the evaluation of cancer driver genes

    PubMed Central

    Tokheim, Collin J.; Papadopoulos, Nickolas; Kinzler, Kenneth W.; Vogelstein, Bert; Karchin, Rachel

    2016-01-01

    Sequencing has identified millions of somatic mutations in human cancers, but distinguishing cancer driver genes remains a major challenge. Numerous methods have been developed to identify driver genes, but evaluation of the performance of these methods is hindered by the lack of a gold standard, that is, bona fide driver gene mutations. Here, we establish an evaluation framework that can be applied to driver gene prediction methods. We used this framework to compare the performance of eight such methods. One of these methods, described here, incorporated a machine-learning–based ratiometric approach. We show that the driver genes predicted by each of the eight methods vary widely. Moreover, the P values reported by several of the methods were inconsistent with the uniform values expected, thus calling into question the assumptions that were used to generate them. Finally, we evaluated the potential effects of unexplained variability in mutation rates on false-positive driver gene predictions. Our analysis points to the strengths and weaknesses of each of the currently available methods and offers guidance for improving them in the future. PMID:27911828

  20. Identification of cancer genes that are independent of dominant proliferation and lineage programs

    PubMed Central

    Selfors, Laura M.; Stover, Daniel G.; Harris, Isaac S.; Brugge, Joan S.; Coloff, Jonathan L.

    2017-01-01

    Large, multidimensional cancer datasets provide a resource that can be mined to identify candidate therapeutic targets for specific subgroups of tumors. Here, we analyzed human breast cancer data to identify transcriptional programs associated with tumors bearing specific genetic driver alterations. Using an unbiased approach, we identified thousands of genes whose expression was enriched in tumors with specific genetic alterations. However, expression of the vast majority of these genes was not enriched if associations were analyzed within individual breast tumor molecular subtypes, across multiple tumor types, or after gene expression was normalized to account for differences in proliferation or tumor lineage. Together with linear modeling results, these findings suggest that most transcriptional programs associated with specific genetic alterations in oncogenes and tumor suppressors are highly context-dependent and are predominantly linked to differences in proliferation programs between distinct breast cancer subtypes. We demonstrate that such proliferation-dependent gene expression dominates tumor transcriptional programs relative to matched normal tissues. However, we also identified a relatively small group of cancer-associated genes that are both proliferation- and lineage-independent. A subset of these genes are attractive candidate targets for combination therapy because they are essential in breast cancer cell lines, druggable, enriched in stem-like breast cancer cells, and resistant to chemotherapy-induced down-regulation. PMID:29229826

  1. dbCPG: A web resource for cancer predisposition genes.

    PubMed

    Wei, Ran; Yao, Yao; Yang, Wu; Zheng, Chun-Hou; Zhao, Min; Xia, Junfeng

    2016-06-21

    Cancer predisposition genes (CPGs) are genes in which inherited mutations confer highly or moderately increased risks of developing cancer. Identification of these genes and understanding the biological mechanisms that underlie them is crucial for the prevention, early diagnosis, and optimized management of cancer. Over the past decades, great efforts have been made to identify CPGs through multiple strategies. However, information on these CPGs and their molecular functions is scattered. To address this issue and provide a comprehensive resource for researchers, we developed the Cancer Predisposition Gene Database (dbCPG, Database URL: http://bioinfo.ahu.edu.cn:8080/dbCPG/index.jsp), the first literature-based gene resource for exploring human CPGs. It contains 827 human (724 protein-coding, 23 non-coding, and 80 unknown type genes), 637 rats, and 658 mouse CPGs. Furthermore, data mining was performed to gain insights into the understanding of the CPGs data, including functional annotation, gene prioritization, network analysis of prioritized genes and overlap analysis across multiple cancer types. A user-friendly web interface with multiple browse, search, and upload functions was also developed to facilitate access to the latest information on CPGs. Taken together, the dbCPG database provides a comprehensive data resource for further studies of cancer predisposition genes.

  2. dbCPG: A web resource for cancer predisposition genes

    PubMed Central

    Wei, Ran; Yao, Yao; Yang, Wu; Zheng, Chun-Hou; Zhao, Min; Xia, Junfeng

    2016-01-01

    Cancer predisposition genes (CPGs) are genes in which inherited mutations confer highly or moderately increased risks of developing cancer. Identification of these genes and understanding the biological mechanisms that underlie them is crucial for the prevention, early diagnosis, and optimized management of cancer. Over the past decades, great efforts have been made to identify CPGs through multiple strategies. However, information on these CPGs and their molecular functions is scattered. To address this issue and provide a comprehensive resource for researchers, we developed the Cancer Predisposition Gene Database (dbCPG, Database URL: http://bioinfo.ahu.edu.cn:8080/dbCPG/index.jsp), the first literature-based gene resource for exploring human CPGs. It contains 827 human (724 protein-coding, 23 non-coding, and 80 unknown type genes), 637 rats, and 658 mouse CPGs. Furthermore, data mining was performed to gain insights into the understanding of the CPGs data, including functional annotation, gene prioritization, network analysis of prioritized genes and overlap analysis across multiple cancer types. A user-friendly web interface with multiple browse, search, and upload functions was also developed to facilitate access to the latest information on CPGs. Taken together, the dbCPG database provides a comprehensive data resource for further studies of cancer predisposition genes. PMID:27192119

  3. Gene Discovery in Bladder Cancer Progression using cDNA Microarrays

    PubMed Central

    Sanchez-Carbayo, Marta; Socci, Nicholas D.; Lozano, Juan Jose; Li, Wentian; Charytonowicz, Elizabeth; Belbin, Thomas J.; Prystowsky, Michael B.; Ortiz, Angel R.; Childs, Geoffrey; Cordon-Cardo, Carlos

    2003-01-01

    To identify gene expression changes along progression of bladder cancer, we compared the expression profiles of early-stage and advanced bladder tumors using cDNA microarrays containing 17,842 known genes and expressed sequence tags. The application of bootstrapping techniques to hierarchical clustering segregated early-stage and invasive transitional carcinomas into two main clusters. Multidimensional analysis confirmed these clusters and more importantly, it separated carcinoma in situ from papillary superficial lesions and subgroups within early-stage and invasive tumors displaying different overall survival. Additionally, it recognized early-stage tumors showing gene profiles similar to invasive disease. Different techniques including standard t-test, single-gene logistic regression, and support vector machine algorithms were applied to identify relevant genes involved in bladder cancer progression. Cytokeratin 20, neuropilin-2, p21, and p33ING1 were selected among the top ranked molecular targets differentially expressed and validated by immunohistochemistry using tissue microarrays (n = 173). Their expression patterns were significantly associated with pathological stage, tumor grade, and altered retinoblastoma (RB) expression. Moreover, p33ING1 expression levels were significantly associated with overall survival. Analysis of the annotation of the most significant genes revealed the relevance of critical genes and pathways during bladder cancer progression, including the overexpression of oncogenic genes such as DEK in superficial tumors or immune response genes such as Cd86 antigen in invasive disease. Gene profiling successfully classified bladder tumors based on their progression and clinical outcome. The present study has identified molecular biomarkers of potential clinical significance and critical molecular targets associated with bladder cancer progression. PMID:12875971

  4. Identifying core gene modules in glioblastoma based on multilayer factor-mediated dysfunctional regulatory networks through integrating multi-dimensional genomic data

    PubMed Central

    Ping, Yanyan; Deng, Yulan; Wang, Li; Zhang, Hongyi; Zhang, Yong; Xu, Chaohan; Zhao, Hongying; Fan, Huihui; Yu, Fulong; Xiao, Yun; Li, Xia

    2015-01-01

    The driver genetic aberrations collectively regulate core cellular processes underlying cancer development. However, identifying the modules of driver genetic alterations and characterizing their functional mechanisms are still major challenges for cancer studies. Here, we developed an integrative multi-omics method CMDD to identify the driver modules and their affecting dysregulated genes through characterizing genetic alteration-induced dysregulated networks. Applied to glioblastoma (GBM), the CMDD identified a core gene module of 17 genes, including seven known GBM drivers, and their dysregulated genes. The module showed significant association with shorter survival of GBM. When classifying driver genes in the module into two gene sets according to their genetic alteration patterns, we found that one gene set directly participated in the glioma pathway, while the other indirectly regulated the glioma pathway, mostly, via their dysregulated genes. Both of the two gene sets were significant contributors to survival and helpful for classifying GBM subtypes, suggesting their critical roles in GBM pathogenesis. Also, by applying the CMDD to other six cancers, we identified some novel core modules associated with overall survival of patients. Together, these results demonstrate integrative multi-omics data can identify driver modules and uncover their dysregulated genes, which is useful for interpreting cancer genome. PMID:25653168

  5. RET is a potential tumor suppressor gene in colorectal cancer

    PubMed Central

    Luo, Yanxin; Tsuchiya, Karen D.; Park, Dong Il; Fausel, Rebecca; Kanngurn, Samornmas; Welcsh, Piri; Dzieciatkowski, Slavomir; Wang, Jianping; Grady, William M.

    2012-01-01

    Cancer arises as the consequence of mutations and epigenetic alterations that activate oncogenes and inactivate tumor suppressor genes. Through a genome-wide screen for methylated genes in colon neoplasms, we identified aberrantly methylated RET in colorectal cancer. RET, a transmembrane receptor tyrosine kinase and a receptor for the GDNF-family ligands, was one of the first oncogenes to be identified and has been shown to be an oncogene in thyroid cancer and pheochromocytoma. However, unexpectedly, we found RET is methylated in 27% of colon adenomas and in 63% of colorectal cancers, and now provide evidence that RET has tumor suppressor activity in colon cancer. The aberrant methylation of RET correlates with decreased RET expression, whereas the restoration of RET in colorectal cancer cell lines results in apoptosis. Furthermore, in support of a tumor suppressor function of RET, mutant RET has also been found in primary colorectal cancer. We now show that these mutations inactivate RET, which is consistent with RET being a tumor suppressor gene in the colon. These findings suggest that the aberrant methylation of RET and the mutational inactivation of RET promote colorectal cancer formation and that RET can serve as a tumor suppressor gene in the colon. Moreover, the increased frequency of methylated RET in colon cancers compared to adenomas suggests RET inactivation is involved in the progression of colon adenomas to cancer. PMID:22751117

  6. The database of chromosome imbalance regions and genes resided in lung cancer from Asian and Caucasian identified by array-comparative genomic hybridization

    PubMed Central

    2012-01-01

    Background Cancer-related genes show racial differences. Therefore, identification and characterization of DNA copy number alteration regions in different racial groups helps to dissect the mechanism of tumorigenesis. Methods Array-comparative genomic hybridization (array-CGH) was analyzed for DNA copy number profile in 40 Asian and 20 Caucasian lung cancer patients. Three methods including MetaCore analysis for disease and pathway correlations, concordance analysis between array-CGH database and the expression array database, and literature search for copy number variation genes were performed to select novel lung cancer candidate genes. Four candidate oncogenes were validated for DNA copy number and mRNA and protein expression by quantitative polymerase chain reaction (qPCR), chromogenic in situ hybridization (CISH), reverse transcriptase-qPCR (RT-qPCR), and immunohistochemistry (IHC) in more patients. Results We identified 20 chromosomal imbalance regions harboring 459 genes for Caucasian and 17 regions containing 476 genes for Asian lung cancer patients. Seven common chromosomal imbalance regions harboring 117 genes, included gain on 3p13-14, 6p22.1, 9q21.13, 13q14.1, and 17p13.3; and loss on 3p22.2-22.3 and 13q13.3 were found both in Asian and Caucasian patients. Gene validation for four genes including ARHGAP19 (10q24.1) functioning in Rho activity control, FRAT2 (10q24.1) involved in Wnt signaling, PAFAH1B1 (17p13.3) functioning in motility control, and ZNF322A (6p22.1) involved in MAPK signaling was performed using qPCR and RT-qPCR. Mean gene dosage and mRNA expression level of the four candidate genes in tumor tissues were significantly higher than the corresponding normal tissues (P<0.001~P=0.06). In addition, CISH analysis of patients indicated that copy number amplification indeed occurred for ARHGAP19 and ZNF322A genes in lung cancer patients. IHC analysis of paraffin blocks from Asian Caucasian patients demonstrated that the frequency of PAFAH1B1

  7. Inference of combinatorial Boolean rules of synergistic gene sets from cancer microarray datasets.

    PubMed

    Park, Inho; Lee, Kwang H; Lee, Doheon

    2010-06-15

    Gene set analysis has become an important tool for the functional interpretation of high-throughput gene expression datasets. Moreover, pattern analyses based on inferred gene set activities of individual samples have shown the ability to identify more robust disease signatures than individual gene-based pattern analyses. Although a number of approaches have been proposed for gene set-based pattern analysis, the combinatorial influence of deregulated gene sets on disease phenotype classification has not been studied sufficiently. We propose a new approach for inferring combinatorial Boolean rules of gene sets for a better understanding of cancer transcriptome and cancer classification. To reduce the search space of the possible Boolean rules, we identify small groups of gene sets that synergistically contribute to the classification of samples into their corresponding phenotypic groups (such as normal and cancer). We then measure the significance of the candidate Boolean rules derived from each group of gene sets; the level of significance is based on the class entropy of the samples selected in accordance with the rules. By applying the present approach to publicly available prostate cancer datasets, we identified 72 significant Boolean rules. Finally, we discuss several identified Boolean rules, such as the rule of glutathione metabolism (down) and prostaglandin synthesis regulation (down), which are consistent with known prostate cancer biology. Scripts written in Python and R are available at http://biosoft.kaist.ac.kr/~ihpark/. The refined gene sets and the full list of the identified Boolean rules are provided in the Supplementary Material. Supplementary data are available at Bioinformatics online.

  8. COGENT (COlorectal cancer GENeTics) revisited

    PubMed Central

    Houlston, Richard S.

    2012-01-01

    Many colorectal cancers (CRCs) develop in genetically susceptible individuals most of whom are not carriers of germ line mismatch repair or APC gene mutations and much of the heritable risk of CRC appears to be attributable to the co-inheritance of multiple low-risk variants. The accumulated experience to date in identifying this class of susceptibility allele has highlighted the need to conduct statistically and methodologically rigorous studies and the need for the multi-centre collaboration. This has been the motivation for establishing the COGENT (COlorectal cancer GENeTics) consortium which now includes over 20 research groups in Europe, Australia, the Americas, China and Japan actively working on CRC genetics. Here, we review the rationale for identifying low-penetrance variants for CRC and the current and future challenges for COGENT. PMID:22294761

  9. LGscore: A method to identify disease-related genes using biological literature and Google data.

    PubMed

    Kim, Jeongwoo; Kim, Hyunjin; Yoon, Youngmi; Park, Sanghyun

    2015-04-01

    Since the genome project in 1990s, a number of studies associated with genes have been conducted and researchers have confirmed that genes are involved in disease. For this reason, the identification of the relationships between diseases and genes is important in biology. We propose a method called LGscore, which identifies disease-related genes using Google data and literature data. To implement this method, first, we construct a disease-related gene network using text-mining results. We then extract gene-gene interactions based on co-occurrences in abstract data obtained from PubMed, and calculate the weights of edges in the gene network by means of Z-scoring. The weights contain two values: the frequency and the Google search results. The frequency value is extracted from literature data, and the Google search result is obtained using Google. We assign a score to each gene through a network analysis. We assume that genes with a large number of links and numerous Google search results and frequency values are more likely to be involved in disease. For validation, we investigated the top 20 inferred genes for five different diseases using answer sets. The answer sets comprised six databases that contain information on disease-gene relationships. We identified a significant number of disease-related genes as well as candidate genes for Alzheimer's disease, diabetes, colon cancer, lung cancer, and prostate cancer. Our method was up to 40% more accurate than existing methods. Copyright © 2015 Elsevier Inc. All rights reserved.

  10. Genes, dreams, and cancer.

    PubMed Central

    Sikora, K.

    1994-01-01

    There have been tremendous advances in our understanding of cancer from the application of molecular biology over the past decade. The disease is caused by a series of defects in the genes that accelerate growth--oncogenes--and those that slow down cellular turnover--tumour suppressor genes. The proteins they encode provide a promising hunting ground in which to design and test new anticancer drugs. Several treatment strategies are now under clinical trial entailing direct gene transfer. These include the use of gene marking to detect minimal residual disease, the production of novel cancer vaccines by the insertion of genes which uncloak cancer cells so making them visible to the host's immune system, the isolation and coupling of cancer specific molecular switches upstream of drug activating genes, and the correction of aberrant oncogenes or tumour suppressor genes. The issues in these approaches are likely to have a profound impact on the management of cancer patients as we enter the next century. Images p1221-a PMID:8180542

  11. A study of over 35,000 women with breast cancer tested with a 25-gene panel of hereditary cancer genes.

    PubMed

    Buys, Saundra S; Sandbach, John F; Gammon, Amanda; Patel, Gayle; Kidd, John; Brown, Krystal L; Sharma, Lavania; Saam, Jennifer; Lancaster, Johnathan; Daly, Mary B

    2017-05-15

    As panel testing becomes more common in clinical practice, it is important to understand the prevalence and trends associated with the pathogenic variants (PVs) identified. This is especially true for genetically heterogeneous cancers, such as breast cancer (BC), in which PVs in different genes may be associated with various risks and cancer subtypes. The authors evaluated the outcomes of genetic testing among women who had a personal history of BC. A total of 35,409 women with a single diagnosis of BC who underwent clinical genetic testing with a 25-gene panel were included in the current analysis. Women with multiple BCs and men with BC were excluded. The frequency and distribution of PVs were assessed for the overall cohort, among women with triple-negative BC (TNBC) (n = 4797), and by age at diagnosis. PVs were identified in 9.3% of women tested; 51.5% of PVs were identified in genes other than breast cancer 1 (BRCA1) and BRCA2, including checkpoint kinase 2 (CHEK2) (11.7%), ataxia telangiectasia mutated (ATM; ATM serine/threonine kinase) (9.7%), and partner and localizer of BRCA2 (PALB2) (9.3%). The prevalence of PVs in BRCA1, PALB2, BRCA1-associated RING domain 1 (BARD1), BRCA1-interacting protein C-terminal helicase 1 (BRIP1), and RAD51 paralog C (RAD51C) was statistically higher among women with TNBC. The PV rate was higher among women aged <40 years, lower among women aged >59 years, and relatively constant (8.5%-9.0%) among women who were diagnosed between ages 40 and 59 years. These results demonstrate that panel testing increased the number of women identified as carrying a PV in this cohort compared with BRCA testing alone. Furthermore, the proportion of women identified who carried a PV in this cohort did not decrease between ages 40 and 59 years. Cancer 2017;123:1721-1730. © 2017 American Cancer Society. © 2017 American Cancer Society.

  12. Germ-line variants identified by next generation sequencing in a panel of estrogen and cancer associated genes correlate with poor clinical outcome in Lynch syndrome patients.

    PubMed

    Jóri, Balazs; Kamps, Rick; Xanthoulea, Sofia; Delvoux, Bert; Blok, Marinus J; Van de Vijver, Koen K; de Koning, Bart; Oei, Felicia Trups; Tops, Carli M; Speel, Ernst Jm; Kruitwagen, Roy F; Gomez-Garcia, Encarna B; Romano, Andrea

    2015-12-01

    The risk to develop colorectal and endometrial cancers among subjects testing positive for a pathogenic Lynch syndrome mutation varies, making the risk prediction difficult. Genetic risk modifiers alter the risk conferred by inherited Lynch syndrome mutations, and their identification can improve genetic counseling. We aimed at identifying rare genetic modifiers of the risk of Lynch syndrome endometrial cancer. A family based approach was used to assess the presence of genetic risk modifiers among 35 Lynch syndrome mutation carriers having either a poor clinical phenotype (early age of endometrial cancer diagnosis or multiple cancers) or a neutral clinical phenotype. Putative genetic risk modifiers were identified by Next Generation Sequencing among a panel of 154 genes involved in endometrial physiology and carcinogenesis. A simple pipeline, based on an allele frequency lower than 0.001 and on predicted non-conservative amino-acid substitutions returned 54 variants that were considered putative risk modifiers. The presence of two or more risk modifying variants in women carrying a pathogenic Lynch syndrome mutation was associated with a poor clinical phenotype. A gene-panel is proposed that comprehends genes that can carry variants with putative modifying effects on the risk of Lynch syndrome endometrial cancer. Validation in further studies is warranted before considering the possible use of this tool in genetic counseling.

  13. RCDB: Renal Cancer Gene Database.

    PubMed

    Ramana, Jayashree

    2012-05-18

    Renal cell carcinoma or RCC is one of the common and most lethal urological cancers, with 40% of the patients succumbing to death because of metastatic progression of the disease. Treatment of metastatic RCC remains highly challenging because of its resistance to chemotherapy as well as radiotherapy, besides surgical resection. Whereas RCC comprises tumors with differing histological types, clear cell RCC remains the most common. A major problem in the clinical management of patients presenting with localized ccRCC is the inability to determine tumor aggressiveness and accurately predict the risk of metastasis following surgery. As a measure to improve the diagnosis and prognosis of RCC, researchers have identified several molecular markers through a number of techniques. However the wealth of information available is scattered in literature and not easily amenable to data-mining. To reduce this gap, this work describes a comprehensive repository called Renal Cancer Gene Database, as an integrated gateway to study renal cancer related data. Renal Cancer Gene Database is a manually curated compendium of 240 protein-coding and 269 miRNA genes contributing to the etiology and pathogenesis of various forms of renal cell carcinomas. The protein coding genes have been classified according to the kind of gene alteration observed in RCC. RCDB also includes the miRNAsdysregulated in RCC, along with the corresponding information regarding the type of RCC and/or metastatic or prognostic significance. While some of the miRNA genes showed an association with other types of cancers few were unique to RCC. Users can query the database using keywords, category and chromosomal location of the genes. The knowledgebase can be freely accessed via a user-friendly web interface at http://www.juit.ac.in/attachments/jsr/rcdb/homenew.html. It is hoped that this database would serve as a useful complement to the existing public resources and as a good starting point for researchers and

  14. Screening for susceptibility genes in hereditary non-polyposis colorectal cancer.

    PubMed

    Yu, Li; Yin, Bo; Qu, Kaiying; Li, Jingjing; Jin, Qiao; Liu, Ling; Liu, Chunlan; Zhu, Yuxing; Wang, Qi; Peng, Xiaowei; Zhou, Jianda; Cao, Peiguo; Cao, Ke

    2018-06-01

    In the present study, hereditary non-polyposis colorectal cancer (HNPCC) susceptibility genes were screened for using whole exome sequencing in 3 HNPCC patients from 1 family and using single nucleotide polymorphism (SNP) genotyping assays in 96 other colorectal cancer and control samples. Peripheral blood was obtained from 3 HNPCC patients from 1 family; the proband and the proband's brother and cousin. High-throughput sequencing was performed using whole exome capture technology. Sequences were aligned against the HAPMAP, dbSNP130 and 1,000 Genome Project databases. Reported common variations and synonymous mutations were filtered out. Non-synonymous single nucleotide variants in the 3 HNPCC patients were integrated and the candidate genes were identified. Finally, SNP genotyping was performed for the genes in 96 peripheral blood samples. In total, 60.4 Gb of data was retrieved from the 3 HNPCC patients using whole exome capture technology. Subsequently, according to certain screening criteria, 15 candidate genes were identified. Among the 96 samples that had been SNP genotyped, 92 were successfully genotyped for 15 gene loci, while genotyping for HTRA1 failed in 4 sporadic colorectal cancer patient samples. In 12 control subjects and 81 sporadic colorectal cancer patients, genotypes at 13 loci were wild-type, namely DDX20, ZFYVE26, PIK3R3, SLC26A8, ZEB2, TP53INP1, SLC11A1, LRBA, CEBPZ, ETAA1, SEMA3G, IFRD2 and FAT1 . The CEP290 genotype was mutant in 1 sporadic colorectal cancer patient and was wild-type in all other subjects. A total of 5 of the 12 control subjects and 30 of the 81 sporadic colorectal cancer patients had a mutant HTRA1 genotype. In all 3 HNPCC patients, the same mutant genotypes were identified at all 15 gene loci. Overall, 13 potential susceptibility genes for HNPCC were identified, namely DDX20, ZFYVE26, PIK3R3, SLC26A8, ZEB2, TP53INP1, SLC11A1, LRBA, CEBPZ, ETAA1, SEMA3G, IFRD2 and FAT1 .

  15. Transcriptional Network Analysis Identifies BACH1 as a Master Regulator of Breast Cancer Bone Metastasis

    PubMed Central

    Liang, Yajun; Wu, Heng; Lei, Rong; Chong, Robert A.; Wei, Yong; Lu, Xin; Tagkopoulos, Ilias; Kung, Sun-Yuan; Yang, Qifeng; Hu, Guohong; Kang, Yibin

    2012-01-01

    The application of functional genomic analysis of breast cancer metastasis has led to the identification of a growing number of organ-specific metastasis genes, which often function in concert to facilitate different steps of the metastatic cascade. However, the gene regulatory network that controls the expression of these metastasis genes remains largely unknown. Here, we demonstrate a computational approach for the deconvolution of transcriptional networks to discover master regulators of breast cancer bone metastasis. Several known regulators of breast cancer bone metastasis such as Smad4 and HIF1 were identified in our analysis. Experimental validation of the networks revealed BACH1, a basic leucine zipper transcription factor, as the common regulator of several functional metastasis genes, including MMP1 and CXCR4. Ectopic expression of BACH1 enhanced the malignance of breast cancer cells, and conversely, BACH1 knockdown significantly reduced bone metastasis. The expression of BACH1 and its target genes was linked to the higher risk of breast cancer recurrence in patients. This study established BACH1 as the master regulator of breast cancer bone metastasis and provided a paradigm to identify molecular determinants in complex pathological processes. PMID:22875853

  16. Cancer predisposition genes: molecular mechanisms and clinical impact on personalized cancer care: examples of Lynch and HBOC syndromes

    PubMed Central

    Wang, Qing

    2016-01-01

    Up to 10% of cancers occur through the inherited mutation of a group of genes called cancer predisposition genes. Individuals who carry a mutant allele of these genes have an increased susceptibility to cancer. A growing number of cancer susceptibility genes are being identified, and the physiopathology of germline mutation-based cancer development is also being elucidated with accumulating clinical and molecular data. More importantly, the identification of familial mutations has become routine practice, which is a perfect example of bench-to-bed translational medicine. Recently, other clinical applications of predisposition genes have been exploited, especially as efficient biomarkers predicting prognosis or response to treatment. Thus, it appears interesting to give an overview of the advances and impacts of predisposition genes in personalized cancer care by taking representative and common cancer syndromes as examples: Lynch syndrome for the first example, which is related to cancer susceptibility, and breast and ovary cancer syndrome for the second example, which involves BRCA deficiency-related targeted therapy. PMID:26616728

  17. An evidence-based knowledgebase of metastasis suppressors to identify key pathways relevant to cancer metastasis

    PubMed Central

    Zhao, Min; Li, Zhe; Qu, Hong

    2015-01-01

    Metastasis suppressor genes (MS genes) are genes that play important roles in inhibiting the process of cancer metastasis without preventing growth of the primary tumor. Identification of these genes and understanding their functions are critical for investigation of cancer metastasis. Recent studies on cancer metastasis have identified many new susceptibility MS genes. However, the comprehensive illustration of diverse cellular processes regulated by metastasis suppressors during the metastasis cascade is lacking. Thus, the relationship between MS genes and cancer risk is still unclear. To unveil the cellular complexity of MS genes, we have constructed MSGene (http://MSGene.bioinfo-minzhao.org/), the first literature-based gene resource for exploring human MS genes. In total, we manually curated 194 experimentally verified MS genes and mapped to 1448 homologous genes from 17 model species. Follow-up functional analyses associated 194 human MS genes with epithelium/tissue morphogenesis and epithelia cell proliferation. In addition, pathway analysis highlights the prominent role of MS genes in activation of platelets and coagulation system in tumor metastatic cascade. Moreover, global mutation pattern of MS genes across multiple cancers may reveal common cancer metastasis mechanisms. All these results illustrate the importance of MSGene to our understanding on cell development and cancer metastasis. PMID:26486520

  18. Locus-specific gene repositioning in prostate cancer

    PubMed Central

    Leshner, Marc; Devine, Michelle; Roloff, Gregory W.; True, Lawrence D.; Misteli, Tom; Meaburn, Karen J.

    2016-01-01

    Genes occupy preferred spatial positions within interphase cell nuclei. However, positioning patterns are not an innate feature of a locus, and genes can alter their localization in response to physiological and pathological changes. Here we screen the radial positioning patterns of 40 genes in normal, hyperplasic, and malignant human prostate tissues. We find that the overall spatial organization of the genome in prostate tissue is largely conserved among individuals. We identify three genes whose nuclear positions are robustly altered in neoplastic prostate tissues. FLI1 and MMP9 position differently in prostate cancer than in normal tissue and prostate hyperplasia, whereas MMP2 is repositioned in both prostate cancer and hyperplasia. Our data point to locus-specific reorganization of the genome during prostate disease. PMID:26564800

  19. Prevalence and Penetrance of Major Genes and Polygenes for Colorectal Cancer

    PubMed Central

    Win, Aung Ko; Jenkins, Mark A.; Dowty, James G.; Antoniou, Antonis C.; Lee, Andrew; Giles, Graham G.; Buchanan, Daniel D.; Clendenning, Mark; Rosty, Christophe; Ahnen, Dennis J.; Thibodeau, Stephen N.; Casey, Graham; Gallinger, Steven; Le Marchand, Loïc; Haile, Robert W.; Potter, John D.; Zheng, Yingye; Lindor, Noralane M.; Newcomb, Polly A.; Hopper, John L.; MacInnis, Robert J.

    2016-01-01

    Background While high-risk mutations in identified major susceptibility genes (DNA mismatch repair genes and MUTYH) account for some familial aggregation of colorectal cancer, their population prevalence and the causes of the remaining familial aggregation are not known. Methods We studied the families of 5,744 colorectal cancer cases (probands) recruited from population cancer registries in the USA, Canada and Australia and screened probands for mutations in mismatch repair genes and MUTYH. We conducted modified segregation analyses using the cancer history of first-degree relatives, conditional on the proband’s age at diagnosis. We estimated the prevalence of mutations in the identified genes, the prevalence of and hazard ratio for unidentified major gene mutations, and the variance of the residual polygenic component. Results We estimated that 1 in 279 of the population carry mutations in mismatch repair genes (MLH1= 1 in 1946, MSH2= 1 in 2841, MSH6= 1 in 758, PMS2= 1 in 714), 1 in 45 carry mutations in MUTYH, and 1 in 504 carry mutations associated with an average 31-fold increased risk of colorectal cancer in unidentified major genes. The estimated polygenic variance was reduced by 30–50% after allowing for unidentified major genes and decreased from 3.3 for age <40 years to 0.5 for age ≥70 years (equivalent to sibling relative risks of 5.1 to 1.3, respectively). Conclusion Unidentified major genes might explain one-third to one-half of the missing heritability of colorectal cancer. Impact Our findings could aid gene discovery and development of better colorectal cancer risk prediction models. PMID:27799157

  20. Prediction of epigenetically regulated genes in breast cancer cell lines.

    PubMed

    Loss, Leandro A; Sadanandam, Anguraj; Durinck, Steffen; Nautiyal, Shivani; Flaucher, Diane; Carlton, Victoria E H; Moorhead, Martin; Lu, Yontao; Gray, Joe W; Faham, Malek; Spellman, Paul; Parvin, Bahram

    2010-06-04

    Methylation of CpG islands within the DNA promoter regions is one mechanism that leads to aberrant gene expression in cancer. In particular, the abnormal methylation of CpG islands may silence associated genes. Therefore, using high-throughput microarrays to measure CpG island methylation will lead to better understanding of tumor pathobiology and progression, while revealing potentially new biomarkers. We have examined a recently developed high-throughput technology for measuring genome-wide methylation patterns called mTACL. Here, we propose a computational pipeline for integrating gene expression and CpG island methylation profiles to identify epigenetically regulated genes for a panel of 45 breast cancer cell lines, which is widely used in the Integrative Cancer Biology Program (ICBP). The pipeline (i) reduces the dimensionality of the methylation data, (ii) associates the reduced methylation data with gene expression data, and (iii) ranks methylation-expression associations according to their epigenetic regulation. Dimensionality reduction is performed in two steps: (i) methylation sites are grouped across the genome to identify regions of interest, and (ii) methylation profiles are clustered within each region. Associations between the clustered methylation and the gene expression data sets generate candidate matches within a fixed neighborhood around each gene. Finally, the methylation-expression associations are ranked through a logistic regression, and their significance is quantified through permutation analysis. Our two-step dimensionality reduction compressed 90% of the original data, reducing 137,688 methylation sites to 14,505 clusters. Methylation-expression associations produced 18,312 correspondences, which were used to further analyze epigenetic regulation. Logistic regression was used to identify 58 genes from these correspondences that showed a statistically significant negative correlation between methylation profiles and gene expression in the

  1. A network-based, integrative study to identify core biological pathways that drive breast cancer clinical subtypes

    PubMed Central

    Dutta, B; Pusztai, L; Qi, Y; André, F; Lazar, V; Bianchini, G; Ueno, N; Agarwal, R; Wang, B; Shiang, C Y; Hortobagyi, G N; Mills, G B; Symmans, W F; Balázsi, G

    2012-01-01

    Background: The rapid collection of diverse genome-scale data raises the urgent need to integrate and utilise these resources for biological discovery or biomedical applications. For example, diverse transcriptomic and gene copy number variation data are currently collected for various cancers, but relatively few current methods are capable to utilise the emerging information. Methods: We developed and tested a data-integration method to identify gene networks that drive the biology of breast cancer clinical subtypes. The method simultaneously overlays gene expression and gene copy number data on protein–protein interaction, transcriptional-regulatory and signalling networks by identifying coincident genomic and transcriptional disturbances in local network neighborhoods. Results: We identified distinct driver-networks for each of the three common clinical breast cancer subtypes: oestrogen receptor (ER)+, human epidermal growth factor receptor 2 (HER2)+, and triple receptor-negative breast cancers (TNBC) from patient and cell line data sets. Driver-networks inferred from independent datasets were significantly reproducible. We also confirmed the functional relevance of a subset of randomly selected driver-network members for TNBC in gene knockdown experiments in vitro. We found that TNBC driver-network members genes have increased functional specificity to TNBC cell lines and higher functional sensitivity compared with genes selected by differential expression alone. Conclusion: Clinical subtype-specific driver-networks identified through data integration are reproducible and functionally important. PMID:22343619

  2. Integrating text mining, data mining, and network analysis for identifying genetic breast cancer trends.

    PubMed

    Jurca, Gabriela; Addam, Omar; Aksac, Alper; Gao, Shang; Özyer, Tansel; Demetrick, Douglas; Alhajj, Reda

    2016-04-26

    Breast cancer is a serious disease which affects many women and may lead to death. It has received considerable attention from the research community. Thus, biomedical researchers aim to find genetic biomarkers indicative of the disease. Novel biomarkers can be elucidated from the existing literature. However, the vast amount of scientific publications on breast cancer make this a daunting task. This paper presents a framework which investigates existing literature data for informative discoveries. It integrates text mining and social network analysis in order to identify new potential biomarkers for breast cancer. We utilized PubMed for the testing. We investigated gene-gene interactions, as well as novel interactions such as gene-year, gene-country, and abstract-country to find out how the discoveries varied over time and how overlapping/diverse are the discoveries and the interest of various research groups in different countries. Interesting trends have been identified and discussed, e.g., different genes are highlighted in relationship to different countries though the various genes were found to share functionality. Some text analysis based results have been validated against results from other tools that predict gene-gene relations and gene functions.

  3. Gene signature critical to cancer phenotype as a paradigm for anti-cancer drug discovery

    PubMed Central

    Sampson, Erik R.; McMurray, Helene R.; Hassane, Duane C.; Newman, Laurel; Salzman, Peter; Jordan, Craig T.; Land, Hartmut

    2013-01-01

    Malignant cell transformation commonly results in the deregulation of thousands of cellular genes, an observation that suggests a complex biological process and an inherently challenging scenario for the development of effective cancer interventions. To better define the genes/pathways essential to regulating the malignant phenotype, we recently described a novel strategy based on the cooperative nature of carcinogenesis that focuses on genes synergistically deregulated in response to cooperating oncogenic mutations. These so-called “cooperation response genes” (CRGs) are highly enriched for genes critical for the cancer phenotype, thereby suggesting their causal role in the malignant state. Here we show that CRGs play an essential role in drug-mediated anti-cancer activity and that anti-cancer agents can be identified through their ability to antagonize the CRG expression profile. These findings provide proof-of-concept for the use of the CRG signature as a novel means of drug discovery with relevance to underlying anti-cancer drug mechanisms. PMID:22964631

  4. Text Mining in Cancer Gene and Pathway Prioritization

    PubMed Central

    Luo, Yuan; Riedlinger, Gregory; Szolovits, Peter

    2014-01-01

    Prioritization of cancer implicated genes has received growing attention as an effective way to reduce wet lab cost by computational analysis that ranks candidate genes according to the likelihood that experimental verifications will succeed. A multitude of gene prioritization tools have been developed, each integrating different data sources covering gene sequences, differential expressions, function annotations, gene regulations, protein domains, protein interactions, and pathways. This review places existing gene prioritization tools against the backdrop of an integrative Omic hierarchy view toward cancer and focuses on the analysis of their text mining components. We explain the relatively slow progress of text mining in gene prioritization, identify several challenges to current text mining methods, and highlight a few directions where more effective text mining algorithms may improve the overall prioritization task and where prioritizing the pathways may be more desirable than prioritizing only genes. PMID:25392685

  5. Text mining in cancer gene and pathway prioritization.

    PubMed

    Luo, Yuan; Riedlinger, Gregory; Szolovits, Peter

    2014-01-01

    Prioritization of cancer implicated genes has received growing attention as an effective way to reduce wet lab cost by computational analysis that ranks candidate genes according to the likelihood that experimental verifications will succeed. A multitude of gene prioritization tools have been developed, each integrating different data sources covering gene sequences, differential expressions, function annotations, gene regulations, protein domains, protein interactions, and pathways. This review places existing gene prioritization tools against the backdrop of an integrative Omic hierarchy view toward cancer and focuses on the analysis of their text mining components. We explain the relatively slow progress of text mining in gene prioritization, identify several challenges to current text mining methods, and highlight a few directions where more effective text mining algorithms may improve the overall prioritization task and where prioritizing the pathways may be more desirable than prioritizing only genes.

  6. A Gene Gravity Model for the Evolution of Cancer Genomes: A Study of 3,000 Cancer Genomes across 9 Cancer Types

    PubMed Central

    Lin, Chen-Ching; Zhao, Junfei; Jia, Peilin; Li, Wen-Hsiung; Zhao, Zhongming

    2015-01-01

    Cancer development and progression result from somatic evolution by an accumulation of genomic alterations. The effects of those alterations on the fitness of somatic cells lead to evolutionary adaptations such as increased cell proliferation, angiogenesis, and altered anticancer drug responses. However, there are few general mathematical models to quantitatively examine how perturbations of a single gene shape subsequent evolution of the cancer genome. In this study, we proposed the gene gravity model to study the evolution of cancer genomes by incorporating the genome-wide transcription and somatic mutation profiles of ~3,000 tumors across 9 cancer types from The Cancer Genome Atlas into a broad gene network. We found that somatic mutations of a cancer driver gene may drive cancer genome evolution by inducing mutations in other genes. This functional consequence is often generated by the combined effect of genetic and epigenetic (e.g., chromatin regulation) alterations. By quantifying cancer genome evolution using the gene gravity model, we identified six putative cancer genes (AHNAK, COL11A1, DDX3X, FAT4, STAG2, and SYNE1). The tumor genomes harboring the nonsynonymous somatic mutations in these genes had a higher mutation density at the genome level compared to the wild-type groups. Furthermore, we provided statistical evidence that hypermutation of cancer driver genes on inactive X chromosomes is a general feature in female cancer genomes. In summary, this study sheds light on the functional consequences and evolutionary characteristics of somatic mutations during tumorigenesis by propelling adaptive cancer genome evolution, which would provide new perspectives for cancer research and therapeutics. PMID:26352260

  7. A Gene Gravity Model for the Evolution of Cancer Genomes: A Study of 3,000 Cancer Genomes across 9 Cancer Types.

    PubMed

    Cheng, Feixiong; Liu, Chuang; Lin, Chen-Ching; Zhao, Junfei; Jia, Peilin; Li, Wen-Hsiung; Zhao, Zhongming

    2015-09-01

    Cancer development and progression result from somatic evolution by an accumulation of genomic alterations. The effects of those alterations on the fitness of somatic cells lead to evolutionary adaptations such as increased cell proliferation, angiogenesis, and altered anticancer drug responses. However, there are few general mathematical models to quantitatively examine how perturbations of a single gene shape subsequent evolution of the cancer genome. In this study, we proposed the gene gravity model to study the evolution of cancer genomes by incorporating the genome-wide transcription and somatic mutation profiles of ~3,000 tumors across 9 cancer types from The Cancer Genome Atlas into a broad gene network. We found that somatic mutations of a cancer driver gene may drive cancer genome evolution by inducing mutations in other genes. This functional consequence is often generated by the combined effect of genetic and epigenetic (e.g., chromatin regulation) alterations. By quantifying cancer genome evolution using the gene gravity model, we identified six putative cancer genes (AHNAK, COL11A1, DDX3X, FAT4, STAG2, and SYNE1). The tumor genomes harboring the nonsynonymous somatic mutations in these genes had a higher mutation density at the genome level compared to the wild-type groups. Furthermore, we provided statistical evidence that hypermutation of cancer driver genes on inactive X chromosomes is a general feature in female cancer genomes. In summary, this study sheds light on the functional consequences and evolutionary characteristics of somatic mutations during tumorigenesis by propelling adaptive cancer genome evolution, which would provide new perspectives for cancer research and therapeutics.

  8. Three-Dimensional Gene Map of Cancer Cell Types: Structural Entropy Minimisation Principle for Defining Tumour Subtypes

    PubMed Central

    Li, Angsheng; Yin, Xianchen; Pan, Yicheng

    2016-01-01

    In this study, we propose a method for constructing cell sample networks from gene expression profiles, and a structural entropy minimisation principle for detecting natural structure of networks and for identifying cancer cell subtypes. Our method establishes a three-dimensional gene map of cancer cell types and subtypes. The identified subtypes are defined by a unique gene expression pattern, and a three-dimensional gene map is established by defining the unique gene expression pattern for each identified subtype for cancers, including acute leukaemia, lymphoma, multi-tissue, lung cancer and healthy tissue. Our three-dimensional gene map demonstrates that a true tumour type may be divided into subtypes, each defined by a unique gene expression pattern. Clinical data analyses demonstrate that most cell samples of an identified subtype share similar survival times, survival indicators and International Prognostic Index (IPI) scores and indicate that distinct subtypes identified by our algorithms exhibit different overall survival times, survival ratios and IPI scores. Our three-dimensional gene map establishes a high-definition, one-to-one map between the biologically and medically meaningful tumour subtypes and the gene expression patterns, and identifies remarkable cells that form singleton submodules. PMID:26842724

  9. A Penalized Robust Method for Identifying Gene-Environment Interactions

    PubMed Central

    Shi, Xingjie; Liu, Jin; Huang, Jian; Zhou, Yong; Xie, Yang; Ma, Shuangge

    2015-01-01

    In high-throughput studies, an important objective is to identify gene-environment interactions associated with disease outcomes and phenotypes. Many commonly adopted methods assume specific parametric or semiparametric models, which may be subject to model mis-specification. In addition, they usually use significance level as the criterion for selecting important interactions. In this study, we adopt the rank-based estimation, which is much less sensitive to model specification than some of the existing methods and includes several commonly encountered data and models as special cases. Penalization is adopted for the identification of gene-environment interactions. It achieves simultaneous estimation and identification and does not rely on significance level. For computation feasibility, a smoothed rank estimation is further proposed. Simulation shows that under certain scenarios, for example with contaminated or heavy-tailed data, the proposed method can significantly outperform the existing alternatives with more accurate identification. We analyze a lung cancer prognosis study with gene expression measurements under the AFT (accelerated failure time) model. The proposed method identifies interactions different from those using the alternatives. Some of the identified genes have important implications. PMID:24616063

  10. Genome-wide association study identifies novel breast cancer susceptibility loci

    PubMed Central

    Easton, Douglas F.; Pooley, Karen A.; Dunning, Alison M.; Pharoah, Paul D. P.; Thompson, Deborah; Ballinger, Dennis G.; Struewing, Jeffery P.; Morrison, Jonathan; Field, Helen; Luben, Robert; Wareham, Nicholas; Ahmed, Shahana; Healey, Catherine S.; Bowman, Richard; Meyer, Kerstin B.; Haiman, Christopher A.; Kolonel, Laurence K.; Henderson, Brian E.; Marchand, Loic Le; Brennan, Paul; Sangrajrang, Suleeporn; Gaborieau, Valerie; Odefrey, Fabrice; Shen, Chen-Yang; Wu, Pei-Ei; Wang, Hui-Chun; Eccles, Diana; Evans, D. Gareth; Peto, Julian; Fletcher, Olivia; Johnson, Nichola; Seal, Sheila; Stratton, Michael R.; Rahman, Nazneen; Chenevix-Trench, Georgia; Bojesen, Stig E.; Nordestgaard, Børge G.; Axelsson, Christen K.; Garcia-Closas, Montserrat; Brinton, Louise; Chanock, Stephen; Lissowska, Jolanta; Peplonska, Beata; Nevanlinna, Heli; Fagerholm, Rainer; Eerola, Hannaleena; Kang, Daehee; Yoo, Keun-Young; Noh, Dong-Young; Ahn, Sei-Hyun; Hunter, David J.; Hankinson, Susan E.; Cox, David G.; Hall, Per; Wedren, Sara; Liu, Jianjun; Low, Yen-Ling; Bogdanova, Natalia; Schürmann, Peter; Dörk, Thilo; Tollenaar, Rob A. E. M.; Jacobi, Catharina E.; Devilee, Peter; Klijn, Jan G. M.; Sigurdson, Alice J.; Doody, Michele M.; Alexander, Bruce H.; Zhang, Jinghui; Cox, Angela; Brock, Ian W.; MacPherson, Gordon; Reed, Malcolm W. R.; Couch, Fergus J.; Goode, Ellen L.; Olson, Janet E.; Meijers-Heijboer, Hanne; van den Ouweland, Ans; Uitterlinden, André; Rivadeneira, Fernando; Milne, Roger L.; Ribas, Gloria; Gonzalez-Neira, Anna; Benitez, Javier; Hopper, John L.; McCredie, Margaret; Southey, Melissa; Giles, Graham G.; Schroen, Chris; Justenhoven, Christina; Brauch, Hiltrud; Hamann, Ute; Ko, Yon-Dschun; Spurdle, Amanda B.; Beesley, Jonathan; Chen, Xiaoqing; Mannermaa, Arto; Kosma, Veli-Matti; Kataja, Vesa; Hartikainen, Jaana; Day, Nicholas E.; Cox, David R.; Ponder, Bruce A. J.; Luccarini, Craig; Conroy, Don; Shah, Mitul; Munday, Hannah; Jordan, Clare; Perkins, Barbara; West, Judy; Redman, Karen; Driver, Kristy; Aghmesheh, Morteza; Amor, David; Andrews, Lesley; Antill, Yoland; Armes, Jane; Armitage, Shane; Arnold, Leanne; Balleine, Rosemary; Begley, Glenn; Beilby, John; Bennett, Ian; Bennett, Barbara; Berry, Geoffrey; Blackburn, Anneke; Brennan, Meagan; Brown, Melissa; Buckley, Michael; Burke, Jo; Butow, Phyllis; Byron, Keith; Callen, David; Campbell, Ian; Chenevix-Trench, Georgia; Clarke, Christine; Colley, Alison; Cotton, Dick; Cui, Jisheng; Culling, Bronwyn; Cummings, Margaret; Dawson, Sarah-Jane; Dixon, Joanne; Dobrovic, Alexander; Dudding, Tracy; Edkins, Ted; Eisenbruch, Maurice; Farshid, Gelareh; Fawcett, Susan; Field, Michael; Firgaira, Frank; Fleming, Jean; Forbes, John; Friedlander, Michael; Gaff, Clara; Gardner, Mac; Gattas, Mike; George, Peter; Giles, Graham; Gill, Grantley; Goldblatt, Jack; Greening, Sian; Grist, Scott; Haan, Eric; Harris, Marion; Hart, Stewart; Hayward, Nick; Hopper, John; Humphrey, Evelyn; Jenkins, Mark; Jones, Alison; Kefford, Rick; Kirk, Judy; Kollias, James; Kovalenko, Sergey; Lakhani, Sunil; Leary, Jennifer; Lim, Jacqueline; Lindeman, Geoff; Lipton, Lara; Lobb, Liz; Maclurcan, Mariette; Mann, Graham; Marsh, Deborah; McCredie, Margaret; McKay, Michael; McLachlan, Sue Anne; Meiser, Bettina; Milne, Roger; Mitchell, Gillian; Newman, Beth; O'Loughlin, Imelda; Osborne, Richard; Peters, Lester; Phillips, Kelly; Price, Melanie; Reeve, Jeanne; Reeve, Tony; Richards, Robert; Rinehart, Gina; Robinson, Bridget; Rudzki, Barney; Salisbury, Elizabeth; Sambrook, Joe; Saunders, Christobel; Scott, Clare; Scott, Elizabeth; Scott, Rodney; Seshadri, Ram; Shelling, Andrew; Southey, Melissa; Spurdle, Amanda; Suthers, Graeme; Taylor, Donna; Tennant, Christopher; Thorne, Heather; Townshend, Sharron; Tucker, Kathy; Tyler, Janet; Venter, Deon; Visvader, Jane; Walpole, Ian; Ward, Robin; Waring, Paul; Warner, Bev; Warren, Graham; Watson, Elizabeth; Williams, Rachael; Wilson, Judy; Winship, Ingrid; Young, Mary Ann; Bowtell, David; Green, Adele; deFazio, Anna; Chenevix-Trench, Georgia; Gertig, Dorota; Webb, Penny

    2009-01-01

    Breast cancer exhibits familial aggregation, consistent with variation in genetic susceptibility to the disease. Known susceptibility genes account for less than 25% of the familial risk of breast cancer, and the residual genetic variance is likely to be due to variants conferring more moderate risks. To identify further susceptibility alleles, we conducted a two-stage genome-wide association study in 4,398 breast cancer cases and 4,316 controls, followed by a third stage in which 30 single nucleotide polymorphisms (SNPs) were tested for confirmation in 21,860 cases and 22,578 controls from 22 studies. We used 227,876 SNPs that were estimated to correlate with 77% of known common SNPs in Europeans at r2>0.5. SNPs in five novel independent loci exhibited strong and consistent evidence of association with breast cancer (P<10−7). Four of these contain plausible causative genes (FGFR2, TNRC9, MAP3K1 and LSP1). At the second stage, 1,792 SNPs were significant at the P<0.05 level compared with an estimated 1,343 that would be expected by chance, indicating that many additional common susceptibility alleles may be identifiable by this approach. PMID:17529967

  11. Prediction of epigenetically regulated genes in breast cancer cell lines

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Loss, Leandro A; Sadanandam, Anguraj; Durinck, Steffen

    Methylation of CpG islands within the DNA promoter regions is one mechanism that leads to aberrant gene expression in cancer. In particular, the abnormal methylation of CpG islands may silence associated genes. Therefore, using high-throughput microarrays to measure CpG island methylation will lead to better understanding of tumor pathobiology and progression, while revealing potentially new biomarkers. We have examined a recently developed high-throughput technology for measuring genome-wide methylation patterns called mTACL. Here, we propose a computational pipeline for integrating gene expression and CpG island methylation profles to identify epigenetically regulated genes for a panel of 45 breast cancer cell lines,more » which is widely used in the Integrative Cancer Biology Program (ICBP). The pipeline (i) reduces the dimensionality of the methylation data, (ii) associates the reduced methylation data with gene expression data, and (iii) ranks methylation-expression associations according to their epigenetic regulation. Dimensionality reduction is performed in two steps: (i) methylation sites are grouped across the genome to identify regions of interest, and (ii) methylation profles are clustered within each region. Associations between the clustered methylation and the gene expression data sets generate candidate matches within a fxed neighborhood around each gene. Finally, the methylation-expression associations are ranked through a logistic regression, and their significance is quantified through permutation analysis. Our two-step dimensionality reduction compressed 90% of the original data, reducing 137,688 methylation sites to 14,505 clusters. Methylation-expression associations produced 18,312 correspondences, which were used to further analyze epigenetic regulation. Logistic regression was used to identify 58 genes from these correspondences that showed a statistically signifcant negative correlation between methylation profles and gene expression in

  12. Inferring gene dependency network specific to phenotypic alteration based on gene expression data and clinical information of breast cancer.

    PubMed

    Zhou, Xionghui; Liu, Juan

    2014-01-01

    Although many methods have been proposed to reconstruct gene regulatory network, most of them, when applied in the sample-based data, can not reveal the gene regulatory relations underlying the phenotypic change (e.g. normal versus cancer). In this paper, we adopt phenotype as a variable when constructing the gene regulatory network, while former researches either neglected it or only used it to select the differentially expressed genes as the inputs to construct the gene regulatory network. To be specific, we integrate phenotype information with gene expression data to identify the gene dependency pairs by using the method of conditional mutual information. A gene dependency pair (A,B) means that the influence of gene A on the phenotype depends on gene B. All identified gene dependency pairs constitute a directed network underlying the phenotype, namely gene dependency network. By this way, we have constructed gene dependency network of breast cancer from gene expression data along with two different phenotype states (metastasis and non-metastasis). Moreover, we have found the network scale free, indicating that its hub genes with high out-degrees may play critical roles in the network. After functional investigation, these hub genes are found to be biologically significant and specially related to breast cancer, which suggests that our gene dependency network is meaningful. The validity has also been justified by literature investigation. From the network, we have selected 43 discriminative hubs as signature to build the classification model for distinguishing the distant metastasis risks of breast cancer patients, and the result outperforms those classification models with published signatures. In conclusion, we have proposed a promising way to construct the gene regulatory network by using sample-based data, which has been shown to be effective and accurate in uncovering the hidden mechanism of the biological process and identifying the gene signature for

  13. Frequency of Germline Mutations in 25 Cancer Susceptibility Genes in a Sequential Series of Patients With Breast Cancer

    PubMed Central

    Lin, Nancy U.; Kidd, John; Allen, Brian A.; Singh, Nanda; Wenstrup, Richard J.; Hartman, Anne-Renee; Winer, Eric P.; Garber, Judy E.

    2016-01-01

    Purpose Testing for germline mutations in BRCA1/2 is standard for select patients with breast cancer to guide clinical management. Next-generation sequencing (NGS) allows testing for mutations in additional breast cancer predisposition genes. The frequency of germline mutations detected by using NGS has been reported in patients with breast cancer who were referred for BRCA1/2 testing or with triple-negative breast cancer. We assessed the frequency and predictors of mutations in 25 cancer predisposition genes, including BRCA1/2, in a sequential series of patients with breast cancer at an academic institution to examine the utility of genetic testing in this population. Methods Patients with stages I to III breast cancer who were seen at a single cancer center between 2010 and 2012, and who agreed to participate in research DNA banking, were included (N = 488). Personal and family cancer histories were collected and germline DNA was sequenced with NGS to identify mutations. Results Deleterious mutations were identified in 10.7% of women, including 6.1% in BRCA1/2 (5.1% in non-Ashkenazi Jewish patients) and 4.6% in other breast/ovarian cancer predisposition genes including CHEK2 (n = 10), ATM (n = 4), BRIP1 (n = 4), and one each in PALB2, PTEN, NBN, RAD51C, RAD51D, MSH6, and PMS2. Whereas young age (P < .01), Ashkenazi Jewish ancestry (P < .01), triple-negative breast cancer (P = .01), and family history of breast/ovarian cancer (P = .01) predicted for BRCA1/2 mutations, no factors predicted for mutations in other breast cancer predisposition genes. Conclusion Among sequential patients with breast cancer, 10.7% were found to have a germline mutation in a gene that predisposes women to breast or ovarian cancer, using a panel of 25 predisposition genes. Factors that predict for BRCA1/2 mutations do not predict for mutations in other breast/ovarian cancer susceptibility genes when these genes are analyzed as a single group. Additional cohorts will be helpful to define

  14. Large-scale association analysis identifies new lung cancer susceptibility loci and heterogeneity in genetic susceptibility across histological subtypes

    PubMed Central

    McKay, James D.; Hung, Rayjean J.; Han, Younghun; Zong, Xuchen; Carreras-Torres, Robert; Christiani, David C.; Caporaso, Neil E.; Johansson, Mattias; Xiao, Xiangjun; Li, Yafang; Byun, Jinyoung; Dunning, Alison; Pooley, Karen A.; Qian, David C.; Ji, Xuemei; Liu, Geoffrey; Timofeeva, Maria N.; Bojesen, Stig E.; Wu, Xifeng; Le Marchand, Loic; Albanes, Demetrios; Bickeböller, Heike; Aldrich, Melinda C.; Bush, William S.; Tardon, Adonina; Rennert, Gad; Teare, M. Dawn; Field, John K.; Kiemeney, Lambertus A.; Lazarus, Philip; Haugen, Aage; Lam, Stephen; Schabath, Matthew B.; Andrew, Angeline S.; Shen, Hongbing; Hong, Yun-Chul; Yuan, Jian-Min; Bertazzi, Pier Alberto; Pesatori, Angela C.; Ye, Yuanqing; Diao, Nancy; Su, Li; Zhang, Ruyang; Brhane, Yonathan; Leighl, Natasha; Johansen, Jakob S.; Mellemgaard, Anders; Saliba, Walid; Haiman, Christopher A.; Wilkens, Lynne R.; Fernandez-Somoano, Ana; Fernandez-Tardon, Guillermo; van der Heijden, Henricus F.M.; Kim, Jin Hee; Dai, Juncheng; Hu, Zhibin; Davies, Michael PA; Marcus, Michael W.; Brunnström, Hans; Manjer, Jonas; Melander, Olle; Muller, David C.; Overvad, Kim; Trichopoulou, Antonia; Tumino, Rosario; Doherty, Jennifer A.; Barnett, Matt P.; Chen, Chu; Goodman, Gary E.; Cox, Angela; Taylor, Fiona; Woll, Penella; Brüske, Irene; Wichmann, H.-Erich; Manz, Judith; Muley, Thomas R.; Risch, Angela; Rosenberger, Albert; Grankvist, Kjell; Johansson, Mikael; Shepherd, Frances A.; Tsao, Ming-Sound; Arnold, Susanne M.; Haura, Eric B.; Bolca, Ciprian; Holcatova, Ivana; Janout, Vladimir; Kontic, Milica; Lissowska, Jolanta; Mukeria, Anush; Ognjanovic, Simona; Orlowski, Tadeusz M.; Scelo, Ghislaine; Swiatkowska, Beata; Zaridze, David; Bakke, Per; Skaug, Vidar; Zienolddiny, Shanbeh; Duell, Eric J.; Butler, Lesley M.; Koh, Woon-Puay; Gao, Yu-Tang; Houlston, Richard S.; McLaughlin, John; Stevens, Victoria L.; Joubert, Philippe; Lamontagne, Maxime; Nickle, David C.; Obeidat, Ma’en; Timens, Wim; Zhu, Bin; Song, Lei; Kachuri, Linda; Artigas, María Soler; Tobin, Martin D.; Wain, Louise V.; Rafnar, Thorunn; Thorgeirsson, Thorgeir E.; Reginsson, Gunnar W.; Stefansson, Kari; Hancock, Dana B.; Bierut, Laura J.; Spitz, Margaret R.; Gaddis, Nathan C.; Lutz, Sharon M.; Gu, Fangyi; Johnson, Eric O.; Kamal, Ahsan; Pikielny, Claudio; Zhu, Dakai; Lindströem, Sara; Jiang, Xia; Tyndale, Rachel F.; Chenevix-Trench, Georgia; Beesley, Jonathan; Bossé, Yohan; Chanock, Stephen; Brennan, Paul; Landi, Maria Teresa; Amos, Christopher I.

    2017-01-01

    Summary While several lung cancer susceptibility loci have been identified, much of lung cancer heritability remains unexplained. Here, 14,803 cases and 12,262 controls of European descent were genotyped on the OncoArray and combined with existing data for an aggregated GWAS analysis of lung cancer on 29,266 patients and 56,450 controls. We identified 18 susceptibility loci achieving genome wide significance, including 10 novel loci. The novel loci highlighted the striking heterogeneity in genetic susceptibility across lung cancer histological subtypes, with four loci associated with lung cancer overall and six with lung adenocarcinoma. Gene expression quantitative trait analysis (eQTL) in 1,425 normal lung tissues highlighted RNASET2, SECISBP2L and NRG1 as candidate genes. Other loci include genes such as a cholinergic nicotinic receptor, CHRNA2, and the telomere-related genes, OFBC1 and RTEL1. Further exploration of the target genes will continue to provide new insights into the etiology of lung cancer. PMID:28604730

  15. The Potential for Tumor Suppressor Gene Therapy in Head and Neck Cancer

    PubMed Central

    Birkeland, Andrew C.; Ludwig, Megan L.; Spector, Matthew E.; Brenner, J. Chad

    2016-01-01

    Head and neck squamous cell carcinoma remains a highly morbid and fatal disease. Importantly, genomic sequencing of head and neck cancers has identified frequent mutations in tumor suppressor genes. While targeted therapeutics increasingly are being investigated in head and neck cancer, the majority of these agents are against overactive/overexpressed oncogenes. Therapy to restore lost tumor suppressor gene function remains a key and under-addressed niche in trials for head and neck cancer. Recent advances in gene editing have captured the interest of both the scientific community and the public. As our technology for gene editing and gene expression modulation improves, addressing lost tumor suppressor gene function in head and neck cancers is becoming a reality. This review will summarize new techniques, challenges to implementation, future directions, and ethical ramifications of gene therapy in head and neck cancer. PMID:26896601

  16. Gene-Environment Interactions in Cancer Epidemiology: A National Cancer Institute Think Tank Report

    PubMed Central

    Hutter, Carolyn M.; Mechanic, Leah E.; Chatterjee, Nilanjan; Kraft, Peter; Gillander, Elizabeth M.

    2014-01-01

    Cancer risk is determined by a complex interplay of genetic and environmental factors. Genome-wide association studies (GWAS) have identified hundreds of common (minor allele frequency [MAF]>0.05) and less common (0.01cancer. The marginal effects of most of these variants have been small (odds ratios: 1.1–1.4). There remain unanswered questions on how best to incorporate the joint effects of genes and environment, including gene-environment interactions, into epidemiologic studies of cancer. To help address these questions, and to better inform research priorities and allocation of resources, the National Cancer Institute sponsored a “Gene-Environment Think Tank” on January 10th–011th, 2012. The objective of the Think Tank was to facilitate discussions on: 1) the state of the science; 2) the goals of gene-environment interaction studies in cancer epidemiology; and 3) opportunities for developing novel study designs and analysis tools. This report summarizes the Think Tank discussion, with a focus on contemporary approaches to the analysis of gene-environment interactions. Selecting the appropriate methods requires first identifying the relevant scientific question and rationale, with an important distinction made between analyses aiming to characterize the joint effects of putative or established genetic and environmental factors and analyses aiming to discover novel risk factors or novel interaction effects. Other discussion items include measurement error, statistical power, significance and replication. Additional designs, exposure assessments, and analytical approaches need to be considered as we move from the current small number of success stories to a fuller understanding of the interplay of genetic and environmental factors. PMID:24123198

  17. Gene expression profiles help identify the tissue of origin for metastatic brain cancers.

    PubMed

    Wu, Alan H B; Drees, Julia C; Wang, Hangpin; VandenBerg, Scott R; Lal, Anita; Henner, William D; Pillai, Raji

    2010-04-26

    Metastatic brain cancers are the most common intracranial tumor and occur in about 15% of all cancer patients. In up to 10% of these patients, the primary tumor tissue remains unknown, even after a time consuming and costly workup. The Pathwork Tissue of Origin Test (Pathwork Diagnostics, Redwood City, CA, USA) is a gene expression test to aid in the diagnosis of metastatic, poorly differentiated and undifferentiated tumors. It measures the expression pattern of 1,550 genes in these tumors and compares it to the expression pattern of a panel of 15 known tumor types. The purpose of this study was to evaluate the performance of the Tissue of Origin Test in the diagnosis of primary sites for metastatic brain cancer patients. Fifteen fresh-frozen metastatic brain tumor specimens of known origins met specimen requirements. These specimens were entered into the study and processed using the Tissue of Origin Test. Results were compared to the known primary site and the agreement between the two results was assessed. Fourteen of the fifteen specimens produced microarray data files that passed all quality metrics. One originated from a tissue type that was off-panel. Among the remaining 13 cases, the Tissue of Origin Test accurately predicted the available diagnosis in 12/13 (92.3%) cases. This study demonstrates the accuracy of the Tissue of Origin Test when applied to predict the tissue of origin of metastatic brain tumors. This test could be a very useful tool for pathologists as they classify metastatic brain cancers.

  18. Gene expression profiles help identify the Tissue of Origin for metastatic brain cancers

    PubMed Central

    2010-01-01

    Background Metastatic brain cancers are the most common intracranial tumor and occur in about 15% of all cancer patients. In up to 10% of these patients, the primary tumor tissue remains unknown, even after a time consuming and costly workup. The Pathwork® Tissue of Origin Test (Pathwork Diagnostics, Redwood City, CA, USA) is a gene expression test to aid in the diagnosis of metastatic, poorly differentiated and undifferentiated tumors. It measures the expression pattern of 1,550 genes in these tumors and compares it to the expression pattern of a panel of 15 known tumor types. The purpose of this study was to evaluate the performance of the Tissue of Origin Test in the diagnosis of primary sites for metastatic brain cancer patients. Methods Fifteen fresh-frozen metastatic brain tumor specimens of known origins met specimen requirements. These specimens were entered into the study and processed using the Tissue of Origin Test. Results were compared to the known primary site and the agreement between the two results was assessed. Results Fourteen of the fifteen specimens produced microarray data files that passed all quality metrics. One originated from a tissue type that was off-panel. Among the remaining 13 cases, the Tissue of Origin Test accurately predicted the available diagnosis in 12/13 (92.3%) cases. Discussion This study demonstrates the accuracy of the Tissue of Origin Test when applied to predict the tissue of origin of metastatic brain tumors. This test could be a very useful tool for pathologists as they classify metastatic brain cancers. PMID:20420692

  19. Aberrant RNA splicing in cancer; expression changes and driver mutations of splicing factor genes.

    PubMed

    Sveen, A; Kilpinen, S; Ruusulehto, A; Lothe, R A; Skotheim, R I

    2016-05-12

    Alternative splicing is a widespread process contributing to structural transcript variation and proteome diversity. In cancer, the splicing process is commonly disrupted, resulting in both functional and non-functional end-products. Cancer-specific splicing events are known to contribute to disease progression; however, the dysregulated splicing patterns found on a genome-wide scale have until recently been less well-studied. In this review, we provide an overview of aberrant RNA splicing and its regulation in cancer. We then focus on the executors of the splicing process. Based on a comprehensive catalog of splicing factor encoding genes and analyses of available gene expression and somatic mutation data, we identify cancer-associated patterns of dysregulation. Splicing factor genes are shown to be significantly differentially expressed between cancer and corresponding normal samples, and to have reduced inter-individual expression variation in cancer. Furthermore, we identify enrichment of predicted cancer-critical genes among the splicing factors. In addition to previously described oncogenic splicing factor genes, we propose 24 novel cancer-critical splicing factors predicted from somatic mutations.

  20. Identifying microRNA/mRNA dysregulations in ovarian cancer

    PubMed Central

    2012-01-01

    Background MicroRNAs are a class of noncoding RNA molecules that co-regulate the expression of multiple genes via mRNA transcript degradation or translation inhibition. Since they often target entire pathways, they may be better drug targets than genes or proteins. MicroRNAs are known to be dysregulated in many tumours and associated with aggressive or poor prognosis phenotypes. Since they regulate mRNA in a tissue specific manner, their functional mRNA targets are poorly understood. In previous work, we developed a method to identify direct mRNA targets of microRNA using patient matched microRNA/mRNA expression data using an anti-correlation signature. This method, applied to clear cell Renal Cell Carcinoma (ccRCC), revealed many new regulatory pathways compromised in ccRCC. In the present paper, we apply this method to identify dysregulated microRNA/mRNA mechanisms in ovarian cancer using data from The Cancer Genome Atlas (TCGA). Methods TCGA Microarray data was normalized and samples whose class labels (tumour or normal) were ambiguous with respect to consensus ensemble K-Means clustering were removed. Significantly anti-correlated and correlated genes/microRNA differentially expressed between tumour and normal samples were identified. TargetScan was used to identify gene targets of microRNA. Results We identified novel microRNA/mRNA mechanisms in ovarian cancer. For example, the expression level of RAD51AP1 was found to be strongly anti-correlated with the expression of hsa-miR-140-3p, which was significantly down-regulated in the tumour samples. The anti-correlation signature was present separately in the tumour and normal samples, suggesting a direct causal dysregulation of RAD51AP1 by hsa-miR-140-3p in the ovary. Other pairs of potentially biological relevance include: hsa-miR-145/E2F3, hsa-miR-139-5p/TOP2A, and hsa-miR-133a/GCLC. We also identified sets of positively correlated microRNA/mRNA pairs that are most likely result from indirect regulatory

  1. Identifying microRNA/mRNA dysregulations in ovarian cancer.

    PubMed

    Miles, Gregory D; Seiler, Michael; Rodriguez, Lorna; Rajagopal, Gunaretnam; Bhanot, Gyan

    2012-03-27

    MicroRNAs are a class of noncoding RNA molecules that co-regulate the expression of multiple genes via mRNA transcript degradation or translation inhibition. Since they often target entire pathways, they may be better drug targets than genes or proteins. MicroRNAs are known to be dysregulated in many tumours and associated with aggressive or poor prognosis phenotypes. Since they regulate mRNA in a tissue specific manner, their functional mRNA targets are poorly understood. In previous work, we developed a method to identify direct mRNA targets of microRNA using patient matched microRNA/mRNA expression data using an anti-correlation signature. This method, applied to clear cell Renal Cell Carcinoma (ccRCC), revealed many new regulatory pathways compromised in ccRCC. In the present paper, we apply this method to identify dysregulated microRNA/mRNA mechanisms in ovarian cancer using data from The Cancer Genome Atlas (TCGA). TCGA Microarray data was normalized and samples whose class labels (tumour or normal) were ambiguous with respect to consensus ensemble K-Means clustering were removed. Significantly anti-correlated and correlated genes/microRNA differentially expressed between tumour and normal samples were identified. TargetScan was used to identify gene targets of microRNA. We identified novel microRNA/mRNA mechanisms in ovarian cancer. For example, the expression level of RAD51AP1 was found to be strongly anti-correlated with the expression of hsa-miR-140-3p, which was significantly down-regulated in the tumour samples. The anti-correlation signature was present separately in the tumour and normal samples, suggesting a direct causal dysregulation of RAD51AP1 by hsa-miR-140-3p in the ovary. Other pairs of potentially biological relevance include: hsa-miR-145/E2F3, hsa-miR-139-5p/TOP2A, and hsa-miR-133a/GCLC. We also identified sets of positively correlated microRNA/mRNA pairs that are most likely result from indirect regulatory mechanisms. Our findings identify

  2. Integrative gene network construction to analyze cancer recurrence using semi-supervised learning.

    PubMed

    Park, Chihyun; Ahn, Jaegyoon; Kim, Hyunjin; Park, Sanghyun

    2014-01-01

    The prognosis of cancer recurrence is an important research area in bioinformatics and is challenging due to the small sample sizes compared to the vast number of genes. There have been several attempts to predict cancer recurrence. Most studies employed a supervised approach, which uses only a few labeled samples. Semi-supervised learning can be a great alternative to solve this problem. There have been few attempts based on manifold assumptions to reveal the detailed roles of identified cancer genes in recurrence. In order to predict cancer recurrence, we proposed a novel semi-supervised learning algorithm based on a graph regularization approach. We transformed the gene expression data into a graph structure for semi-supervised learning and integrated protein interaction data with the gene expression data to select functionally-related gene pairs. Then, we predicted the recurrence of cancer by applying a regularization approach to the constructed graph containing both labeled and unlabeled nodes. The average improvement rate of accuracy for three different cancer datasets was 24.9% compared to existing supervised and semi-supervised methods. We performed functional enrichment on the gene networks used for learning. We identified that those gene networks are significantly associated with cancer-recurrence-related biological functions. Our algorithm was developed with standard C++ and is available in Linux and MS Windows formats in the STL library. The executable program is freely available at: http://embio.yonsei.ac.kr/~Park/ssl.php.

  3. Mithramycin is a gene-selective Sp1 inhibitor that identifies a biological intersection between cancer and neurodegeneration.

    PubMed

    Sleiman, Sama F; Langley, Brett C; Basso, Manuela; Berlin, Jill; Xia, Li; Payappilly, Jimmy B; Kharel, Madan K; Guo, Hengchang; Marsh, J Lawrence; Thompson, Leslie Michels; Mahishi, Lata; Ahuja, Preeti; MacLellan, W Robb; Geschwind, Daniel H; Coppola, Giovanni; Rohr, Jürgen; Ratan, Rajiv R

    2011-05-04

    Oncogenic transformation of postmitotic neurons triggers cell death, but the identity of genes critical for degeneration remain unclear. The antitumor antibiotic mithramycin prolongs survival of mouse models of Huntington's disease in vivo and inhibits oxidative stress-induced death in cortical neurons in vitro. We had correlated protection by mithramycin with its ability to bind to GC-rich DNA and globally displace Sp1 family transcription factors. To understand how antitumor drugs prevent neurodegeneration, here we use structure-activity relationships of mithramycin analogs to discover that selective DNA-binding inhibition of the drug is necessary for its neuroprotective effect. We identify several genes (Myc, c-Src, Hif1α, and p21(waf1/cip1)) involved in neoplastic transformation, whose altered expression correlates with protective doses of mithramycin or its analogs. Most interestingly, inhibition of one these genes, Myc, is neuroprotective, whereas forced expression of Myc induces Rattus norvegicus neuronal cell death. These results support a model in which cancer cell transformation shares key genetic components with neurodegeneration.

  4. Identifying Breast Cancer Oncogenes

    DTIC Science & Technology

    2009-10-01

    study by Boehm et al. (2007) identified IKBKE as a breast cancer oncogene that cooperates with HMLE -MEKDD to replace the function of myr-AKT in...1-0767 TITLE: Identifying Breast Cancer Oncogenes ~ PRINCIPAL INVESTIGATOR: Yashaswi Shrestha...Identifying Breast Cancer Oncogenes 5a. CONTRACT NUMBER W81XWH-08-1-0767 5b. GRANT NUMBER BC083061 - PreDoc 5c. PROGRAM ELEMENT NUMBER 6

  5. Genome-wide methylation analysis identifies genes silenced in non-seminoma cell lines

    PubMed Central

    Noor, Dzul Azri Mohamed; Jeyapalan, Jennie N; Alhazmi, Safiah; Carr, Matthew; Squibb, Benjamin; Wallace, Claire; Tan, Christopher; Cusack, Martin; Hughes, Jaime; Reader, Tom; Shipley, Janet; Sheer, Denise; Scotting, Paul J

    2016-01-01

    Silencing of genes by DNA methylation is a common phenomenon in many types of cancer. However, the genome-wide effect of DNA methylation on gene expression has been analysed in relatively few cancers. Germ cell tumours (GCTs) are a complex group of malignancies. They are unique in developing from a pluripotent progenitor cell. Previous analyses have suggested that non-seminomas exhibit much higher levels of DNA methylation than seminomas. The genomic targets that are methylated, the extent to which this results in gene silencing and the identity of the silenced genes most likely to play a role in the tumours’ biology have not yet been established. In this study, genome-wide methylation and expression analysis of GCT cell lines was combined with gene expression data from primary tumours to address this question. Genome methylation was analysed using the Illumina infinium HumanMethylome450 bead chip system and gene expression was analysed using Affymetrix GeneChip Human Genome U133 Plus 2.0 arrays. Regulation by methylation was confirmed by demethylation using 5-aza-2-deoxycytidine and reverse transcription–quantitative PCR. Large differences in the level of methylation of the CpG islands of individual genes between tumour cell lines correlated well with differential gene expression. Treatment of non-seminoma cells with 5-aza-2-deoxycytidine verified that methylation of all genes tested played a role in their silencing in yolk sac tumour cells and many of these genes were also differentially expressed in primary tumours. Genes silenced by methylation in the various GCT cell lines were identified. Several pluripotency-associated genes were identified as a major functional group of silenced genes. PMID:29263807

  6. Genome-wide methylation analysis identifies genes silenced in non-seminoma cell lines.

    PubMed

    Noor, Dzul Azri Mohamed; Jeyapalan, Jennie N; Alhazmi, Safiah; Carr, Matthew; Squibb, Benjamin; Wallace, Claire; Tan, Christopher; Cusack, Martin; Hughes, Jaime; Reader, Tom; Shipley, Janet; Sheer, Denise; Scotting, Paul J

    2016-01-01

    Silencing of genes by DNA methylation is a common phenomenon in many types of cancer. However, the genome-wide effect of DNA methylation on gene expression has been analysed in relatively few cancers. Germ cell tumours (GCTs) are a complex group of malignancies. They are unique in developing from a pluripotent progenitor cell. Previous analyses have suggested that non-seminomas exhibit much higher levels of DNA methylation than seminomas. The genomic targets that are methylated, the extent to which this results in gene silencing and the identity of the silenced genes most likely to play a role in the tumours' biology have not yet been established. In this study, genome-wide methylation and expression analysis of GCT cell lines was combined with gene expression data from primary tumours to address this question. Genome methylation was analysed using the Illumina infinium HumanMethylome450 bead chip system and gene expression was analysed using Affymetrix GeneChip Human Genome U133 Plus 2.0 arrays. Regulation by methylation was confirmed by demethylation using 5-aza-2-deoxycytidine and reverse transcription-quantitative PCR. Large differences in the level of methylation of the CpG islands of individual genes between tumour cell lines correlated well with differential gene expression. Treatment of non-seminoma cells with 5-aza-2-deoxycytidine verified that methylation of all genes tested played a role in their silencing in yolk sac tumour cells and many of these genes were also differentially expressed in primary tumours. Genes silenced by methylation in the various GCT cell lines were identified. Several pluripotency-associated genes were identified as a major functional group of silenced genes.

  7. MVisAGe Identifies Concordant and Discordant Genomic Alterations of Driver Genes in Squamous Tumors.

    PubMed

    Walter, Vonn; Du, Ying; Danilova, Ludmila; Hayward, Michele C; Hayes, D Neil

    2018-06-15

    Integrated analyses of multiple genomic datatypes are now common in cancer profiling studies. Such data present opportunities for numerous computational experiments, yet analytic pipelines are limited. Tools such as the cBioPortal and Regulome Explorer, although useful, are not easy to access programmatically or to implement locally. Here, we introduce the MVisAGe R package, which allows users to quantify gene-level associations between two genomic datatypes to investigate the effect of genomic alterations (e.g., DNA copy number changes on gene expression). Visualizing Pearson/Spearman correlation coefficients according to the genomic positions of the underlying genes provides a powerful yet novel tool for conducting exploratory analyses. We demonstrate its utility by analyzing three publicly available cancer datasets. Our approach highlights canonical oncogenes in chr11q13 that displayed the strongest associations between expression and copy number, including CCND1 and CTTN , genes not identified by copy number analysis in the primary reports. We demonstrate highly concordant usage of shared oncogenes on chr3q, yet strikingly diverse oncogene usage on chr11q as a function of HPV infection status. Regions of chr19 that display remarkable associations between methylation and gene expression were identified, as were previously unreported miRNA-gene expression associations that may contribute to the epithelial-to-mesenchymal transition. Significance: This study presents an important bioinformatics tool that will enable integrated analyses of multiple genomic datatypes. Cancer Res; 78(12); 3375-85. ©2018 AACR . ©2018 American Association for Cancer Research.

  8. Discovery of mutations in homologous recombination genes in African-American women with breast cancer.

    PubMed

    Ding, Yuan Chun; Adamson, Aaron W; Steele, Linda; Bailis, Adam M; John, Esther M; Tomlinson, Gail; Neuhausen, Susan L

    2018-04-01

    African-American women are more likely to develop aggressive breast cancer at younger ages and experience poorer cancer prognoses than non-Hispanic Caucasians. Deficiency in repair of DNA by homologous recombination (HR) is associated with cancer development, suggesting that mutations in genes that affect this process may cause breast cancer. Inherited pathogenic mutations have been identified in genes involved in repairing DNA damage, but few studies have focused on African-Americans. We screened for germline mutations in seven HR repair pathway genes in DNA of 181 African-American women with breast cancer, evaluated the potential effects of identified missense variants using in silico prediction software, and functionally characterized a set of missense variants by yeast two-hybrid assays. We identified five likely-damaging variants, including two PALB2 truncating variants (Q151X and W1038X) and three novel missense variants (RAD51C C135R, and XRCC3 L297P and V337E) that abolish protein-protein interactions in yeast two-hybrid assays. Our results add to evidence that HR gene mutations account for a proportion of the genetic risk for developing breast cancer in African-Americans. Identifying additional mutations that diminish HR may provide a tool for better assessing breast cancer risk and improving approaches for targeted treatment.

  9. Differential co-expression analysis reveals a novel prognostic gene module in ovarian cancer.

    PubMed

    Gov, Esra; Arga, Kazim Yalcin

    2017-07-10

    Ovarian cancer is one of the most significant disease among gynecological disorders that women suffered from over the centuries. However, disease-specific and effective biomarkers were still not available, since studies have focused on individual genes associated with ovarian cancer, ignoring the interactions and associations among the gene products. Here, ovarian cancer differential co-expression networks were reconstructed via meta-analysis of gene expression data and co-expressed gene modules were identified in epithelial cells from ovarian tumor and healthy ovarian surface epithelial samples to propose ovarian cancer associated genes and their interactions. We propose a novel, highly interconnected, differentially co-expressed, and co-regulated gene module in ovarian cancer consisting of 84 prognostic genes. Furthermore, the specificity of the module to ovarian cancer was shown through analyses of datasets in nine other cancers. These observations underscore the importance of transcriptome based systems biomarkers research in deciphering the elusive pathophysiology of ovarian cancer, and here, we present reciprocal interplay between candidate ovarian cancer genes and their transcriptional regulatory dynamics. The corresponding gene module might provide new insights on ovarian cancer prognosis and treatment strategies that continue to place a significant burden on global health.

  10. CHK2, A Candidate Prostate Cancer Susceptibility Gene

    DTIC Science & Technology

    2003-01-01

    To identify prostate cancer susceptibility genes, we applied a mutation screening of candidate gene approach. We screened for mutations in CHEK2 , the...families, 400 sporadic cases, and 423 unaffected men as control. A total of 28 (4.8%) germline CHEK2 mutations were found among 578 patients and...additional 11 in 9 families. Sixteen of 18 unique CHEK2 mutations identified in this study were not detected among 423 unaffected men, suggesting a

  11. Novel recurrently mutated genes in African American colon cancers.

    PubMed

    Guda, Kishore; Veigl, Martina L; Varadan, Vinay; Nosrati, Arman; Ravi, Lakshmeswari; Lutterbaugh, James; Beard, Lydia; Willson, James K V; Sedwick, W David; Wang, Zhenghe John; Molyneaux, Neil; Miron, Alexander; Adams, Mark D; Elston, Robert C; Markowitz, Sanford D; Willis, Joseph E

    2015-01-27

    We used whole-exome and targeted sequencing to characterize somatic mutations in 103 colorectal cancers (CRC) from African Americans, identifying 20 new genes as significantly mutated in CRC. Resequencing 129 Caucasian derived CRCs confirmed a 15-gene set as a preferential target for mutations in African American CRCs. Two predominant genes, ephrin type A receptor 6 (EPHA6) and folliculin (FLCN), with mutations exclusive to African American CRCs, are by genetic and biological criteria highly likely African American CRC driver genes. These previously unsuspected differences in the mutational landscapes of CRCs arising among individuals of different ethnicities have potential to impact on broader disparities in cancer behaviors.

  12. Combining Gene Signatures Improves Prediction of Breast Cancer Survival

    PubMed Central

    Zhao, Xi; Naume, Bjørn; Langerød, Anita; Frigessi, Arnoldo; Kristensen, Vessela N.; Børresen-Dale, Anne-Lise; Lingjærde, Ole Christian

    2011-01-01

    cancer survival. The presented methodology is broadly applicable to breast cancer risk assessment using any new identified gene set. PMID:21423775

  13. Integrated analysis of gene expression and methylation profiles of 48 candidate genes in breast cancer patients.

    PubMed

    Li, Zibo; Heng, Jianfu; Yan, Jinhua; Guo, Xinwu; Tang, Lili; Chen, Ming; Peng, Limin; Wu, Yepeng; Wang, Shouman; Xiao, Zhi; Deng, Zhongping; Dai, Lizhong; Wang, Jun

    2016-11-01

    Gene-specific methylation and expression have shown biological and clinical importance for breast cancer diagnosis and prognosis. Integrated analysis of gene methylation and gene expression may identify genes associated with biology mechanism and clinical outcome of breast cancer and aid in clinical management. Using high-throughput microfluidic quantitative PCR, we analyzed the expression profiles of 48 candidate genes in 96 Chinese breast cancer patients and investigated their correlation with gene methylation and associations with breast cancer clinical parameters. Breast cancer-specific gene expression alternation was found in 25 genes with significant expression difference between paired tumor and normal tissues. A total of 9 genes (CCND2, EGFR, GSTP1, PGR, PTGS2, RECK, SOX17, TNFRSF10D, and WIF1) showed significant negative correlation between methylation and gene expression, which were validated in the TCGA database. Total 23 genes (ACADL, APC, BRCA2, CADM1, CAV1, CCND2, CST6, EGFR, ESR2, GSTP1, ICAM5, NPY, PGR, PTGS2, RECK, RUNX3, SFRP1, SOX17, SYK, TGFBR2, TNFRSF10D, WIF1, and WRN) annotated with potential TFBSs in the promoter regions showed negative correlation between methylation and expression. In logistics regression analysis, 31 of the 48 genes showed improved performance in disease prediction with combination of methylation and expression coefficient. Our results demonstrated the complex correlation and the possible regulatory mechanisms between DNA methylation and gene expression. Integration analysis of methylation and expression of candidate genes could improve performance in breast cancer prediction. These findings would contribute to molecular characterization and identification of biomarkers for potential clinical applications.

  14. TGFβ Receptor 1: An Immune Susceptibility Gene in HPV-Associated Cancer

    PubMed Central

    Levovitz, Chaya; Chen, Dan; Ivansson, Emma; Gyllensten, Ulf; Finnigan, John P.; Alshawish, Sara; Zhang, Weijia; Schadt, Eric E.; Posner, Marshal R.; Genden, Eric M.; Boffetta, Paolo; Sikora, Andrew G.

    2015-01-01

    Only a minority of those exposed to human papillomavirus (HPV) develop HPV-related cervical and oropharyngeal cancer. Because host immunity affects infection and progression to cancer, we tested the hypothesis that genetic variation in immune-related genes is a determinant of susceptibility to oropharyngeal cancer and other HPV-associated cancers by performing a multitier integrative computational analysis with oropharyngeal cancer data from a head and neck cancer genome-wide association study (GWAS). Independent analyses, including single-gene, gene-interconnectivity, protein–protein interaction, gene expression, and pathway analysis, identified immune genes and pathways significantly associated with oropharyngeal cancer. TGFβR1, which intersected all tiers of analysis and thus selected for validation, replicated significantly in the head and neck cancer GWAS limited to HPV-seropositive cases and an independent cervical cancer GWAS. The TGFβR1 containing p38–MAPK pathway was significantly associated with oropharyngeal cancer and cervical cancer, and TGFβR1 was overexpressed in oropharyngeal cancer, cervical cancer, and HPV+ head and neck cancer tumors. These concordant analyses implicate TGFβR1 signaling as a process dysregulated across HPV-related cancers. This study demonstrates that genetic variation in immune-related genes is associated with susceptibility to oropharyngeal cancer and implicates TGFβR1/TGFβ signaling in the development of both oropharyngeal cancer and cervical cancer. Better understanding of the immunogenetic basis of susceptibility to HPV-associated cancers may provide insight into host/virus interactions and immune processes dysregulated in the minority of HPV-exposed individuals who progress to cancer. PMID:25273091

  15. A 15-gene signature for prediction of colon cancer recurrence and prognosis based on SVM.

    PubMed

    Xu, Guangru; Zhang, Minghui; Zhu, Hongxing; Xu, Jinhua

    2017-03-10

    To screen the gene signature for distinguishing patients with high risks from those with low-risks for colon cancer recurrence and predicting their prognosis. Five microarray datasets of colon cancer samples were collected from Gene Expression Omnibus database and one was obtained from The Cancer Genome Atlas (TCGA). After preprocessing, data in GSE17537 were analyzed using the Linear Models for Microarray data (LIMMA) method to identify the differentially expressed genes (DEGs). The DEGs further underwent PPI network-based neighborhood scoring and support vector machine (SVM) analyses to screen the feature genes associated with recurrence and prognosis, which were then validated by four datasets GSE38832, GSE17538, GSE28814 and TCGA using SVM and Cox regression analyses. A total of 1207 genes were identified as DEGs between recurrence and no-recurrence samples, including 726 downregulated and 481 upregulated genes. Using SVM analysis and five gene expression profile data confirmation, a 15-gene signature (HES5, ZNF417, GLRA2, OR8D2, HOXA7, FABP6, MUSK, HTR6, GRIP2, KLRK1, VEGFA, AKAP12, RHEB, NCRNA00152 and PMEPA1) were identified as a predictor of recurrence risk and prognosis for colon cancer patients. Our identified 15-gene signature may be useful to classify colon cancer patients with different prognosis and some genes in this signature may represent new therapeutic targets. Copyright © 2016. Published by Elsevier B.V.

  16. Differential analysis between somatic mutation and germline variation profiles reveals cancer-related genes.

    PubMed

    Przytycki, Pawel F; Singh, Mona

    2017-08-25

    A major aim of cancer genomics is to pinpoint which somatically mutated genes are involved in tumor initiation and progression. We introduce a new framework for uncovering cancer genes, differential mutation analysis, which compares the mutational profiles of genes across cancer genomes with their natural germline variation across healthy individuals. We present DiffMut, a fast and simple approach for differential mutational analysis, and demonstrate that it is more effective in discovering cancer genes than considerably more sophisticated approaches. We conclude that germline variation across healthy human genomes provides a powerful means for characterizing somatic mutation frequency and identifying cancer driver genes. DiffMut is available at https://github.com/Singh-Lab/Differential-Mutation-Analysis .

  17. An integrative somatic mutation analysis to identify pathways linked with survival outcomes across 19 cancer types

    PubMed Central

    Park, Sunho; Kim, Seung-Jun; Yu, Donghyeon; Peña-Llopis, Samuel; Gao, Jianjiong; Park, Jin Suk; Chen, Beibei; Norris, Jessie; Wang, Xinlei; Chen, Min; Kim, Minsoo; Yong, Jeongsik; Wardak, Zabi; Choe, Kevin; Story, Michael; Starr, Timothy; Cheong, Jae-Ho; Hwang, Tae Hyun

    2016-01-01

    Motivation: Identification of altered pathways that are clinically relevant across human cancers is a key challenge in cancer genomics. Precise identification and understanding of these altered pathways may provide novel insights into patient stratification, therapeutic strategies and the development of new drugs. However, a challenge remains in accurately identifying pathways altered by somatic mutations across human cancers, due to the diverse mutation spectrum. We developed an innovative approach to integrate somatic mutation data with gene networks and pathways, in order to identify pathways altered by somatic mutations across cancers. Results: We applied our approach to The Cancer Genome Atlas (TCGA) dataset of somatic mutations in 4790 cancer patients with 19 different types of tumors. Our analysis identified cancer-type-specific altered pathways enriched with known cancer-relevant genes and targets of currently available drugs. To investigate the clinical significance of these altered pathways, we performed consensus clustering for patient stratification using member genes in the altered pathways coupled with gene expression datasets from 4870 patients from TCGA, and multiple independent cohorts confirmed that the altered pathways could be used to stratify patients into subgroups with significantly different clinical outcomes. Of particular significance, certain patient subpopulations with poor prognosis were identified because they had specific altered pathways for which there are available targeted therapies. These findings could be used to tailor and intensify therapy in these patients, for whom current therapy is suboptimal. Availability and implementation: The code is available at: http://www.taehyunlab.org. Contact: jhcheong@yuhs.ac or taehyun.hwang@utsouthwestern.edu or taehyun.cs@gmail.com Supplementary information: Supplementary data are available at Bioinformatics online. PMID:26635139

  18. Systematic genomic identification of colorectal cancer genes delineating advanced from early clinical stage and metastasis

    PubMed Central

    2013-01-01

    Background Colorectal cancer is the third leading cause of cancer deaths in the United States. The initial assessment of colorectal cancer involves clinical staging that takes into account the extent of primary tumor invasion, determining the number of lymph nodes with metastatic cancer and the identification of metastatic sites in other organs. Advanced clinical stage indicates metastatic cancer, either in regional lymph nodes or in distant organs. While the genomic and genetic basis of colorectal cancer has been elucidated to some degree, less is known about the identity of specific cancer genes that are associated with advanced clinical stage and metastasis. Methods We compiled multiple genomic data types (mutations, copy number alterations, gene expression and methylation status) as well as clinical meta-data from The Cancer Genome Atlas (TCGA). We used an elastic-net regularized regression method on the combined genomic data to identify genetic aberrations and their associated cancer genes that are indicators of clinical stage. We ranked candidate genes by their regression coefficient and level of support from multiple assay modalities. Results A fit of the elastic-net regularized regression to 197 samples and integrated analysis of four genomic platforms identified the set of top gene predictors of advanced clinical stage, including: WRN, SYK, DDX5 and ADRA2C. These genetic features were identified robustly in bootstrap resampling analysis. Conclusions We conducted an analysis integrating multiple genomic features including mutations, copy number alterations, gene expression and methylation. This integrated approach in which one considers all of these genomic features performs better than any individual genomic assay. We identified multiple genes that robustly delineate advanced clinical stage, suggesting their possible role in colorectal cancer metastatic progression. PMID:24308539

  19. Gene methylation in gastric cancer.

    PubMed

    Qu, Yiping; Dang, Siwen; Hou, Peng

    2013-09-23

    Gastric cancer is one of the most common malignancies and remains the second leading cause of cancer-related death worldwide. Over 70% of new cases and deaths occur in developing countries. In the early years of the molecular biology revolution, cancer research mainly focuses on genetic alterations, including gastric cancer. Epigenetic mechanisms are essential for normal development and maintenance of tissue-specific gene expression patterns in mammals. Disruption of epigenetic processes can lead to altered gene function and malignant cellular transformation. Recent advancements in the rapidly evolving field of cancer epigenetics have shown extensive reprogramming of every component of the epigenetic machinery in cancer, including DNA methylation, histone modifications, nucleosome positioning, noncoding RNAs, and microRNAs. Aberrant DNA methylation in the promoter regions of gene, which leads to inactivation of tumor suppressor and other cancer-related genes in cancer cells, is the most well-defined epigenetic hallmark in gastric cancer. The advantages of gene methylation as a target for detection and diagnosis of cancer in biopsy specimens and non-invasive body fluids such as serum and gastric washes have led to many studies of application in gastric cancer. This review focuses on the most common and important phenomenon of epigenetics, DNA methylation, in gastric cancer and illustrates the impact epigenetics has had on this field. Copyright © 2013 The Authors. Published by Elsevier B.V. All rights reserved.

  20. Large-scale association analysis identifies new lung cancer susceptibility loci and heterogeneity in genetic susceptibility across histological subtypes.

    PubMed

    McKay, James D; Hung, Rayjean J; Han, Younghun; Zong, Xuchen; Carreras-Torres, Robert; Christiani, David C; Caporaso, Neil E; Johansson, Mattias; Xiao, Xiangjun; Li, Yafang; Byun, Jinyoung; Dunning, Alison; Pooley, Karen A; Qian, David C; Ji, Xuemei; Liu, Geoffrey; Timofeeva, Maria N; Bojesen, Stig E; Wu, Xifeng; Le Marchand, Loic; Albanes, Demetrios; Bickeböller, Heike; Aldrich, Melinda C; Bush, William S; Tardon, Adonina; Rennert, Gad; Teare, M Dawn; Field, John K; Kiemeney, Lambertus A; Lazarus, Philip; Haugen, Aage; Lam, Stephen; Schabath, Matthew B; Andrew, Angeline S; Shen, Hongbing; Hong, Yun-Chul; Yuan, Jian-Min; Bertazzi, Pier Alberto; Pesatori, Angela C; Ye, Yuanqing; Diao, Nancy; Su, Li; Zhang, Ruyang; Brhane, Yonathan; Leighl, Natasha; Johansen, Jakob S; Mellemgaard, Anders; Saliba, Walid; Haiman, Christopher A; Wilkens, Lynne R; Fernandez-Somoano, Ana; Fernandez-Tardon, Guillermo; van der Heijden, Henricus F M; Kim, Jin Hee; Dai, Juncheng; Hu, Zhibin; Davies, Michael P A; Marcus, Michael W; Brunnström, Hans; Manjer, Jonas; Melander, Olle; Muller, David C; Overvad, Kim; Trichopoulou, Antonia; Tumino, Rosario; Doherty, Jennifer A; Barnett, Matt P; Chen, Chu; Goodman, Gary E; Cox, Angela; Taylor, Fiona; Woll, Penella; Brüske, Irene; Wichmann, H-Erich; Manz, Judith; Muley, Thomas R; Risch, Angela; Rosenberger, Albert; Grankvist, Kjell; Johansson, Mikael; Shepherd, Frances A; Tsao, Ming-Sound; Arnold, Susanne M; Haura, Eric B; Bolca, Ciprian; Holcatova, Ivana; Janout, Vladimir; Kontic, Milica; Lissowska, Jolanta; Mukeria, Anush; Ognjanovic, Simona; Orlowski, Tadeusz M; Scelo, Ghislaine; Swiatkowska, Beata; Zaridze, David; Bakke, Per; Skaug, Vidar; Zienolddiny, Shanbeh; Duell, Eric J; Butler, Lesley M; Koh, Woon-Puay; Gao, Yu-Tang; Houlston, Richard S; McLaughlin, John; Stevens, Victoria L; Joubert, Philippe; Lamontagne, Maxime; Nickle, David C; Obeidat, Ma'en; Timens, Wim; Zhu, Bin; Song, Lei; Kachuri, Linda; Artigas, María Soler; Tobin, Martin D; Wain, Louise V; Rafnar, Thorunn; Thorgeirsson, Thorgeir E; Reginsson, Gunnar W; Stefansson, Kari; Hancock, Dana B; Bierut, Laura J; Spitz, Margaret R; Gaddis, Nathan C; Lutz, Sharon M; Gu, Fangyi; Johnson, Eric O; Kamal, Ahsan; Pikielny, Claudio; Zhu, Dakai; Lindströem, Sara; Jiang, Xia; Tyndale, Rachel F; Chenevix-Trench, Georgia; Beesley, Jonathan; Bossé, Yohan; Chanock, Stephen; Brennan, Paul; Landi, Maria Teresa; Amos, Christopher I

    2017-07-01

    Although several lung cancer susceptibility loci have been identified, much of the heritability for lung cancer remains unexplained. Here 14,803 cases and 12,262 controls of European descent were genotyped on the OncoArray and combined with existing data for an aggregated genome-wide association study (GWAS) analysis of lung cancer in 29,266 cases and 56,450 controls. We identified 18 susceptibility loci achieving genome-wide significance, including 10 new loci. The new loci highlight the striking heterogeneity in genetic susceptibility across the histological subtypes of lung cancer, with four loci associated with lung cancer overall and six loci associated with lung adenocarcinoma. Gene expression quantitative trait locus (eQTL) analysis in 1,425 normal lung tissue samples highlights RNASET2, SECISBP2L and NRG1 as candidate genes. Other loci include genes such as a cholinergic nicotinic receptor, CHRNA2, and the telomere-related genes OFBC1 and RTEL1. Further exploration of the target genes will continue to provide new insights into the etiology of lung cancer.

  1. Cross-platform method for identifying candidate network biomarkers for prostate cancer.

    PubMed

    Jin, G; Zhou, X; Cui, K; Zhang, X-S; Chen, L; Wong, S T C

    2009-11-01

    Discovering biomarkers using mass spectrometry (MS) and microarray expression profiles is a promising strategy in molecular diagnosis. Here, the authors proposed a new pipeline for biomarker discovery that integrates disease information for proteins and genes, expression profiles in both genomic and proteomic levels, and protein-protein interactions (PPIs) to discover high confidence network biomarkers. Using this pipeline, a total of 474 molecules (genes and proteins) related to prostate cancer were identified and a prostate-cancer-related network (PCRN) was derived from the integrative information. Thus, a set of candidate network biomarkers were identified from multiple expression profiles composed by eight microarray datasets and one proteomics dataset. The network biomarkers with PPIs can accurately distinguish the prostate patients from the normal ones, which potentially provide more reliable hits of biomarker candidates than conventional biomarker discovery methods.

  2. Genomic analyses identify molecular subtypes of pancreatic cancer.

    PubMed

    Bailey, Peter; Chang, David K; Nones, Katia; Johns, Amber L; Patch, Ann-Marie; Gingras, Marie-Claude; Miller, David K; Christ, Angelika N; Bruxner, Tim J C; Quinn, Michael C; Nourse, Craig; Murtaugh, L Charles; Harliwong, Ivon; Idrisoglu, Senel; Manning, Suzanne; Nourbakhsh, Ehsan; Wani, Shivangi; Fink, Lynn; Holmes, Oliver; Chin, Venessa; Anderson, Matthew J; Kazakoff, Stephen; Leonard, Conrad; Newell, Felicity; Waddell, Nick; Wood, Scott; Xu, Qinying; Wilson, Peter J; Cloonan, Nicole; Kassahn, Karin S; Taylor, Darrin; Quek, Kelly; Robertson, Alan; Pantano, Lorena; Mincarelli, Laura; Sanchez, Luis N; Evers, Lisa; Wu, Jianmin; Pinese, Mark; Cowley, Mark J; Jones, Marc D; Colvin, Emily K; Nagrial, Adnan M; Humphrey, Emily S; Chantrill, Lorraine A; Mawson, Amanda; Humphris, Jeremy; Chou, Angela; Pajic, Marina; Scarlett, Christopher J; Pinho, Andreia V; Giry-Laterriere, Marc; Rooman, Ilse; Samra, Jaswinder S; Kench, James G; Lovell, Jessica A; Merrett, Neil D; Toon, Christopher W; Epari, Krishna; Nguyen, Nam Q; Barbour, Andrew; Zeps, Nikolajs; Moran-Jones, Kim; Jamieson, Nigel B; Graham, Janet S; Duthie, Fraser; Oien, Karin; Hair, Jane; Grützmann, Robert; Maitra, Anirban; Iacobuzio-Donahue, Christine A; Wolfgang, Christopher L; Morgan, Richard A; Lawlor, Rita T; Corbo, Vincenzo; Bassi, Claudio; Rusev, Borislav; Capelli, Paola; Salvia, Roberto; Tortora, Giampaolo; Mukhopadhyay, Debabrata; Petersen, Gloria M; Munzy, Donna M; Fisher, William E; Karim, Saadia A; Eshleman, James R; Hruban, Ralph H; Pilarsky, Christian; Morton, Jennifer P; Sansom, Owen J; Scarpa, Aldo; Musgrove, Elizabeth A; Bailey, Ulla-Maja Hagbo; Hofmann, Oliver; Sutherland, Robert L; Wheeler, David A; Gill, Anthony J; Gibbs, Richard A; Pearson, John V; Waddell, Nicola; Biankin, Andrew V; Grimmond, Sean M

    2016-03-03

    Integrated genomic analysis of 456 pancreatic ductal adenocarcinomas identified 32 recurrently mutated genes that aggregate into 10 pathways: KRAS, TGF-β, WNT, NOTCH, ROBO/SLIT signalling, G1/S transition, SWI-SNF, chromatin modification, DNA repair and RNA processing. Expression analysis defined 4 subtypes: (1) squamous; (2) pancreatic progenitor; (3) immunogenic; and (4) aberrantly differentiated endocrine exocrine (ADEX) that correlate with histopathological characteristics. Squamous tumours are enriched for TP53 and KDM6A mutations, upregulation of the TP63∆N transcriptional network, hypermethylation of pancreatic endodermal cell-fate determining genes and have a poor prognosis. Pancreatic progenitor tumours preferentially express genes involved in early pancreatic development (FOXA2/3, PDX1 and MNX1). ADEX tumours displayed upregulation of genes that regulate networks involved in KRAS activation, exocrine (NR5A2 and RBPJL), and endocrine differentiation (NEUROD1 and NKX2-2). Immunogenic tumours contained upregulated immune networks including pathways involved in acquired immune suppression. These data infer differences in the molecular evolution of pancreatic cancer subtypes and identify opportunities for therapeutic development.

  3. Prostate cancer-associated gene expression alterations determined from needle biopsies.

    PubMed

    Qian, David Z; Huang, Chung-Ying; O'Brien, Catherine A; Coleman, Ilsa M; Garzotto, Mark; True, Lawrence D; Higano, Celestia S; Vessella, Robert; Lange, Paul H; Nelson, Peter S; Beer, Tomasz M

    2009-05-01

    To accurately identify gene expression alterations that differentiate neoplastic from normal prostate epithelium using an approach that avoids contamination by unwanted cellular components and is not compromised by acute gene expression changes associated with tumor devascularization and resulting ischemia. Approximately 3,000 neoplastic and benign prostate epithelial cells were isolated using laser capture microdissection from snap-frozen prostate biopsy specimens provided by 31 patients who subsequently participated in a clinical trial of preoperative chemotherapy. cDNA synthesized from amplified total RNA was hybridized to custom-made microarrays composed of 6,200 clones derived from the Prostate Expression Database. Expression differences for selected genes were verified using quantitative reverse transcription-PCR. Comparative analyses identified 954 transcript alterations associated with cancer (q < 0.01%), including 149 differentially expressed genes with no known functional roles. Gene expression changes associated with ischemia and surgical removal of the prostate gland were absent. Genes up-regulated in prostate cancer were statistically enriched in categories related to cellular metabolism, energy use, signal transduction, and molecular transport. Genes down-regulated in prostate cancers were enriched in categories related to immune response, cellular responses to pathogens, and apoptosis. A heterogeneous pattern of androgen receptor expression changes was noted. In exploratory analyses, androgen receptor down-regulation was associated with a lower probability of cancer relapse after neoadjuvant chemotherapy followed by radical prostatectomy. Assessments of tumor phenotypes based on gene expression for treatment stratification and drug targeting of oncogenic alterations may best be ascertained using biopsy-based analyses where the effects of ischemia do not complicate interpretation.

  4. Prostate Cancer-Associated Gene Expression Alterations Determined from Needle Biopsies

    PubMed Central

    Qian, David Z.; Huang, Chung-Ying; O'Brien, Catherine A.; Coleman, Ilsa M.; Garzotto, Mark; True, Lawrence D.; Higano, Celestia S.; Vessella, Robert; Lange, Paul H.; Nelson, Peter S.; Beer, Tomasz M.

    2010-01-01

    Purpose To accurately identify gene expression alterations that differentiate neoplastic from normal prostate epithelium using an approach that avoids contamination by unwanted cellular components and is not compromised by acute gene expression changes associated with tumor devascularization and resulting ischemia. Experimental Design Approximately 3,000 neoplastic and benign prostate epithelial cells were isolated using laser capture microdissection from snap-frozen prostate biopsy specimens provided by 31 patients who subsequently participated in a clinical trial of preoperative chemotherapy. cDNA synthesized from amplified total RNA was hybridized to custom-made microarrays comprised of 6200 clones derived from the Prostate Expression Database. Expression differences for selected genes were verified using quantitative RT-PCR. Results Comparative analyses identified 954 transcript alterations associated with cancer (q value <0.01%) including 149 differentially expressed genes with no known functional roles. Gene expression changes associated with ischemia and surgical removal of the prostate gland were absent. Genes up-regulated in prostate cancer were statistically enriched in categories related to cellular metabolism, energy utilization, signal transduction, and molecular transport. Genes down-regulated in prostate cancers were enriched in categories related to immune response, cellular responses to pathogens, and apoptosis. A heterogeneous pattern of AR expression changes was noted. In exploratory analyses, AR down regulation was associated with a lower probability of cancer relapse after neoadjuvant chemotherapy followed by radical prostatectomy. Conclusions Assessments of tumor phenotypes based on gene expression for treatment stratification and drug targeting of oncogenic alterations may best be ascertained using biopsy-based analyses where the effects of ischemia do not complicate interpretation. PMID:19366833

  5. GSNFS: Gene subnetwork biomarker identification of lung cancer expression data.

    PubMed

    Doungpan, Narumol; Engchuan, Worrawat; Chan, Jonathan H; Meechai, Asawin

    2016-12-05

    Gene expression has been used to identify disease gene biomarkers, but there are ongoing challenges. Single gene or gene-set biomarkers are inadequate to provide sufficient understanding of complex disease mechanisms and the relationship among those genes. Network-based methods have thus been considered for inferring the interaction within a group of genes to further study the disease mechanism. Recently, the Gene-Network-based Feature Set (GNFS), which is capable of handling case-control and multiclass expression for gene biomarker identification, has been proposed, partly taking into account of network topology. However, its performance relies on a greedy search for building subnetworks and thus requires further improvement. In this work, we establish a new approach named Gene Sub-Network-based Feature Selection (GSNFS) by implementing the GNFS framework with two proposed searching and scoring algorithms, namely gene-set-based (GS) search and parent-node-based (PN) search, to identify subnetworks. An additional dataset is used to validate the results. The two proposed searching algorithms of the GSNFS method for subnetwork expansion are concerned with the degree of connectivity and the scoring scheme for building subnetworks and their topology. For each iteration of expansion, the neighbour genes of a current subnetwork, whose expression data improved the overall subnetwork score, is recruited. While the GS search calculated the subnetwork score using an activity score of a current subnetwork and the gene expression values of its neighbours, the PN search uses the expression value of the corresponding parent of each neighbour gene. Four lung cancer expression datasets were used for subnetwork identification. In addition, using pathway data and protein-protein interaction as network data in order to consider the interaction among significant genes were discussed. Classification was performed to compare the performance of the identified gene subnetworks with three

  6. Comprehensive Ex Vivo Transposon Mutagenesis Identifies Genes That Promote Growth Factor Independence and Leukemogenesis.

    PubMed

    Guo, Yabin; Updegraff, Barrett L; Park, Sunho; Durakoglugil, Deniz; Cruz, Victoria H; Maddux, Sarah; Hwang, Tae Hyun; O'Donnell, Kathryn A

    2016-02-15

    Aberrant signaling through cytokine receptors and their downstream signaling pathways is a major oncogenic mechanism underlying hematopoietic malignancies. To better understand how these pathways become pathologically activated and to potentially identify new drivers of hematopoietic cancers, we developed a high-throughput functional screening approach using ex vivo mutagenesis with the Sleeping Beauty transposon. We analyzed over 1,100 transposon-mutagenized pools of Ba/F3 cells, an IL3-dependent pro-B-cell line, which acquired cytokine independence and tumor-forming ability. Recurrent transposon insertions could be mapped to genes in the JAK/STAT and MAPK pathways, confirming the ability of this strategy to identify known oncogenic components of cytokine signaling pathways. In addition, recurrent insertions were identified in a large set of genes that have been found to be mutated in leukemia or associated with survival, but were not previously linked to the JAK/STAT or MAPK pathways nor shown to functionally contribute to leukemogenesis. Forced expression of these novel genes resulted in IL3-independent growth in vitro and tumorigenesis in vivo, validating this mutagenesis-based approach for identifying new genes that promote cytokine signaling and leukemogenesis. Therefore, our findings provide a broadly applicable approach for classifying functionally relevant genes in diverse malignancies and offer new insights into the impact of cytokine signaling on leukemia development. ©2015 American Association for Cancer Research.

  7. Germline pathogenic variants in PALB2 and other cancer-predisposing genes in families with hereditary diffuse gastric cancer without CDH1 mutation: a whole-exome sequencing study.

    PubMed

    Fewings, Eleanor; Larionov, Alexey; Redman, James; Goldgraben, Mae A; Scarth, James; Richardson, Susan; Brewer, Carole; Davidson, Rosemarie; Ellis, Ian; Evans, D Gareth; Halliday, Dorothy; Izatt, Louise; Marks, Peter; McConnell, Vivienne; Verbist, Louis; Mayes, Rebecca; Clark, Graeme R; Hadfield, James; Chin, Suet-Feung; Teixeira, Manuel R; Giger, Olivier T; Hardwick, Richard; di Pietro, Massimiliano; O'Donovan, Maria; Pharoah, Paul; Caldas, Carlos; Fitzgerald, Rebecca C; Tischkowitz, Marc

    2018-04-26

    Germline pathogenic variants in the E-cadherin gene (CDH1) are strongly associated with the development of hereditary diffuse gastric cancer. There is a paucity of data to guide risk assessment and management of families with hereditary diffuse gastric cancer that do not carry a CDH1 pathogenic variant, making it difficult to make informed decisions about surveillance and risk-reducing surgery. We aimed to identify new candidate genes associated with predisposition to hereditary diffuse gastric cancer in affected families without pathogenic CDH1 variants. We did whole-exome sequencing on DNA extracted from the blood of 39 individuals (28 individuals diagnosed with hereditary diffuse gastric cancer and 11 unaffected first-degree relatives) in 22 families without pathogenic CDH1 variants. Genes with loss-of-function variants were prioritised using gene-interaction analysis to identify clusters of genes that could be involved in predisposition to hereditary diffuse gastric cancer. Protein-affecting germline variants were identified in probands from six families with hereditary diffuse gastric cancer; variants were found in genes known to predispose to cancer and in lesser-studied DNA repair genes. A frameshift deletion in PALB2 was found in one member of a family with a history of gastric and breast cancer. Two different MSH2 variants were identified in two unrelated affected individuals, including one frameshift insertion and one previously described start-codon loss. One family had a unique combination of variants in the DNA repair genes ATR and NBN. Two variants in the DNA repair gene RECQL5 were identified in two unrelated families: one missense variant and a splice-acceptor variant. The results of this study suggest a role for the known cancer predisposition gene PALB2 in families with hereditary diffuse gastric cancer and no detected pathogenic CDH1 variants. We also identified new candidate genes associated with disease risk in these families. UK Medical

  8. New genes linked to lung cancer susceptibility in Asian women

    Cancer.gov

    An international group of scientists has identified three genes that predispose Asian women who have never smoked to lung cancer. The discovery of specific genetic variations, which have not previously been associated with lung cancer risk in other popul

  9. Integrative molecular network analysis identifies emergent enzalutamide resistance mechanisms in prostate cancer

    PubMed Central

    King, Carly J.; Woodward, Josha; Schwartzman, Jacob; Coleman, Daniel J.; Lisac, Robert; Wang, Nicholas J.; Van Hook, Kathryn; Gao, Lina; Urrutia, Joshua; Dane, Mark A.; Heiser, Laura M.; Alumkal, Joshi J.

    2017-01-01

    Recent work demonstrates that castration-resistant prostate cancer (CRPC) tumors harbor countless genomic aberrations that control many hallmarks of cancer. While some specific mutations in CRPC may be actionable, many others are not. We hypothesized that genomic aberrations in cancer may operate in concert to promote drug resistance and tumor progression, and that organization of these genomic aberrations into therapeutically targetable pathways may improve our ability to treat CRPC. To identify the molecular underpinnings of enzalutamide-resistant CRPC, we performed transcriptional and copy number profiling studies using paired enzalutamide-sensitive and resistant LNCaP prostate cancer cell lines. Gene networks associated with enzalutamide resistance were revealed by performing an integrative genomic analysis with the PAthway Representation and Analysis by Direct Reference on Graphical Models (PARADIGM) tool. Amongst the pathways enriched in the enzalutamide-resistant cells were those associated with MEK, EGFR, RAS, and NFKB. Functional validation studies of 64 genes identified 10 candidate genes whose suppression led to greater effects on cell viability in enzalutamide-resistant cells as compared to sensitive parental cells. Examination of a patient cohort demonstrated that several of our functionally-validated gene hits are deregulated in metastatic CRPC tumor samples, suggesting that they may be clinically relevant therapeutic targets for patients with enzalutamide-resistant CRPC. Altogether, our approach demonstrates the potential of integrative genomic analyses to clarify determinants of drug resistance and rational co-targeting strategies to overcome resistance. PMID:29340039

  10. Google Goes Cancer: Improving Outcome Prediction for Cancer Patients by Network-Based Ranking of Marker Genes

    PubMed Central

    Roy, Janine; Aust, Daniela; Knösel, Thomas; Rümmele, Petra; Jahnke, Beatrix; Hentrich, Vera; Rückert, Felix; Niedergethmann, Marco; Weichert, Wilko; Bahra, Marcus; Schlitt, Hans J.; Settmacher, Utz; Friess, Helmut; Büchler, Markus; Saeger, Hans-Detlev; Schroeder, Michael; Pilarsky, Christian; Grützmann, Robert

    2012-01-01

    Predicting the clinical outcome of cancer patients based on the expression of marker genes in their tumors has received increasing interest in the past decade. Accurate predictors of outcome and response to therapy could be used to personalize and thereby improve therapy. However, state of the art methods used so far often found marker genes with limited prediction accuracy, limited reproducibility, and unclear biological relevance. To address this problem, we developed a novel computational approach to identify genes prognostic for outcome that couples gene expression measurements from primary tumor samples with a network of known relationships between the genes. Our approach ranks genes according to their prognostic relevance using both expression and network information in a manner similar to Google's PageRank. We applied this method to gene expression profiles which we obtained from 30 patients with pancreatic cancer, and identified seven candidate marker genes prognostic for outcome. Compared to genes found with state of the art methods, such as Pearson correlation of gene expression with survival time, we improve the prediction accuracy by up to 7%. Accuracies were assessed using support vector machine classifiers and Monte Carlo cross-validation. We then validated the prognostic value of our seven candidate markers using immunohistochemistry on an independent set of 412 pancreatic cancer samples. Notably, signatures derived from our candidate markers were independently predictive of outcome and superior to established clinical prognostic factors such as grade, tumor size, and nodal status. As the amount of genomic data of individual tumors grows rapidly, our algorithm meets the need for powerful computational approaches that are key to exploit these data for personalized cancer therapies in clinical practice. PMID:22615549

  11. SBCDDB: Sleeping Beauty Cancer Driver Database for gene discovery in mouse models of human cancers

    PubMed Central

    Mann, Michael B

    2018-01-01

    Abstract Large-scale oncogenomic studies have identified few frequently mutated cancer drivers and hundreds of infrequently mutated drivers. Defining the biological context for rare driving events is fundamentally important to increasing our understanding of the druggable pathways in cancer. Sleeping Beauty (SB) insertional mutagenesis is a powerful gene discovery tool used to model human cancers in mice. Our lab and others have published a number of studies that identify cancer drivers from these models using various statistical and computational approaches. Here, we have integrated SB data from primary tumor models into an analysis and reporting framework, the Sleeping Beauty Cancer Driver DataBase (SBCDDB, http://sbcddb.moffitt.org), which identifies drivers in individual tumors or tumor populations. Unique to this effort, the SBCDDB utilizes a single, scalable, statistical analysis method that enables data to be grouped by different biological properties. This allows for SB drivers to be evaluated (and re-evaluated) under different contexts. The SBCDDB provides visual representations highlighting the spatial attributes of transposon mutagenesis and couples this functionality with analysis of gene sets, enabling users to interrogate relationships between drivers. The SBCDDB is a powerful resource for comparative oncogenomic analyses with human cancer genomics datasets for driver prioritization. PMID:29059366

  12. Candidate Luminal B Breast Cancer Genes Identified by Genome, Gene Expression and DNA Methylation Profiling

    PubMed Central

    Addou-Klouche, Lynda; Finetti, Pascal; Saade, Marie-Rose; Manai, Marwa; Carbuccia, Nadine; Bekhouche, Ismahane; Letessier, Anne; Charafe-Jauffret, Emmanuelle; Jacquemier, Jocelyne; Spicuglia, Salvatore; de The, Hugues; Viens, Patrice; Bertucci, François; Birnbaum, Daniel; Chaffanet, Max

    2014-01-01

    Breast cancers (BCs) of the luminal B subtype are estrogen receptor-positive (ER+), highly proliferative, resistant to standard therapies and have a poor prognosis. To better understand this subtype we compared DNA copy number aberrations (CNAs), DNA promoter methylation, gene expression profiles, and somatic mutations in nine selected genes, in 32 luminal B tumors with those observed in 156 BCs of the other molecular subtypes. Frequent CNAs included 8p11-p12 and 11q13.1-q13.2 amplifications, 7q11.22-q34, 8q21.12-q24.23, 12p12.3-p13.1, 12q13.11-q24.11, 14q21.1-q23.1, 17q11.1-q25.1, 20q11.23-q13.33 gains and 6q14.1-q24.2, 9p21.3-p24,3, 9q21.2, 18p11.31-p11.32 losses. A total of 237 and 101 luminal B-specific candidate oncogenes and tumor suppressor genes (TSGs) presented a deregulated expression in relation with their CNAs, including 11 genes previously reported associated with endocrine resistance. Interestingly, 88% of the potential TSGs are located within chromosome arm 6q, and seven candidate oncogenes are potential therapeutic targets. A total of 100 candidate oncogenes were validated in a public series of 5,765 BCs and the overexpression of 67 of these was associated with poor survival in luminal tumors. Twenty-four genes presented a deregulated expression in relation with a high DNA methylation level. FOXO3, PIK3CA and TP53 were the most frequent mutated genes among the nine tested. In a meta-analysis of next-generation sequencing data in 875 BCs, KCNB2 mutations were associated with luminal B cases while candidate TSGs MDN1 (6q15) and UTRN (6q24), were mutated in this subtype. In conclusion, we have reported luminal B candidate genes that may play a role in the development and/or hormone resistance of this aggressive subtype. PMID:24416132

  13. Evolutionary Origins of Cancer Driver Genes and Implications for Cancer Prognosis

    PubMed Central

    Chu, Xin-Yi; Zhou, Xiong-Hui; Cui, Ze-Jia; Zhang, Hong-Yu

    2017-01-01

    The cancer atavistic theory suggests that carcinogenesis is a reverse evolution process. It is thus of great interest to explore the evolutionary origins of cancer driver genes and the relevant mechanisms underlying the carcinogenesis. Moreover, the evolutionary features of cancer driver genes could be helpful in selecting cancer biomarkers from high-throughput data. In this study, through analyzing the cancer endogenous molecular networks, we revealed that the subnetwork originating from eukaryota could control the unlimited proliferation of cancer cells, and the subnetwork originating from eumetazoa could recapitulate the other hallmarks of cancer. In addition, investigations based on multiple datasets revealed that cancer driver genes were enriched in genes originating from eukaryota, opisthokonta, and eumetazoa. These results have important implications for enhancing the robustness of cancer prognosis models through selecting the gene signatures by the gene age information. PMID:28708071

  14. Evolutionary Origins of Cancer Driver Genes and Implications for Cancer Prognosis.

    PubMed

    Chu, Xin-Yi; Jiang, Ling-Han; Zhou, Xiong-Hui; Cui, Ze-Jia; Zhang, Hong-Yu

    2017-07-14

    The cancer atavistic theory suggests that carcinogenesis is a reverse evolution process. It is thus of great interest to explore the evolutionary origins of cancer driver genes and the relevant mechanisms underlying the carcinogenesis. Moreover, the evolutionary features of cancer driver genes could be helpful in selecting cancer biomarkers from high-throughput data. In this study, through analyzing the cancer endogenous molecular networks, we revealed that the subnetwork originating from eukaryota could control the unlimited proliferation of cancer cells, and the subnetwork originating from eumetazoa could recapitulate the other hallmarks of cancer. In addition, investigations based on multiple datasets revealed that cancer driver genes were enriched in genes originating from eukaryota, opisthokonta, and eumetazoa. These results have important implications for enhancing the robustness of cancer prognosis models through selecting the gene signatures by the gene age information.

  15. Screening for genes and subnetworks associated with pancreatic cancer based on the gene expression profile.

    PubMed

    Long, Jin; Liu, Zhe; Wu, Xingda; Xu, Yuanhong; Ge, Chunlin

    2016-05-01

    The present study aimed to screen for potential genes and subnetworks associated with pancreatic cancer (PC) using the gene expression profile. The expression profile GSE 16515 was downloaded from the Gene Expression Omnibus database, which included 36 PC tissue samples and 16 normal samples. Limma package in R language was used to screen differentially expressed genes (DEGs), which were grouped as up‑ and downregulated genes. Then, PFSNet was applied to perform subnetwork analysis for all the DEGs. Moreover, Gene Ontology (GO) and REACTOME pathway enrichment analysis of up‑ and downregulated genes was performed, followed by protein‑protein interaction (PPI) network construction using Search Tool for the Retrieval of Interacting Genes Search Tool for the Retrieval of Interacting Genes. In total, 1,989 DEGs including 1,461 up‑ and 528 downregulated genes were screened out. Subnetworks including pancreatic cancer in PC tissue samples and intercellular adhesion in normal samples were identified, respectively. A total of 8 significant REACTOME pathways for upregulated DEGs, such as hemostasis and cell cycle, mitotic were identified. Moreover, 4 significant REACTOME pathways for downregulated DEGs, including regulation of β‑cell development and transmembrane transport of small molecules were screened out. Additionally, DEGs with high connectivity degrees, such as CCNA2 (cyclin A2) and PBK (PDZ binding kinase), of the module in the protein‑protein interaction network were mainly enriched with cell‑division cycle. CCNA2 and PBK of the module and their relative pathway cell‑division cycle, and two subnetworks (pancreatic cancer and intercellular adhesion subnetworks) may be pivotal for further understanding of the molecular mechanism of PC.

  16. Tumor testing to identify lynch syndrome in two Australian colorectal cancer cohorts.

    PubMed

    Buchanan, Daniel D; Clendenning, Mark; Rosty, Christophe; Eriksen, Stine V; Walsh, Michael D; Walters, Rhiannon J; Thibodeau, Stephen N; Stewart, Jenna; Preston, Susan; Win, Aung Ko; Flander, Louisa; Ouakrim, Driss Ait; Macrae, Finlay A; Boussioutas, Alex; Winship, Ingrid M; Giles, Graham G; Hopper, John L; Southey, Melissa C; English, Dallas; Jenkins, Mark A

    2017-02-01

    Tumor testing of colorectal cancers (CRC) for mismatch repair (MMR) deficiency is an effective approach to identify carriers of germline MMR gene mutation (Lynch syndrome). The aim of this study was to identify MMR gene mutation carriers in two cohorts of population-based CRC utilizing a combination of tumor and germline testing approaches. Colorectal cancers from 813 patients diagnosed with CRC < 60 years of age from the Australasian Colorectal Cancer Family Registry (ACCFR) and from 826 patients from the Melbourne Collaborative Cohort Study (MCCS) were tested for MMR protein expression using immunohistochemistry, microsatellite instability (MSI), BRAF V600E somatic mutation, and for MLH1 methylation. MMR gene mutation testing (Sanger sequencing and Multiplex Ligation Dependent Probe Amplification) was performed on germline DNA of patients with MMR-deficient tumors and a subset of MMR-proficient CRCs. Of the 813 ACCFR probands, 90 probands demonstrated tumor MMR deficiency (11.1%), and 42 had a MMR gene germline mutation (5.2%). For the MCCS, MMR deficiency was identified in the tumors of 103 probands (12.5%) and seven had a germline mutation (0.8%). All the mutation carriers were diagnosed prior to 70 years of age. Probands with a MMR-deficient CRC without MLH1 methylation and a gene mutation were considered Lynch-like and comprised 41.1% and 25.2% of the MMR-deficient CRCs for the ACCFR and MCCS, respectively. Identification of MMR gene mutation carriers in Australian CRC-affected patients is optimized by immunohistochemistry screening of CRC diagnosed before 70 years of age. A significant proportion of MMR-deficient CRCs will have unknown etiology (Lynch-like) proving problematic for clinical management. © 2016 Journal of Gastroenterology and Hepatology Foundation and John Wiley & Sons Australia, Ltd.

  17. Network-based approach to identify prognostic biomarkers for estrogen receptor-positive breast cancer treatment with tamoxifen.

    PubMed

    Liu, Rong; Guo, Cheng-Xian; Zhou, Hong-Hao

    2015-01-01

    This study aims to identify effective gene networks and prognostic biomarkers associated with estrogen receptor positive (ER+) breast cancer using human mRNA studies. Weighted gene coexpression network analysis was performed with a complex ER+ breast cancer transcriptome to investigate the function of networks and key genes in the prognosis of breast cancer. We found a significant correlation of an expression module with distant metastasis-free survival (HR = 2.25; 95% CI .21.03-4.88 in discovery set; HR = 1.78; 95% CI = 1.07-2.93 in validation set). This module contained genes enriched in the biological process of the M phase. From this module, we further identified and validated 5 hub genes (CDK1, DLGAP5, MELK, NUSAP1, and RRM2), the expression levels of which were strongly associated with poor survival. Highly expressed MELK indicated poor survival in luminal A and luminal B breast cancer molecular subtypes. This gene was also found to be associated with tamoxifen resistance. Results indicated that a network-based approach may facilitate the discovery of biomarkers for the prognosis of ER+ breast cancer and may also be used as a basis for establishing personalized therapies. Nevertheless, before the application of this approach in clinical settings, in vivo and in vitro experiments and multi-center randomized controlled clinical trials are still needed.

  18. A functional cancer genomics screen identifies a druggable synthetic lethal interaction between MSH3 and PRKDC.

    PubMed

    Dietlein, Felix; Thelen, Lisa; Jokic, Mladen; Jachimowicz, Ron D; Ivan, Laura; Knittel, Gero; Leeser, Uschi; van Oers, Johanna; Edelmann, Winfried; Heukamp, Lukas C; Reinhardt, H Christian

    2014-05-01

    Here, we use a large-scale cell line-based approach to identify cancer cell-specific mutations that are associated with DNA-dependent protein kinase catalytic subunit (DNA-PKcs) dependence. For this purpose, we profiled the mutational landscape across 1,319 cancer-associated genes of 67 distinct cell lines and identified numerous genes involved in homologous recombination-mediated DNA repair, including BRCA1, BRCA2, ATM, PAXIP, and RAD50, as being associated with non-oncogene addiction to DNA-PKcs. Mutations in the mismatch repair gene MSH3, which have been reported to occur recurrently in numerous human cancer entities, emerged as the most significant predictors of DNA-PKcs addiction. Concordantly, DNA-PKcs inhibition robustly induced apoptosis in MSH3-mutant cell lines in vitro and displayed remarkable single-agent efficacy against MSH3-mutant tumors in vivo. Thus, we here identify a therapeutically actionable synthetic lethal interaction between MSH3 and the non-homologous end joining kinase DNA-PKcs. Our observations recommend DNA-PKcs inhibition as a therapeutic concept for the treatment of human cancers displaying homologous recombination defects.

  19. Harnessing the complexity of gene expression data from cancer: from single gene to structural pathway methods

    PubMed Central

    2012-01-01

    High-dimensional gene expression data provide a rich source of information because they capture the expression level of genes in dynamic states that reflect the biological functioning of a cell. For this reason, such data are suitable to reveal systems related properties inside a cell, e.g., in order to elucidate molecular mechanisms of complex diseases like breast or prostate cancer. However, this is not only strongly dependent on the sample size and the correlation structure of a data set, but also on the statistical hypotheses tested. Many different approaches have been developed over the years to analyze gene expression data to (I) identify changes in single genes, (II) identify changes in gene sets or pathways, and (III) identify changes in the correlation structure in pathways. In this paper, we review statistical methods for all three types of approaches, including subtypes, in the context of cancer data and provide links to software implementations and tools and address also the general problem of multiple hypotheses testing. Further, we provide recommendations for the selection of such analysis methods. Reviewers This article was reviewed by Arcady Mushegian, Byung-Soo Kim and Joel Bader. PMID:23227854

  20. Characterization of transformation related genes in oral cancer cells.

    PubMed

    Chang, D D; Park, N H; Denny, C T; Nelson, S F; Pe, M

    1998-04-16

    A cDNA representational difference analysis (cDNA-RDA) and an arrayed filter technique were used to characterize transformation-related genes in oral cancer. From an initial comparison of normal oral epithelial cells and a human papilloma virus (HPV)-immortalized oral epithelial cell line, we obtained 384 differentially expressed gene fragments and arrayed them on a filter. Two hundred and twelve redundant clones were identified by three rounds of back hybridization. Sequence analysis of the remaining clones revealed 99 unique clones corresponding to 69 genes. The expression of these transformation related gene fragments in three nontumorigenic HPV-immortalized oral epithelial cell lines and three oral cancer cell lines were simultaneously monitored using a cDNA array hybridization. Although there was a considerable cell line-to-cell line variability in the expression of these clones, a reliable prediction of their expression could be made from the cDNA array hybridization. Our study demonstrates the utility of combining cDNA-RDA and arrayed filters in high-throughput gene expression difference analysis. The differentially expressed genes identified in this study should be informative in studying oral epithelial cell carcinogenesis.

  1. Gene therapy in pancreatic cancer

    PubMed Central

    Liu, Si-Xue; Xia, Zhong-Sheng; Zhong, Ying-Qiang

    2014-01-01

    Pancreatic cancer (PC) is a highly lethal disease and notoriously difficult to treat. Only a small proportion of PC patients are eligible for surgical resection, whilst conventional chemoradiotherapy only has a modest effect with substantial toxicity. Gene therapy has become a new widely investigated therapeutic approach for PC. This article reviews the basic rationale, gene delivery methods, therapeutic targets and developments of laboratory research and clinical trials in gene therapy of PC by searching the literature published in English using the PubMed database and analyzing clinical trials registered on the Gene Therapy Clinical Trials Worldwide website (http://www. wiley.co.uk/genmed/ clinical). Viral vectors are main gene delivery tools in gene therapy of cancer, and especially, oncolytic virus shows brighter prospect due to its tumor-targeting property. Efficient therapeutic targets for gene therapy include tumor suppressor gene p53, mutant oncogene K-ras, anti-angiogenesis gene VEGFR, suicide gene HSK-TK, cytosine deaminase and cytochrome p450, multiple cytokine genes and so on. Combining different targets or combination strategies with traditional chemoradiotherapy may be a more effective approach to improve the efficacy of cancer gene therapy. Cancer gene therapy is not yet applied in clinical practice, but basic and clinical studies have demonstrated its safety and clinical benefits. Gene therapy will be a new and promising field for the treatment of PC. PMID:25309069

  2. Gene sensitizes cancer cells to chemotherapy drugs

    Cancer.gov

    NCI scientists have found that a gene, Schlafen-11 (SLFN11), sensitizes cells to substances known to cause irreparable damage to DNA.  As part of their study, the researchers used a repository of 60 cell types to identify predictors of cancer cell respons

  3. Expression profiling identifies novel Hh/Gli regulated genes in developing zebrafish embryos.

    PubMed Central

    Bergeron, Sadie A.; Milla, Luis A.; Villegas, Rosario; Shen, Meng-Chieh; Burgess, Shawn M.; Allende, Miguel L.; Karlstrom, Rolf O.; Palma, Verónica

    2008-01-01

    The Hedgehog (Hh) signaling pathway plays critical instructional roles during embryonic development. Mis-regulation of Hh/Gli signaling is a major causative factor in human congenital disorders and in a variety of cancers. The zebrafish is a powerful genetic model for the study of Hh signaling during embryogenesis, as a large number of mutants have been identified affecting different components of the Hh/Gli signaling system. By performing global profiling of gene expression in different Hh/Gli gain- and loss-of-function scenarios we identified several known (e.g. ptc1 and nkx2.2a) as well as a large number of novel Hh regulated genes that are differentially expressed in embryos with altered Hh/Gli signaling function. By uncovering changes in tissue specific gene expression, we revealed new embryological processes that are influenced by Hh signaling. We thus provide a comprehensive survey of Hh/Gli regulated genes during embryogenesis and we identify new Hh-regulated genes that may be targets of mis-regulation during tumorogenesis. PMID:18055165

  4. Bone Metastasis in Advanced Breast Cancer: Analysis of Gene Expression Microarray.

    PubMed

    Cosphiadi, Irawan; Atmakusumah, Tubagus D; Siregar, Nurjati C; Muthalib, Abdul; Harahap, Alida; Mansyur, Muchtarruddin

    2018-03-08

    Approximately 30% to 40% of breast cancer recurrences involve bone metastasis (BM). Certain genes have been linked to BM; however, none have been able to predict bone involvement. In this study, we analyzed gene expression profiles in advanced breast cancer patients to elucidate genes that can be used to predict BM. A total of 92 advanced breast cancer patients, including 46 patients with BM and 46 patients without BM, were identified for this study. Immunohistochemistry and gene expression analysis was performed on 81 formalin-fixed paraffin-embedded samples. Data were collected through medical records, and gene expression of 200 selected genes compiled from 6 previous studies was performed using NanoString nCounter. Genetic expression profiles showed that 22 genes were significantly differentially expressed between breast cancer patients with metastasis in bone and other organs (BM+) and non-BM, whereas subjects with only BM showed 17 significantly differentially expressed genes. The following genes were associated with an increasing incidence of BM in the BM+ group: estrogen receptor 1 (ESR1), GATA binding protein 3 (GATA3), and melanophilin with an area under the curve (AUC) of 0.804. In the BM group, the following genes were associated with an increasing incidence of BM: ESR1, progesterone receptor, B-cell lymphoma 2, Rab escort protein, N-acetyltransferase 1, GATA3, annexin A9, and chromosome 9 open reading frame 116. ESR1 and GATA3 showed an increased strength of association with an AUC of 0.928. A combination of the identified 3 genes in BM+ and 8 genes in BM showed better prediction than did each individual gene, and this combination can be used as a training set. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

  5. Identification of upstream transcription factors (TFs) for expression signature genes in breast cancer.

    PubMed

    Zang, Hongyan; Li, Ning; Pan, Yuling; Hao, Jingguang

    2017-03-01

    Breast cancer is a common malignancy among women with a rising incidence. Our intention was to detect transcription factors (TFs) for deeper understanding of the underlying mechanisms of breast cancer. Integrated analysis of gene expression datasets of breast cancer was performed. Then, functional annotation of differentially expressed genes (DEGs) was conducted, including Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment. Furthermore, TFs were identified and a global transcriptional regulatory network was constructed. Seven publically available GEO datasets were obtained, and a set of 1196 DEGs were identified (460 up-regulated and 736 down-regulated). Functional annotation results showed that cell cycle was the most significantly enriched pathway, which was consistent with the fact that cell cycle is closely related to various tumors. Fifty-three differentially expressed TFs were identified, and the regulatory networks consisted of 817 TF-target interactions between 46 TFs and 602 DEGs in the context of breast cancer. Top 10 TFs covering the most downstream DEGs were SOX10, NFATC2, ZNF354C, ARID3A, BRCA1, FOXO3, GATA3, ZEB1, HOXA5 and EGR1. The transcriptional regulatory networks could enable a better understanding of regulatory mechanisms of breast cancer pathology and provide an opportunity for the development of potential therapy.

  6. Inherited mutations in 17 breast cancer susceptibility genes among a large triple-negative breast cancer cohort unselected for family history of breast cancer.

    PubMed

    Couch, Fergus J; Hart, Steven N; Sharma, Priyanka; Toland, Amanda Ewart; Wang, Xianshu; Miron, Penelope; Olson, Janet E; Godwin, Andrew K; Pankratz, V Shane; Olswold, Curtis; Slettedahl, Seth; Hallberg, Emily; Guidugli, Lucia; Davila, Jaime I; Beckmann, Matthias W; Janni, Wolfgang; Rack, Brigitte; Ekici, Arif B; Slamon, Dennis J; Konstantopoulou, Irene; Fostira, Florentia; Vratimos, Athanassios; Fountzilas, George; Pelttari, Liisa M; Tapper, William J; Durcan, Lorraine; Cross, Simon S; Pilarski, Robert; Shapiro, Charles L; Klemp, Jennifer; Yao, Song; Garber, Judy; Cox, Angela; Brauch, Hiltrud; Ambrosone, Christine; Nevanlinna, Heli; Yannoukakos, Drakoulis; Slager, Susan L; Vachon, Celine M; Eccles, Diana M; Fasching, Peter A

    2015-02-01

    Recent advances in DNA sequencing have led to the development of breast cancer susceptibility gene panels for germline genetic testing of patients. We assessed the frequency of mutations in 17 predisposition genes, including BRCA1 and BRCA2, in a large cohort of patients with triple-negative breast cancer (TNBC) unselected for family history of breast or ovarian cancer to determine the utility of germline genetic testing for those with TNBC. Patients with TNBC (N = 1,824) unselected for family history of breast or ovarian cancer were recruited through 12 studies, and germline DNA was sequenced to identify mutations. Deleterious mutations were identified in 14.6% of all patients. Of these, 11.2% had mutations in the BRCA1 (8.5%) and BRCA2 (2.7%) genes. Deleterious mutations in 15 other predisposition genes were detected in 3.7% of patients, with the majority observed in genes involved in homologous recombination, including PALB2 (1.2%) and BARD1, RAD51D, RAD51C, and BRIP1 (0.3% to 0.5%). Patients with TNBC with mutations were diagnosed at an earlier age (P < .001) and had higher-grade tumors (P = .01) than those without mutations. Deleterious mutations in predisposition genes are present at high frequency in patients with TNBC unselected for family history of cancer. Mutation prevalence estimates suggest that patients with TNBC, regardless of age at diagnosis or family history of cancer, should be considered for germline genetic testing of BRCA1 and BRCA2. Although mutations in other predisposition genes are observed among patients with TNBC, better cancer risk estimates are needed before these mutations are used for clinical risk assessment in relatives. © 2014 by American Society of Clinical Oncology.

  7. Inherited Mutations in 17 Breast Cancer Susceptibility Genes Among a Large Triple-Negative Breast Cancer Cohort Unselected for Family History of Breast Cancer

    PubMed Central

    Couch, Fergus J.; Hart, Steven N.; Sharma, Priyanka; Toland, Amanda Ewart; Wang, Xianshu; Miron, Penelope; Olson, Janet E.; Godwin, Andrew K.; Pankratz, V. Shane; Olswold, Curtis; Slettedahl, Seth; Hallberg, Emily; Guidugli, Lucia; Davila, Jaime I.; Beckmann, Matthias W.; Janni, Wolfgang; Rack, Brigitte; Ekici, Arif B.; Slamon, Dennis J.; Konstantopoulou, Irene; Fostira, Florentia; Vratimos, Athanassios; Fountzilas, George; Pelttari, Liisa M.; Tapper, William J.; Durcan, Lorraine; Cross, Simon S.; Pilarski, Robert; Shapiro, Charles L.; Klemp, Jennifer; Yao, Song; Garber, Judy; Cox, Angela; Brauch, Hiltrud; Ambrosone, Christine; Nevanlinna, Heli; Yannoukakos, Drakoulis; Slager, Susan L.; Vachon, Celine M.; Eccles, Diana M.; Fasching, Peter A.

    2015-01-01

    Purpose Recent advances in DNA sequencing have led to the development of breast cancer susceptibility gene panels for germline genetic testing of patients. We assessed the frequency of mutations in 17 predisposition genes, including BRCA1 and BRCA2, in a large cohort of patients with triple-negative breast cancer (TNBC) unselected for family history of breast or ovarian cancer to determine the utility of germline genetic testing for those with TNBC. Patients and Methods Patients with TNBC (N = 1,824) unselected for family history of breast or ovarian cancer were recruited through 12 studies, and germline DNA was sequenced to identify mutations. Results Deleterious mutations were identified in 14.6% of all patients. Of these, 11.2% had mutations in the BRCA1 (8.5%) and BRCA2 (2.7%) genes. Deleterious mutations in 15 other predisposition genes were detected in 3.7% of patients, with the majority observed in genes involved in homologous recombination, including PALB2 (1.2%) and BARD1, RAD51D, RAD51C, and BRIP1 (0.3% to 0.5%). Patients with TNBC with mutations were diagnosed at an earlier age (P < .001) and had higher-grade tumors (P = .01) than those without mutations. Conclusion Deleterious mutations in predisposition genes are present at high frequency in patients with TNBC unselected for family history of cancer. Mutation prevalence estimates suggest that patients with TNBC, regardless of age at diagnosis or family history of cancer, should be considered for germline genetic testing of BRCA1 and BRCA2. Although mutations in other predisposition genes are observed among patients with TNBC, better cancer risk estimates are needed before these mutations are used for clinical risk assessment in relatives. PMID:25452441

  8. DNA methylome profiling identifies novel methylated genes in African American patients with colorectal neoplasia.

    PubMed

    Ashktorab, Hassan; Daremipouran, M; Goel, Ajay; Varma, Sudhir; Leavitt, R; Sun, Xueguang; Brim, Hassan

    2014-04-01

    The identification of genes that are differentially methylated in colorectal cancer (CRC) has potential value for both diagnostic and therapeutic interventions specifically in high-risk populations such as African Americans (AAs). However, DNA methylation patterns in CRC, especially in AAs, have not been systematically explored and remain poorly understood. Here, we performed DNA methylome profiling to identify the methylation status of CpG islands within candidate genes involved in critical pathways important in the initiation and development of CRC. We used reduced representation bisulfite sequencing (RRBS) in colorectal cancer and adenoma tissues that were compared with DNA methylome from a healthy AA subject's colon tissue and peripheral blood DNA. The identified methylation markers were validated in fresh frozen CRC tissues and corresponding normal tissues from AA patients diagnosed with CRC at Howard University Hospital. We identified and validated the methylation status of 355 CpG sites located within 16 gene promoter regions associated with CpG islands. Fifty CpG sites located within CpG islands-in genes ATXN7L1 (2), BMP3 (7), EID3 (15), GAS7 (1), GPR75 (24), and TNFAIP2 (1)-were significantly hypermethylated in tumor vs. normal tissues (P<0.05). The methylation status of BMP3, EID3, GAS7, and GPR75 was confirmed in an independent, validation cohort. Ingenuity pathway analysis mapped three of these markers (GAS7, BMP3 and GPR) in the insulin and TGF-β1 network-the two key pathways in CRC. In addition to hypermethylated genes, our analysis also revealed that LINE-1 repeat elements were progressively hypomethylated in the normal-adenoma-cancer sequence. We conclude that DNA methylome profiling based on RRBS is an effective method for screening aberrantly methylated genes in CRC. While previous studies focused on the limited identification of hypermethylated genes, ours is the first study to systematically and comprehensively identify novel hypermethylated

  9. Expression profiles of loneliness-associated genes for survival prediction in cancer patients.

    PubMed

    You, Liang-Fu; Yeh, Jia-Rong; Su, Mu-Chun

    2014-01-01

    Influence of loneliness on human survival has been established epidemiologically, but genomic research remains undeveloped. We identified 34 loneliness-associated genes which were statistically significant for high- lonely and low-lonely individuals. With the univariate Cox proportional hazards regression model, we obtained corresponding regression coefficients for loneliness-associated genes fo individual cancer patients. Furthermore, risk scores could be generated with the combination of gene expression level multiplied by corresponding regression coefficients of loneliness-associated genes. We verified that high-risk score cancer patients had shorter mean survival time than their low-risk score counterparts. Then we validated the loneliness-associated gene signature in three independent brain cancer cohorts with Kaplan-Meier survival curves (n=77, 85 and 191), significantly separable by log-rank test with hazard ratios (HR) >1 and p-values <0.0001 (HR=2.94, 3.82, and 1.78). Moreover, we validated the loneliness-associated gene signature in bone cancer (HR=5.10, p-value=4.69e-3), lung cancer (HR=2.86, p-value=4.71e-5), ovarian cancer (HR=1.97, p-value=3.11e-5), and leukemia (HR=2.06, p-value=1.79e-4) cohorts. The last lymphoma cohort proved to have an HR=3.50, p-value=1.15e-7. Loneliness- associated genes had good survival prediction for cancer patients, especially bone cancer patients. Our study provided the first indication that expression of loneliness-associated genes are related to survival time of cancer patients.

  10. COMPLEXO: identifying the missing heritability of breast cancer via next generation collaboration.

    PubMed

    Southey, Melissa C; Park, Daniel J; Nguyen-Dumont, Tu; Campbell, Ian; Thompson, Ella; Trainer, Alison H; Chenevix-Trench, Georgia; Simard, Jacques; Dumont, Martine; Soucy, Penny; Thomassen, Mads; Jønson, Lars; Pedersen, Inge S; Hansen, Thomas Vo; Nevanlinna, Heli; Khan, Sofia; Sinilnikova, Olga; Mazoyer, Sylvie; Lesueur, Fabienne; Damiola, Francesca; Schmutzler, Rita; Meindl, Alfons; Hahnen, Eric; Dufault, Michael R; Chris Chan, Tl; Kwong, Ava; Barkardóttir, Rosa; Radice, Paolo; Peterlongo, Paolo; Devilee, Peter; Hilbers, Florentine; Benitez, Javier; Kvist, Anders; Törngren, Therese; Easton, Douglas; Hunter, David; Lindstrom, Sara; Kraft, Peter; Zheng, Wei; Gao, Yu-Tang; Long, Jirong; Ramus, Susan; Feng, Bing-Jian; Weitzel, Jeffrey N; Nathanson, Katherine; Offit, Kenneth; Joseph, Vijai; Robson, Mark; Schrader, Kasmintan; Wang, San; Kim, Yeong C; Lynch, Henry; Snyder, Carrie; Tavtigian, Sean; Neuhausen, Susan; Couch, Fergus J; Goldgar, David E

    2013-06-21

    Linkage analysis, positional cloning, candidate gene mutation scanning and genome-wide association study approaches have all contributed significantly to our understanding of the underlying genetic architecture of breast cancer. Taken together, these approaches have identified genetic variation that explains approximately 30% of the overall familial risk of breast cancer, implying that more, and likely rarer, genetic susceptibility alleles remain to be discovered.

  11. Detection of gene communities in multi-networks reveals cancer drivers

    NASA Astrophysics Data System (ADS)

    Cantini, Laura; Medico, Enzo; Fortunato, Santo; Caselle, Michele

    2015-12-01

    We propose a new multi-network-based strategy to integrate different layers of genomic information and use them in a coordinate way to identify driving cancer genes. The multi-networks that we consider combine transcription factor co-targeting, microRNA co-targeting, protein-protein interaction and gene co-expression networks. The rationale behind this choice is that gene co-expression and protein-protein interactions require a tight coregulation of the partners and that such a fine tuned regulation can be obtained only combining both the transcriptional and post-transcriptional layers of regulation. To extract the relevant biological information from the multi-network we studied its partition into communities. To this end we applied a consensus clustering algorithm based on state of art community detection methods. Even if our procedure is valid in principle for any pathology in this work we concentrate on gastric, lung, pancreas and colorectal cancer and identified from the enrichment analysis of the multi-network communities a set of candidate driver cancer genes. Some of them were already known oncogenes while a few are new. The combination of the different layers of information allowed us to extract from the multi-network indications on the regulatory pattern and functional role of both the already known and the new candidate driver genes.

  12. RNA-seq reveals more consistent reference genes for gene expression studies in human non-melanoma skin cancers

    PubMed Central

    Tan, Jean-Marie; Payne, Elizabeth J.; Lin, Lynlee L.; Sinnya, Sudipta; Raphael, Anthony P.; Lambie, Duncan; Frazer, Ian H.; Dinger, Marcel E.; Soyer, H. Peter

    2017-01-01

    Identification of appropriate reference genes (RGs) is critical to accurate data interpretation in quantitative real-time PCR (qPCR) experiments. In this study, we have utilised next generation RNA sequencing (RNA-seq) to analyse the transcriptome of a panel of non-melanoma skin cancer lesions, identifying genes that are consistently expressed across all samples. Genes encoding ribosomal proteins were amongst the most stable in this dataset. Validation of this RNA-seq data was examined using qPCR to confirm the suitability of a set of highly stable genes for use as qPCR RGs. These genes will provide a valuable resource for the normalisation of qPCR data for the analysis of non-melanoma skin cancer. PMID:28852586

  13. Genetic variation of clock genes and cancer risk: a field synopsis and meta-analysis.

    PubMed

    Benna, Clara; Helfrich-Förster, Charlotte; Rajendran, Senthilkumar; Monticelli, Halenya; Pilati, Pierluigi; Nitti, Donato; Mocellin, Simone

    2017-04-04

    The number of studies on the association between clock genes' polymorphisms and cancer susceptibility has increased over the last years but the results are often conflicting and no comprehensive overview and quantitative summary of the evidence in this field is available. Literature search identified 27 eligible studies comprising 96756 subjects (cases: 38231) and investigating 687 polymorphisms involving 14 clock genes. Overall, 1025 primary and subgroup meta-analyses on 366 gene variants were performed. Study distribution by tumor was as follows: breast cancer (n=15), prostate cancer (n=3), pancreatic cancer (n=2), non-Hodgkin's lymphoma (n=2), glioma (n=1), chronic lymphocytic leukemia (n=1), colorectal cancer (n=1), non-small cell lung cancer (n=1) and ovarian cancer (n=1).We identified 10 single nucleotide polymorphisms (SNPs) significantly associated with cancer risk: NPAS2 rs10165970 (mixed and breast cancer shiftworkers), rs895520 (mixed), rs17024869 (breast) and rs7581886 (breast); CLOCK rs3749474 (breast) and rs11943456 (breast); RORA rs7164773 (breast and breast cancer postmenopausal), rs10519097 (breast); RORB rs7867494 (breast cancer postmenopausal), PER3 rs1012477 (breast cancer subgroups) and assessed the level of quality evidence to be intermediate. We also identified polymorphisms with lower quality statistically significant associations (n=30). Our work supports the hypothesis that genetic variation of clock genes might affect cancer risk. These findings also highlight the need for more efforts in this research field in order to fully establish the contribution of clock gene variants to the risk of developing cancer. We conducted a systematic review and meta-analysis of the evidence on the association between clock genes' germline variants and the risk of developing cancer. To assess result credibility, summary evidence was graded according to the Venice criteria and false positive report probability (FPRP) was calculated to further validate

  14. Increased gene expression noise in human cancers is correlated with low p53 and immune activities as well as late stage cancer.

    PubMed

    Han, Rongfei; Huang, Guanqun; Wang, Yejun; Xu, Yafei; Hu, Yueming; Jiang, Wenqi; Wang, Tianfu; Xiao, Tian; Zheng, Duo

    2016-11-01

    Gene expression in metazoans is delicately organized. As genetic information transmits from DNA to RNA and protein, expression noise is inevitably generated. Recent studies begin to unveil the mechanisms of gene expression noise control, but the changes of gene expression precision in pathologic conditions like cancers are unknown. Here we analyzed the transcriptomic data of human breast, liver, lung and colon cancers, and found that the expression noise of more than 74.9% genes was increased in cancer tissues as compared to adjacent normal tissues. This suggested that gene expression precision controlling collapsed during cancer development. A set of 269 genes with noise increased more than 2-fold were identified across different cancer types. These genes were involved in cell adhesion, catalytic and metabolic functions, implying the vulnerability of deregulation of these processes in cancers. We also observed a tendency of increased expression noise in patients with low p53 and immune activity in breast, liver and lung caners but not in colon cancers, which indicated the contributions of p53 signaling and host immune surveillance to gene expression noise in cancers. Moreover, more than 53.7% genes had increased noise in patients with late stage than early stage cancers, suggesting that gene expression precision was associated with cancer outcome. Together, these results provided genomic scale explorations of gene expression noise control in human cancers.

  15. Identifying candidate drivers of drug response in heterogeneous cancer by mining high throughput genomics data.

    PubMed

    Nabavi, Sheida

    2016-08-15

    With advances in technologies, huge amounts of multiple types of high-throughput genomics data are available. These data have tremendous potential to identify new and clinically valuable biomarkers to guide the diagnosis, assessment of prognosis, and treatment of complex diseases, such as cancer. Integrating, analyzing, and interpreting big and noisy genomics data to obtain biologically meaningful results, however, remains highly challenging. Mining genomics datasets by utilizing advanced computational methods can help to address these issues. To facilitate the identification of a short list of biologically meaningful genes as candidate drivers of anti-cancer drug resistance from an enormous amount of heterogeneous data, we employed statistical machine-learning techniques and integrated genomics datasets. We developed a computational method that integrates gene expression, somatic mutation, and copy number aberration data of sensitive and resistant tumors. In this method, an integrative method based on module network analysis is applied to identify potential driver genes. This is followed by cross-validation and a comparison of the results of sensitive and resistance groups to obtain the final list of candidate biomarkers. We applied this method to the ovarian cancer data from the cancer genome atlas. The final result contains biologically relevant genes, such as COL11A1, which has been reported as a cis-platinum resistant biomarker for epithelial ovarian carcinoma in several recent studies. The described method yields a short list of aberrant genes that also control the expression of their co-regulated genes. The results suggest that the unbiased data driven computational method can identify biologically relevant candidate biomarkers. It can be utilized in a wide range of applications that compare two conditions with highly heterogeneous datasets.

  16. Blood Gene Expression Profiling of Breast Cancer Survivors Experiencing Fibrosis

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Landmark-Hoyvik, Hege, E-mail: hblandma@rr-research.n; Institute for Clinical Medicine, University of Oslo, Oslo; Dumeaux, Vanessa

    2011-03-01

    Purpose: To extend knowledge on the mechanisms and pathways involved in maintenance of radiation-induced fibrosis (RIF) by performing gene expression profiling of whole blood from breast cancer (BC) survivors with and without fibrosis 3-7 years after end of radiotherapy treatment. Methods and Materials: Gene expression profiles from blood were obtained for 254 BC survivors derived from a cohort of survivors, treated with adjuvant radiotherapy for breast cancer 3-7 years earlier. Analyses of transcriptional differences in blood gene expression between BC survivors with fibrosis (n = 31) and BC survivors without fibrosis (n = 223) were performed using R version 2.8.0more » and tools from the Bioconductor project. Gene sets extracted through a literature search on fibrosis and breast cancer were subsequently used in gene set enrichment analysis. Results: Substantial differences in blood gene expression between BC survivors with and without fibrosis were observed, and 87 differentially expressed genes were identified through linear analysis. Transforming growth factor-{beta}1 signaling was identified as the most significant gene set, showing a down-regulation of most of the core genes, together with up-regulation of a transcriptional activator of the inhibitor of fibrinolysis, Plasminogen activator inhibitor 1 in the BC survivors with fibrosis. Conclusion: Transforming growth factor-{beta}1 signaling was found down-regulated during the maintenance phase of fibrosis as opposed to the up-regulation reported during the early, initiating phase of fibrosis. Hence, once the fibrotic tissue has developed, the maintenance phase might rather involve a deregulation of fibrinolysis and altered degradation of extracellular matrix components.« less

  17. Inherited DNA-Repair Gene Mutations in Men with Metastatic Prostate Cancer.

    PubMed

    Pritchard, Colin C; Mateo, Joaquin; Walsh, Michael F; De Sarkar, Navonil; Abida, Wassim; Beltran, Himisha; Garofalo, Andrea; Gulati, Roman; Carreira, Suzanne; Eeles, Rosalind; Elemento, Olivier; Rubin, Mark A; Robinson, Dan; Lonigro, Robert; Hussain, Maha; Chinnaiyan, Arul; Vinson, Jake; Filipenko, Julie; Garraway, Levi; Taplin, Mary-Ellen; AlDubayan, Saud; Han, G Celine; Beightol, Mallory; Morrissey, Colm; Nghiem, Belinda; Cheng, Heather H; Montgomery, Bruce; Walsh, Tom; Casadei, Silvia; Berger, Michael; Zhang, Liying; Zehir, Ahmet; Vijai, Joseph; Scher, Howard I; Sawyers, Charles; Schultz, Nikolaus; Kantoff, Philip W; Solit, David; Robson, Mark; Van Allen, Eliezer M; Offit, Kenneth; de Bono, Johann; Nelson, Peter S

    2016-08-04

    Inherited mutations in DNA-repair genes such as BRCA2 are associated with increased risks of lethal prostate cancer. Although the prevalence of germline mutations in DNA-repair genes among men with localized prostate cancer who are unselected for family predisposition is insufficient to warrant routine testing, the frequency of such mutations in patients with metastatic prostate cancer has not been established. We recruited 692 men with documented metastatic prostate cancer who were unselected for family history of cancer or age at diagnosis. We isolated germline DNA and used multiplex sequencing assays to assess mutations in 20 DNA-repair genes associated with autosomal dominant cancer-predisposition syndromes. A total of 84 germline DNA-repair gene mutations that were presumed to be deleterious were identified in 82 men (11.8%); mutations were found in 16 genes, including BRCA2 (37 men [5.3%]), ATM (11 [1.6%]), CHEK2 (10 [1.9% of 534 men with data]), BRCA1 (6 [0.9%]), RAD51D (3 [0.4%]), and PALB2 (3 [0.4%]). Mutation frequencies did not differ according to whether a family history of prostate cancer was present or according to age at diagnosis. Overall, the frequency of germline mutations in DNA-repair genes among men with metastatic prostate cancer significantly exceeded the prevalence of 4.6% among 499 men with localized prostate cancer (P<0.001), including men with high-risk disease, and the prevalence of 2.7% in the Exome Aggregation Consortium, which includes 53,105 persons without a known cancer diagnosis (P<0.001). In our multicenter study, the incidence of germline mutations in genes mediating DNA-repair processes among men with metastatic prostate cancer was 11.8%, which was significantly higher than the incidence among men with localized prostate cancer. The frequencies of germline mutations in DNA-repair genes among men with metastatic disease did not differ significantly according to age at diagnosis or family history of prostate cancer. (Funded by

  18. Screening for ATM Mutations in an African-American Population to Identify a Predictor of Breast Cancer Susceptibility

    DTIC Science & Technology

    2006-07-01

    ATM genetic variant identified affects radiosensitivity and levels of the protein encoded by the ATM gene for each mutation examined. 15. SUBJECT...women without breast cancer. An additional objective is to determine the functional impact upon the protein encoded by the ATM gene for each mutation ...each ATM variant identified affects radiosensitivity and levels of the protein encoded by the ATM gene for mutations identified. Body STATEMENT

  19. Tumor cell migration screen identifies SRPK1 as breast cancer metastasis determinant

    PubMed Central

    van Roosmalen, Wies; Le Dévédec, Sylvia E.; Golani, Ofra; Smid, Marcel; Pulyakhina, Irina; Timmermans, Annemieke M.; Look, Maxime P.; Zi, Di; Pont, Chantal; de Graauw, Marjo; Naffar-Abu-Amara, Suha; Kirsanova, Catherine; Rustici, Gabriella; Hoen, Peter A.C. ‘t; Martens, John W.M.; Foekens, John A.; Geiger, Benjamin; van de Water, Bob

    2015-01-01

    Tumor cell migration is a key process for cancer cell dissemination and metastasis that is controlled by signal-mediated cytoskeletal and cell matrix adhesion remodeling. Using a phagokinetic track assay with migratory H1299 cells, we performed an siRNA screen of almost 1,500 genes encoding kinases/phosphatases and adhesome- and migration-related proteins to identify genes that affect tumor cell migration speed and persistence. Thirty candidate genes that altered cell migration were validated in live tumor cell migration assays. Eight were associated with metastasis-free survival in breast cancer patients, with integrin β3–binding protein (ITGB3BP), MAP3K8, NIMA-related kinase (NEK2), and SHC-transforming protein 1 (SHC1) being the most predictive. Examination of genes that modulate migration indicated that SRPK1, encoding the splicing factor kinase SRSF protein kinase 1, is relevant to breast cancer outcomes, as it was highly expressed in basal breast cancer. Furthermore, high SRPK1 expression correlated with poor breast cancer disease outcome and preferential metastasis to the lungs and brain. In 2 independent murine models of breast tumor metastasis, stable shRNA-based SRPK1 knockdown suppressed metastasis to distant organs, including lung, liver, and spleen, and inhibited focal adhesion reorganization. Our study provides comprehensive information on the molecular determinants of tumor cell migration and suggests that SRPK1 has potential as a drug target for limiting breast cancer metastasis. PMID:25774502

  20. Tumor cell migration screen identifies SRPK1 as breast cancer metastasis determinant.

    PubMed

    van Roosmalen, Wies; Le Dévédec, Sylvia E; Golani, Ofra; Smid, Marcel; Pulyakhina, Irina; Timmermans, Annemieke M; Look, Maxime P; Zi, Di; Pont, Chantal; de Graauw, Marjo; Naffar-Abu-Amara, Suha; Kirsanova, Catherine; Rustici, Gabriella; Hoen, Peter A C 't; Martens, John W M; Foekens, John A; Geiger, Benjamin; van de Water, Bob

    2015-04-01

    Tumor cell migration is a key process for cancer cell dissemination and metastasis that is controlled by signal-mediated cytoskeletal and cell matrix adhesion remodeling. Using a phagokinetic track assay with migratory H1299 cells, we performed an siRNA screen of almost 1,500 genes encoding kinases/phosphatases and adhesome- and migration-related proteins to identify genes that affect tumor cell migration speed and persistence. Thirty candidate genes that altered cell migration were validated in live tumor cell migration assays. Eight were associated with metastasis-free survival in breast cancer patients, with integrin β3-binding protein (ITGB3BP), MAP3K8, NIMA-related kinase (NEK2), and SHC-transforming protein 1 (SHC1) being the most predictive. Examination of genes that modulate migration indicated that SRPK1, encoding the splicing factor kinase SRSF protein kinase 1, is relevant to breast cancer outcomes, as it was highly expressed in basal breast cancer. Furthermore, high SRPK1 expression correlated with poor breast cancer disease outcome and preferential metastasis to the lungs and brain. In 2 independent murine models of breast tumor metastasis, stable shRNA-based SRPK1 knockdown suppressed metastasis to distant organs, including lung, liver, and spleen, and inhibited focal adhesion reorganization. Our study provides comprehensive information on the molecular determinants of tumor cell migration and suggests that SRPK1 has potential as a drug target for limiting breast cancer metastasis.

  1. Genome-wide screen identifies a novel prognostic signature for breast cancer survival

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Mao, Xuan Y.; Lee, Matthew J.; Zhu, Jeffrey

    Large genomic datasets in combination with clinical data can be used as an unbiased tool to identify genes important in patient survival and discover potential therapeutic targets. We used a genome-wide screen to identify 587 genes significantly and robustly deregulated across four independent breast cancer (BC) datasets compared to normal breast tissue. Gene expression of 381 genes was significantly associated with relapse-free survival (RFS) in BC patients. We used a gene co-expression network approach to visualize the genetic architecture in normal breast and BCs. In normal breast tissue, co-expression cliques were identified enriched for cell cycle, gene transcription, cell adhesion,more » cytoskeletal organization and metabolism. In contrast, in BC, only two major co-expression cliques were identified enriched for cell cycle-related processes or blood vessel development, cell adhesion and mammary gland development processes. Interestingly, gene expression levels of 7 genes were found to be negatively correlated with many cell cycle related genes, highlighting these genes as potential tumor suppressors and novel therapeutic targets. A forward-conditional Cox regression analysis was used to identify a 12-gene signature associated with RFS. A prognostic scoring system was created based on the 12-gene signature. This scoring system robustly predicted BC patient RFS in 60 sampling test sets and was further validated in TCGA and METABRIC BC data. Our integrated study identified a 12-gene prognostic signature that could guide adjuvant therapy for BC patients and includes novel potential molecular targets for therapy.« less

  2. Genome-wide screen identifies a novel prognostic signature for breast cancer survival

    DOE PAGES

    Mao, Xuan Y.; Lee, Matthew J.; Zhu, Jeffrey; ...

    2017-01-21

    Large genomic datasets in combination with clinical data can be used as an unbiased tool to identify genes important in patient survival and discover potential therapeutic targets. We used a genome-wide screen to identify 587 genes significantly and robustly deregulated across four independent breast cancer (BC) datasets compared to normal breast tissue. Gene expression of 381 genes was significantly associated with relapse-free survival (RFS) in BC patients. We used a gene co-expression network approach to visualize the genetic architecture in normal breast and BCs. In normal breast tissue, co-expression cliques were identified enriched for cell cycle, gene transcription, cell adhesion,more » cytoskeletal organization and metabolism. In contrast, in BC, only two major co-expression cliques were identified enriched for cell cycle-related processes or blood vessel development, cell adhesion and mammary gland development processes. Interestingly, gene expression levels of 7 genes were found to be negatively correlated with many cell cycle related genes, highlighting these genes as potential tumor suppressors and novel therapeutic targets. A forward-conditional Cox regression analysis was used to identify a 12-gene signature associated with RFS. A prognostic scoring system was created based on the 12-gene signature. This scoring system robustly predicted BC patient RFS in 60 sampling test sets and was further validated in TCGA and METABRIC BC data. Our integrated study identified a 12-gene prognostic signature that could guide adjuvant therapy for BC patients and includes novel potential molecular targets for therapy.« less

  3. Mutational Landscape of Candidate Genes in Familial Prostate Cancer

    PubMed Central

    Johnson, Anna M.; Zuhlke, Kimberly A.; Plotts, Chris; McDonnell, Shannon K.; Middha, Sumit; Riska, Shaun M.; Thibodeau, Stephen N.; Douglas, Julie A.; Cooney, Kathleen A.

    2014-01-01

    Background Family history is a major risk factor for prostate cancer (PCa), suggesting a genetic component to the disease. However, traditional linkage and association studies have failed to fully elucidate the underlying genetic basis of familial PCa. Methods Here we use a candidate gene approach to identify potential PCa susceptibility variants in whole exome sequencing data from familial PCa cases. Six hundred ninety-seven candidate genes were identified based on function, location near a known chromosome 17 linkage signal, and/or previous association with prostate or other cancers. Single nucleotide variants (SNVs) in these candidate genes were identified in whole exome sequence data from 33 PCa cases from 11 multiplex PCa families (3 cases/family). Results Overall, 4856 candidate gene SNVs were identified, including 1052 missense and 10 nonsense variants. Twenty missense variants were shared by all 3 family members in each family in which they were observed. Additionally, 15 missense variants were shared by 2 of 3 family members and predicted to be deleterious by 5 different algorithms. Four missense variants, BLM Gln123Arg, PARP2 Arg283Gln, LRCC46 Ala295Thr and KIF2B Pro91Leu, and 1 nonsense variant, CYP3A43 Arg441Ter, showed complete co-segregation with PCa status. Twelve additional variants displayed partial co-segregation with PCa. Conclusions Forty-three nonsense and shared, missense variants were identified in our candidate genes. Further research is needed to determine the contribution of these variants to PCa susceptibility. PMID:25111073

  4. Identification of Methylated Genes Associated with Aggressive Bladder Cancer

    PubMed Central

    Marsit, Carmen J.; Houseman, E. Andres; Christensen, Brock C.; Gagne, Luc; Wrensch, Margaret R.; Nelson, Heather H.; Wiemels, Joseph; Zheng, Shichun; Wiencke, John K.; Andrew, Angeline S.; Schned, Alan R.; Karagas, Margaret R.; Kelsey, Karl T.

    2010-01-01

    Approximately 500,000 individuals diagnosed with bladder cancer in the U.S. require routine cystoscopic follow-up to monitor for disease recurrences or progression, resulting in over $2 billion in annual expenditures. Identification of new diagnostic and monitoring strategies are clearly needed, and markers related to DNA methylation alterations hold great promise due to their stability, objective measurement, and known associations with the disease and with its clinical features. To identify novel epigenetic markers of aggressive bladder cancer, we utilized a high-throughput DNA methylation bead-array in two distinct population-based series of incident bladder cancer (n = 73 and n = 264, respectively). We then validated the association between methylation of these candidate loci with tumor grade in a third population (n = 245) through bisulfite pyrosequencing of candidate loci. Array based analyses identified 5 loci for further confirmation with bisulfite pyrosequencing. We identified and confirmed that increased promoter methylation of HOXB2 is significantly and independently associated with invasive bladder cancer and methylation of HOXB2, KRT13 and FRZB together significantly predict high-grade non-invasive disease. Methylation of these genes may be useful as clinical markers of the disease and may point to genes and pathways worthy of additional examination as novel targets for therapeutic treatment. PMID:20808801

  5. Identification of methylated genes associated with aggressive bladder cancer.

    PubMed

    Marsit, Carmen J; Houseman, E Andres; Christensen, Brock C; Gagne, Luc; Wrensch, Margaret R; Nelson, Heather H; Wiemels, Joseph; Zheng, Shichun; Wiencke, John K; Andrew, Angeline S; Schned, Alan R; Karagas, Margaret R; Kelsey, Karl T

    2010-08-23

    Approximately 500,000 individuals diagnosed with bladder cancer in the U.S. require routine cystoscopic follow-up to monitor for disease recurrences or progression, resulting in over $2 billion in annual expenditures. Identification of new diagnostic and monitoring strategies are clearly needed, and markers related to DNA methylation alterations hold great promise due to their stability, objective measurement, and known associations with the disease and with its clinical features. To identify novel epigenetic markers of aggressive bladder cancer, we utilized a high-throughput DNA methylation bead-array in two distinct population-based series of incident bladder cancer (n = 73 and n = 264, respectively). We then validated the association between methylation of these candidate loci with tumor grade in a third population (n = 245) through bisulfite pyrosequencing of candidate loci. Array based analyses identified 5 loci for further confirmation with bisulfite pyrosequencing. We identified and confirmed that increased promoter methylation of HOXB2 is significantly and independently associated with invasive bladder cancer and methylation of HOXB2, KRT13 and FRZB together significantly predict high-grade non-invasive disease. Methylation of these genes may be useful as clinical markers of the disease and may point to genes and pathways worthy of additional examination as novel targets for therapeutic treatment.

  6. Impact of Maspin Polymorphism rs2289520 G/C and Its Interaction with Gene to Gene, Alcohol Consumption Increase Susceptibility to Oral Cancer Occurrence.

    PubMed

    Yang, Po-Yu; Miao, Nae-Fang; Lin, Chiao-Wen; Chou, Ying-Erh; Yang, Shun-Fa; Huang, Hui-Chuan; Chang, Hsiu-Ju; Tsai, Hsiu-Ting

    2016-01-01

    The purpose of this study was to identify gene polymorphisms of mammary serine protease inhibitor (Maspin) specific to patients with oral cancer susceptibility and clinicopathological status. Three single-nucleotide polymorphisms (SNPs) of the Maspin gene from 741 patients with oral cancer and 601 non-cancer controls were analyzed by real-time PCR. The participants with G/G homozygotes or with G/C heterozygotes of Maspin rs2289520 polymorphism had a 2.07-fold (p = 0.01) and a 2.01-fold (p = 0.02) risk of developing oral cancer compared to those with C/C homozygotes. Moreover, gene-gene interaction increased the risk of oral cancer susceptibility among subjects expose to oral cancer related risk factors, including areca, alcohol, and tobacco consumption. G allele of Maspin rs2289520 polymorphism may be a factor that increases the susceptibility to oral cancer. The interactions of gene to oral cancer-related environmental risk factors have a synergetic effect that can further enhance oral cancer development.

  7. Pancreatic cancer genomes reveal aberrations in axon guidance pathway genes

    PubMed Central

    Biankin, Andrew V.; Waddell, Nicola; Kassahn, Karin S.; Gingras, Marie-Claude; Muthuswamy, Lakshmi B.; Johns, Amber L.; Miller, David K.; Wilson, Peter J.; Patch, Ann-Marie; Wu, Jianmin; Chang, David K.; Cowley, Mark J.; Gardiner, Brooke B.; Song, Sarah; Harliwong, Ivon; Idrisoglu, Senel; Nourse, Craig; Nourbakhsh, Ehsan; Manning, Suzanne; Wani, Shivangi; Gongora, Milena; Pajic, Marina; Scarlett, Christopher J.; Gill, Anthony J.; Pinho, Andreia V.; Rooman, Ilse; Anderson, Matthew; Holmes, Oliver; Leonard, Conrad; Taylor, Darrin; Wood, Scott; Xu, Qinying; Nones, Katia; Fink, J. Lynn; Christ, Angelika; Bruxner, Tim; Cloonan, Nicole; Kolle, Gabriel; Newell, Felicity; Pinese, Mark; Mead, R. Scott; Humphris, Jeremy L.; Kaplan, Warren; Jones, Marc D.; Colvin, Emily K.; Nagrial, Adnan M.; Humphrey, Emily S.; Chou, Angela; Chin, Venessa T.; Chantrill, Lorraine A.; Mawson, Amanda; Samra, Jaswinder S.; Kench, James G.; Lovell, Jessica A.; Daly, Roger J.; Merrett, Neil D.; Toon, Christopher; Epari, Krishna; Nguyen, Nam Q.; Barbour, Andrew; Zeps, Nikolajs; Kakkar, Nipun; Zhao, Fengmei; Wu, Yuan Qing; Wang, Min; Muzny, Donna M.; Fisher, William E.; Brunicardi, F. Charles; Hodges, Sally E.; Reid, Jeffrey G.; Drummond, Jennifer; Chang, Kyle; Han, Yi; Lewis, Lora R.; Dinh, Huyen; Buhay, Christian J.; Beck, Timothy; Timms, Lee; Sam, Michelle; Begley, Kimberly; Brown, Andrew; Pai, Deepa; Panchal, Ami; Buchner, Nicholas; De Borja, Richard; Denroche, Robert E.; Yung, Christina K.; Serra, Stefano; Onetto, Nicole; Mukhopadhyay, Debabrata; Tsao, Ming-Sound; Shaw, Patricia A.; Petersen, Gloria M.; Gallinger, Steven; Hruban, Ralph H.; Maitra, Anirban; Iacobuzio-Donahue, Christine A.; Schulick, Richard D.; Wolfgang, Christopher L.; Morgan, Richard A.; Lawlor, Rita T.; Capelli, Paola; Corbo, Vincenzo; Scardoni, Maria; Tortora, Giampaolo; Tempero, Margaret A.; Mann, Karen M.; Jenkins, Nancy A.; Perez-Mancera, Pedro A.; Adams, David J.; Largaespada, David A.; Wessels, Lodewyk F. A.; Rust, Alistair G.; Stein, Lincoln D.; Tuveson, David A.; Copeland, Neal G.; Musgrove, Elizabeth A.; Scarpa, Aldo; Eshleman, James R.; Hudson, Thomas J.; Sutherland, Robert L.; Wheeler, David A.; Pearson, John V.; McPherson, John D.; Gibbs, Richard A.; Grimmond, Sean M.

    2012-01-01

    Pancreatic cancer is a highly lethal malignancy with few effective therapies. We performed exome sequencing and copy number analysis to define genomic aberrations in a prospectively accrued clinical cohort (n = 142) of early (stage I and II) sporadic pancreatic ductal adenocarcinoma. Detailed analysis of 99 informative tumours identified substantial heterogeneity with 2,016 non-silent mutations and 1,628 copy-number variations. We define 16 significantly mutated genes, reaffirming known mutations (KRAS, TP53, CDKN2A, SMAD4, MLL3, TGFBR2, ARID1A and SF3B1), and uncover novel mutated genes including additional genes involved in chromatin modification (EPC1 and ARID2), DNA damage repair (ATM) and other mechanisms (ZIM2, MAP2K4, NALCN, SLC16A4 and MAGEA6). Integrative analysis with in vitro functional data and animal models provided supportive evidence for potential roles for these genetic aberrations in carcinogenesis. Pathway-based analysis of recurrently mutated genes recapitulated clustering in core signalling pathways in pancreatic ductal adenocarcinoma, and identified new mutated genes in each pathway. We also identified frequent and diverse somatic aberrations in genes described traditionally as embryonic regulators of axon guidance, particularly SLIT/ROBO signalling, which was also evident in murine Sleeping Beauty transposon-mediated somatic mutagenesis models of pancreatic cancer, providing further supportive evidence for the potential involvement of axon guidance genes in pancreatic carcinogenesis. PMID:23103869

  8. Pancreatic cancer genomes reveal aberrations in axon guidance pathway genes.

    PubMed

    Biankin, Andrew V; Waddell, Nicola; Kassahn, Karin S; Gingras, Marie-Claude; Muthuswamy, Lakshmi B; Johns, Amber L; Miller, David K; Wilson, Peter J; Patch, Ann-Marie; Wu, Jianmin; Chang, David K; Cowley, Mark J; Gardiner, Brooke B; Song, Sarah; Harliwong, Ivon; Idrisoglu, Senel; Nourse, Craig; Nourbakhsh, Ehsan; Manning, Suzanne; Wani, Shivangi; Gongora, Milena; Pajic, Marina; Scarlett, Christopher J; Gill, Anthony J; Pinho, Andreia V; Rooman, Ilse; Anderson, Matthew; Holmes, Oliver; Leonard, Conrad; Taylor, Darrin; Wood, Scott; Xu, Qinying; Nones, Katia; Fink, J Lynn; Christ, Angelika; Bruxner, Tim; Cloonan, Nicole; Kolle, Gabriel; Newell, Felicity; Pinese, Mark; Mead, R Scott; Humphris, Jeremy L; Kaplan, Warren; Jones, Marc D; Colvin, Emily K; Nagrial, Adnan M; Humphrey, Emily S; Chou, Angela; Chin, Venessa T; Chantrill, Lorraine A; Mawson, Amanda; Samra, Jaswinder S; Kench, James G; Lovell, Jessica A; Daly, Roger J; Merrett, Neil D; Toon, Christopher; Epari, Krishna; Nguyen, Nam Q; Barbour, Andrew; Zeps, Nikolajs; Kakkar, Nipun; Zhao, Fengmei; Wu, Yuan Qing; Wang, Min; Muzny, Donna M; Fisher, William E; Brunicardi, F Charles; Hodges, Sally E; Reid, Jeffrey G; Drummond, Jennifer; Chang, Kyle; Han, Yi; Lewis, Lora R; Dinh, Huyen; Buhay, Christian J; Beck, Timothy; Timms, Lee; Sam, Michelle; Begley, Kimberly; Brown, Andrew; Pai, Deepa; Panchal, Ami; Buchner, Nicholas; De Borja, Richard; Denroche, Robert E; Yung, Christina K; Serra, Stefano; Onetto, Nicole; Mukhopadhyay, Debabrata; Tsao, Ming-Sound; Shaw, Patricia A; Petersen, Gloria M; Gallinger, Steven; Hruban, Ralph H; Maitra, Anirban; Iacobuzio-Donahue, Christine A; Schulick, Richard D; Wolfgang, Christopher L; Morgan, Richard A; Lawlor, Rita T; Capelli, Paola; Corbo, Vincenzo; Scardoni, Maria; Tortora, Giampaolo; Tempero, Margaret A; Mann, Karen M; Jenkins, Nancy A; Perez-Mancera, Pedro A; Adams, David J; Largaespada, David A; Wessels, Lodewyk F A; Rust, Alistair G; Stein, Lincoln D; Tuveson, David A; Copeland, Neal G; Musgrove, Elizabeth A; Scarpa, Aldo; Eshleman, James R; Hudson, Thomas J; Sutherland, Robert L; Wheeler, David A; Pearson, John V; McPherson, John D; Gibbs, Richard A; Grimmond, Sean M

    2012-11-15

    Pancreatic cancer is a highly lethal malignancy with few effective therapies. We performed exome sequencing and copy number analysis to define genomic aberrations in a prospectively accrued clinical cohort (n = 142) of early (stage I and II) sporadic pancreatic ductal adenocarcinoma. Detailed analysis of 99 informative tumours identified substantial heterogeneity with 2,016 non-silent mutations and 1,628 copy-number variations. We define 16 significantly mutated genes, reaffirming known mutations (KRAS, TP53, CDKN2A, SMAD4, MLL3, TGFBR2, ARID1A and SF3B1), and uncover novel mutated genes including additional genes involved in chromatin modification (EPC1 and ARID2), DNA damage repair (ATM) and other mechanisms (ZIM2, MAP2K4, NALCN, SLC16A4 and MAGEA6). Integrative analysis with in vitro functional data and animal models provided supportive evidence for potential roles for these genetic aberrations in carcinogenesis. Pathway-based analysis of recurrently mutated genes recapitulated clustering in core signalling pathways in pancreatic ductal adenocarcinoma, and identified new mutated genes in each pathway. We also identified frequent and diverse somatic aberrations in genes described traditionally as embryonic regulators of axon guidance, particularly SLIT/ROBO signalling, which was also evident in murine Sleeping Beauty transposon-mediated somatic mutagenesis models of pancreatic cancer, providing further supportive evidence for the potential involvement of axon guidance genes in pancreatic carcinogenesis.

  9. ColoLipidGene: signature of lipid metabolism-related genes to predict prognosis in stage-II colon cancer patients

    PubMed Central

    Vargas, Teodoro; Moreno-Rubio, Juan; Herranz, Jesús; Cejas, Paloma; Molina, Susana; González-Vallinas, Margarita; Mendiola, Marta; Burgos, Emilio; Aguayo, Cristina; Custodio, Ana B.; Machado, Isidro; Ramos, David; Gironella, Meritxell; Espinosa-Salinas, Isabel; Ramos, Ricardo; Martín-Hernández, Roberto; Risueño, Alberto; De Las Rivas, Javier; Reglero, Guillermo; Yaya, Ricardo; Fernández-Martos, Carlos; Aparicio, Jorge; Maurel, Joan; Feliu, Jaime; de Molina, Ana Ramírez

    2015-01-01

    Lipid metabolism plays an essential role in carcinogenesis due to the requirements of tumoral cells to sustain increased structural, energetic and biosynthetic precursor demands for cell proliferation. We investigated the association between expression of lipid metabolism-related genes and clinical outcome in intermediate-stage colon cancer patients with the aim of identifying a metabolic profile associated with greater malignancy and increased risk of relapse. Expression profile of 70 lipid metabolism-related genes was determined in 77 patients with stage II colon cancer. Cox regression analyses using c-index methodology was applied to identify a metabolic-related signature associated to prognosis. The metabolic signature was further confirmed in two independent validation sets of 120 patients and additionally, in a group of 264 patients from a public database. The combined analysis of these 4 genes, ABCA1, ACSL1, AGPAT1 and SCD, constitutes a metabolic-signature (ColoLipidGene) able to accurately stratify stage II colon cancer patients with 5-fold higher risk of relapse with strong statistical power in the four independent groups of patients. The identification of a group of 4 genes that predict survival in intermediate-stage colon cancer patients allows delineation of a high-risk group that may benefit from adjuvant therapy, and avoids the toxic and unnecessary chemotherapy in patients classified as low-risk group. PMID:25749516

  10. Gene and pathway level analyses of germline DNA-repair gene variants and prostate cancer susceptibility using the iCOGS-genotyping array.

    PubMed

    Saunders, Edward J; Dadaev, Tokhir; Leongamornlert, Daniel A; Al Olama, Ali Amin; Benlloch, Sara; Giles, Graham G; Wiklund, Fredrik; Gronberg, Henrik; Haiman, Christopher A; Schleutker, Johanna; Nordestgaard, Borge G; Travis, Ruth C; Neal, David; Pasayan, Nora; Khaw, Kay-Tee; Stanford, Janet L; Blot, William J; Thibodeau, Stephen N; Maier, Christiane; Kibel, Adam S; Cybulski, Cezary; Cannon-Albright, Lisa; Brenner, Hermann; Park, Jong Y; Kaneva, Radka; Batra, Jyotsna; Teixeira, Manuel R; Pandha, Hardev; Govindasami, Koveela; Muir, Ken; Easton, Douglas F; Eeles, Rosalind A; Kote-Jarai, Zsofia

    2016-04-12

    Germline mutations within DNA-repair genes are implicated in susceptibility to multiple forms of cancer. For prostate cancer (PrCa), rare mutations in BRCA2 and BRCA1 give rise to moderately elevated risk, whereas two of B100 common, low-penetrance PrCa susceptibility variants identified so far by genome-wide association studies implicate RAD51B and RAD23B. Genotype data from the iCOGS array were imputed to the 1000 genomes phase 3 reference panel for 21 780 PrCa cases and 21 727 controls from the Prostate Cancer Association Group to Investigate Cancer Associated Alterations in the Genome (PRACTICAL) consortium. We subsequently performed single variant, gene and pathway-level analyses using 81 303 SNPs within 20 Kb of a panel of 179 DNA-repair genes. Single SNP analyses identified only the previously reported association with RAD51B. Gene-level analyses using the SKAT-C test from the SNP-set (Sequence) Kernel Association Test (SKAT) identified a significant association with PrCa for MSH5. Pathway-level analyses suggested a possible role for the translesion synthesis pathway in PrCa risk and Homologous recombination/Fanconi Anaemia pathway for PrCa aggressiveness, even though after adjustment for multiple testing these did not remain significant. MSH5 is a novel candidate gene warranting additional follow-up as a prospective PrCa-risk locus. MSH5 has previously been reported as a pleiotropic susceptibility locus for lung, colorectal and serous ovarian cancers.

  11. Microarray analysis of genes associated with cell surface NIS protein levels in breast cancer.

    PubMed

    Beyer, Sasha J; Zhang, Xiaoli; Jimenez, Rafael E; Lee, Mei-Ling T; Richardson, Andrea L; Huang, Kun; Jhiang, Sissy M

    2011-10-11

    Na+/I- symporter (NIS)-mediated iodide uptake allows radioiodine therapy for thyroid cancer. NIS is also expressed in breast tumors, raising potential for radionuclide therapy of breast cancer. However, NIS expression in most breast cancers is low and may not be sufficient for radionuclide therapy. We aimed to identify biomarkers associated with NIS expression such that mechanisms underlying NIS modulation in human breast tumors may be elucidated. Published oligonucleotide microarray data within the National Center for Biotechnology Information Gene Expression Omnibus database were analyzed to identify gene expression tightly correlated with NIS mRNA level among human breast tumors. NIS immunostaining was performed in a tissue microarray composed of 28 human breast tumors which had corresponding oligonucleotide microarray data available for each tumor such that gene expression associated with cell surface NIS protein level could be identified. NIS mRNA levels do not vary among breast tumors or when compared to normal breast tissues when detected by Affymetrix oligonucleotide microarray platforms. Cell surface NIS protein levels are much more variable than their corresponding NIS mRNA levels. Despite a limited number of breast tumors examined, our analysis identified cysteinyl-tRNA synthetase as a biomarker that is highly associated with cell surface NIS protein levels in the ER-positive breast cancer subtype. Further investigation on genes associated with cell surface NIS protein levels within each breast cancer molecular subtype may lead to novel targets for selectively increasing NIS expression/function in a subset of breast cancers patients.

  12. Rrp1b, a New Candidate Susceptibility Gene for Breast Cancer Progression and Metastasis

    PubMed Central

    Crawford, Nigel P. S; Qian, Xiaolan; Ziogas, Argyrios; Papageorge, Alex G; Boersma, Brenda J; Walker, Renard C; Lukes, Luanne; Rowe, William L; Zhang, Jinghui; Ambs, Stefan; Lowy, Douglas R; Anton-Culver, Hoda; Hunter, Kent W

    2007-01-01

    A novel candidate metastasis modifier, ribosomal RNA processing 1 homolog B (Rrp1b), was identified through two independent approaches. First, yeast two-hybrid, immunoprecipitation, and functional assays demonstrated a physical and functional interaction between Rrp1b and the previous identified metastasis modifier Sipa1. In parallel, using mouse and human metastasis gene expression data it was observed that extracellular matrix (ECM) genes are common components of metastasis predictive signatures, suggesting that ECM genes are either important markers or causal factors in metastasis. To investigate the relationship between ECM genes and poor prognosis in breast cancer, expression quantitative trait locus analysis of polyoma middle-T transgene-induced mammary tumor was performed. ECM gene expression was found to be consistently associated with Rrp1b expression. In vitro expression of Rrp1b significantly altered ECM gene expression, tumor growth, and dissemination in metastasis assays. Furthermore, a gene signature induced by ectopic expression of Rrp1b in tumor cells predicted survival in a human breast cancer gene expression dataset. Finally, constitutional polymorphism within RRP1B was found to be significantly associated with tumor progression in two independent breast cancer cohorts. These data suggest that RRP1B may be a novel susceptibility gene for breast cancer progression and metastasis. PMID:18081427

  13. Bioinformatics approaches for cross-species liver cancer analysis based on microarray gene expression profiling

    PubMed Central

    Fang, H; Tong, W; Perkins, R; Shi, L; Hong, H; Cao, X; Xie, Q; Yim, SH; Ward, JM; Pitot, HC; Dragan, YP

    2005-01-01

    Background The completion of the sequencing of human, mouse and rat genomes and knowledge of cross-species gene homologies enables studies of differential gene expression in animal models. These types of studies have the potential to greatly enhance our understanding of diseases such as liver cancer in humans. Genes co-expressed across multiple species are most likely to have conserved functions. We have used various bioinformatics approaches to examine microarray expression profiles from liver neoplasms that arise in albumin-SV40 transgenic rats to elucidate genes, chromosome aberrations and pathways that might be associated with human liver cancer. Results In this study, we first identified 2223 differentially expressed genes by comparing gene expression profiles for two control, two adenoma and two carcinoma samples using an F-test. These genes were subsequently mapped to the rat chromosomes using a novel visualization tool, the Chromosome Plot. Using the same plot, we further mapped the significant genes to orthologous chromosomal locations in human and mouse. Many genes expressed in rat 1q that are amplified in rat liver cancer map to the human chromosomes 10, 11 and 19 and to the mouse chromosomes 7, 17 and 19, which have been implicated in studies of human and mouse liver cancer. Using Comparative Genomics Microarray Analysis (CGMA), we identified regions of potential aberrations in human. Lastly, a pathway analysis was conducted to predict altered human pathways based on statistical analysis and extrapolation from the rat data. All of the identified pathways have been known to be important in the etiology of human liver cancer, including cell cycle control, cell growth and differentiation, apoptosis, transcriptional regulation, and protein metabolism. Conclusion The study demonstrates that the hepatic gene expression profiles from the albumin-SV40 transgenic rat model revealed genes, pathways and chromosome alterations consistent with experimental and

  14. Functional annotation of rare gene aberration drivers of pancreatic cancer | Office of Cancer Genomics

    Cancer.gov

    As we enter the era of precision medicine, characterization of cancer genomes will directly influence therapeutic decisions in the clinic. Here we describe a platform enabling functionalization of rare gene mutations through their high-throughput construction, molecular barcoding and delivery to cancer models for in vivo tumour driver screens. We apply these technologies to identify oncogenic drivers of pancreatic ductal adenocarcinoma (PDAC).

  15. The prediction of candidate genes for cervix related cancer through gene ontology and graph theoretical approach.

    PubMed

    Hindumathi, V; Kranthi, T; Rao, S B; Manimaran, P

    2014-06-01

    With rapidly changing technology, prediction of candidate genes has become an indispensable task in recent years mainly in the field of biological research. The empirical methods for candidate gene prioritization that succors to explore the potential pathway between genetic determinants and complex diseases are highly cumbersome and labor intensive. In such a scenario predicting potential targets for a disease state through in silico approaches are of researcher's interest. The prodigious availability of protein interaction data coupled with gene annotation renders an ease in the accurate determination of disease specific candidate genes. In our work we have prioritized the cervix related cancer candidate genes by employing Csaba Ortutay and his co-workers approach of identifying the candidate genes through graph theoretical centrality measures and gene ontology. With the advantage of the human protein interaction data, cervical cancer gene sets and the ontological terms, we were able to predict 15 novel candidates for cervical carcinogenesis. The disease relevance of the anticipated candidate genes was corroborated through a literature survey. Also the presence of the drugs for these candidates was detected through Therapeutic Target Database (TTD) and DrugMap Central (DMC) which affirms that they may be endowed as potential drug targets for cervical cancer.

  16. Genome-wide association analysis identifies three new breast cancer susceptibility loci.

    PubMed

    Ghoussaini, Maya; Fletcher, Olivia; Michailidou, Kyriaki; Turnbull, Clare; Schmidt, Marjanka K; Dicks, Ed; Dennis, Joe; Wang, Qin; Humphreys, Manjeet K; Luccarini, Craig; Baynes, Caroline; Conroy, Don; Maranian, Melanie; Ahmed, Shahana; Driver, Kristy; Johnson, Nichola; Orr, Nicholas; dos Santos Silva, Isabel; Waisfisz, Quinten; Meijers-Heijboer, Hanne; Uitterlinden, Andre G; Rivadeneira, Fernando; Hall, Per; Czene, Kamila; Irwanto, Astrid; Liu, Jianjun; Nevanlinna, Heli; Aittomäki, Kristiina; Blomqvist, Carl; Meindl, Alfons; Schmutzler, Rita K; Müller-Myhsok, Bertram; Lichtner, Peter; Chang-Claude, Jenny; Hein, Rebecca; Nickels, Stefan; Flesch-Janys, Dieter; Tsimiklis, Helen; Makalic, Enes; Schmidt, Daniel; Bui, Minh; Hopper, John L; Apicella, Carmel; Park, Daniel J; Southey, Melissa; Hunter, David J; Chanock, Stephen J; Broeks, Annegien; Verhoef, Senno; Hogervorst, Frans B L; Fasching, Peter A; Lux, Michael P; Beckmann, Matthias W; Ekici, Arif B; Sawyer, Elinor; Tomlinson, Ian; Kerin, Michael; Marme, Frederik; Schneeweiss, Andreas; Sohn, Christof; Burwinkel, Barbara; Guénel, Pascal; Truong, Thérèse; Cordina-Duverger, Emilie; Menegaux, Florence; Bojesen, Stig E; Nordestgaard, Børge G; Nielsen, Sune F; Flyger, Henrik; Milne, Roger L; Alonso, M Rosario; González-Neira, Anna; Benítez, Javier; Anton-Culver, Hoda; Ziogas, Argyrios; Bernstein, Leslie; Dur, Christina Clarke; Brenner, Hermann; Müller, Heiko; Arndt, Volker; Stegmaier, Christa; Justenhoven, Christina; Brauch, Hiltrud; Brüning, Thomas; Wang-Gohrke, Shan; Eilber, Ursula; Dörk, Thilo; Schürmann, Peter; Bremer, Michael; Hillemanns, Peter; Bogdanova, Natalia V; Antonenkova, Natalia N; Rogov, Yuri I; Karstens, Johann H; Bermisheva, Marina; Prokofieva, Darya; Khusnutdinova, Elza; Lindblom, Annika; Margolin, Sara; Mannermaa, Arto; Kataja, Vesa; Kosma, Veli-Matti; Hartikainen, Jaana M; Lambrechts, Diether; Yesilyurt, Betul T; Floris, Giuseppe; Leunen, Karin; Manoukian, Siranoush; Bonanni, Bernardo; Fortuzzi, Stefano; Peterlongo, Paolo; Couch, Fergus J; Wang, Xianshu; Stevens, Kristen; Lee, Adam; Giles, Graham G; Baglietto, Laura; Severi, Gianluca; McLean, Catriona; Alnaes, Grethe Grenaker; Kristensen, Vessela; Børrensen-Dale, Anne-Lise; John, Esther M; Miron, Alexander; Winqvist, Robert; Pylkäs, Katri; Jukkola-Vuorinen, Arja; Kauppila, Saila; Andrulis, Irene L; Glendon, Gord; Mulligan, Anna Marie; Devilee, Peter; van Asperen, Christie J; Tollenaar, Rob A E M; Seynaeve, Caroline; Figueroa, Jonine D; Garcia-Closas, Montserrat; Brinton, Louise; Lissowska, Jolanta; Hooning, Maartje J; Hollestelle, Antoinette; Oldenburg, Rogier A; van den Ouweland, Ans M W; Cox, Angela; Reed, Malcolm W R; Shah, Mitul; Jakubowska, Ania; Lubinski, Jan; Jaworska, Katarzyna; Durda, Katarzyna; Jones, Michael; Schoemaker, Minouk; Ashworth, Alan; Swerdlow, Anthony; Beesley, Jonathan; Chen, Xiaoqing; Muir, Kenneth R; Lophatananon, Artitaya; Rattanamongkongul, Suthee; Chaiwerawattana, Arkom; Kang, Daehee; Yoo, Keun-Young; Noh, Dong-Young; Shen, Chen-Yang; Yu, Jyh-Cherng; Wu, Pei-Ei; Hsiung, Chia-Ni; Perkins, Annie; Swann, Ruth; Velentzis, Louiza; Eccles, Diana M; Tapper, Will J; Gerty, Susan M; Graham, Nikki J; Ponder, Bruce A J; Chenevix-Trench, Georgia; Pharoah, Paul D P; Lathrop, Mark; Dunning, Alison M; Rahman, Nazneen; Peto, Julian; Easton, Douglas F

    2012-01-22

    Breast cancer is the most common cancer among women. To date, 22 common breast cancer susceptibility loci have been identified accounting for ∼8% of the heritability of the disease. We attempted to replicate 72 promising associations from two independent genome-wide association studies (GWAS) in ∼70,000 cases and ∼68,000 controls from 41 case-control studies and 9 breast cancer GWAS. We identified three new breast cancer risk loci at 12p11 (rs10771399; P = 2.7 × 10(-35)), 12q24 (rs1292011; P = 4.3 × 10(-19)) and 21q21 (rs2823093; P = 1.1 × 10(-12)). rs10771399 was associated with similar relative risks for both estrogen receptor (ER)-negative and ER-positive breast cancer, whereas the other two loci were associated only with ER-positive disease. Two of the loci lie in regions that contain strong plausible candidate genes: PTHLH (12p11) has a crucial role in mammary gland development and the establishment of bone metastasis in breast cancer, and NRIP1 (21q21) encodes an ER cofactor and has a role in the regulation of breast cancer cell growth.

  17. Genome-wide association analysis identifies three new breast cancer susceptibility loci

    PubMed Central

    Ghoussaini, Maya; Fletcher, Olivia; Michailidou, Kyriaki; Turnbull, Clare; Schmidt, Marjanka K; Dicks, Ed; Dennis, Joe; Wang, Qin; Humphreys, Manjeet K; Luccarini, Craig; Baynes, Caroline; Conroy, Don; Maranian, Melanie; Ahmed, Shahana; Driver, Kristy; Johnson, Nichola; Orr, Nicholas; Silva, Isabel dos Santos; Waisfisz, Quinten; Meijers-Heijboer, Hanne; Uitterlinden, Andre G.; Rivadeneira, Fernando; Hall, Per; Czene, Kamila; Irwanto, Astrid; Liu, Jianjun; Nevanlinna, Heli; Aittomäki, Kristiina; Blomqvist, Carl; Meindl, Alfons; Schmutzler, Rita K; Müller-Myhsok, Bertram; Lichtner, Peter; Chang-Claude, Jenny; Hein, Rebecca; Nickels, Stefan; Flesch-Janys, Dieter; Tsimiklis, Helen; Makalic, Enes; Schmidt, Daniel; Bui, Minh; Hopper, John L; Apicella, Carmel; Park, Daniel J; Southey, Melissa; Hunter, David J; Chanock, Stephen J; Broeks, Annegien; Verhoef, Senno; Hogervorst, Frans BL; Fasching, Peter A.; Lux, Michael P.; Beckmann, Matthias W.; Ekici, Arif B.; Sawyer, Elinor; Tomlinson, Ian; Kerin, Michael; Marme, Frederik; Schneeweiss, Andreas; Sohn, Christof; Burwinkel, Barbara; Guénel, Pascal; Truong, Thérèse; Cordina-Duverger, Emilie; Menegaux, Florence; Bojesen, Stig E; Nordestgaard, Børge G; Nielsen, Sune F; Flyger, Henrik; Milne, Roger L.; Alonso, M. Rosario; González-Neira, Anna; Benítez, Javier; Anton-Culver, Hoda; Ziogas, Argyrios; Bernstein, Leslie; Dur, Christina Clarke; Brenner, Hermann; Müller, Heiko; Arndt, Volker; Stegmaier, Christa; Justenhoven, Christina; Brauch, Hiltrud; Brüning, Thomas; Wang-Gohrke, Shan; Eilber, Ursula; Dörk, Thilo; Schürmann, Peter; Bremer, Michael; Hillemanns, Peter; Bogdanova, Natalia V.; Antonenkova, Natalia N.; Rogov, Yuri I.; Karstens, Johann H.; Bermisheva, Marina; Prokofieva, Darya; Khusnutdinova, Elza; Lindblom, Annika; Margolin, Sara; Mannermaa, Arto; Kataja, Vesa; Kosma, Veli-Matti; Hartikainen, Jaana M; Lambrechts, Diether; Yesilyurt, Betul T.; Floris, Giuseppe; Leunen, Karin; Manoukian, Siranoush; Bonanni, Bernardo; Fortuzzi, Stefano; Peterlongo, Paolo; Couch, Fergus J; Wang, Xianshu; Stevens, Kristen; Lee, Adam; Giles, Graham G.; Baglietto, Laura; Severi, Gianluca; McLean, Catriona; Alnæs, Grethe Grenaker; Kristensen, Vessela; Børrensen-Dale, Anne-Lise; John, Esther M.; Miron, Alexander; Winqvist, Robert; Pylkäs, Katri; Jukkola-Vuorinen, Arja; Kauppila, Saila; Andrulis, Irene L.; Glendon, Gord; Mulligan, Anna Marie; Devilee, Peter; van Asperen, Christie J.; Tollenaar, Rob A.E.M.; Seynaeve, Caroline; Figueroa, Jonine D; Garcia-Closas, Montserrat; Brinton, Louise; Lissowska, Jolanta; Hooning, Maartje J.; Hollestelle, Antoinette; Oldenburg, Rogier A.; van den Ouweland, Ans M.W.; Cox, Angela; Reed, Malcolm WR; Shah, Mitul; Jakubowska, Ania; Lubinski, Jan; Jaworska, Katarzyna; Durda, Katarzyna; Jones, Michael; Schoemaker, Minouk; Ashworth, Alan; Swerdlow, Anthony; Beesley, Jonathan; Chen, Xiaoqing; Muir, Kenneth R; Lophatananon, Artitaya; Rattanamongkongul, Suthee; Chaiwerawattana, Arkom; Kang, Daehee; Yoo, Keun-Young; Noh, Dong-Young; Shen, Chen-Yang; Yu, Jyh-Cherng; Wu, Pei-Ei; Hsiung, Chia-Ni; Perkins, Annie; Swann, Ruth; Velentzis, Louiza; Eccles, Diana M; Tapper, Will J; Gerty, Susan M; Graham, Nikki J; Ponder, Bruce A. J.; Chenevix-Trench, Georgia; Pharoah, Paul D.P.; Lathrop, Mark; Dunning, Alison M.; Rahman, Nazneen; Peto, Julian; Easton, Douglas F

    2013-01-01

    Breast cancer is the most common cancer among women. To date, 22 common breast cancer susceptibility loci have been identified accounting for ~ 8% of the heritability of the disease. We followed up 72 promising associations from two independent Genome Wide Association Studies (GWAS) in ~70,000 cases and ~68,000 controls from 41 case-control studies and nine breast cancer GWAS. We identified three new breast cancer risk loci on 12p11 (rs10771399; P=2.7 × 10−35), 12q24 (rs1292011; P=4.3×10−19) and 21q21 (rs2823093; P=1.1×10−12). SNP rs10771399 was associated with similar relative risks for both estrogen receptor (ER)-negative and ER-positive breast cancer, whereas the other two loci were associated only with ER-positive disease. Two of the loci lie in regions that contain strong plausible candidate genes: PTHLH (12p11) plays a crucial role in mammary gland development and the establishment of bone metastasis in breast cancer, while NRIP1 (21q21) encodes an ER co-factor and has a role in the regulation of breast cancer cell growth. PMID:22267197

  18. TP53, PIK3CA, FBXW7 and KRAS Mutations in Esophageal Cancer Identified by Targeted Sequencing.

    PubMed

    Zheng, Huili; Wang, Yan; Tang, Chuanning; Jones, Lindsey; Ye, Hua; Zhang, Guangchun; Cao, Weihai; Li, Jingwen; Liu, Lifeng; Liu, Zhencong; Zhang, Chao; Lou, Feng; Liu, Zhiyuan; Li, Yangyang; Shi, Zhenfen; Zhang, Jingbo; Zhang, Dandan; Sun, Hong; Dong, Haichao; Dong, Zhishou; Guo, Baishuai; Yan, H E; Lu, Qingyu; Huang, Xue; Chen, Si-Yi

    2016-01-01

    Esophageal cancer (EC) is a common malignancy with significant morbidity and mortality. As individual cancers exhibit unique mutation patterns, identifying and characterizing gene mutations in EC that may serve as biomarkers might help predict patient outcome and guide treatment. Traditionally, personalized cancer DNA sequencing was impractical and expensive. Recent technological advancements have made targeted DNA sequencing more cost- and time-effective with reliable results. This technology may be useful for clinicians to direct patient treatment. The Ion PGM and AmpliSeq Cancer Panel was used to identify mutations at 737 hotspot loci of 45 cancer-related genes in 64 EC samples from Chinese patients. Frequent mutations were found in TP53 and less frequent mutations in PIK3CA, FBXW7 and KRAS. These results demonstrate that targeted sequencing can reliably identify mutations in individual tumors that make this technology a possibility for clinical use. Copyright© 2016, International Institute of Anticancer Research (Dr. John G. Delinasios), All rights reserved.

  19. TAGCNA: A Method to Identify Significant Consensus Events of Copy Number Alterations in Cancer

    PubMed Central

    Yuan, Xiguo; Zhang, Junying; Yang, Liying; Zhang, Shengli; Chen, Baodi; Geng, Yaojun; Wang, Yue

    2012-01-01

    Somatic copy number alteration (CNA) is a common phenomenon in cancer genome. Distinguishing significant consensus events (SCEs) from random background CNAs in a set of subjects has been proven to be a valuable tool to study cancer. In order to identify SCEs with an acceptable type I error rate, better computational approaches should be developed based on reasonable statistics and null distributions. In this article, we propose a new approach named TAGCNA for identifying SCEs in somatic CNAs that may encompass cancer driver genes. TAGCNA employs a peel-off permutation scheme to generate a reasonable null distribution based on a prior step of selecting tag CNA markers from the genome being considered. We demonstrate the statistical power of TAGCNA on simulated ground truth data, and validate its applicability using two publicly available cancer datasets: lung and prostate adenocarcinoma. TAGCNA identifies SCEs that are known to be involved with proto-oncogenes (e.g. EGFR, CDK4) and tumor suppressor genes (e.g. CDKN2A, CDKN2B), and provides many additional SCEs with potential biological relevance in these data. TAGCNA can be used to analyze the significance of CNAs in various cancers. It is implemented in R and is freely available at http://tagcna.sourceforge.net/. PMID:22815924

  20. Csa-19, a radiation-responsive human gene, identified by an unbiased two-gel cDNA library screening method in human cancer cells

    NASA Technical Reports Server (NTRS)

    Balcer-Kubiczek, E. K.; Meltzer, S. J.; Han, L. H.; Zhang, X. F.; Shi, Z. M.; Harrison, G. H.; Abraham, J. M.

    1997-01-01

    A novel polymerase chain reaction (PCR)-based method was used to identify candidate genes whose expression is altered in cancer cells by ionizing radiation. Transcriptional induction of randomly selected genes in control versus irradiated human HL60 cells was compared. Among several complementary DNA (cDNA) clones recovered by this approach, one cDNA clone (CL68-5) was downregulated in X-irradiated HL60 cells but unaffected by 12-O-tetradecanoyl phorbol-13-acetate, forskolin, or cyclosporin-A. DNA sequencing of the CL68-5 cDNA revealed 100% nucleotide sequence homology to the reported human Csa-19 gene. Northern blot analysis of RNA from control and irradiated cells revealed the expression of a single 0.7-kilobase (kb) messenger RNA (mRNA) transcript. This 0.7-kb Csa-19 mRNA transcript was also expressed in a variety of human adult and corresponding fetal normal tissues. Moreover, when the effect of X- or fission neutron-irradiation on Csa-19 mRNA was compared in cultured human cells differing in p53 gene status (p53-/- versus p53+/+), downregulation of Csa-19 by X-rays or fission neutrons was similar in p53-wild type and p53-null cell lines. Our results provide the first known example of a radiation-responsive gene in human cancer cells whose expression is not associated with p53, adenylate cyclase or protein kinase C.

  1. Pan-Cancer Analysis of the Mediator Complex Transcriptome Identifies CDK19 and CDK8 as Therapeutic Targets in Advanced Prostate Cancer.

    PubMed

    Brägelmann, Johannes; Klümper, Niklas; Offermann, Anne; von Mässenhausen, Anne; Böhm, Diana; Deng, Mario; Queisser, Angela; Sanders, Christine; Syring, Isabella; Merseburger, Axel S; Vogel, Wenzel; Sievers, Elisabeth; Vlasic, Ignacija; Carlsson, Jessica; Andrén, Ove; Brossart, Peter; Duensing, Stefan; Svensson, Maria A; Shaikhibrahim, Zaki; Kirfel, Jutta; Perner, Sven

    2017-04-01

    Purpose: The Mediator complex is a multiprotein assembly, which serves as a hub for diverse signaling pathways to regulate gene expression. Because gene expression is frequently altered in cancer, a systematic understanding of the Mediator complex in malignancies could foster the development of novel targeted therapeutic approaches. Experimental Design: We performed a systematic deconvolution of the Mediator subunit expression profiles across 23 cancer entities ( n = 8,568) using data from The Cancer Genome Atlas (TCGA). Prostate cancer-specific findings were validated in two publicly available gene expression cohorts and a large cohort of primary and advanced prostate cancer ( n = 622) stained by immunohistochemistry. The role of CDK19 and CDK8 was evaluated by siRNA-mediated gene knockdown and inhibitor treatment in prostate cancer cell lines with functional assays and gene expression analysis by RNAseq. Results: Cluster analysis of TCGA expression data segregated tumor entities, indicating tumor-type-specific Mediator complex compositions. Only prostate cancer was marked by high expression of CDK19 In primary prostate cancer, CDK19 was associated with increased aggressiveness and shorter disease-free survival. During cancer progression, highest levels of CDK19 and of its paralog CDK8 were present in metastases. In vitro , inhibition of CDK19 and CDK8 by knockdown or treatment with a selective CDK8/CDK19 inhibitor significantly decreased migration and invasion. Conclusions: Our analysis revealed distinct transcriptional expression profiles of the Mediator complex across cancer entities indicating differential modes of transcriptional regulation. Moreover, it identified CDK19 and CDK8 to be specifically overexpressed during prostate cancer progression, highlighting their potential as novel therapeutic targets in advanced prostate cancer. Clin Cancer Res; 23(7); 1829-40. ©2016 AACR . ©2016 American Association for Cancer Research.

  2. Stem Cell-Like Gene Expression in Ovarian Cancer Predicts Type II Subtype and Prognosis

    PubMed Central

    Schwede, Matthew; Spentzos, Dimitrios; Bentink, Stefan; Hofmann, Oliver; Haibe-Kains, Benjamin; Harrington, David; Quackenbush, John; Culhane, Aedín C.

    2013-01-01

    Although ovarian cancer is often initially chemotherapy-sensitive, the vast majority of tumors eventually relapse and patients die of increasingly aggressive disease. Cancer stem cells are believed to have properties that allow them to survive therapy and may drive recurrent tumor growth. Cancer stem cells or cancer-initiating cells are a rare cell population and difficult to isolate experimentally. Genes that are expressed by stem cells may characterize a subset of less differentiated tumors and aid in prognostic classification of ovarian cancer. The purpose of this study was the genomic identification and characterization of a subtype of ovarian cancer that has stem cell-like gene expression. Using human and mouse gene signatures of embryonic, adult, or cancer stem cells, we performed an unsupervised bipartition class discovery on expression profiles from 145 serous ovarian tumors to identify a stem-like and more differentiated subgroup. Subtypes were reproducible and were further characterized in four independent, heterogeneous ovarian cancer datasets. We identified a stem-like subtype characterized by a 51-gene signature, which is significantly enriched in tumors with properties of Type II ovarian cancer; high grade, serous tumors, and poor survival. Conversely, the differentiated tumors share properties with Type I, including lower grade and mixed histological subtypes. The stem cell-like signature was prognostic within high-stage serous ovarian cancer, classifying a small subset of high-stage tumors with better prognosis, in the differentiated subtype. In multivariate models that adjusted for common clinical factors (including grade, stage, age), the subtype classification was still a significant predictor of relapse. The prognostic stem-like gene signature yields new insights into prognostic differences in ovarian cancer, provides a genomic context for defining Type I/II subtypes, and potential gene targets which following further validation may be valuable

  3. Gene-environment interactions in cancer epidemiology: a National Cancer Institute Think Tank report.

    PubMed

    Hutter, Carolyn M; Mechanic, Leah E; Chatterjee, Nilanjan; Kraft, Peter; Gillanders, Elizabeth M

    2013-11-01

    Cancer risk is determined by a complex interplay of genetic and environmental factors. Genome-wide association studies (GWAS) have identified hundreds of common (minor allele frequency [MAF] > 0.05) and less common (0.01 < MAF < 0.05) genetic variants associated with cancer. The marginal effects of most of these variants have been small (odds ratios: 1.1-1.4). There remain unanswered questions on how best to incorporate the joint effects of genes and environment, including gene-environment (G × E) interactions, into epidemiologic studies of cancer. To help address these questions, and to better inform research priorities and allocation of resources, the National Cancer Institute sponsored a "Gene-Environment Think Tank" on January 10-11, 2012. The objective of the Think Tank was to facilitate discussions on (1) the state of the science, (2) the goals of G × E interaction studies in cancer epidemiology, and (3) opportunities for developing novel study designs and analysis tools. This report summarizes the Think Tank discussion, with a focus on contemporary approaches to the analysis of G × E interactions. Selecting the appropriate methods requires first identifying the relevant scientific question and rationale, with an important distinction made between analyses aiming to characterize the joint effects of putative or established genetic and environmental factors and analyses aiming to discover novel risk factors or novel interaction effects. Other discussion items include measurement error, statistical power, significance, and replication. Additional designs, exposure assessments, and analytical approaches need to be considered as we move from the current small number of success stories to a fuller understanding of the interplay of genetic and environmental factors. © 2013 WILEY PERIODICALS, INC.

  4. Extracting Fitness Relationships and Oncogenic Patterns among Driver Genes in Cancer.

    PubMed

    Zhang, Xindong; Gao, Lin; Jia, Songwei

    2017-12-25

    Driver mutation provides fitness advantage to cancer cells, the accumulation of which increases the fitness of cancer cells and accelerates cancer progression. This work seeks to extract patterns accumulated by driver genes ("fitness relationships") in tumorigenesis. We introduce a network-based method for extracting the fitness relationships of driver genes by modeling the network properties of the "fitness" of cancer cells. Colon adenocarcinoma (COAD) and skin cutaneous malignant melanoma (SKCM) are employed as case studies. Consistent results derived from different background networks suggest the reliability of the identified fitness relationships. Additionally co-occurrence analysis and pathway analysis reveal the functional significance of the fitness relationships with signaling transduction. In addition, a subset of driver genes called the "fitness core" is recognized for each case. Further analyses indicate the functional importance of the fitness core in carcinogenesis, and provide potential therapeutic opportunities in medicinal intervention. Fitness relationships characterize the functional continuity among driver genes in carcinogenesis, and suggest new insights in understanding the oncogenic mechanisms of cancers, as well as providing guiding information for medicinal intervention.

  5. Strategy of Cancer Targeting Gene-Viro-Therapy (CTGVT) a trend in both cancer gene therapy and cancer virotherapy.

    PubMed

    Liu, Xin-Yuan; Li, Hua-Guang; Zhang, Kang-Jian; Gu, Jin-Fa

    2012-07-01

    Cancer Targeting Gene-Viro-Therapy (CTGVT) and Gene Armed Oncolytic Virus Therapy (GAOVT) both are identical by inserting an antitumor gene into an oncolytic virus. This approach has gradually become a hot topic in cancer therapy, because that CTGVT (GAOVT) has much higher antitumor than that of either gene therapy alone or oncolytic virotherapy alone. We proposed the CTGVT strategy in 1999-2001, insisted it as a long term systematic approach to be examined over 10 years and have published 68 SCI papers some in good Journals. The CD gene armed oncolytic adenovirus therapy (GAOVT) for cancer treatment with potent antitumor effect was also named in our laboratory in 2003. Several modifications to CTGVT will be carried out by our group and will be introduced briefly in this paper. Most importantly, the modifications of CTGVT usually resulted in complete eradication of xenograft tumors in nude mice. In future best antitumor drugs may emerge from the modified CTGVT strategy and not from either gene therapy or virotherapy alone.

  6. K-sam, an amplified gene in stomach cancer, is a member of the heparin-binding growth factor receptor genes

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Hattori, Yutaka; Odagiri, Hiroki; Nakatani, Hiroshi

    1990-08-01

    DNA fragments amplified in a stomach cancer-derived cell line, KATO-III, were previously identified by the in-gel DNA renaturation method, and a 0.2-kilobase-pair fragment of the amplified sequence was subsequently cloned. By genomic walking, a portion of the exon of the gene flanking this 0.2-kilobase-pair fragment was cloned, and the gene was designated as K-sam ({und K}ATO-III cell-derived {und s}tomach cancer {und am}plified gene). The K-sam cDNAs, corresponding to the 3.5-kilobase K-sam mRNA, were cloned from the KATO-III cells. Sequence analysis revealed that this gene coded for 682 amino acid residues that satisfied the characteristics of the receptor tyrosine kinase. Themore » K-sam gene had significant homologies with bek, FLG, and chicken basic fibroblast growth factor receptor gene. The K-sam gene was amplified in KATO-III cells with the major transcript of 3.5-kilobases in size. This gene was also expressed in some other stomach cancer cells, a small cell lung cancer, and germ cell tumors.« less

  7. A Catalog of Genes Homozygously Deleted in Human Lung Cancer and the Candidacy of PTPRD as a Tumor Suppressor Gene

    PubMed Central

    Kohno, Takashi; Otsuka, Ayaka; Girard, Luc; Sato, Masanori; Iwakawa, Reika; Ogiwara, Hideaki; Sanchez-Cespedes, Montse; Minna, John D.; Yokota, Jun

    2010-01-01

    A total of 176 genes homozygously deleted in human lung cancer were identified by DNA array-based whole genome scanning of 52 lung cancer cell lines and subsequent genomic PCR in 74 cell lines, including the 52 cell lines scanned. One or more exons of these genes were homozygously deleted in one (1%) to 20 (27%) cell lines. These genes included known tumor suppressor genes, e.g., CDKN2A/p16, RB1, and SMAD4, and candidate tumor suppressor genes whose hemizygous or homozygous deletions were reported in several types of human cancers, such as FHIT, KEAP1, and LRP1B/LRP-DIP. CDKN2A/p16 and p14ARF located in 9p21 were most frequently deleted (20/74, 27%). The PTPRD gene was most frequently deleted (8/74, 11%) among genes mapping to regions other than 9p21. Somatic mutations, including a nonsense mutation, of the PTPRD gene were detected in 8/74 (11%) of cell lines and 4/95 (4%) of surgical specimens of lung cancer. Reduced PTPRD expression was observed in the majority (>80%) of cell lines and surgical specimens of lung cancer. Therefore, PTPRD is a candidate tumor suppressor gene in lung cancer. Microarray-based expression profiling of 19 lung cancer cell lines also indicated that some of the 176 genes, such as KANK and ADAMTS1, are preferentially inactivated by epigenetic alterations. Genetic/epigenetic as well as functional studies of these 176 genes will increase our understanding of molecular mechanisms behind lung carcinogenesis. PMID:20073072

  8. Ethics of Cancer Gene Transfer Clinical Research.

    PubMed

    Kimmelman, Jonathan

    2015-01-01

    Translation of cancer gene transfer confronts many familiar-and some distinctive-ethical challenges. In what follows, I survey three major ethical dimensions of cancer gene transfer development. Subheading 1 centers on the ethics of planning, designing, and reporting animal studies. Subheading 2 describes basic elements of human subjects protection as pertaining to cancer gene transfer. In Subheading 3, I describe how cancer gene transfer researchers have obligations to downstream consumers of the evidence they produce.

  9. Highly preserved consensus gene modules in human papilloma virus 16 positive cervical cancer and head and neck cancers.

    PubMed

    Zhang, Xianglan; Cha, In-Ho; Kim, Ki-Yeol

    2017-12-26

    In this study, we investigated the consensus gene modules in head and neck cancer (HNC) and cervical cancer (CC). We used a publicly available gene expression dataset, GSE6791, which included 42 HNC, 14 normal head and neck, 20 CC and 8 normal cervical tissue samples. To exclude bias because of different human papilloma virus (HPV) types, we analyzed HPV16-positive samples only. We identified 3824 genes common to HNC and CC samples. Among these, 977 genes showed high connectivity and were used to construct consensus modules. We demonstrated eight consensus gene modules for HNC and CC using the dissimilarity measure and average linkage hierarchical clustering methods. These consensus modules included genes with significant biological functions, including ATP binding and extracellular exosome. Eigengen network analysis revealed the consensus modules were highly preserved with high connectivity. These findings demonstrate that HPV16-positive head and neck and cervical cancers share highly preserved consensus gene modules with common potentially therapeutic targets.

  10. Highly preserved consensus gene modules in human papilloma virus 16 positive cervical cancer and head and neck cancers

    PubMed Central

    Zhang, Xianglan; Cha, In-Ho; Kim, Ki-Yeol

    2017-01-01

    In this study, we investigated the consensus gene modules in head and neck cancer (HNC) and cervical cancer (CC). We used a publicly available gene expression dataset, GSE6791, which included 42 HNC, 14 normal head and neck, 20 CC and 8 normal cervical tissue samples. To exclude bias because of different human papilloma virus (HPV) types, we analyzed HPV16-positive samples only. We identified 3824 genes common to HNC and CC samples. Among these, 977 genes showed high connectivity and were used to construct consensus modules. We demonstrated eight consensus gene modules for HNC and CC using the dissimilarity measure and average linkage hierarchical clustering methods. These consensus modules included genes with significant biological functions, including ATP binding and extracellular exosome. Eigengen network analysis revealed the consensus modules were highly preserved with high connectivity. These findings demonstrate that HPV16-positive head and neck and cervical cancers share highly preserved consensus gene modules with common potentially therapeutic targets. PMID:29371966

  11. Genome-wide gene-asbestos exposure interaction association study identifies a common susceptibility variant on 22q13.31 associated with lung cancer risk

    PubMed Central

    Liu, Chen-yu; Stücker, Isabelle; Chen, Chu; Goodman, Gary; McHugh, Michelle K.; D’Amelio, Anthony M.; Etzel, Carol J.; Li, Su; Lin, Xihong; Christiani, David C.

    2015-01-01

    Background Occupational asbestos exposure has been found to increase lung cancer risk in epidemiological studies. Methods We conducted an asbestos exposure-gene interaction analyses among several Caucasian populations who were current or ex-smokers. The discovery phase included 833 Caucasian cases and 739 Caucasian controls, and used a genome-wide association study (GWAS) to identify single nucleotide polymorphisms (SNPs) with gene-asbestos interaction effects. The top ranked SNPs from the discovery phase were replicated within the International Lung and Cancer Consortium (ILCCO). First, in silico replication was conducted in those groups that had GWAS and asbestos exposure data, including 1,548 cases and 1,527 controls. This step was followed by de novo genotyping to replicate the results from the in silico replication, and included 1,539 cases and 1,761 controls. Multiple logistic regression was used to assess the SNP-asbestos exposure interaction effects on lung cancer risk. Results We observed significantly increased lung cancer risk among MIRLET7BHG (MIRLET7B host gene located at 22q13.31) polymorphisms rs13053856, rs11090910, rs11703832, and rs12170325 heterozygous and homozygous variant allele(s) carriers [p<5×10−7 by likelihood ratio test; df=1]. Among the heterozygous and homozygous variant allele(s) carriers of polymorphisms rs13053856, rs11090910, rs11703832, and rs12170325, each unit increase in the natural log-transformed asbestos exposure score was associated with age-, sex-, smoking status- and center-adjusted ORs of 1.34 (95%CI=1.18–1.51), 1.24 (95%CI=1.14–1.35), 1.28 (95%CI=1.17–1.40), and 1.26 (95%CI=1.15–1.38), respectively for lung cancer risk. Conclusion Our findings suggest that MIRLET7BHG polymorphisms may be important predictive markers for asbestos exposure-related lung cancer. Impact To our knowledge, our study is the first report using a systematic genome-wide analysis in combination with detailed asbestos exposure data and

  12. Systematic analysis of microarray datasets to identify Parkinson's disease‑associated pathways and genes.

    PubMed

    Feng, Yinling; Wang, Xuefeng

    2017-03-01

    In order to investigate commonly disturbed genes and pathways in various brain regions of patients with Parkinson's disease (PD), microarray datasets from previous studies were collected and systematically analyzed. Different normalization methods were applied to microarray datasets from different platforms. A strategy combining gene co‑expression networks and clinical information was adopted, using weighted gene co‑expression network analysis (WGCNA) to screen for commonly disturbed genes in different brain regions of patients with PD. Functional enrichment analysis of commonly disturbed genes was performed using the Database for Annotation, Visualization, and Integrated Discovery (DAVID). Co‑pathway relationships were identified with Pearson's correlation coefficient tests and a hypergeometric distribution‑based test. Common genes in pathway pairs were selected out and regarded as risk genes. A total of 17 microarray datasets from 7 platforms were retained for further analysis. Five gene coexpression modules were identified, containing 9,745, 736, 233, 101 and 93 genes, respectively. One module was significantly correlated with PD samples and thus the 736 genes it contained were considered to be candidate PD‑associated genes. Functional enrichment analysis demonstrated that these genes were implicated in oxidative phosphorylation and PD. A total of 44 pathway pairs and 52 risk genes were revealed, and a risk gene pathway relationship network was constructed. Eight modules were identified and were revealed to be associated with PD, cancers and metabolism. A number of disturbed pathways and risk genes were unveiled in PD, and these findings may help advance understanding of PD pathogenesis.

  13. Identification of TMEM208 and PQLC2 as reference genes for normalizing mRNA expression in colorectal cancer treated with aspirin

    PubMed Central

    Zhu, Yuanyuan; Yang, Chao; Weng, Mingjiao; Zhang, Yan; Yang, Chunhui; Jin, Yinji; Yang, Weiwei; He, Yan; Wu, Yiqi; Zhang, Yuhua; Wang, Guangyu; RajkumarEzakiel Redpath, Riju James; Zhang, Lei; Jin, Xiaoming; Liu, Ying; Sun, Yuchun; Ning, Ning; Qiao, Yu; Zhang, Fengmin; Li, Zhiwei; Wang, Tianzhen; Zhang, Yanqiao; Li, Xiaobo

    2017-01-01

    Numerous evidences indicate that aspirin usage causes a significant reduction in colorectal cancer. However, the molecular mechanisms about aspirin preventing colon cancer are largely unknown. Quantitative reverse transcription polymerase chain reaction (qRT-PCR) is a most frequently used method to identify the target molecules regulated by certain compound. However, this method needs stable internal reference genes to analyze the expression change of the targets. In this study, the transcriptional stabilities of several traditional reference genes were evaluated in colon cancer cells treated with aspirin, and also, the suitable internal reference genes were screened by using a microarray and were further identified by using the geNorm and NormFinder softwares, and then were validated in more cell lines and xenografts. We have showed that three traditional internal reference genes, β-actin, GAPDH and α-tubulin, are not suitable for studying gene transcription in colon cancer cells treated with aspirin, and we have identified and validated TMEM208 and PQLC2 as the ideal internal reference genes for detecting the molecular targets of aspirin in colon cancer in vitro and in vivo. This study reveals stable internal reference genes for studying the target genes of aspirin in colon cancer, which will contribute to identify the molecular mechanism behind aspirin preventing colon cancer. PMID:28184026

  14. Identification of TMEM208 and PQLC2 as reference genes for normalizing mRNA expression in colorectal cancer treated with aspirin.

    PubMed

    Zhu, Yuanyuan; Yang, Chao; Weng, Mingjiao; Zhang, Yan; Yang, Chunhui; Jin, Yinji; Yang, Weiwei; He, Yan; Wu, Yiqi; Zhang, Yuhua; Wang, Guangyu; RajkumarEzakiel Redpath, Riju James; Zhang, Lei; Jin, Xiaoming; Liu, Ying; Sun, Yuchun; Ning, Ning; Qiao, Yu; Zhang, Fengmin; Li, Zhiwei; Wang, Tianzhen; Zhang, Yanqiao; Li, Xiaobo

    2017-04-04

    Numerous evidences indicate that aspirin usage causes a significant reduction in colorectal cancer. However, the molecular mechanisms about aspirin preventing colon cancer are largely unknown. Quantitative reverse transcription polymerase chain reaction (qRT-PCR) is a most frequently used method to identify the target molecules regulated by certain compound. However, this method needs stable internal reference genes to analyze the expression change of the targets. In this study, the transcriptional stabilities of several traditional reference genes were evaluated in colon cancer cells treated with aspirin, and also, the suitable internal reference genes were screened by using a microarray and were further identified by using the geNorm and NormFinder softwares, and then were validated in more cell lines and xenografts. We have showed that three traditional internal reference genes, β-actin, GAPDH and α-tubulin, are not suitable for studying gene transcription in colon cancer cells treated with aspirin, and we have identified and validated TMEM208 and PQLC2 as the ideal internal reference genes for detecting the molecular targets of aspirin in colon cancer in vitro and in vivo. This study reveals stable internal reference genes for studying the target genes of aspirin in colon cancer, which will contribute to identify the molecular mechanism behind aspirin preventing colon cancer.

  15. Identification of copy number variation-driven genes for liver cancer via bioinformatics analysis.

    PubMed

    Lu, Xiaojie; Ye, Kun; Zou, Kailin; Chen, Jinlian

    2014-11-01

    To screen out copy number variation (CNV)-driven differentially expressed genes (DEGs) in liver cancer and advance our understanding of the pathogenesis, an integrated analysis of liver cancer-related CNV data from The Cancer Genome Atlas (TCGA) and gene expression data from EBI Array Express database were performed. The DEGs were identified by package limma based on the cut-off of |log2 (fold-change)|>0.585 and adjusted p-value<0.05. Using hg19 annotation information provided by UCSC, liver cancer-related CNVs were then screened out. TF-target gene interactions were also predicted with information from UCSC using DAVID online tools. As a result, 25 CNV-driven genes were obtained, including tripartite motif containing 28 (TRIM28) and RanBP-type and C3HC4-type zinc finger containing 1 (RBCK1). In the transcriptional regulatory network, 8 known cancer-related transcription factors (TFs) interacted with 21 CNV-driven genes, suggesting that the other 8 TFs may be involved in liver cancer. These genes may be potential biomarkers for early detection and prevention of liver cancer. These findings may improve our knowledge of the pathogenesis of liver cancer. Nevertheless, further experiments are still needed to confirm our findings.

  16. Dietary Nutrient Intake, Ethnicity, and Epigenetic Silencing of Lung Cancer Genes Detected in Sputum in New Mexican Smokers.

    PubMed

    Leng, Shuguang; Picchi, Maria A; Kang, Huining; Wu, Guodong; Filipczak, Piotr T; Juri, Daniel E; Zhang, Xiequn; Gauderman, W James; Gilliland, Frank D; Belinsky, Steven A

    2018-02-01

    Lung cancer gene methylation detected in sputum assesses field cancerization and predicts lung cancer incidence. Hispanic smokers have higher lung cancer susceptibility compared with non-Hispanic whites (NHW). We aimed to identify novel dietary nutrients affecting lung cancer gene methylation and determine the degree of ethnic disparity in methylation explained by diet. Dietary intakes of 139 nutrients were assessed using a validated Harvard food frequency questionnaire in 327 Hispanics and 1,502 NHWs from the Lovelace Smokers Cohort. Promoter methylation of 12 lung cancer genes was assessed in sputum DNA. A global association was identified between dietary intake and gene methylation ( P permutation = 0.003). Seventeen nutrient measurements were identified with magnitude of association with methylation greater than that seen for folate. A stepwise approach identified B12, manganese, sodium, and saturated fat as the minimally correlated set of nutrients whose optimal intakes could reduce the methylation by 36% ( P permutation < 0.001). Six protective nutrients included vitamin D, B12, manganese, magnesium, niacin, and folate. Approximately 42% of ethnic disparity in methylation was explained by insufficient intake of protective nutrients in Hispanics compared with NHWs. Functional validation of protective nutrients showed an enhanced DNA repair capacity toward double-strand DNA breaks, a mechanistic biomarker strongly linked to acquisition of lung cancer gene methylation in smokers. Dietary intake is a major modifiable factor for preventing promoter methylation of lung cancer genes in smokers' lungs. Complex dietary supplements could be developed on the basis of these protective nutrients for lung cancer chemoprevention in smokers. Hispanic smokers may benefit the most from this complex for reducing their lung cancer susceptibility. Cancer Prev Res; 11(2); 93-102. ©2017 AACR . ©2017 American Association for Cancer Research.

  17. MicroRNA genes are frequently located near mouse cancer susceptibility loci

    PubMed Central

    Sevignani, Cinzia; Calin, George A.; Nnadi, Stephanie C.; Shimizu, Masayoshi; Davuluri, Ramana V.; Hyslop, Terry; Demant, Peter; Croce, Carlo M.; Siracusa, Linda D.

    2007-01-01

    MicroRNAs (miRNAs) are short 19- to 24-nt RNA molecules that have been shown to regulate the expression of other genes in a variety of eukaryotic systems. Abnormal expression of miRNAs has been observed in several human cancers, and furthermore, germ-line and somatic mutations in human miRNAs were recently identified in patients with chronic lymphocytic leukemia. Thus, human miRNAs can act as tumor suppressor genes or oncogenes, where mutations, deletions, or amplifications can underlie the development of certain types of leukemia. In addition, previous studies have shown that miRNA expression profiles can distinguish among human solid tumors from different organs. Because a single miRNA can simultaneously influence the expression of two or more protein-coding genes, we hypothesized that miRNAs could be candidate genes for cancer risk. Research in complex trait genetics has demonstrated that genetic background determines cancer susceptibility or resistance in various tissues, such as colon and lung, of different inbred mouse strains. We compared the genome positions of mouse tumor susceptibility loci with those of mouse miRNAs. Here, we report a statistically significant association between the chromosomal location of miRNAs and those of mouse cancer susceptibility loci that influence the development of solid tumors. Furthermore, we identified distinct patterns of flanking DNA sequences for several miRNAs located at or near susceptibility loci in inbred strains with different tumor susceptibilities. These data provide a catalog of miRNA genes in inbred strains that could represent genes involved in the development and penetrance of solid tumors. PMID:17470785

  18. Integrated Analysis of Mutation Data from Various Sources Identifies Key Genes and Signaling Pathways in Hepatocellular Carcinoma

    PubMed Central

    Wei, Lin; Tang, Ruqi; Lian, Baofeng; Zhao, Yingjun; He, Xianghuo; Xie, Lu

    2014-01-01

    Background Recently, a number of studies have performed genome or exome sequencing of hepatocellular carcinoma (HCC) and identified hundreds or even thousands of mutations in protein-coding genes. However, these studies have only focused on a limited number of candidate genes, and many important mutation resources remain to be explored. Principal Findings In this study, we integrated mutation data obtained from various sources and performed pathway and network analysis. We identified 113 pathways that were significantly mutated in HCC samples and found that the mutated genes included in these pathways contained high percentages of known cancer genes, and damaging genes and also demonstrated high conservation scores, indicating their important roles in liver tumorigenesis. Five classes of pathways that were mutated most frequently included (a) proliferation and apoptosis related pathways, (b) tumor microenvironment related pathways, (c) neural signaling related pathways, (d) metabolic related pathways, and (e) circadian related pathways. Network analysis further revealed that the mutated genes with the highest betweenness coefficients, such as the well-known cancer genes TP53, CTNNB1 and recently identified novel mutated genes GNAL and the ADCY family, may play key roles in these significantly mutated pathways. Finally, we highlight several key genes (e.g., RPS6KA3 and PCLO) and pathways (e.g., axon guidance) in which the mutations were associated with clinical features. Conclusions Our workflow illustrates the increased statistical power of integrating multiple studies of the same subject, which can provide biological insights that would otherwise be masked under individual sample sets. This type of bioinformatics approach is consistent with the necessity of making the best use of the ever increasing data provided in valuable databases, such as TCGA, to enhance the speed of deciphering human cancers. PMID:24988079

  19. Integrated analysis of mutation data from various sources identifies key genes and signaling pathways in hepatocellular carcinoma.

    PubMed

    Zhang, Yuannv; Qiu, Zhaoping; Wei, Lin; Tang, Ruqi; Lian, Baofeng; Zhao, Yingjun; He, Xianghuo; Xie, Lu

    2014-01-01

    Recently, a number of studies have performed genome or exome sequencing of hepatocellular carcinoma (HCC) and identified hundreds or even thousands of mutations in protein-coding genes. However, these studies have only focused on a limited number of candidate genes, and many important mutation resources remain to be explored. In this study, we integrated mutation data obtained from various sources and performed pathway and network analysis. We identified 113 pathways that were significantly mutated in HCC samples and found that the mutated genes included in these pathways contained high percentages of known cancer genes, and damaging genes and also demonstrated high conservation scores, indicating their important roles in liver tumorigenesis. Five classes of pathways that were mutated most frequently included (a) proliferation and apoptosis related pathways, (b) tumor microenvironment related pathways, (c) neural signaling related pathways, (d) metabolic related pathways, and (e) circadian related pathways. Network analysis further revealed that the mutated genes with the highest betweenness coefficients, such as the well-known cancer genes TP53, CTNNB1 and recently identified novel mutated genes GNAL and the ADCY family, may play key roles in these significantly mutated pathways. Finally, we highlight several key genes (e.g., RPS6KA3 and PCLO) and pathways (e.g., axon guidance) in which the mutations were associated with clinical features. Our workflow illustrates the increased statistical power of integrating multiple studies of the same subject, which can provide biological insights that would otherwise be masked under individual sample sets. This type of bioinformatics approach is consistent with the necessity of making the best use of the ever increasing data provided in valuable databases, such as TCGA, to enhance the speed of deciphering human cancers.

  20. Integrated Bioinformatics, Environmental Epidemiologic and Genomic Approaches to Identify Environmental and Molecular Links between Endometriosis and Breast Cancer

    PubMed Central

    Roy, Deodutta; Morgan, Marisa; Yoo, Changwon; Deoraj, Alok; Roy, Sandhya; Yadav, Vijay Kumar; Garoub, Mohannad; Assaggaf, Hamza; Doke, Mayur

    2015-01-01

    We present a combined environmental epidemiologic, genomic, and bioinformatics approach to identify: exposure of environmental chemicals with estrogenic activity; epidemiologic association between endocrine disrupting chemical (EDC) and health effects, such as, breast cancer or endometriosis; and gene-EDC interactions and disease associations. Human exposure measurement and modeling confirmed estrogenic activity of three selected class of environmental chemicals, polychlorinated biphenyls (PCBs), bisphenols (BPs), and phthalates. Meta-analysis showed that PCBs exposure, not Bisphenol A (BPA) and phthalates, increased the summary odds ratio for breast cancer and endometriosis. Bioinformatics analysis of gene-EDC interactions and disease associations identified several hundred genes that were altered by exposure to PCBs, phthalate or BPA. EDCs-modified genes in breast neoplasms and endometriosis are part of steroid hormone signaling and inflammation pathways. All three EDCs–PCB 153, phthalates, and BPA influenced five common genes—CYP19A1, EGFR, ESR2, FOS, and IGF1—in breast cancer as well as in endometriosis. These genes are environmentally and estrogen responsive, altered in human breast and uterine tumors and endometriosis lesions, and part of Mitogen Activated Protein Kinase (MAPK) signaling pathways in cancer. Our findings suggest that breast cancer and endometriosis share some common environmental and molecular risk factors. PMID:26512648

  1. Gene panel testing for inherited cancer risk.

    PubMed

    Hall, Michael J; Forman, Andrea D; Pilarski, Robert; Wiesner, Georgia; Giri, Veda N

    2014-09-01

    Next-generation sequencing technologies have ushered in the capability to assess multiple genes in parallel for genetic alterations that may contribute to inherited risk for cancers in families. Thus, gene panel testing is now an option in the setting of genetic counseling and testing for cancer risk. This article describes the many gene panel testing options clinically available to assess inherited cancer susceptibility, the potential advantages and challenges associated with various types of panels, clinical scenarios in which gene panels may be particularly useful in cancer risk assessment, and testing and counseling considerations. Given the potential issues for patients and their families, gene panel testing for inherited cancer risk is recommended to be offered in conjunction or consultation with an experienced cancer genetic specialist, such as a certified genetic counselor or geneticist, as an integral part of the testing process. Copyright © 2014 by the National Comprehensive Cancer Network.

  2. Inflammatory Gene Polymorphisms in Lung Cancer Susceptibility.

    PubMed

    Eaton, Keith D; Romine, Perrin E; Goodman, Gary E; Thornquist, Mark D; Barnett, Matt J; Petersdorf, Effie W

    2018-05-01

    Chronic inflammation has been implicated in carcinogenesis, with increasing evidence of its role in lung cancer. We aimed to evaluate the role of genetic polymorphisms in inflammation-related genes in the risk for development of lung cancer. A nested case-control study design was used, and 625 cases and 625 well-matched controls were selected from participants in the β-Carotene and Retinol Efficacy Trial, which is a large, prospective lung cancer chemoprevention trial. The association between lung cancer incidence and survival and 23 polymorphisms descriptive of 11 inflammation-related genes (interferon gamma gene [IFNG], interleukin 10 gene [IL10], interleukin 1 alpha gene [IL1A], interleukin 1 beta gene [IL1B], interleukin 2 gene [IL2], interleukin 4 receptor gene [IL4R], interleukin 4 gene [IL4], interleukin 6 gene [IL6], prostaglandin-endoperoxide synthase 2 gene [PTGS2] (also known as COX2), transforming growth factor beta 1 gene [TGFB1], and tumor necrosis factor alpha gene [TNFA]) was evaluated. Of the 23 polymorphisms, two were associated with risk for lung cancer. Compared with individuals with the wild-type (CC) variant, individuals carrying the minor allele variants of the IL-1β-511C>T promoter polymorphism (rs16944) (CT and TT) had decreased odds of lung cancer (OR = 0.74, [95% confidence interval (CI): 0.58-0.94] and OR = 0.71 [95% CI: 0.50-1.01], respectively, p = 0.03). Similar results were observed for the IL-1β-1464 C>G promoter polymorphism (rs1143623), with presence of the minor variants CG and CC having decreased odds of lung cancer (OR = 0.75 [95% CI: 0.59-0.95] and OR = 0.69 [95% CI: 0.46-1.03], respectively, p = 0.03). Survival was not influenced by genotype. This study provides further evidence that IL1B promoter polymorphisms may modulate the risk for development of lung cancer. Copyright © 2018 International Association for the Study of Lung Cancer. Published by Elsevier Inc. All rights reserved.

  3. Large-scale genotyping identifies 41 new loci associated with breast cancer risk.

    PubMed

    Michailidou, Kyriaki; Hall, Per; Gonzalez-Neira, Anna; Ghoussaini, Maya; Dennis, Joe; Milne, Roger L; Schmidt, Marjanka K; Chang-Claude, Jenny; Bojesen, Stig E; Bolla, Manjeet K; Wang, Qin; Dicks, Ed; Lee, Andrew; Turnbull, Clare; Rahman, Nazneen; Fletcher, Olivia; Peto, Julian; Gibson, Lorna; Dos Santos Silva, Isabel; Nevanlinna, Heli; Muranen, Taru A; Aittomäki, Kristiina; Blomqvist, Carl; Czene, Kamila; Irwanto, Astrid; Liu, Jianjun; Waisfisz, Quinten; Meijers-Heijboer, Hanne; Adank, Muriel; van der Luijt, Rob B; Hein, Rebecca; Dahmen, Norbert; Beckman, Lars; Meindl, Alfons; Schmutzler, Rita K; Müller-Myhsok, Bertram; Lichtner, Peter; Hopper, John L; Southey, Melissa C; Makalic, Enes; Schmidt, Daniel F; Uitterlinden, Andre G; Hofman, Albert; Hunter, David J; Chanock, Stephen J; Vincent, Daniel; Bacot, François; Tessier, Daniel C; Canisius, Sander; Wessels, Lodewyk F A; Haiman, Christopher A; Shah, Mitul; Luben, Robert; Brown, Judith; Luccarini, Craig; Schoof, Nils; Humphreys, Keith; Li, Jingmei; Nordestgaard, Børge G; Nielsen, Sune F; Flyger, Henrik; Couch, Fergus J; Wang, Xianshu; Vachon, Celine; Stevens, Kristen N; Lambrechts, Diether; Moisse, Matthieu; Paridaens, Robert; Christiaens, Marie-Rose; Rudolph, Anja; Nickels, Stefan; Flesch-Janys, Dieter; Johnson, Nichola; Aitken, Zoe; Aaltonen, Kirsimari; Heikkinen, Tuomas; Broeks, Annegien; Veer, Laura J Van't; van der Schoot, C Ellen; Guénel, Pascal; Truong, Thérèse; Laurent-Puig, Pierre; Menegaux, Florence; Marme, Frederik; Schneeweiss, Andreas; Sohn, Christof; Burwinkel, Barbara; Zamora, M Pilar; Perez, Jose Ignacio Arias; Pita, Guillermo; Alonso, M Rosario; Cox, Angela; Brock, Ian W; Cross, Simon S; Reed, Malcolm W R; Sawyer, Elinor J; Tomlinson, Ian; Kerin, Michael J; Miller, Nicola; Henderson, Brian E; Schumacher, Fredrick; Le Marchand, Loic; Andrulis, Irene L; Knight, Julia A; Glendon, Gord; Mulligan, Anna Marie; Lindblom, Annika; Margolin, Sara; Hooning, Maartje J; Hollestelle, Antoinette; van den Ouweland, Ans M W; Jager, Agnes; Bui, Quang M; Stone, Jennifer; Dite, Gillian S; Apicella, Carmel; Tsimiklis, Helen; Giles, Graham G; Severi, Gianluca; Baglietto, Laura; Fasching, Peter A; Haeberle, Lothar; Ekici, Arif B; Beckmann, Matthias W; Brenner, Hermann; Müller, Heiko; Arndt, Volker; Stegmaier, Christa; Swerdlow, Anthony; Ashworth, Alan; Orr, Nick; Jones, Michael; Figueroa, Jonine; Lissowska, Jolanta; Brinton, Louise; Goldberg, Mark S; Labrèche, France; Dumont, Martine; Winqvist, Robert; Pylkäs, Katri; Jukkola-Vuorinen, Arja; Grip, Mervi; Brauch, Hiltrud; Hamann, Ute; Brüning, Thomas; Radice, Paolo; Peterlongo, Paolo; Manoukian, Siranoush; Bonanni, Bernardo; Devilee, Peter; Tollenaar, Rob A E M; Seynaeve, Caroline; van Asperen, Christi J; Jakubowska, Anna; Lubinski, Jan; Jaworska, Katarzyna; Durda, Katarzyna; Mannermaa, Arto; Kataja, Vesa; Kosma, Veli-Matti; Hartikainen, Jaana M; Bogdanova, Natalia V; Antonenkova, Natalia N; Dörk, Thilo; Kristensen, Vessela N; Anton-Culver, Hoda; Slager, Susan; Toland, Amanda E; Edge, Stephen; Fostira, Florentia; Kang, Daehee; Yoo, Keun-Young; Noh, Dong-Young; Matsuo, Keitaro; Ito, Hidemi; Iwata, Hiroji; Sueta, Aiko; Wu, Anna H; Tseng, Chiu-Chen; Van Den Berg, David; Stram, Daniel O; Shu, Xiao-Ou; Lu, Wei; Gao, Yu-Tang; Cai, Hui; Teo, Soo Hwang; Yip, Cheng Har; Phuah, Sze Yee; Cornes, Belinda K; Hartman, Mikael; Miao, Hui; Lim, Wei Yen; Sng, Jen-Hwei; Muir, Kenneth; Lophatananon, Artitaya; Stewart-Brown, Sarah; Siriwanarangsan, Pornthep; Shen, Chen-Yang; Hsiung, Chia-Ni; Wu, Pei-Ei; Ding, Shian-Ling; Sangrajrang, Suleeporn; Gaborieau, Valerie; Brennan, Paul; McKay, James; Blot, William J; Signorello, Lisa B; Cai, Qiuyin; Zheng, Wei; Deming-Halverson, Sandra; Shrubsole, Martha; Long, Jirong; Simard, Jacques; Garcia-Closas, Montse; Pharoah, Paul D P; Chenevix-Trench, Georgia; Dunning, Alison M; Benitez, Javier; Easton, Douglas F

    2013-04-01

    Breast cancer is the most common cancer among women. Common variants at 27 loci have been identified as associated with susceptibility to breast cancer, and these account for ∼9% of the familial risk of the disease. We report here a meta-analysis of 9 genome-wide association studies, including 10,052 breast cancer cases and 12,575 controls of European ancestry, from which we selected 29,807 SNPs for further genotyping. These SNPs were genotyped in 45,290 cases and 41,880 controls of European ancestry from 41 studies in the Breast Cancer Association Consortium (BCAC). The SNPs were genotyped as part of a collaborative genotyping experiment involving four consortia (Collaborative Oncological Gene-environment Study, COGS) and used a custom Illumina iSelect genotyping array, iCOGS, comprising more than 200,000 SNPs. We identified SNPs at 41 new breast cancer susceptibility loci at genome-wide significance (P < 5 × 10(-8)). Further analyses suggest that more than 1,000 additional loci are involved in breast cancer susceptibility.

  4. Large-scale genotyping identifies 41 new loci associated with breast cancer risk

    PubMed Central

    Michailidou, Kyriaki; Hall, Per; Gonzalez-Neira, Anna; Ghoussaini, Maya; Dennis, Joe; Milne, Roger L; Schmidt, Marjanka K; Chang-Claude, Jenny; Bojesen, Stig E; Bolla, Manjeet K; Wang, Qin; Dicks, Ed; Lee, Andrew; Turnbull, Clare; Rahman, Nazneen; Fletcher, Olivia; Peto, Julian; Gibson, Lorna; Silva, Isabel dos Santos; Nevanlinna, Heli; Muranen, Taru A; Aittomäki, Kristiina; Blomqvist, Carl; Czene, Kamila; Irwanto, Astrid; Liu, Jianjun; Waisfisz, Quinten; Meijers-Heijboer, Hanne; Adank, Muriel; van der Luijt, Rob B; Hein, Rebecca; Dahmen, Norbert; Beckman, Lars; Meindl, Alfons; Schmutzler, Rita K; Müller-Myhsok, Bertram; Lichtner, Peter; Hopper, John L; Southey, Melissa C; Makalic, Enes; Schmidt, Daniel F; Uitterlinden, Andre G; Hofman, Albert; Hunter, David J; Chanock, Stephen J; Vincent, Daniel; Bacot, François; Tessier, Daniel C; Canisius, Sander; Wessels, Lodewyk F A; Haiman, Christopher A; Shah, Mitul; Luben, Robert; Brown, Judith; Luccarini, Craig; Schoof, Nils; Humphreys, Keith; Li, Jingmei; Nordestgaard, Børge G; Nielsen, Sune F; Flyger, Henrik; Couch, Fergus J; Wang, Xianshu; Vachon, Celine; Stevens, Kristen N; Lambrechts, Diether; Moisse, Matthieu; Paridaens, Robert; Christiaens, Marie-Rose; Rudolph, Anja; Nickels, Stefan; Flesch-Janys, Dieter; Johnson, Nichola; Aitken, Zoe; Aaltonen, Kirsimari; Heikkinen, Tuomas; Broeks, Annegien; Van’t Veer, Laura J; van der Schoot, C Ellen; Guénel, Pascal; Truong, Thérèse; Laurent-Puig, Pierre; Menegaux, Florence; Marme, Frederik; Schneeweiss, Andreas; Sohn, Christof; Burwinkel, Barbara; Zamora, M Pilar; Perez, Jose Ignacio Arias; Pita, Guillermo; Alonso, M Rosario; Cox, Angela; Brock, Ian W; Cross, Simon S; Reed, Malcolm W R; Sawyer, Elinor J; Tomlinson, Ian; Kerin, Michael J; Miller, Nicola; Henderson, Brian E; Schumacher, Fredrick; Le Marchand, Loic; Andrulis, Irene L; Knight, Julia A; Glendon, Gord; Mulligan, Anna Marie; Lindblom, Annika; Margolin, Sara; Hooning, Maartje J; Hollestelle, Antoinette; van den Ouweland, Ans M W; Jager, Agnes; Bui, Quang M; Stone, Jennifer; Dite, Gillian S; Apicella, Carmel; Tsimiklis, Helen; Giles, Graham G; Severi, Gianluca; Baglietto, Laura; Fasching, Peter A; Haeberle, Lothar; Ekici, Arif B; Beckmann, Matthias W; Brenner, Hermann; Müller, Heiko; Arndt, Volker; Stegmaier, Christa; Swerdlow, Anthony; Ashworth, Alan; Orr, Nick; Jones, Michael; Figueroa, Jonine; Lissowska, Jolanta; Brinton, Louise; Goldberg, Mark S; Labrèche, France; Dumont, Martine; Winqvist, Robert; Pylkäs, Katri; Jukkola-Vuorinen, Arja; Grip, Mervi; Brauch, Hiltrud; Hamann, Ute; Brüning, Thomas; Radice, Paolo; Peterlongo, Paolo; Manoukian, Siranoush; Bonanni, Bernardo; Devilee, Peter; Tollenaar, Rob A E M; Seynaeve, Caroline; van Asperen, Christi J; Jakubowska, Anna; Lubinski, Jan; Jaworska, Katarzyna; Durda, Katarzyna; Mannermaa, Arto; Kataja, Vesa; Kosma, Veli-Matti; Hartikainen, Jaana M; Bogdanova, Natalia V; Antonenkova, Natalia N; Dörk, Thilo; Kristensen, Vessela N; Anton-Culver, Hoda; Slager, Susan; Toland, Amanda E; Edge, Stephen; Fostira, Florentia; Kang, Daehee; Yoo, Keun-Young; Noh, Dong-Young; Matsuo, Keitaro; Ito, Hidemi; Iwata, Hiroji; Sueta, Aiko; Wu, Anna H; Tseng, Chiu-Chen; Van Den Berg, David; Stram, Daniel O; Shu, Xiao-Ou; Lu, Wei; Gao, Yu-Tang; Cai, Hui; Teo, Soo Hwang; Yip, Cheng Har; Phuah, Sze Yee; Cornes, Belinda K; Hartman, Mikael; Miao, Hui; Lim, Wei Yen; Sng, Jen-Hwei; Muir, Kenneth; Lophatananon, Artitaya; Stewart-Brown, Sarah; Siriwanarangsan, Pornthep; Shen, Chen-Yang; Hsiung, Chia-Ni; Wu, Pei-Ei; Ding, Shian-Ling; Sangrajrang, Suleeporn; Gaborieau, Valerie; Brennan, Paul; McKay, James; Blot, William J; Signorello, Lisa B; Cai, Qiuyin; Zheng, Wei; Deming-Halverson, Sandra; Shrubsole, Martha; Long, Jirong; Simard, Jacques; Garcia-Closas, Montse; Pharoah, Paul D P; Chenevix-Trench, Georgia; Dunning, Alison M; Benitez, Javier; Easton, Douglas F

    2013-01-01

    Breast cancer is the most common cancer among women. Common variants at 27 loci have been identified as associated with susceptibility to breast cancer, and these account for ~9% of the familial risk of the disease. We report here a meta-analysis of 9 genome-wide association studies, including 10,052 breast cancer cases and 12,575 controls of European ancestry, from which we selected 29,807 SNPs for further genotyping. These SNPs were genotyped in 45,290 cases and 41,880 controls of European ancestry from 41 studies in the Breast Cancer Association Consortium (BCAC). The SNPs were genotyped as part of a collaborative genotyping experiment involving four consortia (Collaborative Oncological Gene-environment Study, COGS) and used a custom Illumina iSelect genotyping array, iCOGS, comprising more than 200,000 SNPs. We identified SNPs at 41 new breast cancer susceptibility loci at genome-wide significance (P < 5 × 10−8). Further analyses suggest that more than 1,000 additional loci are involved in breast cancer susceptibility. PMID:23535729

  5. Tumour testing to identify Lynch syndrome in two Australian colorectal cancer cohorts

    PubMed Central

    Eriksen, Stine V.; Walsh, Michael D.; Walters, Rhiannon J.; Thibodeau, Stephen N.; Stewart, Jenna; Preston, Susan; Win, Aung Ko; Flander, Louisa; Ouakrim, Driss Ait; Macrae, Finlay A.; Boussioutas, Alex; Winship, Ingrid M.; Giles, Graham G.; Hopper, John L.; Southey, Melissa C.

    2016-01-01

    Background and Aim Tumour testing of colorectal cancers (CRC) for mismatch repair (MMR) deficiency is an effective approach to identify carriers of germline MMR gene mutation (Lynch syndrome). The aim of this study was to identify MMR gene mutation carriers in two cohorts of population-based CRC utilising a combination of tumour and germline testing approaches. Methods CRCs from 813 patients diagnosed with CRC <60 years of age from the Australasian Colorectal Cancer Family Registry (ACCFR) and from 826 patients from the Melbourne Collaborative Cohort Study (MCCS) were tested for MMR protein expression using immunohistochemistry (IHC), microsatellite instability (MSI), BRAFV600E somatic mutation and for MLH1 methylation. MMR gene mutation testing (Sanger sequencing and MLPA) was performed on germline DNA of patients with MMR-deficient tumours and a subset of MMR-proficient CRCs. Results Of the 813 ACCFR probands, 90 probands demonstrated tumour MMR-deficiency (11.1%) and 42 had a MMR gene germline mutation (5.2%). For the MCCS, MMR-deficiency was identified in the tumours of 103 probands (12.5%) and 7 had a germline mutation (0.8%). All the mutation carriers were diagnosed prior to 70 years of age. Probands with a MMR-deficient CRC without MLH1 methylation and a gene mutation were considered Lynch-like and comprised 41.1% and 22.3% of the MMR-deficient CRCs for the ACCFR and MCCS, respectively. Conclusions Identification of MMR gene mutation carriers in Australian CRC-affected patients is optimised by IHC screening of CRC diagnosed before 70 years. A significant proportion of MMR-deficient CRCs will have unknown aetiology (Lynch-like) proving problematic for clinical management. PMID:27273229

  6. Identification of Linkages between EDCs in Personal Care Products and Breast Cancer through Data Integration Combined with Gene Network Analysis.

    PubMed

    Jeong, Hyeri; Kim, Jongwoon; Kim, Youngjun

    2017-09-30

    Approximately 1000 chemicals have been reported to possibly have endocrine disrupting effects, some of which are used in consumer products, such as personal care products (PCPs) and cosmetics. We conducted data integration combined with gene network analysis to: (i) identify causal molecular mechanisms between endocrine disrupting chemicals (EDCs) used in PCPs and breast cancer; and (ii) screen candidate EDCs associated with breast cancer. Among EDCs used in PCPs, four EDCs having correlation with breast cancer were selected, and we curated 27 common interacting genes between those EDCs and breast cancer to perform the gene network analysis. Based on the gene network analysis, ESR1, TP53, NCOA1, AKT1, and BCL6 were found to be key genes to demonstrate the molecular mechanisms of EDCs in the development of breast cancer. Using GeneMANIA, we additionally predicted 20 genes which could interact with the 27 common genes. In total, 47 genes combining the common and predicted genes were functionally grouped with the gene ontology and KEGG pathway terms. With those genes, we finally screened candidate EDCs for their potential to increase breast cancer risk. This study highlights that our approach can provide insights to understand mechanisms of breast cancer and identify potential EDCs which are in association with breast cancer.

  7. Identification of Linkages between EDCs in Personal Care Products and Breast Cancer through Data Integration Combined with Gene Network Analysis

    PubMed Central

    Kim, Jongwoon

    2017-01-01

    Approximately 1000 chemicals have been reported to possibly have endocrine disrupting effects, some of which are used in consumer products, such as personal care products (PCPs) and cosmetics. We conducted data integration combined with gene network analysis to: (i) identify causal molecular mechanisms between endocrine disrupting chemicals (EDCs) used in PCPs and breast cancer; and (ii) screen candidate EDCs associated with breast cancer. Among EDCs used in PCPs, four EDCs having correlation with breast cancer were selected, and we curated 27 common interacting genes between those EDCs and breast cancer to perform the gene network analysis. Based on the gene network analysis, ESR1, TP53, NCOA1, AKT1, and BCL6 were found to be key genes to demonstrate the molecular mechanisms of EDCs in the development of breast cancer. Using GeneMANIA, we additionally predicted 20 genes which could interact with the 27 common genes. In total, 47 genes combining the common and predicted genes were functionally grouped with the gene ontology and KEGG pathway terms. With those genes, we finally screened candidate EDCs for their potential to increase breast cancer risk. This study highlights that our approach can provide insights to understand mechanisms of breast cancer and identify potential EDCs which are in association with breast cancer. PMID:28973975

  8. cDNA Microarray Gene Expression Profiling of Hedgehog Signaling Pathway Inhibition in Human Colon Cancer Cells

    PubMed Central

    Shi, Ting; Mazumdar, Tapati; DeVecchio, Jennifer; Duan, Zhong-Hui; Agyeman, Akwasi; Aziz, Mohammad; Houghton, Janet A.

    2010-01-01

    Background Hedgehog (HH) signaling plays a critical role in normal cellular processes, in normal mammalian gastrointestinal development and differentiation, and in oncogenesis and maintenance of the malignant phenotype in a variety of human cancers. Increasing evidence further implicates the involvement of HH signaling in oncogenesis and metastatic behavior of colon cancers. However, genomic approaches to elucidate the role of HH signaling in cancers in general are lacking, and data derived on HH signaling in colon cancer is extremely limited. Methodology/Principal Findings To identify unique downstream targets of the GLI genes, the transcriptional regulators of HH signaling, in the context of colon carcinoma, we employed a small molecule inhibitor of both GLI1 and GLI2, GANT61, in two human colon cancer cell lines, HT29 and GC3/c1. Cell cycle analysis demonstrated accumulation of GANT61-treated cells at the G1/S boundary. cDNA microarray gene expression profiling of 18,401 genes identified Differentially Expressed Genes (DEGs) both common and unique to HT29 and GC3/c1. Analyses using GenomeStudio (statistics), Matlab (heat map), Ingenuity (canonical pathway analysis), or by qRT-PCR, identified p21Cip1 (CDKN1A) and p15Ink4b (CDKN2B), which play a role in the G1/S checkpoint, as up-regulated genes at the G1/S boundary. Genes that determine further cell cycle progression at G1/S including E2F2, CYCLIN E2 (CCNE2), CDC25A and CDK2, and genes that regulate passage of cells through G2/M (CYCLIN A2 [CCNA2], CDC25C, CYCLIN B2 [CCNB2], CDC20 and CDC2 [CDK1], were down-regulated. In addition, novel genes involved in stress response, DNA damage response, DNA replication and DNA repair were identified following inhibition of HH signaling. Conclusions/Significance This study identifies genes that are involved in HH-dependent cellular proliferation in colon cancer cells, and following its inhibition, genes that regulate cell cycle progression and events downstream of the G1/S

  9. Integration of High-Risk Human Papillomavirus into Cellular Cancer-Related Genes in Head and Neck Cancer Cell Lines

    PubMed Central

    Walline, Heather M; Komarck, Christine M; McHugh, Jonathan B; Tang, Alice L; Owen, John H; Teh, Bin T; McKean, Erin; Glover, Thomas; Graham, Martin P; Prince, Mark E; Chepeha, Douglas B; Chinn, Steven B; Ferris, Robert L; Gollin, Susanne M; Hoffmann, Thomas K; Bier, Henning; Brakenhoff, Ruud; Bradford, Carol R; Carey, Thomas E

    2017-01-01

    Background HPV-positive oropharyngeal cancer is generally associated with excellent response to therapy, but some HPV-positive tumors progress despite aggressive therapy. This study evaluates viral oncogene expression and viral integration sites in HPV16 and HPV18-positive squamous carcinoma cell lines. Methods E6-E7 alternate transcripts were assessed by RT-PCR. Detection of integrated papillomavirus sequences (DIPS-PCR) and sequencing identified viral insertion sites and affected host genes. Cellular gene expression was assessed across viral integration sites. Results All HPV-positive cell lines expressed alternate HPVE6/E7 splicing indicative of active viral oncogenesis. HPV integration occurred within cancer-related genes TP63, DCC, JAK1, TERT, ATR, ETV6, PGR, PTPRN2, and TMEM237 in 8 HNSCC lines but UM-SCC-105 and UM-GCC-1 had only intergenic integration. Conclusions HPV integration into cancer-related genes occurred in 7/9 HPV-positive cell lines and of these six were from tumors that progressed. HPV integration into cancer-related genes may be a secondary carcinogenic driver in HPV-driven tumors. PMID:28236344

  10. Nicotine and oxidative stress induced exomic variations are concordant and overrepresented in cancer-associated genes

    PubMed Central

    Bavarva, Jasmin H.; Tae, Hongseok; McIver, Lauren; Garner, Harold R.

    2014-01-01

    Although the connection between cancer and cigarette smoke is well established, nicotine is not characterized as a carcinogen. Here, we used exome sequencing to identify nicotine and oxidative stress-induced somatic mutations in normal human epithelial cells and its correlation with cancer. We identified over 6,400 SNVs, indels and microsatellites in each of the stress exposed cells relative to the control, of which, 2,159 were consistently observed at all nicotine doses. These included 429 nsSNVs including 158 novel and 79 cancer-associated. Over 80% of consistently nicotine induced variants overlap with variations detected in oxidative stressed cells, indicating that nicotine induced genomic alterations could be mediated through oxidative stress. Nicotine induced mutations were distributed across 1,585 genes, of which 49% were associated with cancer. MUC family genes were among the top mutated genes. Analysis of 591 lung carcinoma tumor exomes from The Cancer Genome Atlas (TCGA) revealed that 20% of non-small-cell lung cancer tumors in smokers have mutations in at least one of the MUC4, MUC6 or MUC12 genes in contrast to only 6% in non-smokers. These results indicate that nicotine induces genomic variations, promotes instability potentially mediated by oxidative stress, implicating nicotine in carcinogenesis, and establishes MUC genes as potential targets. PMID:24947164

  11. Identification of genes containing expanded purine repeats in the human genome and their apparent protective role against cancer.

    PubMed

    Singh, Himanshu Narayan; Rajeswari, Moganty R

    2016-01-01

    Purine repeat sequences present in a gene are unique as they have high propensity to form unusual DNA-triple helix structures. Friedreich's ataxia is the only human disease that is well known to be associated with DNA-triplexes formed by purine repeats. The purpose of this study was to recognize the expanded purine repeats (EPRs) in human genome and find their correlation with cancer pathogenesis. We developed "PuRepeatFinder.pl" algorithm to identify non-overlapping EPRs without pyrimidine interruptions in the human genome and customized for searching repeat lengths, n ≥ 200. A total of 1158 EPRs were identified in the genome which followed Wakeby distribution. Two hundred and ninety-six EPRs were found in geneic regions of 282 genes (EPR-genes). Gene clustering of EPR-genes was done based on their cellular function and a large number of EPR-genes were found to be enzymes/enzyme modulators. Meta-analysis of 282 EPR-genes identified only 63 EPR-genes in association with cancer, mostly in breast, lung, and blood cancers. Protein-protein interaction network analysis of all 282 EPR-genes identified proteins including those in cadherins and VEGF. The two observations, that EPRs can induce mutations under malignant conditions and that identification of some EPR-gene products in vital cell signaling-mediated pathways, together suggest the crucial role of EPRs in carcinogenesis. The new link between EPR-genes and their functionally interacting proteins throws a new dimension in the present understanding of cancer pathogenesis and can help in planning therapeutic strategies. Validation of present results using techniques like NGS is required to establish the role of the EPR genes in cancer pathology.

  12. Identifying Breast Cancer Oncogenes

    DTIC Science & Technology

    2010-10-01

    08-1-0767 TITLE: Identifying Breast Cancer Oncogenes PRINCIPAL INVESTIGATOR: Yashaswi Shrestha... Breast Cancer Oncogenes 5a. CONTRACT NUMBER W81XWH-08-1-0767 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) Yashaswi...SUPPLEMENTARY NOTES 14. ABSTRACT Breast cancer is attributed to genetic alterations, the majority of which are yet to be characterized. Oncogenic

  13. Gene expression profiling demonstrates WNT/β-catenin pathway genes alteration in Mexican patients with colorectal cancer and diabetes mellitus.

    PubMed

    Ivonne Wence-Chavez, Laura; Palomares-Chacon, Ulises; Pablo Flores-Gutierrez, Juan; Felipe Jave-Suarez, Luis; Del Carmen Aguilar-Lemarroy, Adriana; Barros-Nunez, Patricio; Esperanza Flores-Martinez, Silvia; Sanchez-Corona, Jose; Alejandra Rosales-Reynoso, Monica

    2017-01-01

    Several studies have shown a strong association between diabetes mellitus (DM) and increased risk of colorectal cancer (CRC). The fundamental mechanisms that support this association are not entirely understood; however, it is believed that hyperinsulinemia and hyperglycemia may be involved. Some proposed mechanisms include upregulation of mitogenic signaling pathways like MAPK, PI3K, mTOR, and WNT, which are involved in cell proliferation, growth, and cancer cell survival. The purpose of this study was to evaluate the gene expression profile and identify differently expressed genes involved in mitogenic pathways in CRC patients with and without DM. In this study, microarray analysis of gene expression followed by quantitative PCR (qPCR) was performed in cancer tissue from CRC patients with and without DM to identify the gene expression profiles and validate the differently expressed genes. Among the study groups, some differently expressed genes were identified. However, when bioinformatics clustering tools were used, a significant modulation of genes involved in the WNT pathway was evident. Therefore, we focused on genes participating in this pathway, such as WNT3A, LRP6, TCF7L2, and FRA-1. Validation of the expression levels of those genes by qPCR showed that CRC patients without type 2 diabetes mellitus (T2DM) expressed significantly more WNT3Ay LRP6, but less TCF7L2 and FRA-1 compared to controls, while in CRC patients with DM the expression levels of WNT3A, LRP6, TCF7L2, and FRA-1 were significantly higher compared to controls. Our results suggest that WNT/β-catenin pathway is upregulated in patients with CRC and DM, demonstrating its importance and involvement in both pathologies.

  14. Genetic basis of interindividual susceptibility to cancer cachexia: selection of potential candidate gene polymorphisms for association studies.

    PubMed

    Johns, N; Tan, B H; MacMillan, M; Solheim, T S; Ross, J A; Baracos, V E; Damaraju, S; Fearon, K C H

    2014-12-01

    Cancer cachexia is a complex and multifactorial disease. Evolving definitions highlight the fact that a diverse range of biological processes contribute to cancer cachexia. Part of the variation in who will and who will not develop cancer cachexia may be genetically determined. As new definitions, classifications and biological targets continue to evolve, there is a need for reappraisal of the literature for future candidate association studies. This review summarizes genes identified or implicated as well as putative candidate genes contributing to cachexia, identified through diverse technology platforms and model systems to further guide association studies. A systematic search covering 1986-2012 was performed for potential candidate genes / genetic polymorphisms relating to cancer cachexia. All candidate genes were reviewed for functional polymorphisms or clinically significant polymorphisms associated with cachexia using the OMIM and GeneRIF databases. Pathway analysis software was used to reveal possible network associations between genes. Functionality of SNPs/genes was explored based on published literature, algorithms for detecting putative deleterious SNPs and interrogating the database for expression of quantitative trait loci (eQTLs). A total of 154 genes associated with cancer cachexia were identified and explored for functional polymorphisms. Of these 154 genes, 119 had a combined total of 281 polymorphisms with functional and/or clinical significance in terms of cachexia associated with them. Of these, 80 polymorphisms (in 51 genes) were replicated in more than one study with 24 polymorphisms found to influence two or more hallmarks of cachexia (i.e., inflammation, loss of fat mass and/or lean mass and reduced survival). Selection of candidate genes and polymorphisms is a key element of multigene study design. The present study provides a contemporary basis to select genes and/or polymorphisms for further association studies in cancer cachexia, and

  15. GSCALite: A Web Server for Gene Set Cancer Analysis.

    PubMed

    Liu, Chun-Jie; Hu, Fei-Fei; Xia, Mengxuan; Han, Leng; Zhang, Qiong; Guo, An-Yuan

    2018-05-22

    The availability of cancer genomic data makes it possible to analyze genes related to cancer. Cancer is usually the result of a set of genes and the signal of a single gene could be covered by background noise. Here, we present a web server named Gene Set Cancer Analysis (GSCALite) to analyze a set of genes in cancers with the following functional modules. (i) Differential expression in tumor vs normal, and the survival analysis; (ii) Genomic variations and their survival analysis; (iii) Gene expression associated cancer pathway activity; (iv) miRNA regulatory network for genes; (v) Drug sensitivity for genes; (vi) Normal tissue expression and eQTL for genes. GSCALite is a user-friendly web server for dynamic analysis and visualization of gene set in cancer and drug sensitivity correlation, which will be of broad utilities to cancer researchers. GSCALite is available on http://bioinfo.life.hust.edu.cn/web/GSCALite/. guoay@hust.edu.cn or zhangqiong@hust.edu.cn. Supplementary data are available at Bioinformatics online.

  16. Integrative analysis of multi-omics data for identifying multi-markers for diagnosing pancreatic cancer

    PubMed Central

    2015-01-01

    Background microRNA (miRNA) expression plays an influential role in cancer classification and malignancy, and miRNAs are feasible as alternative diagnostic markers for pancreatic cancer, a highly aggressive neoplasm with silent early symptoms, high metastatic potential, and resistance to conventional therapies. Methods In this study, we evaluated the benefits of multi-omics data analysis by integrating miRNA and mRNA expression data in pancreatic cancer. Using support vector machine (SVM) modelling and leave-one-out cross validation (LOOCV), we evaluated the diagnostic performance of single- or multi-markers based on miRNA and mRNA expression profiles from 104 PDAC tissues and 17 benign pancreatic tissues. For selecting even more reliable and robust markers, we performed validation by independent datasets from the Gene Expression Omnibus (GEO) and the Cancer Genome Atlas (TCGA) data depositories. For validation, miRNA activity was estimated by miRNA-target gene interaction and mRNA expression datasets in pancreatic cancer. Results Using a comprehensive identification approach, we successfully identified 705 multi-markers having powerful diagnostic performance for PDAC. In addition, these marker candidates annotated with cancer pathways using gene ontology analysis. Conclusions Our prediction models have strong potential for the diagnosis of pancreatic cancer. PMID:26328610

  17. RUBIC identifies driver genes by detecting recurrent DNA copy number breaks

    PubMed Central

    van Dyk, Ewald; Hoogstraat, Marlous; ten Hoeve, Jelle; Reinders, Marcel J. T.; Wessels, Lodewyk F. A.

    2016-01-01

    The frequent recurrence of copy number aberrations across tumour samples is a reliable hallmark of certain cancer driver genes. However, state-of-the-art algorithms for detecting recurrent aberrations fail to detect several known drivers. In this study, we propose RUBIC, an approach that detects recurrent copy number breaks, rather than recurrently amplified or deleted regions. This change of perspective allows for a simplified approach as recursive peak splitting procedures and repeated re-estimation of the background model are avoided. Furthermore, we control the false discovery rate on the level of called regions, rather than at the probe level, as in competing algorithms. We benchmark RUBIC against GISTIC2 (a state-of-the-art approach) and RAIG (a recently proposed approach) on simulated copy number data and on three SNP6 and NGS copy number data sets from TCGA. We show that RUBIC calls more focal recurrent regions and identifies a much larger fraction of known cancer genes. PMID:27396759

  18. Gene expression profile of mouse prostate tumors reveals dysregulations in major biological processes and identifies potential murine targets for preclinical development of human prostate cancer therapy.

    PubMed

    Haram, Kerstyn M; Peltier, Heidi J; Lu, Bin; Bhasin, Manoj; Otu, Hasan H; Choy, Bob; Regan, Meredith; Libermann, Towia A; Latham, Gary J; Sanda, Martin G; Arredouani, Mohamed S

    2008-10-01

    Translation of preclinical studies into effective human cancer therapy is hampered by the lack of defined molecular expression patterns in mouse models that correspond to the human counterpart. We sought to generate an open source TRAMP mouse microarray dataset and to use this array to identify differentially expressed genes from human prostate cancer (PCa) that have concordant expression in TRAMP tumors, and thereby represent lead targets for preclinical therapy development. We performed microarrays on total RNA extracted and amplified from eight TRAMP tumors and nine normal prostates. A subset of differentially expressed genes was validated by QRT-PCR. Differentially expressed TRAMP genes were analyzed for concordant expression in publicly available human prostate array datasets and a subset of resulting genes was analyzed by QRT-PCR. Cross-referencing differentially expressed TRAMP genes to public human prostate array datasets revealed 66 genes with concordant expression in mouse and human PCa; 56 between metastases and normal and 10 between primary tumor and normal tissues. Of these 10 genes, two, Sox4 and Tubb2a, were validated by QRT-PCR. Our analysis also revealed various dysregulations in major biologic pathways in the TRAMP prostates. We report a TRAMP microarray dataset of which a gene subset was validated by QRT-PCR with expression patterns consistent with previous gene-specific TRAMP studies. Concordance analysis between TRAMP and human PCa associated genes supports the utility of the model and suggests several novel molecular targets for preclinical therapy.

  19. The prognostic significance of specific HOX gene expression patterns in ovarian cancer.

    PubMed

    Kelly, Zoe; Moller-Levet, Carla; McGrath, Sophie; Butler-Manuel, Simon; Kavitha Madhuri, Thumuluru; Kierzek, Andrzej M; Pandha, Hardev; Morgan, Richard; Michael, Agnieszka

    2016-10-01

    HOX genes are vital for all aspects of mammalian growth and differentiation, and their dysregulated expression is related to ovarian carcinogenesis. The aim of the current study was to establish the prognostic value of HOX dysregulation as well as its role in platinum resistance. The potential to target HOX proteins through the HOX/PBX interaction was also explored in the context of platinum resistance. HOX gene expression was determined in ovarian cancer cell lines and primary EOCs by QPCR, and compared to expression in normal ovarian epithelium and fallopian tube tissue samples. Statistical analysis included one-way ANOVA and t-tests, using statistical software R and GraphPad. The analysis identified 36 of the 39 HOX genes as being overexpressed in high grade serous EOC compared to normal tissue. We detected a molecular HOX gene-signature that predicted poor outcome. Overexpression of HOXB4 and HOXB9 was identified in high grade serous cell lines after platinum resistance developed. Targeting the HOX/PBX dimer with the HXR9 peptide enhanced the cytotoxicity of cisplatin in platinum-resistant ovarian cancer. In conclusion, this study has shown the HOX genes are highly dysregulated in ovarian cancer with high expression of HOXA13, B6, C13, D1 and D13 being predictive of poor clinical outcome. Targeting the HOX/PBX dimer in platinum-resistant cancer represents a potentially new therapeutic option that should be further developed and tested in clinical trials. © 2016 The Authors International Journal of Cancer published by John Wiley & Sons Ltd on behalf of UICC.

  20. Next-Generation Sequencing-based genomic profiling of brain metastases of primary ovarian cancer identifies high number of BRCA-mutations.

    PubMed

    Balendran, S; Liebmann-Reindl, S; Berghoff, A S; Reischer, T; Popitsch, N; Geier, C B; Kenner, L; Birner, P; Streubel, B; Preusser, M

    2017-07-01

    Ovarian cancer represents the most common gynaecological malignancy and has the highest mortality of all female reproductive cancers. It has a rare predilection to develop brain metastases (BM). In this study, we evaluated the mutational profile of ovarian cancer metastases through Next-Generation Sequencing (NGS) with the aim of identifying potential clinically actionable genetic alterations with options for small molecule targeted therapy. Library preparation was conducted using Illumina TruSight Rapid Capture Kit in combination with a cancer specific enrichment kit covering 94 genes. BRCA-mutations were confirmed by using TruSeq Custom Amplicon Low Input Kit in combination with a custom-designed BRCA gene panel. In our cohort all eight sequenced BM samples exhibited a multitude of variant alterations, each with unique molecular profiles. The 37 identified variants were distributed over 22 cancer-related genes (23.4%). The number of mutated genes per sample ranged from 3 to 7 with a median of 4.5. The most commonly altered genes were BRCA1/2, TP53, and ATM. In total, 7 out of 8 samples revealed either a BRCA1 or a BRCA2 pathogenic mutation. Furthermore, all eight BM samples showed mutations in at least one DNA repair gene. Our NGS study of BM of ovarian carcinoma revealed a significant number of BRCA-mutations beside TP53, ATM and CHEK2 mutations. These findings strongly suggest the implication of BRCA and DNA repair malfunction in ovarian cancer metastasizing to the brain. Based on these findings, pharmacological PARP inhibition could be one potential targeted therapeutic for brain metastatic ovarian cancer patients.

  1. NIH Researchers Identify OCD Risk Gene

    MedlinePlus

    ... News From NIH NIH Researchers Identify OCD Risk Gene Past Issues / Summer 2006 Table of Contents For ... and Alcoholism (NIAAA) have identified a previously unknown gene variant that doubles an individual's risk for obsessive- ...

  2. Defining Aggressive Prostate Cancer Using a 12-Gene Model1

    PubMed Central

    Riva, Alberto; Kim, Robert; Varambally, Sooryanarayana; He, Le; Kutok, Jeff; Aster, Jonathan C; Tang, Jeffery; Kuefer, Rainer; Hofer, Matthias D; Febbo, Phillip G; Chinnaiyan, Arul M; Rubin, Mark A

    2006-01-01

    Abstract The critical clinical question in prostate cancer research is: How do we develop means of distinguishing aggressive disease from indolent disease? Using a combination of proteomic and expression array data, we identified a set of 36 genes with concordant dysregulation of protein products that could be evaluated in situ by quantitative immunohistochemistry. Another five prostate cancer biomarkers were included using linear discriminant analysis, we determined that the optimal model used to predict prostate cancer progression consisted of 12 proteins. Using a separate patient population, transcriptional levels of the 12 genes encoding for these proteins predicted prostate-specific antigen failure in 79 men following surgery for clinically localized prostate cancer (P = .0015). This study demonstrates that cross-platform models can lead to predictive models with the possible advantage of being more robust through this selection process. PMID:16533427

  3. Inactivation of LLC1 gene in nonsmall cell lung cancer

    PubMed Central

    Hong, Kyeong-Man; Yang, Sei-Hoon; Chowdhuri, Sinchita R.; Player, Audrey; Hames, Megan; Fukuoka, Junya; Meerzaman, Daoud; Dracheva, Tatiana; Sun, Zhifu; Yang, Ping; Jen, Jin

    2007-01-01

    Serial analysis of gene expression studies led us to identify a previously unknown gene, c20orf85, that is present in the normal lung epithelium, but absent or downregulated in most primary non-small cell lung cancers and lung cancer cell lines. We named this gene LLC1 for Low in Lung Cancer 1. LLC1 is located on chromosome 20q13.3 and has a 70% GC content in the promoter region. It has 4 exons and encodes a protein containing 137 amino acids. By in situ hybridization, we observed that LLC1 message is localized in normal lung bronchial epithelial cells, but absent in 13 of 14 lung adenocarcinoma and 9 out of 10 lung squamous carcinoma samples. Methylation at CpG sites of the LLC1 promoter was frequently observed in lung cancer cell lines and in a fraction of primary lung cancer tissues. Treatment with 5-aza deoxycytidine resulted in a reduced methylation of the LLC1 promoter concomitant with the increase of LLC1 expression. These results suggest that inactivation of LLC1 by means of promoter methylation is a frequent event in nonsmall cell lung cancer and may play a role in lung tumorigenesis. PMID:17304513

  4. Networking of differentially expressed genes in human cancer cells resistant to methotrexate

    PubMed Central

    2009-01-01

    Background The need for an integrated view of data obtained from high-throughput technologies gave rise to network analyses. These are especially useful to rationalize how external perturbations propagate through the expression of genes. To address this issue in the case of drug resistance, we constructed biological association networks of genes differentially expressed in cell lines resistant to methotrexate (MTX). Methods Seven cell lines representative of different types of cancer, including colon cancer (HT29 and Caco2), breast cancer (MCF-7 and MDA-MB-468), pancreatic cancer (MIA PaCa-2), erythroblastic leukemia (K562) and osteosarcoma (Saos-2), were used. The differential expression pattern between sensitive and MTX-resistant cells was determined by whole human genome microarrays and analyzed with the GeneSpring GX software package. Genes deregulated in common between the different cancer cell lines served to generate biological association networks using the Pathway Architect software. Results Dikkopf homolog-1 (DKK1) is a highly interconnected node in the network generated with genes in common between the two colon cancer cell lines, and functional validations of this target using small interfering RNAs (siRNAs) showed a chemosensitization toward MTX. Members of the UDP-glucuronosyltransferase 1A (UGT1A) family formed a network of genes differentially expressed in the two breast cancer cell lines. siRNA treatment against UGT1A also showed an increase in MTX sensitivity. Eukaryotic translation elongation factor 1 alpha 1 (EEF1A1) was overexpressed among the pancreatic cancer, leukemia and osteosarcoma cell lines, and siRNA treatment against EEF1A1 produced a chemosensitization toward MTX. Conclusions Biological association networks identified DKK1, UGT1As and EEF1A1 as important gene nodes in MTX-resistance. Treatments using siRNA technology against these three genes showed chemosensitization toward MTX. PMID:19732436

  5. Genome-Wide Meta-Analyses of Breast, Ovarian, and Prostate Cancer Association Studies Identify Multiple New Susceptibility Loci Shared by at Least Two Cancer Types.

    PubMed

    Kar, Siddhartha P; Beesley, Jonathan; Amin Al Olama, Ali; Michailidou, Kyriaki; Tyrer, Jonathan; Kote-Jarai, ZSofia; Lawrenson, Kate; Lindstrom, Sara; Ramus, Susan J; Thompson, Deborah J; Kibel, Adam S; Dansonka-Mieszkowska, Agnieszka; Michael, Agnieszka; Dieffenbach, Aida K; Gentry-Maharaj, Aleksandra; Whittemore, Alice S; Wolk, Alicja; Monteiro, Alvaro; Peixoto, Ana; Kierzek, Andrzej; Cox, Angela; Rudolph, Anja; Gonzalez-Neira, Anna; Wu, Anna H; Lindblom, Annika; Swerdlow, Anthony; Ziogas, Argyrios; Ekici, Arif B; Burwinkel, Barbara; Karlan, Beth Y; Nordestgaard, Børge G; Blomqvist, Carl; Phelan, Catherine; McLean, Catriona; Pearce, Celeste Leigh; Vachon, Celine; Cybulski, Cezary; Slavov, Chavdar; Stegmaier, Christa; Maier, Christiane; Ambrosone, Christine B; Høgdall, Claus K; Teerlink, Craig C; Kang, Daehee; Tessier, Daniel C; Schaid, Daniel J; Stram, Daniel O; Cramer, Daniel W; Neal, David E; Eccles, Diana; Flesch-Janys, Dieter; Edwards, Digna R Velez; Wokozorczyk, Dominika; Levine, Douglas A; Yannoukakos, Drakoulis; Sawyer, Elinor J; Bandera, Elisa V; Poole, Elizabeth M; Goode, Ellen L; Khusnutdinova, Elza; Høgdall, Estrid; Song, Fengju; Bruinsma, Fiona; Heitz, Florian; Modugno, Francesmary; Hamdy, Freddie C; Wiklund, Fredrik; Giles, Graham G; Olsson, Håkan; Wildiers, Hans; Ulmer, Hans-Ulrich; Pandha, Hardev; Risch, Harvey A; Darabi, Hatef; Salvesen, Helga B; Nevanlinna, Heli; Gronberg, Henrik; Brenner, Hermann; Brauch, Hiltrud; Anton-Culver, Hoda; Song, Honglin; Lim, Hui-Yi; McNeish, Iain; Campbell, Ian; Vergote, Ignace; Gronwald, Jacek; Lubiński, Jan; Stanford, Janet L; Benítez, Javier; Doherty, Jennifer A; Permuth, Jennifer B; Chang-Claude, Jenny; Donovan, Jenny L; Dennis, Joe; Schildkraut, Joellen M; Schleutker, Johanna; Hopper, John L; Kupryjanczyk, Jolanta; Park, Jong Y; Figueroa, Jonine; Clements, Judith A; Knight, Julia A; Peto, Julian; Cunningham, Julie M; Pow-Sang, Julio; Batra, Jyotsna; Czene, Kamila; Lu, Karen H; Herkommer, Kathleen; Khaw, Kay-Tee; Matsuo, Keitaro; Muir, Kenneth; Offitt, Kenneth; Chen, Kexin; Moysich, Kirsten B; Aittomäki, Kristiina; Odunsi, Kunle; Kiemeney, Lambertus A; Massuger, Leon F A G; Fitzgerald, Liesel M; Cook, Linda S; Cannon-Albright, Lisa; Hooning, Maartje J; Pike, Malcolm C; Bolla, Manjeet K; Luedeke, Manuel; Teixeira, Manuel R; Goodman, Marc T; Schmidt, Marjanka K; Riggan, Marjorie; Aly, Markus; Rossing, Mary Anne; Beckmann, Matthias W; Moisse, Matthieu; Sanderson, Maureen; Southey, Melissa C; Jones, Michael; Lush, Michael; Hildebrandt, Michelle A T; Hou, Ming-Feng; Schoemaker, Minouk J; Garcia-Closas, Montserrat; Bogdanova, Natalia; Rahman, Nazneen; Le, Nhu D; Orr, Nick; Wentzensen, Nicolas; Pashayan, Nora; Peterlongo, Paolo; Guénel, Pascal; Brennan, Paul; Paulo, Paula; Webb, Penelope M; Broberg, Per; Fasching, Peter A; Devilee, Peter; Wang, Qin; Cai, Qiuyin; Li, Qiyuan; Kaneva, Radka; Butzow, Ralf; Kopperud, Reidun Kristin; Schmutzler, Rita K; Stephenson, Robert A; MacInnis, Robert J; Hoover, Robert N; Winqvist, Robert; Ness, Roberta; Milne, Roger L; Travis, Ruth C; Benlloch, Sara; Olson, Sara H; McDonnell, Shannon K; Tworoger, Shelley S; Maia, Sofia; Berndt, Sonja; Lee, Soo Chin; Teo, Soo-Hwang; Thibodeau, Stephen N; Bojesen, Stig E; Gapstur, Susan M; Kjær, Susanne Krüger; Pejovic, Tanja; Tammela, Teuvo L J; Dörk, Thilo; Brüning, Thomas; Wahlfors, Tiina; Key, Tim J; Edwards, Todd L; Menon, Usha; Hamann, Ute; Mitev, Vanio; Kosma, Veli-Matti; Setiawan, Veronica Wendy; Kristensen, Vessela; Arndt, Volker; Vogel, Walther; Zheng, Wei; Sieh, Weiva; Blot, William J; Kluzniak, Wojciech; Shu, Xiao-Ou; Gao, Yu-Tang; Schumacher, Fredrick; Freedman, Matthew L; Berchuck, Andrew; Dunning, Alison M; Simard, Jacques; Haiman, Christopher A; Spurdle, Amanda; Sellers, Thomas A; Hunter, David J; Henderson, Brian E; Kraft, Peter; Chanock, Stephen J; Couch, Fergus J; Hall, Per; Gayther, Simon A; Easton, Douglas F; Chenevix-Trench, Georgia; Eeles, Rosalind; Pharoah, Paul D P; Lambrechts, Diether

    2016-09-01

    Breast, ovarian, and prostate cancers are hormone-related and may have a shared genetic basis, but this has not been investigated systematically by genome-wide association (GWA) studies. Meta-analyses combining the largest GWA meta-analysis data sets for these cancers totaling 112,349 cases and 116,421 controls of European ancestry, all together and in pairs, identified at P < 10(-8) seven new cross-cancer loci: three associated with susceptibility to all three cancers (rs17041869/2q13/BCL2L11; rs7937840/11q12/INCENP; rs1469713/19p13/GATAD2A), two breast and ovarian cancer risk loci (rs200182588/9q31/SMC2; rs8037137/15q26/RCCD1), and two breast and prostate cancer risk loci (rs5013329/1p34/NSUN4; rs9375701/6q23/L3MBTL3). Index variants in five additional regions previously associated with only one cancer also showed clear association with a second cancer type. Cell-type-specific expression quantitative trait locus and enhancer-gene interaction annotations suggested target genes with potential cross-cancer roles at the new loci. Pathway analysis revealed significant enrichment of death receptor signaling genes near loci with P < 10(-5) in the three-cancer meta-analysis. We demonstrate that combining large-scale GWA meta-analysis findings across cancer types can identify completely new risk loci common to breast, ovarian, and prostate cancers. We show that the identification of such cross-cancer risk loci has the potential to shed new light on the shared biology underlying these hormone-related cancers. Cancer Discov; 6(9); 1052-67. ©2016 AACR.This article is highlighted in the In This Issue feature, p. 932. ©2016 American Association for Cancer Research.

  6. An 8-gene qRT-PCR-based gene expression score that has prognostic value in early breast cancer

    PubMed Central

    2010-01-01

    Background Gene expression profiling may improve prognostic accuracy in patients with early breast cancer. Our objective was to demonstrate that it is possible to develop a simple molecular signature to predict distant relapse. Methods We included 153 patients with stage I-II hormonal receptor-positive breast cancer. RNA was isolated from formalin-fixed paraffin-embedded samples and qRT-PCR amplification of 83 genes was performed with gene expression assays. The genes we analyzed were those included in the 70-Gene Signature, the Recurrence Score and the Two-Gene Index. The association among gene expression, clinical variables and distant metastasis-free survival was analyzed using Cox regression models. Results An 8-gene prognostic score was defined. Distant metastasis-free survival at 5 years was 97% for patients defined as low-risk by the prognostic score versus 60% for patients defined as high-risk. The 8-gene score remained a significant factor in multivariate analysis and its performance was similar to that of two validated gene profiles: the 70-Gene Signature and the Recurrence Score. The validity of the signature was verified in independent cohorts obtained from the GEO database. Conclusions This study identifies a simple gene expression score that complements histopathological prognostic factors in breast cancer, and can be determined in paraffin-embedded samples. PMID:20584321

  7. Single-cell mRNA sequencing identifies subclonal heterogeneity in anti-cancer drug responses of lung adenocarcinoma cells.

    PubMed

    Kim, Kyu-Tae; Lee, Hye Won; Lee, Hae-Ock; Kim, Sang Cheol; Seo, Yun Jee; Chung, Woosung; Eum, Hye Hyeon; Nam, Do-Hyun; Kim, Junhyong; Joo, Kyeung Min; Park, Woong-Yang

    2015-06-19

    Intra-tumoral genetic and functional heterogeneity correlates with cancer clinical prognoses. However, the mechanisms by which intra-tumoral heterogeneity impacts therapeutic outcome remain poorly understood. RNA sequencing (RNA-seq) of single tumor cells can provide comprehensive information about gene expression and single-nucleotide variations in individual tumor cells, which may allow for the translation of heterogeneous tumor cell functional responses into customized anti-cancer treatments. We isolated 34 patient-derived xenograft (PDX) tumor cells from a lung adenocarcinoma patient tumor xenograft. Individual tumor cells were subjected to single cell RNA-seq for gene expression profiling and expressed mutation profiling. Fifty tumor-specific single-nucleotide variations, including KRAS(G12D), were observed to be heterogeneous in individual PDX cells. Semi-supervised clustering, based on KRAS(G12D) mutant expression and a risk score representing expression of 69 lung adenocarcinoma-prognostic genes, classified PDX cells into four groups. PDX cells that survived in vitro anti-cancer drug treatment displayed transcriptome signatures consistent with the group characterized by KRAS(G12D) and low risk score. Single-cell RNA-seq on viable PDX cells identified a candidate tumor cell subgroup associated with anti-cancer drug resistance. Thus, single-cell RNA-seq is a powerful approach for identifying unique tumor cell-specific gene expression profiles which could facilitate the development of optimized clinical anti-cancer strategies.

  8. Genetic variation of clock genes and cancer risk: a field synopsis and meta-analysis

    PubMed Central

    Benna, Clara; Helfrich-Förster, Charlotte; Rajendran, Senthilkumar; Monticelli, Halenya; Pilati, Pierluigi; Nitti, Donato; Mocellin, Simone

    2017-01-01

    BACKGROUND The number of studies on the association between clock genes’ polymorphisms and cancer susceptibility has increased over the last years but the results are often conflicting and no comprehensive overview and quantitative summary of the evidence in this field is available. RESULTS Literature search identified 27 eligible studies comprising 96756 subjects (cases: 38231) and investigating 687 polymorphisms involving 14 clock genes. Overall, 1025 primary and subgroup meta-analyses on 366 gene variants were performed. Study distribution by tumor was as follows: breast cancer (n=15), prostate cancer (n=3), pancreatic cancer (n=2), non-Hodgkin's lymphoma (n=2), glioma (n=1), chronic lymphocytic leukemia (n=1), colorectal cancer (n=1), non-small cell lung cancer (n=1) and ovarian cancer (n=1). We identified 10 single nucleotide polymorphisms (SNPs) significantly associated with cancer risk: NPAS2 rs10165970 (mixed and breast cancer shiftworkers), rs895520 (mixed), rs17024869 (breast) and rs7581886 (breast); CLOCK rs3749474 (breast) and rs11943456 (breast); RORA rs7164773 (breast and breast cancer postmenopausal), rs10519097 (breast); RORB rs7867494 (breast cancer postmenopausal), PER3 rs1012477 (breast cancer subgroups) and assessed the level of quality evidence to be intermediate. We also identified polymorphisms with lower quality statistically significant associations (n=30). CONCLUSIONS Our work supports the hypothesis that genetic variation of clock genes might affect cancer risk. These findings also highlight the need for more efforts in this research field in order to fully establish the contribution of clock gene variants to the risk of developing cancer. METHODS We conducted a systematic review and meta-analysis of the evidence on the association between clock genes’ germline variants and the risk of developing cancer. To assess result credibility, summary evidence was graded according to the Venice criteria and false positive report probability

  9. Cross-species functional analysis of cancer-associated fibroblasts identifies a critical role for CLCF1 and IL6 in non-small cell lung cancer in vivo

    PubMed Central

    Vicent, Silvestre; Sayles, Leanne C.; Vaka, Dedeepya; Khatri, Purvesh; Gevaert, Olivier; Chen, Ron; Zheng, Yanyan; Gillespie, Anna K.; Clarke, Nicole; Xu, Yue; Shrager, Joseph; Hoang, Chuong D.; Plevritis, Sylvia; Butte, Atul J.; Sweet-Cordero, E. Alejandro

    2013-01-01

    Cancer-associated fibroblasts (CAFs) have been reported to support tumor progression by a variety of mechanisms. However, their role in the progression of non-small cell lung cancer (NSCLC) remains poorly defined. In addition, the extent to which specific proteins secreted by CAFs contribute directly to tumor growth is unclear. To study the role of CAFs in NSCLC, a cross-species functional characterization of mouse and human lung CAFs was performed. CAFs supported the growth of lung cancer cells in vivo by secretion of soluble factors that directly stimulate the growth of tumor cells. Gene expression analysis comparing normal mouse lung fibroblasts (NFs) and mouse lung CAFs identified multiple genes that correlate with the CAF phenotype. A gene signature of secreted genes upregulated in CAFs was an independent marker of poor survival in NSCLC patients. This secreted gene signature was upregulated in NFs after long-term exposure to tumor cells, demonstrating that NFs are “educated” by tumor cells to acquire a CAF-like phenotype. Functional studies identified important roles for CLCF1-CNTFR and IL6-IL6R signaling, in promoting growth of NSCLC cells. This study identifies novel soluble factors contributing to the CAF protumorigenic phenotype in NSCLC and suggests new avenues for the development of therapeutic strategies. PMID:22962265

  10. Network-Based Integration of Disparate Omic Data To Identify "Silent Players" in Cancer

    PubMed Central

    Ruffalo, Matthew

    2015-01-01

    Development of high-throughput monitoring technologies enables interrogation of cancer samples at various levels of cellular activity. Capitalizing on these developments, various public efforts such as The Cancer Genome Atlas (TCGA) generate disparate omic data for large patient cohorts. As demonstrated by recent studies, these heterogeneous data sources provide the opportunity to gain insights into the molecular changes that drive cancer pathogenesis and progression. However, these insights are limited by the vast search space and as a result low statistical power to make new discoveries. In this paper, we propose methods for integrating disparate omic data using molecular interaction networks, with a view to gaining mechanistic insights into the relationship between molecular changes at different levels of cellular activity. Namely, we hypothesize that genes that play a role in cancer development and progression may be implicated by neither frequent mutation nor differential expression, and that network-based integration of mutation and differential expression data can reveal these “silent players”. For this purpose, we utilize network-propagation algorithms to simulate the information flow in the cell at a sample-specific resolution. We then use the propagated mutation and expression signals to identify genes that are not necessarily mutated or differentially expressed genes, but have an essential role in tumor development and patient outcome. We test the proposed method on breast cancer and glioblastoma multiforme data obtained from TCGA. Our results show that the proposed method can identify important proteins that are not readily revealed by molecular data, providing insights beyond what can be gleaned by analyzing different types of molecular data in isolation. PMID:26683094

  11. VarWalker: Personalized Mutation Network Analysis of Putative Cancer Genes from Next-Generation Sequencing Data

    PubMed Central

    Jia, Peilin; Zhao, Zhongming

    2014-01-01

    A major challenge in interpreting the large volume of mutation data identified by next-generation sequencing (NGS) is to distinguish driver mutations from neutral passenger mutations to facilitate the identification of targetable genes and new drugs. Current approaches are primarily based on mutation frequencies of single-genes, which lack the power to detect infrequently mutated driver genes and ignore functional interconnection and regulation among cancer genes. We propose a novel mutation network method, VarWalker, to prioritize driver genes in large scale cancer mutation data. VarWalker fits generalized additive models for each sample based on sample-specific mutation profiles and builds on the joint frequency of both mutation genes and their close interactors. These interactors are selected and optimized using the Random Walk with Restart algorithm in a protein-protein interaction network. We applied the method in >300 tumor genomes in two large-scale NGS benchmark datasets: 183 lung adenocarcinoma samples and 121 melanoma samples. In each cancer, we derived a consensus mutation subnetwork containing significantly enriched consensus cancer genes and cancer-related functional pathways. These cancer-specific mutation networks were then validated using independent datasets for each cancer. Importantly, VarWalker prioritizes well-known, infrequently mutated genes, which are shown to interact with highly recurrently mutated genes yet have been ignored by conventional single-gene-based approaches. Utilizing VarWalker, we demonstrated that network-assisted approaches can be effectively adapted to facilitate the detection of cancer driver genes in NGS data. PMID:24516372

  12. VarWalker: personalized mutation network analysis of putative cancer genes from next-generation sequencing data.

    PubMed

    Jia, Peilin; Zhao, Zhongming

    2014-02-01

    A major challenge in interpreting the large volume of mutation data identified by next-generation sequencing (NGS) is to distinguish driver mutations from neutral passenger mutations to facilitate the identification of targetable genes and new drugs. Current approaches are primarily based on mutation frequencies of single-genes, which lack the power to detect infrequently mutated driver genes and ignore functional interconnection and regulation among cancer genes. We propose a novel mutation network method, VarWalker, to prioritize driver genes in large scale cancer mutation data. VarWalker fits generalized additive models for each sample based on sample-specific mutation profiles and builds on the joint frequency of both mutation genes and their close interactors. These interactors are selected and optimized using the Random Walk with Restart algorithm in a protein-protein interaction network. We applied the method in >300 tumor genomes in two large-scale NGS benchmark datasets: 183 lung adenocarcinoma samples and 121 melanoma samples. In each cancer, we derived a consensus mutation subnetwork containing significantly enriched consensus cancer genes and cancer-related functional pathways. These cancer-specific mutation networks were then validated using independent datasets for each cancer. Importantly, VarWalker prioritizes well-known, infrequently mutated genes, which are shown to interact with highly recurrently mutated genes yet have been ignored by conventional single-gene-based approaches. Utilizing VarWalker, we demonstrated that network-assisted approaches can be effectively adapted to facilitate the detection of cancer driver genes in NGS data.

  13. Comparison of gene-expression profiles between diffuse- and intestinal-type gastric cancers using a genome-wide cDNA microarray.

    PubMed

    Jinawath, Natini; Furukawa, Yoichi; Hasegawa, Suguru; Li, Meihua; Tsunoda, Tatsuhiko; Satoh, Seiji; Yamaguchi, Toshiharu; Imamura, Hiroshi; Inoue, Masatomo; Shiozaki, Hitoshi; Nakamura, Yusuke

    2004-09-02

    Gastric cancer is the fourth leading cause of cancer-related death in the world. Two histologically distinct types of gastric carcinoma, 'intestinal' and 'diffuse', have different epidemiological and pathophysiological features that suggest different mechanisms of carcinogenesis. A number of studies have investigated intestinal-type gastric cancers at the molecular level, but little is known about mechanisms involved in the diffuse type, which has a more invasive phenotype and poorer prognosis. To clarify the mechanisms that underlie its development and/or progression, we compared the expression profiles of 20 laser-microbeam-microdissected diffuse-type gastric-cancer tissues with corresponding noncancerous mucosae by means of a cDNA microarray containing 23,040 genes. We identified 153 genes that were commonly upregulated and more than 1500 that were commonly downregulated in the tumors. We also identified a number of genes related to tumor progression. Furthermore, comparison of the expression profiles of diffuse-type with those of intestinal-type gastric cancers identified 46 genes that may represent distinct molecular signatures of each histological type. The putative signature of diffuse-type cancer exhibited altered expression of genes related to cell-matrix interaction and extracellular-matrix (ECM) components, whereas that of intestinal-type cancer represented enhancement of cell growth. These data provide insight into different mechanisms underlying gastric carcinogenesis and may also serve as a starting point for identifying novel diagnostic markers and/or therapeutic targets for diffuse-type gastric cancers.

  14. Identifying Determinants of PARP Inhibitor Sensitivity in Ovarian Cancer

    DTIC Science & Technology

    2016-10-01

    inhibitors. Ovarian cancer patients that harbored germ- line BRCA1 mutations treated with PARP inhibitors exhibited meaningful responses in early phase...hypothesized that a range of common ovarian cancer predisposing germ- line BRCA1 gene mutations produce semi-functional proteins that are capable of...we have started our work examining exome sequences and gene expression in PARPi sensitive and resistance cancer cell lines . I attended and presented

  15. Exome-wide Sequencing Shows Low Mutation Rates and Identifies Novel Mutated Genes in Seminomas.

    PubMed

    Cutcutache, Ioana; Suzuki, Yuka; Tan, Iain Beehuat; Ramgopal, Subhashini; Zhang, Shenli; Ramnarayanan, Kalpana; Gan, Anna; Lee, Heng Hong; Tay, Su Ting; Ooi, Aikseng; Ong, Choon Kiat; Bolthouse, Jonathan T; Lane, Brian R; Anema, John G; Kahnoski, Richard J; Tan, Patrick; Teh, Bin Tean; Rozen, Steven G

    2015-07-01

    Testicular germ cell tumors are the most common cancer diagnosed in young men, and seminomas are the most common type of these cancers. There have been no exome-wide examinations of genes mutated in seminomas or of overall rates of nonsilent somatic mutations in these tumors. The objective was to analyze somatic mutations in seminomas to determine which genes are affected and to determine rates of nonsilent mutations. Eight seminomas and matched normal samples were surgically obtained from eight patients. DNA was extracted from tissue samples and exome sequenced on massively parallel Illumina DNA sequencers. Single-nucleotide polymorphism chip-based copy number analysis was also performed to assess copy number alterations. The DNA sequencing read data were analyzed to detect somatic mutations including single-nucleotide substitutions and short insertions and deletions. The detected mutations were validated by independent sequencing and further checked for subclonality. The rate of nonsynonymous somatic mutations averaged 0.31 mutations/Mb. We detected nonsilent somatic mutations in 96 genes that were not previously known to be mutated in seminomas, of which some may be driver mutations. Many of the mutations appear to have been present in subclonal populations. In addition, two genes, KIT and KRAS, were affected in two tumors each with mutations that were previously observed in other cancers and are presumably oncogenic. Our study, the first report on exome sequencing of seminomas, detected somatic mutations in 96 new genes, several of which may be targetable drivers. Furthermore, our results show that seminoma mutation rates are five times higher than previously thought, but are nevertheless low compared to other common cancers. Similar low rates are seen in other cancers that also have excellent rates of remission achieved with chemotherapy. We examined the DNA sequences of seminomas, the most common type of testicular germ cell cancer. Our study identified 96

  16. NRF2-regulated metabolic gene signature as a prognostic biomarker in non-small cell lung cancer

    PubMed Central

    Namani, Akhileshwar; Cui, Qin Qin; Wu, Yihe; Wang, Hongyan; Wang, Xiu Jun; Tang, Xiuwen

    2017-01-01

    Mutations in Kelch-like ECH-associated protein 1 (KEAP1) cause the aberrant activation of nuclear factor erythroid-derived 2-like 2 (NRF2), which leads to oncogenesis and drug resistance in lung cancer cells. Our study was designed to identify the genes involved in lung cancer progression targeted by NRF2. A series of microarray experiments in normal and cancer cells, as well as in animal models, have revealed regulatory genes downstream of NRF2 that are involved in wide variety of pathways. Specifically, we carried out individual and combinatorial microarray analysis of KEAP1 overexpression and NRF2 siRNA-knockdown in a KEAP1 mutant-A549 non-small cell lung cancer (NSCLC) cell line. As a result, we identified a list of genes which were mainly involved in metabolic functions in NSCLC by using functional annotation analysis. In addition, we carried out in silico analysis to characterize the antioxidant responsive element sequences in the promoter regions of known and putative NRF2-regulated metabolic genes. We further identified an NRF2-regulated metabolic gene signature (NRMGS) by correlating the microarray data with lung adenocarcinoma RNA-Seq gene expression data from The Cancer Genome Atlas followed by qRT-PCR validation, and finally showed that higher expression of the signature conferred a poor prognosis in 8 independent NSCLC cohorts. Our findings provide novel prognostic biomarkers for NSCLC. PMID:29050246

  17. Robust gene network analysis reveals alteration of the STAT5a network as a hallmark of prostate cancer.

    PubMed

    Reddy, Anupama; Huang, C Chris; Liu, Huiqing; Delisi, Charles; Nevalainen, Marja T; Szalma, Sandor; Bhanot, Gyan

    2010-01-01

    We develop a general method to identify gene networks from pair-wise correlations between genes in a microarray data set and apply it to a public prostate cancer gene expression data from 69 primary prostate tumors. We define the degree of a node as the number of genes significantly associated with the node and identify hub genes as those with the highest degree. The correlation network was pruned using transcription factor binding information in VisANT (http://visant.bu.edu/) as a biological filter. The reliability of hub genes was determined using a strict permutation test. Separate networks for normal prostate samples, and prostate cancer samples from African Americans (AA) and European Americans (EA) were generated and compared. We found that the same hubs control disease progression in AA and EA networks. Combining AA and EA samples, we generated networks for low low (<7) and high (≥7) Gleason grade tumors. A comparison of their major hubs with those of the network for normal samples identified two types of changes associated with disease: (i) Some hub genes increased their degree in the tumor network compared to their degree in the normal network, suggesting that these genes are associated with gain of regulatory control in cancer (e.g. possible turning on of oncogenes). (ii) Some hubs reduced their degree in the tumor network compared to their degree in the normal network, suggesting that these genes are associated with loss of regulatory control in cancer (e.g. possible loss of tumor suppressor genes). A striking result was that for both AA and EA tumor samples, STAT5a, CEBPB and EGR1 are major hubs that gain neighbors compared to the normal prostate network. Conversely, HIF-lα is a major hub that loses connections in the prostate cancer network compared to the normal prostate network. We also find that the degree of these hubs changes progressively from normal to low grade to high grade disease, suggesting that these hubs are master regulators of

  18. Identification of hub subnetwork based on topological features of genes in breast cancer

    PubMed Central

    ZHUANG, DA-YONG; JIANG, LI; HE, QING-QING; ZHOU, PENG; YUE, TAO

    2015-01-01

    The aim of this study was to provide functional insight into the identification of hub subnetworks by aggregating the behavior of genes connected in a protein-protein interaction (PPI) network. We applied a protein network-based approach to identify subnetworks which may provide new insight into the functions of pathways involved in breast cancer rather than individual genes. Five groups of breast cancer data were downloaded and analyzed from the Gene Expression Omnibus (GEO) database of high-throughput gene expression data to identify gene signatures using the genome-wide global significance (GWGS) method. A PPI network was constructed using Cytoscape and clusters that focused on highly connected nodes were obtained using the molecular complex detection (MCODE) clustering algorithm. Pathway analysis was performed to assess the functional relevance of selected gene signatures based on the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Topological centrality was used to characterize the biological importance of gene signatures, pathways and clusters. The results revealed that, cluster1, as well as the cell cycle and oocyte meiosis pathways were significant subnetworks in the analysis of degree and other centralities, in which hub nodes mostly distributed. The most important hub nodes, with top ranked centrality, were also similar with the common genes from the above three subnetwork intersections, which was viewed as a hub subnetwork with more reproducible than individual critical genes selected without network information. This hub subnetwork attributed to the same biological process which was essential in the function of cell growth and death. This increased the accuracy of identifying gene interactions that took place within the same functional process and was potentially useful for the development of biomarkers and networks for breast cancer. PMID:25573623

  19. Using Functional Signatures to Identify Repositioned Drugs for Breast, Myelogenous Leukemia and Prostate Cancer

    PubMed Central

    Shigemizu, Daichi; Hu, Zhenjun; Hung, Jui-Hung; Huang, Chia-Ling; Wang, Yajie; DeLisi, Charles

    2012-01-01

    The cost and time to develop a drug continues to be a major barrier to widespread distribution of medication. Although the genomic revolution appears to have had little impact on this problem, and might even have exacerbated it because of the flood of additional and usually ineffective leads, the emergence of high throughput resources promises the possibility of rapid, reliable and systematic identification of approved drugs for originally unintended uses. In this paper we develop and apply a method for identifying such repositioned drug candidates against breast cancer, myelogenous leukemia and prostate cancer by looking for inverse correlations between the most perturbed gene expression levels in human cancer tissue and the most perturbed expression levels induced by bioactive compounds. The method uses variable gene signatures to identify bioactive compounds that modulate a given disease. This is in contrast to previous methods that use small and fixed signatures. This strategy is based on the observation that diseases stem from failed/modified cellular functions, irrespective of the particular genes that contribute to the function, i.e., this strategy targets the functional signatures for a given cancer. This function-based strategy broadens the search space for the effective drugs with an impressive hit rate. Among the 79, 94 and 88 candidate drugs for breast cancer, myelogenous leukemia and prostate cancer, 32%, 13% and 17% respectively are either FDA-approved/in-clinical-trial drugs, or drugs with suggestive literature evidences, with an FDR of 0.01. These findings indicate that the method presented here could lead to a substantial increase in efficiency in drug discovery and development, and has potential application for the personalized medicine. PMID:22346740

  20. Synthetic lethal RNAi screening identifies sensitizing targets for gemcitabine therapy in pancreatic cancer

    PubMed Central

    Azorsa, David O; Gonzales, Irma M; Basu, Gargi D; Choudhary, Ashish; Arora, Shilpi; Bisanz, Kristen M; Kiefer, Jeffrey A; Henderson, Meredith C; Trent, Jeffrey M; Von Hoff, Daniel D; Mousses, Spyro

    2009-01-01

    Background Pancreatic cancer retains a poor prognosis among the gastrointestinal cancers. It affects 230,000 individuals worldwide, has a very high mortality rate, and remains one of the most challenging malignancies to treat successfully. Treatment with gemcitabine, the most widely used chemotherapeutic against pancreatic cancer, is not curative and resistance may occur. Combinations of gemcitabine with other chemotherapeutic drugs or biological agents have resulted in limited improvement. Methods In order to improve gemcitabine response in pancreatic cancer cells, we utilized a synthetic lethal RNAi screen targeting 572 known kinases to identify genes that when silenced would sensitize pancreatic cancer cells to gemcitabine. Results Results from the RNAi screens identified several genes that, when silenced, potentiated the growth inhibitory effects of gemcitabine in pancreatic cancer cells. The greatest potentiation was shown by siRNA targeting checkpoint kinase 1 (CHK1). Validation of the screening results was performed in MIA PaCa-2 and BxPC3 pancreatic cancer cells by examining the dose response of gemcitabine treatment in the presence of either CHK1 or CHK2 siRNA. These results showed a three to ten-fold decrease in the EC50 for CHK1 siRNA-treated cells versus control siRNA-treated cells while treatment with CHK2 siRNA resulted in no change compared to controls. CHK1 was further targeted with specific small molecule inhibitors SB 218078 and PD 407824 in combination with gemcitabine. Results showed that treatment of MIA PaCa-2 cells with either of the CHK1 inhibitors SB 218078 or PD 407824 led to sensitization of the pancreatic cancer cells to gemcitabine. Conclusion These findings demonstrate the effectiveness of synthetic lethal RNAi screening as a tool for identifying sensitizing targets to chemotherapeutic agents. These results also indicate that CHK1 could serve as a putative therapeutic target for sensitizing pancreatic cancer cells to gemcitabine. PMID

  1. Discovery of cancer common and specific driver gene sets

    PubMed Central

    2017-01-01

    Abstract Cancer is known as a disease mainly caused by gene alterations. Discovery of mutated driver pathways or gene sets is becoming an important step to understand molecular mechanisms of carcinogenesis. However, systematically investigating commonalities and specificities of driver gene sets among multiple cancer types is still a great challenge, but this investigation will undoubtedly benefit deciphering cancers and will be helpful for personalized therapy and precision medicine in cancer treatment. In this study, we propose two optimization models to de novo discover common driver gene sets among multiple cancer types (ComMDP) and specific driver gene sets of one certain or multiple cancer types to other cancers (SpeMDP), respectively. We first apply ComMDP and SpeMDP to simulated data to validate their efficiency. Then, we further apply these methods to 12 cancer types from The Cancer Genome Atlas (TCGA) and obtain several biologically meaningful driver pathways. As examples, we construct a common cancer pathway model for BRCA and OV, infer a complex driver pathway model for BRCA carcinogenesis based on common driver gene sets of BRCA with eight cancer types, and investigate specific driver pathways of the liquid cancer lymphoblastic acute myeloid leukemia (LAML) versus other solid cancer types. In these processes more candidate cancer genes are also found. PMID:28168295

  2. Identifying Driver Genomic Alterations in Cancers by Searching Minimum-Weight, Mutually Exclusive Sets

    PubMed Central

    Lu, Songjian; Lu, Kevin N.; Cheng, Shi-Yuan; Hu, Bo; Ma, Xiaojun; Nystrom, Nicholas; Lu, Xinghua

    2015-01-01

    An important goal of cancer genomic research is to identify the driving pathways underlying disease mechanisms and the heterogeneity of cancers. It is well known that somatic genome alterations (SGAs) affecting the genes that encode the proteins within a common signaling pathway exhibit mutual exclusivity, in which these SGAs usually do not co-occur in a tumor. With some success, this characteristic has been utilized as an objective function to guide the search for driver mutations within a pathway. However, mutual exclusivity alone is not sufficient to indicate that genes affected by such SGAs are in common pathways. Here, we propose a novel, signal-oriented framework for identifying driver SGAs. First, we identify the perturbed cellular signals by mining the gene expression data. Next, we search for a set of SGA events that carries strong information with respect to such perturbed signals while exhibiting mutual exclusivity. Finally, we design and implement an efficient exact algorithm to solve an NP-hard problem encountered in our approach. We apply this framework to the ovarian and glioblastoma tumor data available at the TCGA database, and perform systematic evaluations. Our results indicate that the signal-oriented approach enhances the ability to find informative sets of driver SGAs that likely constitute signaling pathways. PMID:26317392

  3. Genome-wide CRISPR screen identifies HNRNPL as a prostate cancer dependency regulating RNA splicing.

    PubMed

    Fei, Teng; Chen, Yiwen; Xiao, Tengfei; Li, Wei; Cato, Laura; Zhang, Peng; Cotter, Maura B; Bowden, Michaela; Lis, Rosina T; Zhao, Shuang G; Wu, Qiu; Feng, Felix Y; Loda, Massimo; He, Housheng Hansen; Liu, X Shirley; Brown, Myles

    2017-06-27

    Alternative RNA splicing plays an important role in cancer. To determine which factors involved in RNA processing are essential in prostate cancer, we performed a genome-wide CRISPR/Cas9 knockout screen to identify the genes that are required for prostate cancer growth. Functional annotation defined a set of essential spliceosome and RNA binding protein (RBP) genes, including most notably heterogeneous nuclear ribonucleoprotein L (HNRNPL). We defined the HNRNPL-bound RNA landscape by RNA immunoprecipitation coupled with next-generation sequencing and linked these RBP-RNA interactions to changes in RNA processing. HNRNPL directly regulates the alternative splicing of a set of RNAs, including those encoding the androgen receptor, the key lineage-specific prostate cancer oncogene. HNRNPL also regulates circular RNA formation via back splicing. Importantly, both HNRNPL and its RNA targets are aberrantly expressed in human prostate tumors, supporting their clinical relevance. Collectively, our data reveal HNRNPL and its RNA clients as players in prostate cancer growth and potential therapeutic targets.

  4. Identification of Significant Gene Signatures and Prognostic Biomarkers for Patients With Cervical Cancer by Integrated Bioinformatic Methods

    PubMed Central

    Li, Xiaofang; Tian, Run; Gao, Hugh; Yan, Feng; Ying, Le; Yang, Yongkang; Yang, Pei

    2018-01-01

    Cervical cancer is the leading cause of death with gynecological malignancies. We aimed to explore the molecular mechanism of carcinogenesis and biomarkers for cervical cancer by integrated bioinformatic analysis. We employed RNA-sequencing details of 254 cervical squamous cell carcinomas and 3 normal samples from The Cancer Genome Atlas. To explore the distinct pathways, messenger RNA expression was submitted to a Gene Set Enrichment Analysis. Kyoto Encyclopedia of Genes and Genomes and protein–protein interaction network analysis of differentially expressed genes were performed. Then, we conducted pathway enrichment analysis for modules acquired in protein–protein interaction analysis and obtained a list of pathways in every module. After intersecting the results from the 3 approaches, we evaluated the survival rates of both mutual pathways and genes in the pathway, and 5 survival-related genes were obtained. Finally, Cox hazards ratio analysis of these 5 genes was performed. DNA replication pathway (P < .001; 12 genes included) was suggested to have the strongest association with the prognosis of cervical squamous cancer. In total, 5 of the 12 genes, namely, minichromosome maintenance 2, minichromosome maintenance 4, minichromosome maintenance 5, proliferating cell nuclear antigen, and ribonuclease H2 subunit A were significantly correlated with survival. Minichromosome maintenance 5 was shown as an independent prognostic biomarker for patients with cervical cancer. This study identified a distinct pathway (DNA replication). Five genes which may be prognostic biomarkers and minichromosome maintenance 5 were identified as independent prognostic biomarkers for patients with cervical cancer. PMID:29642758

  5. Novel Nonsense Variants c.58C>T (p.Q20X) and c.256G>T (p.E85X) in the CHEK2 Gene Identified dentified in Breast Cancer Patients from Balochistan.

    PubMed

    Baloch, Abdul Hameed; Khosa, Ahmad Nawaz; Bangulzai, Nasrullah; Shuja, Jamila; Naseeb, Hafiz Khush; Jan, Mohammad; Marghazani, Illahi Bakhsh; Kakar, Masood-Ul-Haq; Baloch, Dost Mohammad; Cheema, Abdul Majeed; Ahmad, Jamil

    2016-01-01

    Breast cancer is the most commonly occurring and leading cause of cancer deaths among women globally. Hereditary cases account 5-10% of all the cases and CHEK2 is considered as a moderate penetrance breast cancer risk gene. CHEK2 plays a crucial role in response to DNA damage to promote cell cycle arrest and repair DNA damage or induce apoptosis. Our objective in the current study was to analyze mutations in the CHEK2 gene related to breast cancer in Balochistan. A total of 271 individuals including breast cancer patients and normal subjects were enrolled. All 14 exons of CHEK2 were amplified and sequenced. The majority of the patients (>95%) had invasive ductal carcinomas (IDCs), 52.1% were diagnosed with tumor grade III and 56.1% and 27.5% were diagnosed with advance stages III and IV. Two novel nonsense variants i.e. c.58C>T (P.Q20X) and c.256G>T (p.E85X) at exon 1 and 2 in two breast cancer patients were identified in the current study. Both the variants identified were novel and have not been reported elsewhere.

  6. Copy-number and gene dependency analysis reveals partial copy loss of wild-type SF3B1 as a novel cancer vulnerability. | Office of Cancer Genomics

    Cancer.gov

    Genomic instability is a hallmark of human cancer, and results in widespread somatic copy number alterations. We used a genome-scale shRNA viability screen in human cancer cell lines to systematically identify genes that are essential in the context of particular copy-number alterations (copy-number associated gene dependencies). The most enriched class of copy-number associated gene dependencies was CYCLOPS (Copy-number alterations Yielding Cancer Liabilities Owing to Partial losS) genes, and spliceosome components were the most prevalent.

  7. A genome-wide analysis of long noncoding RNA profile identifies differentially expressed lncRNAs associated with Esophageal cancer.

    PubMed

    Liu, Wenjia; Zhang, Yiyang; Chen, Min; Shi, Liangliang; Xu, Lei; Zou, Xiaoping

    2018-06-21

    Esophageal cancer is one of the most common cancers and a leading cause of cancer-related death worldwide. However, the mechanism of esophageal cancer pathogenesis remains poorly understood. Long noncoding RNAs (lncRNAs) dysregulation have been reported to involve in various human cancers, which highlights the potential of lncRNAs used as novel biomarkers for cancer diagnosis. Although more efforts have been made to identify novel lncRNAs signature in esophageal cancer, the expression pattern, prognostic value, and biological function of most lncRNAs in esophageal cancer still need to be systematically investigated. In this study, we comprehensively analyzed the expression profile of lncRNAs in more than 200 esophageal cancer patients tissue samples from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). We identified thousands of lncRNAs are differentially expressed in esophageal cancer tissues, and many of those lncRNAs expression are associated with patients overall survival or recurrence-free survival time. Moreover, copy number variation analyses revealed that genomic loci copy number amplification or deletion might contribute to these lncRNAs dysregulation. Among these lncRNAs, DUXAP8 and LINC00460 were significantly upregulated, and GO enrichment analyses indicated that the two lncRNAs associated protein-coding genes involve with many known biological processes, such as cell cycle and cell-cell adherens junction. Further experimental validation revealed that knockdown of DUXAP8 could impair esophageal cancer cells proliferation and invasion in vitro. Taken together, our findings identified more aberrantly expressed lncRNAs in esophageal cancer that may provide a useful resource for identifying novel esophageal cancer associated lncRNAs. © 2018 The Authors. Cancer Medicine published by John Wiley & Sons Ltd.

  8. Theranostic Imaging of Cancer Gene Therapy.

    PubMed

    Sekar, Thillai V; Paulmurugan, Ramasamy

    2016-01-01

    Gene-directed enzyme prodrug therapy (GDEPT) is a promising therapeutic approach for treating cancers of various phenotypes. This strategy is independent of various other chemotherapeutic drugs used for treating cancers where the drugs are mainly designed to target endogenous cellular mechanisms, which are different in various cancer subtypes. In GDEPT an external enzyme, which is different from the cellular proteins, is expressed to convert the injected prodrug in to a toxic metabolite, that normally kill cancer cells express this protein. Theranostic imaging is an approach used to directly monitor the expression of these gene therapy enzymes while evaluating therapeutic effect. We recently developed a dual-GDEPT system where we combined mutant human herpes simplex thymidine kinase (HSV1sr39TK) and E. coli nitroreductase (NTR) enzyme, to improve therapeutic efficiency of cancer gene therapy by simultaneously injecting two prodrugs at a lower dose. In this approach we use two different prodrugs such as ganciclovir (GCV) and CB1954 to target two different cellular mechanisms to kill cancer cells. The developed dual GDEPT system was highly efficacious than that of either of the system used independently. In this chapter, we describe the complete protocol involved for in vitro and in vivo imaging of therapeutic cancer gene therapy evaluation.

  9. The TERT gene harbors multiple variants associated with pancreatic cancer susceptibility

    PubMed Central

    Campa, Daniele; Rizzato, Cosmeri; Stolzenberg-Solomon, Rachael; Pacetti, Paola; Vodicka, Pavel; Cleary, Sean P.; Capurso, Gabriele; Bueno-de-Mesquita, H. Bas; Werner, Jens; Gazouli, Maria; Butterbach, Katja; Ivanauskas, Audrius; Giese, Nathalia; Petersen, Gloria M.; Fogar, Paola; Wang, Zhaoming; Bassi, Claudio; Ryska, Miroslav; Theodoropoulos, George E.; Kooperberg, Charles; Li, Donghui; Greenhalf, William; Pasquali, Claudio; Hackert, Thilo; Fuchs, Charles S.; Mohelnikova-Duchonova, Beatrice; Sperti, Cosimo; Funel, Niccola; Dieffenbach, Aida Karina; Wareham, Nicholas J.; Buring, Julie; Holcátová, Ivana; Costello, Eithne; Zambon, Carlo-Federico; Kupcinskas, Juozas; Risch, Harvey A.; Kraft, Peter; Bracci, Paige M.; Pezzilli, Raffaele; Olson, Sara H.; Sesso, Howard D.; Hartge, Patricia; Strobel, Oliver; Małecka-Panas, Ewa; Visvanathan, Kala; Arslan, Alan A.; Pedrazzoli, Sergio; Souček, Pavel; Gioffreda, Domenica; Key, Timothy J.; Talar-Wojnarowska, Renata; Scarpa, Aldo; Mambrini, Andrea; Jacobs, Eric J.; Jamroziak, Krzysztof; Klein, Alison; Tavano, Francesca; Bambi, Franco; Landi, Stefano; Austin, Melissa A.; Vodickova, Ludmila; Brenner, Hermann; Chanock, Stephen J.; Fave, Gianfranco Delle; Piepoli, Ada; Cantore, Maurizio; Zheng, Wei; Wolpin, Brian M.; Amundadottir, Laufey T.; Canzian, Federico

    2015-01-01

    A small number of common susceptibility loci have been identified for pancreatic cancer, one of which is marked by rs401681 in the TERT – CLPTM1L gene region on chr5p15.33. Since this region is characterized by low linkage disequilibrium (LD), we sought to identify additional SNPs could be related to pancreatic cancer risk, independently of rs401681. We performed an in-depth analysis of genetic variability of the telomerase reverse transcriptase (TERT) and the telomerase RNA component (TERC) genes, in 5,550 subjects with pancreatic cancer and 7,585 controls from the PANcreatic Disease ReseArch (PANDoRA) and the PanScan consortia. We identified a significant association between a variant in TERT and pancreatic cancer risk (rs2853677, OR=0.85; 95% CI=0.80–0.90, P=8.3×10−8). Additional analysis adjusting rs2853677 for rs401681 indicated that the two SNPs are independently associated with pancreatic cancer risk, as suggested by the low LD between them (r2=0.07, D´=0.28). Three additional SNPs in TERT reached statistical significance after correction for multiple testing: rs2736100 (P=3.0×10−5), rs4583925 (P=4.0×10−5) and rs2735948 (P=5.0×10−5). In conclusion, we confirmed that the TERT locus is associated with pancreatic cancer risk, possibly through several independent variants. PMID:25940397

  10. Biomarkers identified for prostate cancer patients through genome-scale screening.

    PubMed

    Wang, Lei-Yun; Cui, Jia-Jia; Zhu, Tao; Shao, Wei-Hua; Zhao, Yi; Wang, Sai; Zhang, Yu-Peng; Wu, Ji-Chu; Zhang, Le

    2017-11-03

    Prostate cancer is a threat to men and usually occurs in aged males. Though prostate specific antigen level and Gleason score are utilized for evaluation of the prostate cancer in clinic, the biomarkers for this malignancy have not been widely recognized. Furthermore, the outcome varies across individuals receiving comparable treatment regimens and the underlying mechanism is still unclear. We supposed that genetic feature may be responsible for, at least in part, this process and conducted a two-cohort study to compare the genetic difference in tumorous and normal tissues of prostate cancer patients. The Gene Expression Omnibus dataset were used and a total of 41 genes were found significantly differently expressed in tumor tissues as compared with normal prostate tissues. Four genes (SPOCK3, SPON1, PTN and TGFB3) were selected for further evaluation after Gene Ontology analysis, Kyoto Encyclopedia of Genes and Genomes pathway analysis and clinical association analysis. MIR1908 was also found decreased expression level in prostate cancer whose target genes were found expressing in both prostate tumor and normal tissues. These results indicated that these potential biomarkers deserve attention in prostate cancer patients and the underlying mechanism should be further investigated.

  11. MethHC: a database of DNA methylation and gene expression in human cancer.

    PubMed

    Huang, Wei-Yun; Hsu, Sheng-Da; Huang, Hsi-Yuan; Sun, Yi-Ming; Chou, Chih-Hung; Weng, Shun-Long; Huang, Hsien-Da

    2015-01-01

    We present MethHC (http://MethHC.mbc.nctu.edu.tw), a database comprising a systematic integration of a large collection of DNA methylation data and mRNA/microRNA expression profiles in human cancer. DNA methylation is an important epigenetic regulator of gene transcription, and genes with high levels of DNA methylation in their promoter regions are transcriptionally silent. Increasing numbers of DNA methylation and mRNA/microRNA expression profiles are being published in different public repositories. These data can help researchers to identify epigenetic patterns that are important for carcinogenesis. MethHC integrates data such as DNA methylation, mRNA expression, DNA methylation of microRNA gene and microRNA expression to identify correlations between DNA methylation and mRNA/microRNA expression from TCGA (The Cancer Genome Atlas), which includes 18 human cancers in more than 6000 samples, 6548 microarrays and 12 567 RNA sequencing data. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

  12. OGEE v2: an update of the online gene essentiality database with special focus on differentially essential genes in human cancer cell lines.

    PubMed

    Chen, Wei-Hua; Lu, Guanting; Chen, Xiao; Zhao, Xing-Ming; Bork, Peer

    2017-01-04

    OGEE is an Online GEne Essentiality database. To enhance our understanding of the essentiality of genes, in OGEE we collected experimentally tested essential and non-essential genes, as well as associated gene properties known to contribute to gene essentiality. We focus on large-scale experiments, and complement our data with text-mining results. We organized tested genes into data sets according to their sources, and tagged those with variable essentiality statuses across data sets as conditionally essential genes, intending to highlight the complex interplay between gene functions and environments/experimental perturbations. Developments since the last public release include increased numbers of species and gene essentiality data sets, inclusion of non-coding essential sequences and genes with intermediate essentiality statuses. In addition, we included 16 essentiality data sets from cancer cell lines, corresponding to 9 human cancers; with OGEE, users can easily explore the shared and differentially essential genes within and between cancer types. These genes, especially those derived from cell lines that are similar to tumor samples, could reveal the oncogenic drivers, paralogous gene expression pattern and chromosomal structure of the corresponding cancer types, and can be further screened to identify targets for cancer therapy and/or new drug development. OGEE is freely available at http://ogee.medgenius.info. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

  13. Researchers Use a Kinome Screen to Identify New Therapeutic Targets | Office of Cancer Genomics

    Cancer.gov

    The tumor suppressor p53 is mutated in over 50% of head and neck squamous cell carcinomas (HNSCC), yet there are currently no available therapies to target it. CTD2 researchers at the Fred Hutchison Cancer Research Center hypothesized that HNSCC cancer cells with p53 mutations are dependent on particular kinases for survival. In a study published in Clinical Cancer Research, they sought to identify these kinases using RNAi against known kinase genes in mouse and human cell lines.

  14. Genome-scale analysis identifies GJB2 and ERO1LB as prognosis markers in patients with pancreatic cancer.

    PubMed

    Zhu, Tao; Gao, Yuan-Feng; Chen, Yi-Xin; Wang, Zhi-Bin; Yin, Ji-Ye; Mao, Xiao-Yuan; Li, Xi; Zhang, Wei; Zhou, Hong-Hao; Liu, Zhao-Qian

    2017-03-28

    Pancreatic cancer is a complex and heterogeneous disease with the etiology largely unknown. The deadly nature of pancreatic cancer, with an extremely low 5-year survival rate, renders urgent a better understanding of the molecular events underlying it. The aim of this study is to investigate the gene expression module of pancreatic adenocarcinoma and to identify differentially expressed genes (DEGs) with prognostic potentials. Transcriptome microarray data of five GEO datasets (GSE15471, GSE16515, GSE18670, GSE32676, GSE71989), including 117 primary tumor samples and 73 normal pancreatic tissue samples, were utilized to identify DEGs. The five sets of DEGs had an overlapping subset consisting of 98 genes (90 up-regulated and 8 down-regulated), which were probably common to pancreatic cancer. Gene ontology (GO) analysis of the 98 DEGs showed that cell cycle and cell adhesion were the major enriched processes, and extracellular matrix (ECM)-receptor interaction and p53 signaling pathway were the most enriched pathways according to Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Elevated expression of gap junction protein beta 2 (GJB2) and reduced endoplasmic reticulum oxidoreductase 1-like beta (ERO1LB) expression were validated in an independent cohort. Kaplan-Meier survival analysis revealed that GJB2 and ERO1LB levels were significantly associated with the overall survival of pancreatic cancer patients. GJB2 and ERO1LB are implicated in pancreatic cancer progression and can be used to predict patient survival. Therapeutic strategies targeting GJB2 and facilitating ERO1LB expression may deserve evaluation to improve prognosis of pancreatic cancer patients.

  15. Customizing chemotherapy for colon cancer: the potential of gene expression profiling.

    PubMed

    Mariadason, John M; Arango, Diego; Augenlicht, Leonard H

    2004-06-01

    The value of gene expression profiling, or microarray analysis, for the classification and prognosis of multiple forms of cancer is now clearly established. For colon cancer, expression profiling can readily discriminate between normal and tumor tissue, and to some extent between tumors of different histopathological stage and prognosis. While a definitive in vivo study demonstrating the potential of this methodology for predicting response to chemotherapy is presently lacking, the ability of microarrays to distinguish other subtleties of colon cancer phenotype, as well as recent in vitro proof-of-principle experiments utilizing colon cancer cell lines, illustrate the potential of this methodology for predicting the probability of response to specific chemotherapeutic agents. This review discusses some of the recent advances in the use of microarray analysis for understanding and distinguishing colon cancer subtypes, and attempts to identify challenges that need to be overcome in order to achieve the goal of using gene expression profiling for customizing chemotherapy in colon cancer.

  16. Somatic mutations of the histone H3K27 demethylase gene UTX in human cancer.

    PubMed

    van Haaften, Gijs; Dalgliesh, Gillian L; Davies, Helen; Chen, Lina; Bignell, Graham; Greenman, Chris; Edkins, Sarah; Hardy, Claire; O'Meara, Sarah; Teague, Jon; Butler, Adam; Hinton, Jonathan; Latimer, Calli; Andrews, Jenny; Barthorpe, Syd; Beare, Dave; Buck, Gemma; Campbell, Peter J; Cole, Jennifer; Forbes, Simon; Jia, Mingming; Jones, David; Kok, Chai Yin; Leroy, Catherine; Lin, Meng-Lay; McBride, David J; Maddison, Mark; Maquire, Simon; McLay, Kirsten; Menzies, Andrew; Mironenko, Tatiana; Mulderrig, Lee; Mudie, Laura; Pleasance, Erin; Shepherd, Rebecca; Smith, Raffaella; Stebbings, Lucy; Stephens, Philip; Tang, Gurpreet; Tarpey, Patrick S; Turner, Rachel; Turrell, Kelly; Varian, Jennifer; West, Sofie; Widaa, Sara; Wray, Paul; Collins, V Peter; Ichimura, Koichi; Law, Simon; Wong, John; Yuen, Siu Tsan; Leung, Suet Yi; Tonon, Giovanni; DePinho, Ronald A; Tai, Yu-Tzu; Anderson, Kenneth C; Kahnoski, Richard J; Massie, Aaron; Khoo, Sok Kean; Teh, Bin Tean; Stratton, Michael R; Futreal, P Andrew

    2009-05-01

    Somatically acquired epigenetic changes are present in many cancers. Epigenetic regulation is maintained via post-translational modifications of core histones. Here, we describe inactivating somatic mutations in the histone lysine demethylase gene UTX, pointing to histone H3 lysine methylation deregulation in multiple tumor types. UTX reintroduction into cancer cells with inactivating UTX mutations resulted in slowing of proliferation and marked transcriptional changes. These data identify UTX as a new human cancer gene.

  17. Gene delivery for cancer therapy.

    PubMed

    Zhang, Teng

    2014-01-01

    Gene therapy has potential in the treatment of human cancers. However, its clinical implication has only achieved little success due to the lack of an efficient gene delivery system. A major hurdle in the current available approaches is in the ability to transduce target tissues at very high efficiencies that ultimately lead to therapeutic levels of transgene expression. This review outlines the characteristics and utilities of several available gene delivery systems, including their advantages and drawbacks in the context of cancer treatment. A perspective of existing challenges and future directions is also included.

  18. Differentially expressed genes in nonsmall cell lung cancer: expression profiling of cancer-related genes in squamous cell lung cancer.

    PubMed

    Kettunen, Eeva; Anttila, Sisko; Seppänen, Jouni K; Karjalainen, Antti; Edgren, Henrik; Lindström, Irmeli; Salovaara, Reijo; Nissén, Anna-Maria; Salo, Jarmo; Mattson, Karin; Hollmén, Jaakko; Knuutila, Sakari; Wikman, Harriet

    2004-03-01

    The expression patterns of cancer-related genes in 13 cases of squamous cell lung cancer (SCC) were characterized and compared with those in normal lung tissue and 13 adenocarcinomas (AC), the other major type of nonsmall cell lung cancer (NSCLC). cDNA array was used to screen the gene expression levels and the array results were verified using a real-time reverse-transcriptase-polymerase chain reaction (RT-PCR). Thirty-nine percent of the 25 most upregulated and the 25 most downregulated genes were common to SCC and AC. Of these genes, DSP, HMGA1 (alias HMGIY), TIMP1, MIF, CCNB1, TN, MMP11, and MMP12 were upregulated and COPEB (alias CPBP), TYROBP, BENE, BMPR2, SOCS3, TIMP3, CAV1, and CAV2 were downregulated. The expression levels of several genes from distinct protein families (cytokeratins and hemidesmosomal proteins) were markedly increased in SCC compared with AC and normal lung. In addition, several genes, overexpressed in SCC, such as HMGA1, CDK4, IGFBP3, MMP9, MMP11, MMP12, and MMP14, fell into distinct chromosomal loci, which we have detected as gained regions on the basis of comparative genomic hybridization data. Our study revealed new candidate genes involved in NSCLC.

  19. Shared Gene Expression Alterations in Nasal and Bronchial Epithelium for Lung Cancer Detection.

    PubMed

    2017-07-01

    We previously derived and validated a bronchial epithelial gene expression biomarker to detect lung cancer in current and former smokers. Given that bronchial and nasal epithelial gene expression are similarly altered by cigarette smoke exposure, we sought to determine if cancer-associated gene expression might also be detectable in the more readily accessible nasal epithelium. Nasal epithelial brushings were prospectively collected from current and former smokers undergoing diagnostic evaluation for pulmonary lesions suspicious for lung cancer in the AEGIS-1 (n = 375) and AEGIS-2 (n = 130) clinical trials and gene expression profiled using microarrays. All statistical tests were two-sided. We identified 535 genes that were differentially expressed in the nasal epithelium of AEGIS-1 patients diagnosed with lung cancer vs those with benign disease after one year of follow-up ( P  < .001). Using bronchial gene expression data from the AEGIS-1 patients, we found statistically significant concordant cancer-associated gene expression alterations between the two airway sites ( P  < .001). Differentially expressed genes in the nose were enriched for genes associated with the regulation of apoptosis and immune system signaling. A nasal lung cancer classifier derived in the AEGIS-1 cohort that combined clinical factors (age, smoking status, time since quit, mass size) and nasal gene expression (30 genes) had statistically significantly higher area under the curve (0.81; 95% confidence interval [CI] = 0.74 to 0.89, P  = .01) and sensitivity (0.91; 95% CI = 0.81 to 0.97, P  = .03) than a clinical-factor only model in independent samples from the AEGIS-2 cohort. These results support that the airway epithelial field of lung cancer-associated injury in ever smokers extends to the nose and demonstrates the potential of using nasal gene expression as a noninvasive biomarker for lung cancer detection. © The Author 2017. Published by Oxford

  20. Epigenomic study identifies a novel mesenchyme homeobox2-GLI1 transcription axis involved in cancer drug resistance, overall survival and therapy prognosis in lung cancer patients

    PubMed Central

    Armas-López, Leonel; Piña-Sánchez, Patricia; Arrieta, Oscar; de Alba, Enrique Guzman; Ortiz-Quintero, Blanca; Santillán-Doherty, Patricio; Christiani, David C.; Zúñiga, Joaquín; Ávila-Moreno, Federico

    2017-01-01

    Several homeobox-related gene (HOX) transcription factors such as mesenchyme HOX-2 (MEOX2) have previously been associated with cancer drug resistance, malignant progression and/or clinical prognostic responses in lung cancer patients; however, the mechanisms involved in these responses have yet to be elucidated. Here, an epigenomic strategy was implemented to identify novel MEOX2 gene promoter transcription targets and propose a new molecular mechanism underlying lung cancer drug resistance and poor clinical prognosis. Chromatin immunoprecipitation (ChIP) assays derived from non-small cell lung carcinomas (NSCLC) hybridized on gene promoter tiling arrays and bioinformatics analyses were performed, and quantitative, functional and clinical validation were also carried out. We statistically identified a common profile consisting of 78 gene promoter targets, including Hedgehog-GLI1 gene promoter sequences (FDR≤0.1 and FDR≤0.2). The GLI-1 gene promoter region from −2,192 to −109 was occupied by MEOX2, accompanied by transcriptionally active RNA Pol II and was epigenetically linked to the active histones H3K27Ac and H3K4me3; these associations were quantitatively validated. Moreover, siRNA genetic silencing assays identified a MEOX2-GLI1 axis involved in cellular cytotoxic resistance to cisplatinum in a dose-dependent manner, as well as cellular migration and proliferation. Finally, Kaplan-Maier survival analyses identified significant MEOX2-dependent GLI-1 protein expression associated with clinical progression and poorer overall survival using an independent cohort of NSCLC patients undergoing platinum-based oncological therapy with both epidermal growth factor receptor (EGFR)-non-mutated and EGFR-mutated status. In conclusion, this is the first study to investigate epigenome-wide MEOX2-transcription factor occupation identifying a novel overexpressed MEOX2-GLI1 axis and its clinical association with platinum-based cancer drug resistance and EGFR

  1. Prediction of novel target genes and pathways involved in bevacizumab-resistant colorectal cancer

    PubMed Central

    Makondi, Precious Takondwa; Lee, Chia-Hwa; Huang, Chien-Yu; Chu, Chi-Ming; Chang, Yu-Jia

    2018-01-01

    Bevacizumab combined with cytotoxic chemotherapy is the backbone of metastatic colorectal cancer (mCRC) therapy; however, its treatment efficacy is hampered by therapeutic resistance. Therefore, understanding the mechanisms underlying bevacizumab resistance is crucial to increasing the therapeutic efficacy of bevacizumab. The Gene Expression Omnibus (GEO) database (dataset, GSE86525) was used to identify the key genes and pathways involved in bevacizumab-resistant mCRC. The GEO2R web tool was used to identify differentially expressed genes (DEGs). Functional and pathway enrichment analyses of the DEGs were performed using the Database for Annotation, Visualization, and Integrated Discovery(DAVID). Protein–protein interaction (PPI) networks were established using the Search Tool for the Retrieval of Interacting Genes/Proteins database(STRING) and visualized using Cytoscape software. A total of 124 DEGs were obtained, 57 of which upregulated and 67 were downregulated. PPI network analysis showed that seven upregulated genes and nine downregulated genes exhibited high PPI degrees. In the functional enrichment, the DEGs were mainly enriched in negative regulation of phosphate metabolic process and positive regulation of cell cycle process gene ontologies (GOs); the enriched pathways were the phosphoinositide 3-kinase-serine/threonine kinase signaling pathway, bladder cancer, and microRNAs in cancer. Cyclin-dependent kinase inhibitor 1A(CDKN1A), toll-like receptor 4 (TLR4), CD19 molecule (CD19), breast cancer 1, early onset (BRCA1), platelet-derived growth factor subunit A (PDGFA), and matrix metallopeptidase 1 (MMP1) were the DEGs involved in the pathways and the PPIs. The clinical validation of the DEGs in mCRC (TNM clinical stages 3 and 4) revealed that high PDGFA expression levels were associated with poor overall survival, whereas high BRCA1 and MMP1 expression levels were associated with favorable progress free survival(PFS). The identified genes and pathways

  2. Gamma-Retrovirus Integration Marks Cell Type-Specific Cancer Genes: A Novel Profiling Tool in Cancer Genomics.

    PubMed

    Gilroy, Kathryn L; Terry, Anne; Naseer, Asif; de Ridder, Jeroen; Allahyar, Amin; Wang, Weiwei; Carpenter, Eric; Mason, Andrew; Wong, Gane K-S; Cameron, Ewan R; Kilbey, Anna; Neil, James C

    2016-01-01

    Retroviruses have been foundational in cancer research since early studies identified proto-oncogenes as targets for insertional mutagenesis. Integration of murine gamma-retroviruses into the host genome favours promoters and enhancers and entails interaction of viral integrase with host BET/bromodomain factors. We report that this integration pattern is conserved in feline leukaemia virus (FeLV), a gamma-retrovirus that infects many human cell types. Analysis of FeLV insertion sites in the MCF-7 mammary carcinoma cell line revealed strong bias towards active chromatin marks with no evidence of significant post-integration growth selection. The most prominent FeLV integration targets had little overlap with the most abundantly expressed transcripts, but were strongly enriched for annotated cancer genes. A meta-analysis based on several gamma-retrovirus integration profiling (GRIP) studies in human cells (CD34+, K562, HepG2) revealed a similar cancer gene bias but also remarkable cell-type specificity, with prominent exceptions including a universal integration hotspot at the long non-coding RNA MALAT1. Comparison of GRIP targets with databases of super-enhancers from the same cell lines showed that these have only limited overlap and that GRIP provides unique insights into the upstream drivers of cell growth. These observations elucidate the oncogenic potency of the gamma-retroviruses and support the wider application of GRIP to identify the genes and growth regulatory circuits that drive distinct cancer types.

  3. Glycosyltransferase gene expression identifies a poor prognostic colorectal cancer subtype associated with mismatch repair deficiency and incomplete glycan synthesis.

    PubMed

    Noda, Masaru; Okayama, Hirokazu; Tachibana, Kazunoshin; Sakamoto, Wataru; Saito, Katsuharu; Thar Min, Aung Kyi; Ashizawa, Mai; Nakajima, Takahiro; Aoto, Keita; Momma, Tomoyuki; Katakura, Kyoko; Ohki, Shinji; Kono, Koji

    2018-05-29

    We aimed to discover glycosyltransferase gene (glycogene)-derived molecular subtypes of colorectal cancer (CRC) associated with patient outcomes. Transcriptomic and epigenomic datasets of non-tumor, pre-cancerous, cancerous tissues and cell lines with somatic mutations, mismatch repair status, clinicopathological and survival information, were assembled (n=4223) and glycogene profiles were analyzed. Immunohistochemistry for a glycogene, GALNT6, was conducted in adenoma and carcinoma specimens (n=403). The functional role and cell surface glycan profiles were further investigated by in vitro loss-of-function assays and lectin microarray analysis. We initially developed and validated a 15-glycogene signature that can identify a poor-prognostic subtype, which closely related to deficient mismatch repair (dMMR) and GALNT6 downregulation. The association of decreased GALNT6 with dMMR was confirmed in multiple datasets of tumors and cell lines, and was further recapitulated by immunohistochemistry, where approximately 15% tumors exhibited loss of GALNT6 protein. GALNT6 mRNA and protein was expressed in premalignant/preinvasive lesions but was subsequently downregulated in a subset of carcinomas, possibly through epigenetic silencing. Decreased GALNT6 was independently associated with poor prognosis in the immunohistochemistry cohort and an additional microarray meta-cohort, by multivariate analyses, and its discriminative power of survival was particularly remarkable in stage III patients. GALNT6 silencing in SW480 cells promoted invasion, migration, chemoresistance and increased cell surface expression of a cancer-associated truncated O-glycan, Tn-antigen. The 15-glycogene signature and the expression levels of GALNT6 mRNA and protein each serve as a novel prognostic biomarker, highlighting the role of dysregulated glycogenes in cancer-associated glycan synthesis and poor prognosis. Copyright ©2018, American Association for Cancer Research.

  4. Systems Pharmacology-Based Discovery of Natural Products for Precision Oncology Through Targeting Cancer Mutated Genes.

    PubMed

    Fang, J; Cai, C; Wang, Q; Lin, P; Zhao, Z; Cheng, F

    2017-03-01

    Massive cancer genomics data have facilitated the rapid revolution of a novel oncology drug discovery paradigm through targeting clinically relevant driver genes or mutations for the development of precision oncology. Natural products with polypharmacological profiles have been demonstrated as promising agents for the development of novel cancer therapies. In this study, we developed an integrated systems pharmacology framework that facilitated identifying potential natural products that target mutated genes across 15 cancer types or subtypes in the realm of precision medicine. High performance was achieved for our systems pharmacology framework. In case studies, we computationally identified novel anticancer indications for several US Food and Drug Administration-approved or clinically investigational natural products (e.g., resveratrol, quercetin, genistein, and fisetin) through targeting significantly mutated genes in multiple cancer types. In summary, this study provides a powerful tool for the development of molecularly targeted cancer therapies through targeting the clinically actionable alterations by exploiting the systems pharmacology of natural products. © 2017 The Authors CPT: Pharmacometrics & Systems Pharmacology published by Wiley Periodicals, Inc. on behalf of American Society for Clinical Pharmacology and Therapeutics.

  5. Frequency of pathogenic germline mutations in cancer susceptibility genes in breast cancer patients.

    PubMed

    Kaur, Raman Preet; Shafi, Gowhar; Benipal, Raja Paramjeet Singh; Munshi, Anjana

    2018-04-26

    In this study, we evaluated the incidence of pathogenic germline mutations in 30 breast cancer susceptibility genes in breast cancer patients. Our aim was to understand the involvement of the inherited mutations in these genes in a breast cancer cohort. Two hundred ninety-six female breast cancer patients including 4.5% of familial breast cancer cases were included in the study. 200 ng of genomic DNA was used to evaluate the pathogenic mutations, detected using Global Screening Array (GSA) microchip (Illumina Inc.) according to the manufacturer's instructions. The pathogenic frameshift and nonsense mutations were observed in BRCA2 (10.9%), MLH1 (58.6%), MTHFR (50%), MSH2 (14.2%), and CYTB (52%) genes. Familial breast cancer patients (4.5%) had variations in BRCA2, MLH1, MSH2, and CYTB genes. 28% of patients with metastasis, recurrence, and death harbored mono/biallelic alterations in MSH2, MLH1, and BRCA2 genes. The results of this study can guide to develop a panel to test the breast cancer patients for pathogenic mutations, from Malwa region of Punjab. The screening of MSH2, MLH1, and BRCA2 should be carried in individuals with or without family history of breast cancer as these genes have been reported to increase the cancer risk by tenfold.

  6. Significant associations between driver gene mutations and DNA methylation alterations across many cancer types

    PubMed Central

    Chen, Yun-Ching; Margolin, Gennady

    2017-01-01

    Recent evidence shows that mutations in several driver genes can cause aberrant methylation patterns, a hallmark of cancer. In light of these findings, we hypothesized that the landscapes of tumor genomes and epigenomes are tightly interconnected. We measured this relationship using principal component analyses and methylation-mutation associations applied at the nucleotide level and with respect to genome-wide trends. We found that a few mutated driver genes were associated with genome-wide patterns of aberrant hypomethylation or CpG island hypermethylation in specific cancer types. In addition, we identified associations between 737 mutated driver genes and site-specific methylation changes. Moreover, using these mutation-methylation associations, we were able to distinguish between two uterine and two thyroid cancer subtypes. The driver gene mutation–associated methylation differences between the thyroid cancer subtypes were linked to differential gene expression in JAK-STAT signaling, NADPH oxidation, and other cancer-related pathways. These results establish that driver gene mutations are associated with methylation alterations capable of shaping regulatory network functions. In addition, the methodology presented here can be used to subdivide tumors into more homogeneous subsets corresponding to underlying molecular characteristics, which could improve treatment efficacy. PMID:29125844

  7. Genome-wide Meta-analyses of Breast, Ovarian and Prostate Cancer Association Studies Identify Multiple New Susceptibility Loci Shared by At Least Two Cancer Types

    PubMed Central

    Kar, Siddhartha P.; Beesley, Jonathan; Al Olama, Ali Amin; Michailidou, Kyriaki; Tyrer, Jonathan; Kote-Jarai, ZSofia; Lawrenson, Kate; Lindstrom, Sara; Ramus, Susan J.; Thompson, Deborah J.; Kibel, Adam S.; Dansonka-Mieszkowska, Agnieszka; Michael, Agnieszka; Dieffenbach, Aida K.; Gentry-Maharaj, Aleksandra; Whittemore, Alice S.; Wolk, Alicja; Monteiro, Alvaro; Peixoto, Ana; Kierzek, Andrzej; Cox, Angela; Rudolph, Anja; Gonzalez-Neira, Anna; Wu, Anna H.; Lindblom, Annika; Swerdlow, Anthony; Ziogas, Argyrios; Ekici, Arif B.; Burwinkel, Barbara; Karlan, Beth Y.; Nordestgaard, Børge G.; Blomqvist, Carl; Phelan, Catherine; McLean, Catriona; Pearce, Celeste Leigh; Vachon, Celine; Cybulski, Cezary; Slavov, Chavdar; Stegmaier, Christa; Maier, Christiane; Ambrosone, Christine B.; Høgdall, Claus K.; Teerlink, Craig C.; Kang, Daehee; Tessier, Daniel C.; Schaid, Daniel J.; Stram, Daniel O.; Cramer, Daniel W.; Neal, David E.; Eccles, Diana; Flesch-Janys, Dieter; Velez Edwards, Digna R.; Wokozorczyk, Dominika; Levine, Douglas A.; Yannoukakos, Drakoulis; Sawyer, Elinor J.; Bandera, Elisa V.; Poole, Elizabeth M.; Goode, Ellen L.; Khusnutdinova, Elza; Høgdall, Estrid; Song, Fengju; Bruinsma, Fiona; Heitz, Florian; Modugno, Francesmary; Hamdy, Freddie C.; Wiklund, Fredrik; Giles, Graham G.; Olsson, Håkan; Wildiers, Hans; Ulmer, Hans-Ulrich; Pandha, Hardev; Risch, Harvey A.; Darabi, Hatef; Salvesen, Helga B.; Nevanlinna, Heli; Gronberg, Henrik; Brenner, Hermann; Brauch, Hiltrud; Anton-Culver, Hoda; Song, Honglin; Lim, Hui-Yi; McNeish, Iain; Campbell, Ian; Vergote, Ignace; Gronwald, Jacek; Lubiński, Jan; Stanford, Janet L.; Benítez, Javier; Doherty, Jennifer A.; Permuth, Jennifer B.; Chang-Claude, Jenny; Donovan, Jenny L.; Dennis, Joe; Schildkraut, Joellen M.; Schleutker, Johanna; Hopper, John L.; Kupryjanczyk, Jolanta; Park, Jong Y.; Figueroa, Jonine; Clements, Judith A.; Knight, Julia A.; Peto, Julian; Cunningham, Julie M.; Pow-Sang, Julio; Batra, Jyotsna; Czene, Kamila; Lu, Karen H.; Herkommer, Kathleen; Khaw, Kay-Tee; Matsuo, Keitaro; Muir, Kenneth; Offitt, Kenneth; Chen, Kexin; Moysich, Kirsten B.; Aittomäki, Kristiina; Odunsi, Kunle; Kiemeney, Lambertus A.; Massuger, Leon F.A.G.; Fitzgerald, Liesel M.; Cook, Linda S.; Cannon-Albright, Lisa; Hooning, Maartje J.; Pike, Malcolm C.; Bolla, Manjeet K.; Luedeke, Manuel; Teixeira, Manuel R.; Goodman, Marc T.; Schmidt, Marjanka K.; Riggan, Marjorie; Aly, Markus; Rossing, Mary Anne; Beckmann, Matthias W.; Moisse, Matthieu; Sanderson, Maureen; Southey, Melissa C.; Jones, Michael; Lush, Michael; Hildebrandt, Michelle A. T.; Hou, Ming-Feng; Schoemaker, Minouk J.; Garcia-Closas, Montserrat; Bogdanova, Natalia; Rahman, Nazneen; Le, Nhu D.; Orr, Nick; Wentzensen, Nicolas; Pashayan, Nora; Peterlongo, Paolo; Guénel, Pascal; Brennan, Paul; Paulo, Paula; Webb, Penelope M.; Broberg, Per; Fasching, Peter A.; Devilee, Peter; Wang, Qin; Cai, Qiuyin; Li, Qiyuan; Kaneva, Radka; Butzow, Ralf; Kopperud, Reidun Kristin; Schmutzler, Rita K.; Stephenson, Robert A.; MacInnis, Robert J.; Hoover, Robert N.; Winqvist, Robert; Ness, Roberta; Milne, Roger L.; Travis, Ruth C.; Benlloch, Sara; Olson, Sara H.; McDonnell, Shannon K.; Tworoger, Shelley S.; Maia, Sofia; Berndt, Sonja; Lee, Soo Chin; Teo, Soo-Hwang; Thibodeau, Stephen N.; Bojesen, Stig E.; Gapstur, Susan M.; Kjær, Susanne Krüger; Pejovic, Tanja; Tammela, Teuvo L.J.; Dörk, Thilo; Brüning, Thomas; Wahlfors, Tiina; Key, Tim J.; Edwards, Todd L.; Menon, Usha; Hamann, Ute; Mitev, Vanio; Kosma, Veli-Matti; Setiawan, Veronica Wendy; Kristensen, Vessela; Arndt, Volker; Vogel, Walther; Zheng, Wei; Sieh, Weiva; Blot, William J.; Kluzniak, Wojciech; Shu, Xiao-Ou; Gao, Yu-Tang; Schumacher, Fredrick; Freedman, Matthew L.; Berchuck, Andrew; Dunning, Alison M.; Simard, Jacques; Haiman, Christopher A.; Spurdle, Amanda; Sellers, Thomas A.; Hunter, David J.; Henderson, Brian E.; Kraft, Peter; Chanock, Stephen J.; Couch, Fergus J.; Hall, Per; Gayther, Simon A.; Easton, Douglas F.; Chenevix-Trench, Georgia; Eeles, Rosalind; Pharoah, Paul D.P.; Lambrechts, Diether

    2016-01-01

    Breast, ovarian, and prostate cancers are hormone-related and may have a shared genetic basis but this has not been investigated systematically by genome-wide association (GWA) studies. Meta-analyses combining the largest GWA meta-analysis data sets for these cancers totaling 112,349 cases and 116,421 controls of European ancestry, all together and in pairs, identified at P < 10−8 seven new cross-cancer loci: three associated with susceptibility to all three cancers (rs17041869/2q13/BCL2L11; rs7937840/11q12/INCENP; rs1469713/19p13/GATAD2A), two breast and ovarian cancer risk loci (rs200182588/9q31/SMC2; rs8037137/15q26/RCCD1), and two breast and prostate cancer risk loci (rs5013329/1p34/NSUN4; rs9375701/6q23/L3MBTL3). Index variants in five additional regions previously associated with only one cancer also showed clear association with a second cancer type. Cell-type specific expression quantitative trait locus and enhancer-gene interaction annotations suggested target genes with potential cross-cancer roles at the new loci. Pathway analysis revealed significant enrichment of death receptor signaling genes near loci with P < 10−5 in the three-cancer meta-analysis. PMID:27432226

  8. Transgelin gene is frequently downregulated by promoter DNA hypermethylation in breast cancer.

    PubMed

    Sayar, Nilufer; Karahan, Gurbet; Konu, Ozlen; Bozkurt, Betul; Bozdogan, Onder; Yulug, Isik G

    2015-01-01

    CpG hypermethylation in gene promoters is a frequent mechanism of tumor suppressor gene silencing in various types of cancers. It usually occurs at early steps of cancer progression and can be detected easily, giving rise to development of promising biomarkers for both detection and progression of cancer, including breast cancer. 5-aza-2'-deoxycytidine (AZA) is a DNA demethylating and anti-cancer agent resulting in induction of genes suppressed via DNA hypermethylation. Using microarray expression profiling of AZA- or DMSO-treated breast cancer and non-tumorigenic breast (NTB) cells, we identified for the first time TAGLN gene as a target of DNA hypermethylation in breast cancer. TAGLN expression was significantly and frequently downregulated via promoter DNA hypermethylation in breast cancer cells compared to NTB cells, and also in 13/21 (61.9 %) of breast tumors compared to matched normal tissues. Analyses of public microarray methylation data showed that TAGLN was also hypermethylated in 63.02 % of tumors compared to normal tissues; relapse-free survival of patients was worse with higher TAGLN methylation; and methylation levels could discriminate between tumors and healthy tissues with 83.14 % sensitivity and 100 % specificity. Additionally, qRT-PCR and immunohistochemistry experiments showed that TAGLN expression was significantly downregulated in two more independent sets of breast tumors compared to normal tissues and was lower in tumors with poor prognosis. Colony formation was increased in TAGLN silenced NTB cells, while decreased in overexpressing BC cells. TAGLN gene is frequently downregulated by DNA hypermethylation, and TAGLN promoter methylation profiles could serve as a future diagnostic biomarker, with possible clinical impact regarding the prognosis in breast cancer.

  9. SomInaClust: detection of cancer genes based on somatic mutation patterns of inactivation and clustering.

    PubMed

    Van den Eynden, Jimmy; Fierro, Ana Carolina; Verbeke, Lieven P C; Marchal, Kathleen

    2015-04-23

    With the advances in high throughput technologies, increasing amounts of cancer somatic mutation data are being generated and made available. Only a small number of (driver) mutations occur in driver genes and are responsible for carcinogenesis, while the majority of (passenger) mutations do not influence tumour biology. In this study, SomInaClust is introduced, a method that accurately identifies driver genes based on their mutation pattern across tumour samples and then classifies them into oncogenes or tumour suppressor genes respectively. SomInaClust starts from the observation that oncogenes mainly contain mutations that, due to positive selection, cluster at similar positions in a gene across patient samples, whereas tumour suppressor genes contain a high number of protein-truncating mutations throughout the entire gene length. The method was shown to prioritize driver genes in 9 different solid cancers. Furthermore it was found to be complementary to existing similar-purpose methods with the additional advantages that it has a higher sensitivity, also for rare mutations (occurring in less than 1% of all samples), and it accurately classifies candidate driver genes in putative oncogenes and tumour suppressor genes. Pathway enrichment analysis showed that the identified genes belong to known cancer signalling pathways, and that the distinction between oncogenes and tumour suppressor genes is biologically relevant. SomInaClust was shown to detect candidate driver genes based on somatic mutation patterns of inactivation and clustering and to distinguish oncogenes from tumour suppressor genes. The method could be used for the identification of new cancer genes or to filter mutation data for further data-integration purposes.

  10. Five endometrial cancer risk loci identified through genome-wide association analysis.

    PubMed

    Cheng, Timothy Ht; Thompson, Deborah J; O'Mara, Tracy A; Painter, Jodie N; Glubb, Dylan M; Flach, Susanne; Lewis, Annabelle; French, Juliet D; Freeman-Mills, Luke; Church, David; Gorman, Maggie; Martin, Lynn; Hodgson, Shirley; Webb, Penelope M; Attia, John; Holliday, Elizabeth G; McEvoy, Mark; Scott, Rodney J; Henders, Anjali K; Martin, Nicholas G; Montgomery, Grant W; Nyholt, Dale R; Ahmed, Shahana; Healey, Catherine S; Shah, Mitul; Dennis, Joe; Fasching, Peter A; Beckmann, Matthias W; Hein, Alexander; Ekici, Arif B; Hall, Per; Czene, Kamila; Darabi, Hatef; Li, Jingmei; Dörk, Thilo; Dürst, Matthias; Hillemanns, Peter; Runnebaum, Ingo; Amant, Frederic; Schrauwen, Stefanie; Zhao, Hui; Lambrechts, Diether; Depreeuw, Jeroen; Dowdy, Sean C; Goode, Ellen L; Fridley, Brooke L; Winham, Stacey J; Njølstad, Tormund S; Salvesen, Helga B; Trovik, Jone; Werner, Henrica Mj; Ashton, Katie; Otton, Geoffrey; Proietto, Tony; Liu, Tao; Mints, Miriam; Tham, Emma; Consortium, Chibcha; Jun Li, Mulin; Yip, Shun H; Wang, Junwen; Bolla, Manjeet K; Michailidou, Kyriaki; Wang, Qin; Tyrer, Jonathan P; Dunlop, Malcolm; Houlston, Richard; Palles, Claire; Hopper, John L; Peto, Julian; Swerdlow, Anthony J; Burwinkel, Barbara; Brenner, Hermann; Meindl, Alfons; Brauch, Hiltrud; Lindblom, Annika; Chang-Claude, Jenny; Couch, Fergus J; Giles, Graham G; Kristensen, Vessela N; Cox, Angela; Cunningham, Julie M; Pharoah, Paul D P; Dunning, Alison M; Edwards, Stacey L; Easton, Douglas F; Tomlinson, Ian; Spurdle, Amanda B

    2016-06-01

    We conducted a meta-analysis of three endometrial cancer genome-wide association studies (GWAS) and two follow-up phases totaling 7,737 endometrial cancer cases and 37,144 controls of European ancestry. Genome-wide imputation and meta-analysis identified five new risk loci of genome-wide significance at likely regulatory regions on chromosomes 13q22.1 (rs11841589, near KLF5), 6q22.31 (rs13328298, in LOC643623 and near HEY2 and NCOA7), 8q24.21 (rs4733613, telomeric to MYC), 15q15.1 (rs937213, in EIF2AK4, near BMF) and 14q32.33 (rs2498796, in AKT1, near SIVA1). We also found a second independent 8q24.21 signal (rs17232730). Functional studies of the 13q22.1 locus showed that rs9600103 (pairwise r(2) = 0.98 with rs11841589) is located in a region of active chromatin that interacts with the KLF5 promoter region. The rs9600103[T] allele that is protective in endometrial cancer suppressed gene expression in vitro, suggesting that regulation of the expression of KLF5, a gene linked to uterine development, is implicated in tumorigenesis. These findings provide enhanced insight into the genetic and biological basis of endometrial cancer.

  11. Identification of a Variety of Mutations in Cancer Predisposition Genes in Patients With Suspected Lynch Syndrome.

    PubMed

    Yurgelun, Matthew B; Allen, Brian; Kaldate, Rajesh R; Bowles, Karla R; Judkins, Thaddeus; Kaushik, Praveen; Roa, Benjamin B; Wenstrup, Richard J; Hartman, Anne-Renee; Syngal, Sapna

    2015-09-01

    Multigene panels are commercially available tools for hereditary cancer risk assessment that allow for next-generation sequencing of numerous genes in parallel. However, it is not clear if these panels offer advantages over traditional genetic testing. We investigated the number of cancer predisposition gene mutations identified by parallel sequencing in individuals with suspected Lynch syndrome. We performed germline analysis with a 25-gene, next-generation sequencing panel using DNA from 1260 individuals who underwent clinical genetic testing for Lynch syndrome from 2012 through 2013. All patients had a history of Lynch syndrome-associated cancer and/or polyps. We classified all identified germline alterations for pathogenicity and calculated the frequencies of pathogenic mutations and variants of uncertain clinical significance (VUS). We also analyzed data on patients' personal and family history of cancer, including fulfillment of clinical guidelines for genetic testing. Of the 1260 patients, 1112 met National Comprehensive Cancer Network (NCCN) criteria for Lynch syndrome testing (88%; 95% confidence interval [CI], 86%-90%). Multigene panel testing identified 114 probands with Lynch syndrome mutations (9.0%; 95% CI, 7.6%-10.8%) and 71 with mutations in other cancer predisposition genes (5.6%; 95% CI, 4.4%-7.1%). Fifteen individuals had mutations in BRCA1 or BRCA2; 93% of these met the NCCN criteria for Lynch syndrome testing and 33% met NCCN criteria for BRCA1 and BRCA2 analysis (P = .0017). An additional 9 individuals carried mutations in other genes linked to high lifetime risks of cancer (5 had mutations in APC, 3 had bi-allelic mutations in MUTYH, and 1 had a mutation in STK11); all of these patients met NCCN criteria for Lynch syndrome testing. A total of 479 individuals had 1 or more VUS (38%; 95% CI, 35%-41%). In individuals with suspected Lynch syndrome, multigene panel testing identified high-penetrance mutations in cancer predisposition genes, many

  12. Prospectively Identified Incident Testicular Cancer Risk in a Familial Testicular Cancer Cohort.

    PubMed

    Pathak, Anand; Adams, Charleen D; Loud, Jennifer T; Nichols, Kathryn; Stewart, Douglas R; Greene, Mark H

    2015-10-01

    Human testicular germ cell tumors (TGCT) have a strong genetic component and a high familial relative risk. However, linkage analyses have not identified a rare, highly penetrant familial TGCT (FTGCT) susceptibility locus. Currently, multiple low-penetrance genes are hypothesized to underlie the familial multiple-case phenotype. The observation that two is the most common number of affected individuals per family presents an impediment to FTGCT gene discovery. Clinically, the prospective TGCT risk in the multiple-case family context is unknown. We performed a prospective analysis of TGCT incidence in a cohort of multiple-affected-person families and sporadic-bilateral-case families; 1,260 men from 140 families (10,207 person-years of follow-up) met our inclusion criteria. Age-, gender-, and calendar time-specific standardized incidence ratios (SIR) for TGCT relative to the general population were calculated using SEER*Stat. Eight incident TGCTs occurred during prospective FTGCT cohort follow-up (versus 0.67 expected; SIR = 11.9; 95% CI, 5.1-23.4; excess absolute risk = 7.2/10,000). We demonstrate that the incidence rate of TGCT is greater among bloodline male relatives from multiple-case testicular cancer families than that expected in the general population, a pattern characteristic of adult-onset Mendelian cancer susceptibility disorders. Two of these incident TGCTs occurred in relatives of sporadic-bilateral cases (0.15 expected; SIR = 13.4; 95% CI, 1.6-48.6). Our data are the first to indicate that despite relatively low numbers of affected individuals per family, members of both multiple-affected-person FTGCT families and sporadic-bilateral TGCT families comprise high-risk groups for incident testicular cancer. Men at high TGCT risk might benefit from tailored risk stratification and surveillance strategies. ©2015 American Association for Cancer Research.

  13. Targeted polymeric nanoparticles for cancer gene therapy

    PubMed Central

    Kim, Jayoung; Wilson, David R.; Zamboni, Camila G.; Green, Jordan J.

    2015-01-01

    In this article, advances in designing polymeric nanoparticles for targeted cancer gene therapy are reviewed. Characterization and evaluation of biomaterials, targeting ligands, and transcriptional elements are each discussed. Advances in biomaterials have driven improvements to nanoparticle stability and tissue targeting, conjugation of ligands to the surface of polymeric nanoparticles enable binding to specific cancer cells, and the design of transcriptional elements has enabled selective DNA expression specific to the cancer cells. Together, these features have improved the performance of polymeric nanoparticles as targeted non-viral gene delivery vectors to treat cancer. As polymeric nanoparticles can be designed to be biodegradable, non-toxic, and to have reduced immunogenicity and tumorigenicity compared to viral platforms, they have significant potential for clinical use. Results of polymeric gene therapy in clinical trials and future directions for the engineering of nanoparticle systems for targeted cancer gene therapy are also presented. PMID:26061296

  14. The low-abundance transcriptome reveals novel biomarkers, specific intracellular pathways and targetable genes associated with advanced gastric cancer.

    PubMed

    Bizama, Carolina; Benavente, Felipe; Salvatierra, Edgardo; Gutiérrez-Moraga, Ana; Espinoza, Jaime A; Fernández, Elmer A; Roa, Iván; Mazzolini, Guillermo; Sagredo, Eduardo A; Gidekel, Manuel; Podhajcer, Osvaldo L

    2014-02-15

    Studies on the low-abundance transcriptome are of paramount importance for identifying the intimate mechanisms of tumor progression that can lead to novel therapies. The aim of the present study was to identify novel markers and targetable genes and pathways in advanced human gastric cancer through analyses of the low-abundance transcriptome. The procedure involved an initial subtractive hybridization step, followed by global gene expression analysis using microarrays. We observed profound differences, both at the single gene and gene ontology levels, between the low-abundance transcriptome and the whole transcriptome. Analysis of the low-abundance transcriptome led to the identification and validation by tissue microarrays of novel biomarkers, such as LAMA3 and TTN; moreover, we identified cancer type-specific intracellular pathways and targetable genes, such as IRS2, IL17, IFNγ, VEGF-C, WISP1, FZD5 and CTBP1 that were not detectable by whole transcriptome analyses. We also demonstrated that knocking down the expression of CTBP1 sensitized gastric cancer cells to mainstay chemotherapeutic drugs. We conclude that the analysis of the low-abundance transcriptome provides useful insights into the molecular basis and treatment of cancer. © 2013 UICC.

  15. Integration of high-risk human papillomavirus into cellular cancer-related genes in head and neck cancer cell lines.

    PubMed

    Walline, Heather M; Goudsmit, Christine M; McHugh, Jonathan B; Tang, Alice L; Owen, John H; Teh, Bin T; McKean, Erin; Glover, Thomas W; Graham, Martin P; Prince, Mark E; Chepeha, Douglas B; Chinn, Steven B; Ferris, Robert L; Gollin, Susanne M; Hoffmann, Thomas K; Bier, Henning; Brakenhoff, Ruud; Bradford, Carol R; Carey, Thomas E

    2017-05-01

    Human papillomavirus (HPV)-positive oropharyngeal cancer is generally associated with excellent response to therapy, but some HPV-positive tumors progress despite aggressive therapy. The purpose of this study was to evaluate viral oncogene expression and viral integration sites in HPV16- and HPV18-positive squamous cell carcinoma lines. E6/E7 alternate transcripts were assessed by reverse transcriptase-polymerase chain reaction (RT-PCR). Detection of integrated papillomavirus sequences (DIPS-PCR) and sequencing identified viral insertion sites and affected host genes. Cellular gene expression was assessed across viral integration sites. All HPV-positive cell lines expressed alternate HPVE6/E7 splicing indicative of active viral oncogenesis. HPV integration occurred within cancer-related genes TP63, DCC, JAK1, TERT, ATR, ETV6, PGR, PTPRN2, and TMEM237 in 8 head and neck squamous cell carcinoma (HNSCC) lines but UM-SCC-105 and UM-GCC-1 had only intergenic integration. HPV integration into cancer-related genes occurred in 7 of 9 HPV-positive cell lines and of these 6 were from tumors that progressed. HPV integration into cancer-related genes may be a secondary carcinogenic driver in HPV-driven tumors. © 2017 Wiley Periodicals, Inc. Head Neck 39: 840-852, 2017. © 2017 Wiley Periodicals, Inc.

  16. Differential Gene Expression in Benign Prostate Epithelium of Men with and without Prostate Cancer: Evidence for a Prostate Cancer Field Effect

    PubMed Central

    Risk, Michael C; Knudsen, Beatrice S; Coleman, Ilsa; Dumpit, Ruth F; Kristal, Alan R; LeMeur, Nolwenn; Gentleman, Robert C; True, Lawrence D; Nelson, Peter S; Lin, Daniel W

    2010-01-01

    Background Several malignancies are known to exhibit a “field-effect” whereby regions beyond tumor boundaries harbor histological or molecular changes that are associated with cancer. We sought to determine if histologically benign prostate epithelium collected from men with prostate cancer exhibits features indicative of pre-malignancy or field effect. Methods Prostate needle biopsies from 15 men with high grade(Gleason 8–10) prostate cancer and 15 age- and BMI-matched controls were identified from a biospecimen repository. Benign epithelia from each patient were isolated by laser capture microdissection. RNA was isolated, amplified, and used for microarray hybridization. Quantitative PCR(qPCR) was used to determine the expression of specific genes of interest. Alterations in protein expression were analyzed through immunohistochemistry. Results Overall patterns of gene expression in microdissected benign-associated benign epithelium (BABE) and cancer-associated benign epithelium (CABE) were similar. Two genes previously associated with prostate cancer, PSMA and SSTR1, were significantly upregulated in the CABE group(FDR <1%). Expression of other prostate cancer-associated genes, including ERG, HOXC4, HOXC5 and MME, were also increased in CABE by qRT-PCR, although other genes commonly altered in prostate cancer were not different between the BABE and CABE samples. The expression of MME and PSMA proteins on IHC coincided with their mRNA alterations. Conclusion Gene expression profiles between benign epithelia of patients with and without prostate cancer are very similar. However, these tissues exhibit differences in the expression levels of several genes previously associated with prostate cancer development or progression. These differences may comprise a field effect and represent early events in carcinogenesis. PMID:20935156

  17. Prognostic significance of aberrant gene methylation in gastric cancer.

    PubMed

    Shi, Jing; Zhang, Guanjun; Yao, Demao; Liu, Wei; Wang, Na; Ji, Meiju; He, Nongyue; Shi, Bingyin; Hou, Peng

    2012-01-01

    Promoter methylation acts as an important alternative to genetic alterations for gene inactivation in gastric carcinogenesis. Although a number of gastric cancer-associated genes have been found to be methylated in gastric cancer, valuable methylation markers for early diagnosis and prognostic evaluation of this cancer remain largely unknown. In the present study, we used methylation-specific PCR (MSP) to analyze promoter methylation of 9 gastric cancer-associated genes, including MLF1, MGMT, p16, RASSF2, hMLH1, HAND1, HRASLS, TM, and FLNc, and their association with clinicopathological characteristics and clinical outcome in a large cohort of gastric cancers. Our data showed that all of these genes were aberrantly methylated in gastric cancer, ranging from 8% to 51%. Moreover, gene methylation was strongly associated with certain clinicopathological characteristics, such as tumor differentiation, lymph node metastasis, and cancer-related death. Of interest, methylation of MGMT, p16, RASSF2, hMLH1, HAND1, and FLNc was closely associated with poor survival in gastric cancer, particularly MGMT, p16, RASSF2 and FLNc. Thus, our findings suggested these epigenetic events may contribute to the initiation and progression of gastric cancer. Importantly, methylation of some genes were closely relevant to poor prognosis in gastric cancer, providing the strong evidences that these hypermethylated genes may be served as valuable biomarkers for prognostic evaluation in this cancer.

  18. Prognostic significance of aberrant gene methylation in gastric cancer

    PubMed Central

    Shi, Jing; Zhang, Guanjun; Yao, Demao; Liu, Wei; Wang, Na; Ji, Meiju; He, Nongyue; Shi, Bingyin; Hou, Peng

    2012-01-01

    Promoter methylation acts as an important alternative to genetic alterations for gene inactivation in gastric carcinogenesis. Although a number of gastric cancer-associated genes have been found to be methylated in gastric cancer, valuable methylation markers for early diagnosis and prognostic evaluation of this cancer remain largely unknown. In the present study, we used methylation-specific PCR (MSP) to analyze promoter methylation of 9 gastric cancer-associated genes, including MLF1, MGMT, p16, RASSF2, hMLH1, HAND1, HRASLS, TM, and FLNc, and their association with clinicopathological characteristics and clinical outcome in a large cohort of gastric cancers. Our data showed that all of these genes were aberrantly methylated in gastric cancer, ranging from 8% to 51%. Moreover, gene methylation was strongly associated with certain clinicopathological characteristics, such as tumor differentiation, lymph node metastasis, and cancer-related death. Of interest, methylation of MGMT, p16, RASSF2, hMLH1, HAND1, and FLNc was closely associated with poor survival in gastric cancer, particularly MGMT, p16, RASSF2 and FLNc. Thus, our findings suggested these epigenetic events may contribute to the initiation and progression of gastric cancer. Importantly, methylation of some genes were closely relevant to poor prognosis in gastric cancer, providing the strong evidences that these hypermethylated genes may be served as valuable biomarkers for prognostic evaluation in this cancer. PMID:22206050

  19. Characterization of Novel Genes Within 8P11-12 Amplicon in Breast Cancer

    DTIC Science & Technology

    2007-06-01

    C-myc amplification in breast cancer: a meta - analysis of its occurrence and prognostic relevance. Br J Cancer, 83: 1688-1695, 2000. 2. Hui, R...Nass SJ, Dickson RB, Trock BJ. C-myc amplification in breast cancer: a meta - analysis of its occurrence and prognostic relevance. Br J Cancer 2000;83...a detailed genomic and expression analysis of the 8p11-p12 amplicon in breast cancer cell lines and identified several novel candidate genes

  20. Potential Susceptibility Loci Identified for Renal Cell Carcinoma by Targeting Obesity-Related Genes.

    PubMed

    Shu, Xiang; Purdue, Mark P; Ye, Yuanqing; Tu, Huakang; Wood, Christopher G; Tannir, Nizar M; Wang, Zhaoming; Albanes, Demetrius; Gapstur, Susan M; Stevens, Victoria L; Rothman, Nathaniel; Chanock, Stephen J; Wu, Xifeng

    2017-09-01

    Background: Obesity is an established risk factor for renal cell carcinoma (RCC). Although genome-wide association studies (GWAS) of RCC have identified several susceptibility loci, additional variants might be missed due to the highly conservative selection. Methods: We conducted a multiphase study utilizing three independent genome-wide scans at MD Anderson Cancer Center (MDA RCC GWAS and MDA RCC OncoArray) and National Cancer Institute (NCI RCC GWAS), which consisted of a total of 3,530 cases and 5,714 controls, to investigate genetic variations in obesity-related genes and RCC risk. Results: In the discovery phase, 32,946 SNPs located at ±10 kb of 2,001 obesity-related genes were extracted from MDA RCC GWAS and analyzed using multivariable logistic regression. Proxies ( R 2 > 0.8) were searched or imputation was performed if SNPs were not directly genotyped in the validation sets. Twenty-one SNPs with P < 0.05 in both MDA RCC GWAS and NCI RCC GWAS were subsequently evaluated in MDA RCC OncoArray. In the overall meta-analysis, significant ( P < 0.05) associations with RCC risk were observed for SNP mapping to IL1RAPL2 [rs10521506-G: OR meta = 0.87 (0.81-0.93), P meta = 2.33 × 10 -5 ], PLIN2 [rs2229536-A: OR meta = 0.87 (0.81-0.93), P meta = 2.33 × 10 -5 ], SMAD3 [rs4601989-A: OR meta = 0.86 (0.80-0.93), P meta = 2.71 × 10 -4 ], MED13L [rs10850596-A: OR meta = 1.14 (1.07-1.23), P meta = 1.50 × 10 -4 ], and TSC1 [rs3761840-G: OR meta = 0.90 (0.85-0.97), P meta = 2.47 × 10 -3 ]. We did not observe any significant cis-expression quantitative trait loci effect for these SNPs in the TCGA KIRC data. Conclusions: Taken together, we found that genetic variation of obesity-related genes could influence RCC susceptibility. Impact: The five identified loci may provide new insights into disease etiology that reveal importance of obesity-related genes in RCC development. Cancer Epidemiol Biomarkers Prev; 26(9); 1436-42. ©2017 AACR . ©2017 American Association for

  1. A Gene Module-Based eQTL Analysis Prioritizing Disease Genes and Pathways in Kidney Cancer.

    PubMed

    Yang, Mary Qu; Li, Dan; Yang, William; Zhang, Yifan; Liu, Jun; Tong, Weida

    2017-01-01

    Clear cell renal cell carcinoma (ccRCC) is the most common and most aggressive form of renal cell cancer (RCC). The incidence of RCC has increased steadily in recent years. The pathogenesis of renal cell cancer remains poorly understood. Many of the tumor suppressor genes, oncogenes, and dysregulated pathways in ccRCC need to be revealed for improvement of the overall clinical outlook of the disease. Here, we developed a systems biology approach to prioritize the somatic mutated genes that lead to dysregulation of pathways in ccRCC. The method integrated multi-layer information to infer causative mutations and disease genes. First, we identified differential gene modules in ccRCC by coupling transcriptome and protein-protein interactions. Each of these modules consisted of interacting genes that were involved in similar biological processes and their combined expression alterations were significantly associated with disease type. Then, subsequent gene module-based eQTL analysis revealed somatic mutated genes that had driven the expression alterations of differential gene modules. Our study yielded a list of candidate disease genes, including several known ccRCC causative genes such as BAP1 and PBRM1 , as well as novel genes such as NOD2, RRM1, CSRNP1, SLC4A2, TTLL1 and CNTN1. The differential gene modules and their driver genes revealed by our study provided a new perspective for understanding the molecular mechanisms underlying the disease. Moreover, we validated the results in independent ccRCC patient datasets. Our study provided a new method for prioritizing disease genes and pathways.

  2. Association between expression of random gene sets and survival is evident in multiple cancer types and may be explained by sub-classification.

    PubMed

    Shimoni, Yishai

    2018-02-01

    One of the goals of cancer research is to identify a set of genes that cause or control disease progression. However, although multiple such gene sets were published, these are usually in very poor agreement with each other, and very few of the genes proved to be functional therapeutic targets. Furthermore, recent findings from a breast cancer gene-expression cohort showed that sets of genes selected randomly can be used to predict survival with a much higher probability than expected. These results imply that many of the genes identified in breast cancer gene expression analysis may not be causal of cancer progression, even though they can still be highly predictive of prognosis. We performed a similar analysis on all the cancer types available in the cancer genome atlas (TCGA), namely, estimating the predictive power of random gene sets for survival. Our work shows that most cancer types exhibit the property that random selections of genes are more predictive of survival than expected. In contrast to previous work, this property is not removed by using a proliferation signature, which implies that proliferation may not always be the confounder that drives this property. We suggest one possible solution in the form of data-driven sub-classification to reduce this property significantly. Our results suggest that the predictive power of random gene sets may be used to identify the existence of sub-classes in the data, and thus may allow better understanding of patient stratification. Furthermore, by reducing the observed bias this may allow more direct identification of biologically relevant, and potentially causal, genes.

  3. Association between expression of random gene sets and survival is evident in multiple cancer types and may be explained by sub-classification

    PubMed Central

    2018-01-01

    One of the goals of cancer research is to identify a set of genes that cause or control disease progression. However, although multiple such gene sets were published, these are usually in very poor agreement with each other, and very few of the genes proved to be functional therapeutic targets. Furthermore, recent findings from a breast cancer gene-expression cohort showed that sets of genes selected randomly can be used to predict survival with a much higher probability than expected. These results imply that many of the genes identified in breast cancer gene expression analysis may not be causal of cancer progression, even though they can still be highly predictive of prognosis. We performed a similar analysis on all the cancer types available in the cancer genome atlas (TCGA), namely, estimating the predictive power of random gene sets for survival. Our work shows that most cancer types exhibit the property that random selections of genes are more predictive of survival than expected. In contrast to previous work, this property is not removed by using a proliferation signature, which implies that proliferation may not always be the confounder that drives this property. We suggest one possible solution in the form of data-driven sub-classification to reduce this property significantly. Our results suggest that the predictive power of random gene sets may be used to identify the existence of sub-classes in the data, and thus may allow better understanding of patient stratification. Furthermore, by reducing the observed bias this may allow more direct identification of biologically relevant, and potentially causal, genes. PMID:29470520

  4. Interactions between household air pollution and GWAS-identified lung cancer susceptibility markers in the Female Lung Cancer Consortium in Asia (FLCCA).

    PubMed

    Hosgood, H Dean; Song, Minsun; Hsiung, Chao Agnes; Yin, Zhihua; Shu, Xiao-Ou; Wang, Zhaoming; Chatterjee, Nilanjan; Zheng, Wei; Caporaso, Neil; Burdette, Laurie; Yeager, Meredith; Berndt, Sonja I; Landi, Maria Teresa; Chen, Chien-Jen; Chang, Gee-Chen; Hsiao, Chin-Fu; Tsai, Ying-Huang; Chien, Li-Hsin; Chen, Kuan-Yu; Huang, Ming-Shyan; Su, Wu-Chou; Chen, Yuh-Min; Chen, Chung-Hsing; Yang, Tsung-Ying; Wang, Chih-Liang; Hung, Jen-Yu; Lin, Chien-Chung; Perng, Reury-Perng; Chen, Chih-Yi; Chen, Kun-Chieh; Li, Yao-Jen; Yu, Chong-Jen; Chen, Yi-Song; Chen, Ying-Hsiang; Tsai, Fang-Yu; Kim, Christopher; Seow, Wei Jie; Bassig, Bryan A; Wu, Wei; Guan, Peng; He, Qincheng; Gao, Yu-Tang; Cai, Qiuyin; Chow, Wong-Ho; Xiang, Yong-Bing; Lin, Dongxin; Wu, Chen; Wu, Yi-Long; Shin, Min-Ho; Hong, Yun-Chul; Matsuo, Keitaro; Chen, Kexin; Wong, Maria Pik; Lu, Dara; Jin, Li; Wang, Jiu-Cun; Seow, Adeline; Wu, Tangchun; Shen, Hongbing; Fraumeni, Joseph F; Yang, Pan-Chyr; Chang, I-Shou; Zhou, Baosen; Chanock, Stephen J; Rothman, Nathaniel; Lan, Qing

    2015-03-01

    We previously carried out a multi-stage genome-wide association study (GWAS) on lung cancer among never smokers in the Female Lung Cancer Consortium in Asia (FLCCA) (6,609 cases, 7,457 controls) that identified novel susceptibility loci at 10q25.2, 6q22.2, and 6p21.32, and confirmed two previously identified loci at 5p15.33 and 3q28. Household air pollution (HAP) attributed to solid fuel burning for heating and cooking, is the leading cause of the overall disease burden in Southeast Asia, and is known to contain lung carcinogens. To evaluate the gene-HAP interactions associated with lung cancer in loci independent of smoking, we analyzed data from studies participating in FLCCA with fuel use information available (n = 3; 1,731 cases; 1,349 controls). Coal use was associated with a 30% increased risk of lung cancer (OR 1.3, 95% CI 1.0-1.6). Among the five a priori SNPs identified by our GWAS, two showed a significant interaction with coal use (HLA Class II rs2395185, p = 0.02; TP63 rs4488809 (rs4600802), p = 0.04). The risk of lung cancer associated with coal exposure varied with the respective alleles for these two SNPs. Our observations provide evidence that genetic variation in HLA Class II and TP63 may modify the association between HAP and lung cancer risk. The roles played in the cell cycle and inflammation pathways by the proteins encoded by these two genes provide biological plausibility for these interactions; however, additional replication studies are needed in other non-smoking populations.

  5. Serial analysis of gene expression identifies connective tissue growth factor expression as a prognostic biomarker in gallbladder cancer.

    PubMed

    Alvarez, Hector; Corvalan, Alejandro; Roa, Juan C; Argani, Pedram; Murillo, Francisco; Edwards, Jennifer; Beaty, Robert; Feldmann, Georg; Hong, Seung-Mo; Mullendore, Michael; Roa, Ivan; Ibañez, Luis; Pimentel, Fernando; Diaz, Alfonso; Riggins, Gregory J; Maitra, Anirban

    2008-05-01

    Gallbladder cancer (GBC) is an uncommon neoplasm in the United States, but one with high mortality rates. This malignancy remains largely understudied at the molecular level such that few targeted therapies or predictive biomarkers exist. We built the first series of serial analysis of gene expression (SAGE) libraries from GBC and nonneoplastic gallbladder mucosa, composed of 21-bp long-SAGE tags. SAGE libraries were generated from three stage-matched GBC patients (representing Hispanic/Latino, Native American, and Caucasian ethnicities, respectively) and one histologically alithiasic gallbladder. Real-time quantitative PCR was done on microdissected epithelium from five matched GBC and corresponding nonneoplastic gallbladder mucosa. Immunohistochemical analysis was done on a panel of 182 archival GBC in high-throughput tissue microarray format. SAGE tags corresponding to connective tissue growth factor (CTGF) transcripts were identified as differentially overexpressed in all pairwise comparisons of GBC (P < 0.001). Real-time quantitative PCR confirmed significant overexpression of CTGF transcripts in microdissected primary GBC (P < 0.05), but not in metastatic GBC, compared with nonneoplastic gallbladder epithelium. By immunohistochemistry, 66 of 182 (36%) GBC had high CTGF antigen labeling, which was significantly associated with better survival on univariate analysis (P = 0.0069, log-rank test). An unbiased analysis of the GBC transcriptome by SAGE has identified CTGF expression as a predictive biomarker of favorable prognosis in this malignancy. The SAGE libraries from GBC and nonneoplastic gallbladder mucosa are publicly available at the Cancer Genome Anatomy Project web site and should facilitate much needed research into this lethal neoplasm.

  6. Association between differential gene expression and body mass index among endometrial cancers from The Cancer Genome Atlas Project.

    PubMed

    Roque, Dario R; Makowski, Liza; Chen, Ting-Huei; Rashid, Naim; Hayes, D Neil; Bae-Jump, Victoria

    2016-08-01

    The Cancer Genome Atlas (TCGA) identified four integrated clusters for endometrial cancer (EC): POLE, MSI, CNL and CNH. We evaluated differences in gene expression profiles of obese and non-obese women with EC and examined the association of body mass index (BMI) within the clusters identified in TCGA. TCGA RNAseq data was used to identify genes related to increasing BMI among ECs. The POLE, MSI and CNL clusters were composed mostly of endometrioid EC. Patient BMI was compared between these three clusters with one-way ANOVA. Association between gene expression and BMI was also assessed while adjusting for confounding effects of potential confounding factors. p-Values testing the association between gene expression and BMI were adjusted for multiple hypothesis testing over the 20,531 genes considered. Mean BMI was statistically different between the ECs in the CNL (35.8) versus POLE (29.8) cluster (p=0.006) and approached significance for the MSI (33.0) versus CNL (35.8) cluster (p=0.05). 181 genes were significantly up- or down-regulated with increasing BMI in endometrioid EC (q-value<0.01), including LPL, IRS-1, IGFBP4, IGFBP7 and the progesterone receptor. DAVID functional annotation analysis revealed significant enrichment in "cell cycle" (adjusted p-value=1.5E-5) and "DNA metabolic processes" (adjusted p-value=1E-3) for the identified genes. Obesity related genes were found to be upregulated with increasing BMI among endometrioid ECs. Patients with POLE tumors have the lowest median BMI when compared to MSI and CNL. Given the heterogeneity among endometrioid EC, consideration should be given to abandoning the Type I and II classification of EC tumors. Copyright © 2016 Elsevier Inc. All rights reserved.

  7. Identification of key genes associated with the effect of estrogen on ovarian cancer using microarray analysis.

    PubMed

    Zhang, Shi-tao; Zuo, Chao; Li, Wan-nan; Fu, Xue-qi; Xing, Shu; Zhang, Xiao-ping

    2016-02-01

    To identify key genes related to the effect of estrogen on ovarian cancer. Microarray data (GSE22600) were downloaded from Gene Expression Omnibus. Eight estrogen and seven placebo treatment samples were obtained using a 2 × 2 factorial designs, which contained 2 cell lines (PEO4 and 2008) and 2 treatments (estrogen and placebo). Differentially expressed genes were identified by Bayesian methods, and the genes with P < 0.05 and |log2FC (fold change)| ≥0.5 were chosen as cut-off criterion. Differentially co-expressed genes (DCGs) and differentially regulated genes (DRGs) were, respectively, identified by DCe function and DRsort function in DCGL package. Topological structure analysis was performed on the important transcriptional factors (TFs) and genes in transcriptional regulatory network using tYNA. Functional enrichment analysis was, respectively, performed for DEGs and the important genes using Gene Ontology and KEGG databases. In total, 465 DEGs were identified. Functional enrichment analysis of DEGs indicated that ACVR2B, LTBP1, BMP7 and MYC involved in TGF-beta signaling pathway. The 2285 DCG pairs and 357 DRGs were identified. Topological structure analysis showed that 52 important TFs and 65 important genes were identified. Functional enrichment analysis of the important genes showed that TP53 and MLH1 participated in DNA damage response and the genes (ACVR2B, LTBP1, BMP7 and MYC) involved in TGF-beta signaling pathway. TP53, MLH1, ACVR2B, LTBP1 and BMP7 might participate in the pathogenesis of ovarian cancer.

  8. Amyloid precursor protein regulates migration and metalloproteinase gene expression in prostate cancer cells

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Miyazaki, Toshiaki; Ikeda, Kazuhiro; Horie-Inoue, Kuniko

    Highlights: • APP knockdown reduced proliferation and migration of prostate cancer cells. • APP knockdown reduced expression of metalloproteinase and EMT-related genes. • APP overexpression promoted LNCaP cell migration. • APP overexpression increased expression of metalloproteinase and EMT-related genes. - Abstract: Amyloid precursor protein (APP) is a type I transmembrane protein, and one of its processed forms, β-amyloid, is considered to play a central role in the development of Alzheimer’s disease. We previously showed that APP is a primary androgen-responsive gene in prostate cancer and that its increased expression is correlated with poor prognosis for patients with prostate cancer. APPmore » has also been implicated in several human malignancies. Nevertheless, the mechanism underlying the pro-proliferative effects of APP on cancers is still not well-understood. In the present study, we explored a pathophysiological role for APP in prostate cancer cells using siRNA targeting APP (siAPP). The proliferation and migration of LNCaP and DU145 prostate cancer cells were significantly suppressed by siAPP. Differentially expressed genes in siAPP-treated cells compared to control siRNA-treated cells were identified by microarray analysis. Notably, several metalloproteinase genes, such as ADAM10 and ADAM17, and epithelial–mesenchymal transition (EMT)-related genes, such as VIM, and SNAI2, were downregulated in siAPP-treated cells as compared to control cells. The expression of these genes was upregulated in LNCaP cells stably expressing APP when compared with control cells. APP-overexpressing LNCaP cells exhibited enhanced migration in comparison to control cells. These results suggest that APP may contribute to the proliferation and migration of prostate cancer cells by modulating the expression of metalloproteinase and EMT-related genes.« less

  9. Investigating a multigene prognostic assay based on significant pathways for Luminal A breast cancer through gene expression profile analysis.

    PubMed

    Gao, Haiyan; Yang, Mei; Zhang, Xiaolan

    2018-04-01

    The present study aimed to investigate potential recurrence-risk biomarkers based on significant pathways for Luminal A breast cancer through gene expression profile analysis. Initially, the gene expression profiles of Luminal A breast cancer patients were downloaded from The Cancer Genome Atlas database. The differentially expressed genes (DEGs) were identified using a Limma package and the hierarchical clustering analysis was conducted for the DEGs. In addition, the functional pathways were screened using Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses and rank ratio calculation. The multigene prognostic assay was exploited based on the statistically significant pathways and its prognostic function was tested using train set and verified using the gene expression data and survival data of Luminal A breast cancer patients downloaded from the Gene Expression Omnibus. A total of 300 DEGs were identified between good and poor outcome groups, including 176 upregulated genes and 124 downregulated genes. The DEGs may be used to effectively distinguish Luminal A samples with different prognoses verified by hierarchical clustering analysis. There were 9 pathways screened as significant pathways and a total of 18 DEGs involved in these 9 pathways were identified as prognostic biomarkers. According to the survival analysis and receiver operating characteristic curve, the obtained 18-gene prognostic assay exhibited good prognostic function with high sensitivity and specificity to both the train and test samples. In conclusion the 18-gene prognostic assay including the key genes, transcription factor 7-like 2, anterior parietal cortex and lymphocyte enhancer factor-1 may provide a new method for predicting outcomes and may be conducive to the promotion of precision medicine for Luminal A breast cancer.

  10. MethylMix 2.0: an R package for identifying DNA methylation genes. | Office of Cancer Genomics

    Cancer.gov

    DNA methylation is an important mechanism regulating gene transcription, and its role in carcinogenesis has been extensively studied. Hyper and hypomethylation of genes is a major mechanism of gene expression deregulation in a wide range of diseases. At the same time, high-throughput DNA methylation assays have been developed generating vast amounts of genome wide DNA methylation measurements. We developed MethylMix, an algorithm implemented in R to identify disease specific hyper and hypomethylated genes.

  11. Association mining of mutated cancer genes in different clinical stages across 11 cancer types.

    PubMed

    Hu, Wangxiong; Li, Xiaofen; Wang, Tingzhang; Zheng, Shu

    2016-10-18

    Many studies have demonstrated that some genes (e.g. APC, BRAF, KRAS, PTEN, TP53) are frequently mutated in cancer, however, underlying mechanism that contributes to their high mutation frequency remains unclear. Here we used Apriori algorithm to find the frequent mutational gene sets (FMGSs) from 4,904 tumors across 11 cancer types as part of the TCGA Pan-Cancer effort and then mined the hidden association rules (ARs) within these FMGSs. Intriguingly, we found that well-known cancer driver genes such as BRAF, KRAS, PTEN, and TP53 were often co-occurred with other driver genes and FMGSs size peaked at an itemset size of 3~4 genes. Besides, the number and constitution of FMGS and ARs differed greatly among different cancers and stages. In addition, FMGS and ARs were rare in endocrine-related cancers such as breast carcinoma, ovarian cystadenocarcinoma, and thyroid carcinoma, but abundant in cancers contact directly with external environments such as skin melanoma and stomach adenocarcinoma. Furthermore, we observed more rules in stage IV than in other stages, indicating that distant metastasis needed more sophisticated gene regulatory network.

  12. Mining the Immune Cell Proteome to Identify Ovarian Cancer-Specific Biomarkers

    DTIC Science & Technology

    2012-03-01

    data and are in the process of identifying gene signatures that can be used as biomarkers for the identification of ovarian cancer-specific biomarkers...groups. The groups showed significant difference in age as well as gestational age, which is expected when considering the disease process . Isolation of...MUC4 in intracellular signaling.32 Oligosaccharides attached to the extracellular domains of mucins have also been shown to interact with different

  13. Gene Therapy of Human Breast Cancer.

    DTIC Science & Technology

    1998-10-01

    gene product of human papilloma virus . They transduced this modified cell line with B7 and showed that immunization with the B7- transduced cell...adeno-LacZ virus , aliquots of 106 human breast cancer cells, purified using methods described above, will be incubated in suspension with adeno-LacZ...v.- Final Report:«DAMD17-94-J-4385 "Gene Therapy of Human Cancer" Page 1 AD GRANT NUMBER DAMD17-94-J-4385 TITLE: Gene Therapy of Human

  14. A novel NOTCH3 mutation identified in patients with oral cancer by whole exome sequencing.

    PubMed

    Yi, Yanjun; Tian, Zhuowei; Ju, Houyu; Ren, Guoxin; Hu, Jingzhou

    2017-06-01

    Oral cancer is a serious disease caused by environmental factors and/or susceptible genes. In the present study, in order to identify useful genetic biomarkers for cancer prediction and prevention, and for personalized treatment, we detected somatic mutations in 5 pairs of oral cancer tissues and blood samples using whole exome sequencing (WES). Finally, we confirmed a novel nonsense single-nucleotide polymorphism (SNP; chr19:15288426A>C) in the NOTCH3 gene with sanger sequencing, which resulted in a N1438T mutation in the protein sequence. Using multiple in silico analyses, this variant was found to mildly damaging effects on the NOTCH3 gene, which was supported by the results from analyses using PANTHER, SNAP and SNPs&GO. However, further analysis using Mutation Taster revealed that this SNP had a probability of 0.9997 to be 'disease causing'. In addition, we performed 3D structure simulation analysis and the results suggested that this variant had little effect on the solubility and hydrophobicity of the protein and thus on its function; however, it decreased the stability of the protein by increasing the total energy following minimization (-1,051.39 kcal/mol for the mutant and -1,229.84 kcal/mol for the native) and decreasing one stabilizing residue of the protein. Less stability of the N1438T mutant was also supported by analysis using I-Mutant with a DDG value of -1.67. Overall, the present study identified and confirmed a novel mutation in the NOTCH3 gene, which may decrease the stability of NOTCH3, and may thus prove to be helpful in cancer prognosis.

  15. MiR-204 down-regulation elicited perturbation of a gene target signature common to human cholangiocarcinoma and gastric cancer.

    PubMed

    Canu, Valeria; Sacconi, Andrea; Lorenzon, Laura; Biagioni, Francesca; Lo Sardo, Federica; Diodoro, Maria Grazia; Muti, Paola; Garofalo, Alfredo; Strano, Sabrina; D'Errico, Antonietta; Grazi, Gian Luca; Cioce, Mario; Blandino, Giovanni

    2017-05-02

    There is high need of novel diagnostic and prognostic tools for tumors of the digestive system, such as gastric cancer and cholangiocarcinoma. We recently found that miR-204 was deeply downregulated in gastric cancer tissues. Here we investigated whether this was common to other tumors of the digestive system and whether this elicited a miR-204-dependent gene target signature, diagnostically and therapeutically relevant. Finally, we assessed the contribution of the identified target genes to the cell cycle progression and clonogenicity of gastric cancer and cholangiocarcinoma cell lines. We employed quantitative PCR and Affymetrix profiling for gene expression studies. In silico analysis aided us to identifying a miR-204 target signature in publicly available databases (TGCA). We employed transient transfection experiments, clonogenic assays and cell cycle profiling to evaluate the biological consequences of miR-204 perturbation. We identified a novel miR-204 gene target signature perturbed in gastric cancer and in cholangiocarcinoma specimens. We validated its prognostic relevance and mechanistically addressed its biological relevance in GC and CC cell lines. We suggest that restoring the physiological levels of miR-204 in some gastrointestinal cancers might be exploited therapeutically.

  16. Gene-expression signatures can distinguish gastric cancer grades and stages.

    PubMed

    Cui, Juan; Li, Fan; Wang, Guoqing; Fang, Xuedong; Puett, J David; Xu, Ying

    2011-03-18

    Microarray gene-expression data of 54 paired gastric cancer and adjacent noncancerous gastric tissues were analyzed, with the aim to establish gene signatures for cancer grades (well-, moderately-, poorly- or un-differentiated) and stages (I, II, III and IV), which have been determined by pathologists. Our statistical analysis led to the identification of a number of gene combinations whose expression patterns serve well as signatures of different grades and different stages of gastric cancer. A 19-gene signature was found to have discerning power between high- and low-grade gastric cancers in general, with overall classification accuracy at 79.6%. An expanded 198-gene panel allows the stratification of cancers into four grades and control, giving rise to an overall classification agreement of 74.2% between each grade designated by the pathologists and our prediction. Two signatures for cancer staging, consisting of 10 genes and 9 genes, respectively, provide high classification accuracies at 90.0% and 84.0%, among early-, advanced-stage cancer and control. Functional and pathway analyses on these signature genes reveal the significant relevance of the derived signatures to cancer grades and progression. To the best of our knowledge, this represents the first study on identification of genes whose expression patterns can serve as markers for cancer grades and stages.

  17. Genome-wide association study identifies multiple loci associated with bladder cancer risk

    PubMed Central

    Figueroa, Jonine D.; Ye, Yuanqing; Siddiq, Afshan; Garcia-Closas, Montserrat; Chatterjee, Nilanjan; Prokunina-Olsson, Ludmila; Cortessis, Victoria K.; Kooperberg, Charles; Cussenot, Olivier; Benhamou, Simone; Prescott, Jennifer; Porru, Stefano; Dinney, Colin P.; Malats, Núria; Baris, Dalsu; Purdue, Mark; Jacobs, Eric J.; Albanes, Demetrius; Wang, Zhaoming; Deng, Xiang; Chung, Charles C.; Tang, Wei; Bas Bueno-de-Mesquita, H.; Trichopoulos, Dimitrios; Ljungberg, Börje; Clavel-Chapelon, Françoise; Weiderpass, Elisabete; Krogh, Vittorio; Dorronsoro, Miren; Travis, Ruth; Tjønneland, Anne; Brenan, Paul; Chang-Claude, Jenny; Riboli, Elio; Conti, David; Gago-Dominguez, Manuela; Stern, Mariana C.; Pike, Malcolm C.; Van Den Berg, David; Yuan, Jian-Min; Hohensee, Chancellor; Rodabough, Rebecca; Cancel-Tassin, Geraldine; Roupret, Morgan; Comperat, Eva; Chen, Constance; De Vivo, Immaculata; Giovannucci, Edward; Hunter, David J.; Kraft, Peter; Lindstrom, Sara; Carta, Angela; Pavanello, Sofia; Arici, Cecilia; Mastrangelo, Giuseppe; Kamat, Ashish M.; Lerner, Seth P.; Barton Grossman, H.; Lin, Jie; Gu, Jian; Pu, Xia; Hutchinson, Amy; Burdette, Laurie; Wheeler, William; Kogevinas, Manolis; Tardón, Adonina; Serra, Consol; Carrato, Alfredo; García-Closas, Reina; Lloreta, Josep; Schwenn, Molly; Karagas, Margaret R.; Johnson, Alison; Schned, Alan; Armenti, Karla R.; Hosain, G.M.; Andriole, Gerald; Grubb, Robert; Black, Amanda; Ryan Diver, W.; Gapstur, Susan M.; Weinstein, Stephanie J.; Virtamo, Jarmo; Haiman, Chris A.; Landi, Maria T.; Caporaso, Neil; Fraumeni, Joseph F.; Vineis, Paolo; Wu, Xifeng; Silverman, Debra T.; Chanock, Stephen; Rothman, Nathaniel

    2014-01-01

    Candidate gene and genome-wide association studies (GWAS) have identified 11 independent susceptibility loci associated with bladder cancer risk. To discover additional risk variants, we conducted a new GWAS of 2422 bladder cancer cases and 5751 controls, followed by a meta-analysis with two independently published bladder cancer GWAS, resulting in a combined analysis of 6911 cases and 11 814 controls of European descent. TaqMan genotyping of 13 promising single nucleotide polymorphisms with P < 1 × 10−5 was pursued in a follow-up set of 801 cases and 1307 controls. Two new loci achieved genome-wide statistical significance: rs10936599 on 3q26.2 (P = 4.53 × 10−9) and rs907611 on 11p15.5 (P = 4.11 × 10−8). Two notable loci were also identified that approached genome-wide statistical significance: rs6104690 on 20p12.2 (P = 7.13 × 10−7) and rs4510656 on 6p22.3 (P = 6.98 × 10−7); these require further studies for confirmation. In conclusion, our study has identified new susceptibility alleles for bladder cancer risk that require fine-mapping and laboratory investigation, which could further understanding into the biological underpinnings of bladder carcinogenesis. PMID:24163127

  18. Gene and cell therapy for pancreatic cancer.

    PubMed

    Singh, Hans Martin; Ungerechts, Guy; Tsimberidou, Apostolia M

    2015-04-01

    The clinical outcomes of patients with pancreatic cancer are poor, and the limited success of classical chemotherapy underscores the need for new, targeted approaches for this disease. The delivery of genetic material to cells allows for a variety of therapeutic concepts. Engineered agents based on synthetic biology are under clinical investigation in various cancers, including pancreatic cancer. This review focuses on Phase I - III clinical trials of gene and cell therapy for pancreatic cancer and on future implications of recent translational research. Trials available in the US National Library of Medicine (www.clinicaltrials.gov) until February 2014 were reviewed and relevant published results of preclinical and clinical studies were retrieved from www.pubmed.gov . In pancreatic cancer, gene and cell therapies are feasible and may have synergistic antitumor activity with standard treatment and/or immunotherapy. Challenges are related to application safety, manufacturing costs, and a new spectrum of adverse events. Further studies are needed to evaluate available agents in carefully designed protocols and combination regimens. Enabling personalized cancer therapy, insights from molecular diagnostic technologies will guide the development and selection of new gene-based drugs. The evolving preclinical and clinical data on gene-based therapies can lay the foundation for future avenues improving patient care in pancreatic cancer.

  19. Alternative RNA splicing of the MEAF6 gene facilitates neuroendocrine prostate cancer progression.

    PubMed

    Lee, Ahn R; Li, Yinan; Xie, Ning; Gleave, Martin E; Cox, Michael E; Collins, Colin C; Dong, Xuesen

    2017-04-25

    Although potent androgen receptor pathway inhibitors (ARPI) improve overall survival of metastatic prostate cancer patients, treatment-induced neuroendocrine prostate cancer (t-NEPC) as a consequence of the selection pressures of ARPI is becoming a more common clinical issue. Improved understanding of the molecular biology of t-NEPC is essential for the development of new effective management approaches for t-NEPC. In this study, we identify a splice variant of the MYST/Esa1-associated factor 6 (MEAF6) gene, MEAF6-1, that is highly expressed in both t-NEPC tumor biopsies and neuroendocrine cell lines of prostate and lung cancers. We show that MEAF6-1 splicing is stimulated by neuronal RNA splicing factor SRRM4. Rather than inducing neuroendocrine trans-differentiation of cells in prostate adenocarcinoma, MEAF6-1 upregulation stimulates cell proliferation, anchorage-independent cell growth, invasion and xenograft tumor growth. Gene microarray identifies that these MEAF6-1 actions are in part mediated by the ID1 and ID3 genes. These findings suggest that the MEAF6-1 variant does not induce neuroendocrine differentiation of prostate cancer cells, but rather facilitates t-NEPC progression by increasing the proliferation rate of cells that have acquired neuroendocrine phenotypes.

  20. Polymorphisms in inflammation pathway genes and endometrial cancer risk

    PubMed Central

    Delahanty, Ryan J.; Xiang, Yong-Bing; Spurdle, Amanda; Beeghly-Fadiel, Alicia; Long, Jirong; Thompson, Deborah; Tomlinson, Ian; Yu, Herbert; Lambrechts, Diether; Dörk, Thilo; Goodman, Marc T.; Zheng, Ying; Salvesen, Helga B.; Bao, Ping-Ping; Amant, Frederic; Beckmann, Matthias W.; Coenegrachts, Lieve; Coosemans, An; Dubrowinskaja, Natalia; Dunning, Alison; Runnebaum, Ingo B.; Easton, Douglas; Ekici, Arif B.; Fasching, Peter A.; Halle, Mari K.; Hein, Alexander; Howarth, Kimberly; Gorman, Maggie; Kaydarova, Dylyara; Krakstad, Camilla; Lose, Felicity; Lu, Lingeng; Lurie, Galina; O’Mara, Tracy; Matsuno, Rayna K.; Pharoah, Paul; Risch, Harvey; Corssen, Madeleine; Trovik, Jone; Turmanov, Nurzhan; Wen, Wanqing; Lu, Wei; Cai, Qiuyin; Zheng, Wei; Shu, Xiao-Ou

    2013-01-01

    Background Experimental and epidemiological evidence have suggested that chronic inflammation may play a critical role in endometrial carcinogenesis. Methods To investigate this hypothesis, a two-stage study was carried out to evaluate single nucleotide polymorphisms (SNPs) in inflammatory pathway genes in association with endometrial cancer risk. In stage 1, 64 candidate pathway genes were identified and 4,542 directly genotyped or imputed SNPs were analyzed among 832 endometrial cancer cases and 2,049 controls, using data from the Shanghai Endometrial Cancer Genetics Study. Linkage disequilibrium of stage 1 SNPs significantly associated with endometrial cancer (P<0.05) indicated that the majority of associations could be linked to one of 24 distinct loci. One SNP from each of the 24 loci was then selected for follow-up genotyping. Of these, 21 SNPs were successfully designed and genotyped in stage 2, which consisted of ten additional studies including 6,604 endometrial cancer cases and 8,511 controls. Results Five of the 21 SNPs had significant allelic odds ratios and 95% confidence intervals as follows: FABP1, 0.92 (0.85-0.99); CXCL3, 1.16 (1.05-1.29); IL6, 1.08 (1.00-1.17); MSR1, 0.90 (0.82-0.98); and MMP9, 0.91 (0.87-0.97). Two of these polymorphisms were independently significant in the replication sample (rs352038 in CXCL3 and rs3918249 in MMP9). The association for the MMP9 polymorphism remained significant after Bonferroni correction and showed a significant association with endometrial cancer in both Asian- and European-ancestry samples. Conclusions These findings lend support to the hypothesis that genetic polymorphisms in genes involved in the inflammatory pathway may contribute to genetic susceptibility to endometrial cancer. Impact Statement This study adds to the growing evidence that inflammation plays an important role in endometrial carcinogenesis. PMID:23221126

  1. Utilizing Gene Tree Variation to Identify Candidate Effector Genes in Zymoseptoria tritici

    PubMed Central

    McDonald, Megan C.; McGinness, Lachlan; Hane, James K.; Williams, Angela H.; Milgate, Andrew; Solomon, Peter S.

    2016-01-01

    Zymoseptoria tritici is a host-specific, necrotrophic pathogen of wheat. Infection by Z. tritici is characterized by its extended latent period, which typically lasts 2 wks, and is followed by extensive host cell death, and rapid proliferation of fungal biomass. This work characterizes the level of genomic variation in 13 isolates, for which we have measured virulence on 11 wheat cultivars with differential resistance genes. Between the reference isolate, IPO323, and the 13 Australian isolates we identified over 800,000 single nucleotide polymorphisms, of which ∼10% had an effect on the coding regions of the genome. Furthermore, we identified over 1700 probable presence/absence polymorphisms in genes across the Australian isolates using de novo assembly. Finally, we developed a gene tree sorting method that quickly identifies groups of isolates within a single gene alignment whose sequence haplotypes correspond with virulence scores on a single wheat cultivar. Using this method, we have identified < 100 candidate effector genes whose gene sequence correlates with virulence toward a wheat cultivar carrying a major resistance gene. PMID:26837952

  2. Molecular insight in gastric cancer induction: an overview of cancer stemness genes.

    PubMed

    Akhavan-Niaki, Haleh; Samadani, Ali Akbar

    2014-04-01

    Gastric cancer is one of the most outgoing human cancers in the world. Two main functional types were described: Intestinal adenocarcinoma and diffuse one. The most important purpose of this review is to analyze and investigate the main genetic factors involved in tumorogenesis of stomach and the molecular mechanism of their expression regulation alongside with the importance of cancer stem cells and their relationship with gastric cancer. It is evident that proper diagnosis of molecular case of cancer may lead to absolute treatment and at least reduction in the disease severity. However, stemness factors such as Sox2, Oct3/4, and Nanog were related with induced pluripotent stem cells, proposing a correlation between these stemness factors and cancer stem cells. Moreover, aberrant induction by Helicobacter pylori of the intestinal-specific homeobox transcription factors, CDX1 and CDX2, also plays an important role in this modification. There are some genes which are directly activated by CDX1 in gastric cancer and distinguished stemness-related reprogramming factors like SALL4 and KLF5. Correspondingly, we also aimed to present the main important epigenetic changes such as DNA methylation, histone modification, and chromatin modeling of stemness genes in disease development. Remarkably, a better understanding of molecular bases of cancer may lead to novel diagnostic, therapeutic, and preventive approaches by some genetic and epigenetic changes such as gene amplifications, gene silencing by DNA methylation, losses of imprinting, LOH, and mutations. Consequently, genome-wide searches of gene expression are widely important for surveying the proper mechanisms of cancer emergence and development. Conspicuously, this review explains an outline of the molecular mechanism and new approaches in gastric cancer.

  3. Global identification of genes regulated by estrogen signaling and demethylation in MCF-7 breast cancer cells

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Putnik, Milica, E-mail: milica.putnik@ki.se; Zhao, Chunyan, E-mail: chunyan.zhao@ki.se; Gustafsson, Jan-Ake, E-mail: jan-ake.gustafsson@ki.se

    Highlights: Black-Right-Pointing-Pointer Estrogen signaling and demethylation can both control gene expression in breast cancers. Black-Right-Pointing-Pointer Cross-talk between these mechanisms is investigated in human MCF-7 breast cancer cells. Black-Right-Pointing-Pointer 137 genes are influenced by both 17{beta}-estradiol and demethylating agent 5-aza-2 Prime -deoxycytidine. Black-Right-Pointing-Pointer A set of genes is identified as targets of both estrogen signaling and demethylation. Black-Right-Pointing-Pointer There is no direct molecular interplay of mediators of estrogen and epigenetic signaling. -- Abstract: Estrogen signaling and epigenetic modifications, in particular DNA methylation, are involved in regulation of gene expression in breast cancers. Here we investigated a potential regulatory cross-talk between thesemore » two pathways by identifying their common target genes and exploring underlying molecular mechanisms in human MCF-7 breast cancer cells. Gene expression profiling revealed that the expression of approximately 140 genes was influenced by both 17{beta}-estradiol (E2) and a demethylating agent 5-aza-2 Prime -deoxycytidine (DAC). Gene ontology (GO) analysis suggests that these genes are involved in intracellular signaling cascades, regulation of cell proliferation and apoptosis. Based on previously reported association with breast cancer, estrogen signaling and/or DNA methylation, CpG island prediction and GO analysis, we selected six genes (BTG3, FHL2, PMAIP1, BTG2, CDKN1A and TGFB2) for further analysis. Tamoxifen reverses the effect of E2 on the expression of all selected genes, suggesting that they are direct targets of estrogen receptor. Furthermore, DAC treatment reactivates the expression of all selected genes in a dose-dependent manner. Promoter CpG island methylation status analysis revealed that only the promoters of BTG3 and FHL2 genes are methylated, with DAC inducing demethylation, suggesting DNA methylation directs

  4. Identification of critical regulatory genes in cancer signaling network using controllability analysis

    NASA Astrophysics Data System (ADS)

    Ravindran, Vandana; Sunitha, V.; Bagler, Ganesh

    2017-05-01

    Cancer is characterized by a complex web of regulatory mechanisms which makes it difficult to identify features that are central to its control. Molecular integrative models of cancer, generated with the help of data from experimental assays, facilitate use of control theory to probe for ways of controlling the state of such a complex dynamic network. We modeled the human cancer signaling network as a directed graph and analyzed it for its controllability, identification of driver nodes and their characterization. We identified the driver nodes using the maximum matching algorithm and classified them as backbone, peripheral and ordinary based on their role in regulatory interactions and control of the network. We found that the backbone driver nodes were key to driving the regulatory network into cancer phenotype (via mutations) as well as for steering into healthy phenotype (as drug targets). This implies that while backbone genes could lead to cancer by virtue of mutations, they are also therapeutic targets of cancer. Further, based on their impact on the size of the set of driver nodes, genes were characterized as indispensable, dispensable and neutral. Indispensable nodes within backbone of the network emerged as central to regulatory mechanisms of control of cancer. In addition to probing the cancer signaling network from the perspective of control, our findings suggest that indispensable backbone driver nodes could be potentially leveraged as therapeutic targets. This study also illustrates the application of structural controllability for studying the mechanisms underlying the regulation of complex diseases.

  5. Novel recurrently mutated genes and a prognostic mutation signature in colorectal cancer.

    PubMed

    Yu, Jun; Wu, William K K; Li, Xiangchun; He, Jun; Li, Xiao-Xing; Ng, Simon S M; Yu, Chang; Gao, Zhibo; Yang, Jie; Li, Miao; Wang, Qiaoxiu; Liang, Qiaoyi; Pan, Yi; Tong, Joanna H; To, Ka F; Wong, Nathalie; Zhang, Ning; Chen, Jie; Lu, Youyong; Lai, Paul B S; Chan, Francis K L; Li, Yingrui; Kung, Hsiang-Fu; Yang, Huanming; Wang, Jun; Sung, Joseph J Y

    2015-04-01

    Characterisation of colorectal cancer (CRC) genomes by next-generation sequencing has led to the discovery of novel recurrently mutated genes. Nevertheless, genomic data has not yet been used for CRC prognostication. To identify recurrent somatic mutations with prognostic significance in patients with CRC. Exome sequencing was performed to identify somatic mutations in tumour tissues of 22 patients with CRC, followed by validation of 187 recurrent and pathway-related genes using targeted capture sequencing in additional 160 cases. Seven significantly mutated genes, including four reported (APC, TP53, KRAS and SMAD4) and three novel recurrently mutated genes (CDH10, FAT4 and DOCK2), exhibited high mutation prevalence (6-14% for novel cancer genes) and higher-than-expected number of non-silent mutations in our CRC cohort. For prognostication, a five-gene-signature (CDH10, COL6A3, SMAD4, TMEM132D, VCAN) was devised, in which mutation(s) in one or more of these genes was significantly associated with better overall survival independent of tumor-node-metastasis (TNM) staging. The median survival time was 80.4 months in the mutant group versus 42.4 months in the wild type group (p=0.0051). The prognostic significance of this signature was successfully verified using the data set from the Cancer Genome Atlas study. The application of next-generation sequencing has led to the identification of three novel significantly mutated genes in CRC and a mutation signature that predicts survival outcomes for stratifying patients with CRC independent of TNM staging. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

  6. Bacteriophage-Derived Vectors for Targeted Cancer Gene Therapy

    PubMed Central

    Pranjol, Md Zahidul Islam; Hajitou, Amin

    2015-01-01

    Cancer gene therapy expanded and reached its pinnacle in research in the last decade. Both viral and non-viral vectors have entered clinical trials, and significant successes have been achieved. However, a systemic administration of a vector, illustrating safe, efficient, and targeted gene delivery to solid tumors has proven to be a major challenge. In this review, we summarize the current progress and challenges in the targeted gene therapy of cancer. Moreover, we highlight the recent developments of bacteriophage-derived vectors and their contributions in targeting cancer with therapeutic genes following systemic administration. PMID:25606974

  7. Bacteriophage-derived vectors for targeted cancer gene therapy.

    PubMed

    Pranjol, Md Zahidul Islam; Hajitou, Amin

    2015-01-19

    Cancer gene therapy expanded and reached its pinnacle in research in the last decade. Both viral and non-viral vectors have entered clinical trials, and significant successes have been achieved. However, a systemic administration of a vector, illustrating safe, efficient, and targeted gene delivery to solid tumors has proven to be a major challenge. In this review, we summarize the current progress and challenges in the targeted gene therapy of cancer. Moreover, we highlight the recent developments of bacteriophage-derived vectors and their contributions in targeting cancer with therapeutic genes following systemic administration.

  8. Association of tannase-producing Staphylococcus lugdunensis with colon cancer and characterization of a novel tannase gene.

    PubMed

    Noguchi, Norihisa; Ohashi, Takashi; Shiratori, Taisei; Narui, Koji; Hagiwara, Tadashi; Ko, Mari; Watanabe, Kiyoshi; Miyahara, Takeo; Taira, Satoru; Moriyasu, Fuminori; Sasatsu, Masanori

    2007-05-01

    The relationship between Streptococcus (St.) bovis endocarditis and colon cancer is well known. In St. bovis, the biotype I strain (formerly, St. gallolyticus) produces tannase that degrades tannins. The aim of this study was to investigate the association of tannase-producing bacteria with colon cancer, and to identify the major tannase-producing bacteria and the gene involved. Tannase-producing bacteria were isolated in tannic acid-treated selective agar medium from feces and rectal swabs of 357 patients who underwent colon endoscopy from 1999 to 2004. Tannase-producing bacteria were isolated more frequently from the colon cancer group (24.3%) than from the adenoma or normal groups (14.4%; P < 0.05). S. gallolyticus, Staphylococcus (S.) lugdunensis, Lactobacillus (L.) plantarum, and L. pentosus were all identified as tannase-producing bacteria. Of these, S. lugdunensis was significantly isolated from the advanced-stage cancer group (22.2%; P < 0.001) more than from the early-stage cancer (8.6%) or adenoma (4.9%) groups. The gene (tanA) for tannase in S. lugdunensis was cloned and sequenced. The tanA gene was associated with all S. lugdunensis but not with other bacteria by Southern blotting and polymerase chain reaction. Tannase-producing S. lugdunensis is associated with advanced-stage colon cancer, and the tanA gene is a useful marker for the detection of S. lugdunensis.

  9. [Utility of chromosome banding with ALU I enzyme for identifying methylated areas in breast cancer].

    PubMed

    Rojas-Atencio, Alicia; Yamarte, Leonard; Urdaneta, Karelis; Soto-Alvarez, Marisol; Alvarez Nava, Francisco; Cañizalez, Jenny; Quintero, Maribel; Atencio, Raquel; González, Richard

    2012-12-01

    Cancer is a group of disorders characterized by uncontrolled cell growth which is produced by two successive events: increased cell proliferation (tumor or neoplasia) and the invasive capacity of these cells (metastasis). DNA methylation is an epigenetic process which has been involved as an important pathogenic factor of cancer. DNA methylation participates in the regulation of gene expression, directly, by preventing the union of transcription factors, and indirectly, by promoting the "closed" structure of the chromatine. The objectives of this study were to identify hypermethyled chromosomal regions through the use of restriction Alu I endonuclease, and to relate cytogenetically these regions with tumor suppressive gene loci. Sixty peripheral blood samples of females with breast cancer were analyzed. Cell cultures were performed and cytogenetic spreads, previously digested with Alu I enzyme, were stained with Giemsa. Chromosomal centromeric and not centromeric regions were stained in 37% of cases. About 96% of stained hypermethyled chromosomal regions (1q, 2q, 6q) were linked with methylated genes associated with breast cancer. In addition, centromeric regions in chromosomes 3, 4, 8, 13, 14, 15 and 17, usually unstained, were found positive to digestion with Alu I enzime and Giemsa staining. We suggest the importance of this technique for the global visualization of the genome which can find methylated genes related to breast cancer, and thus lead to a specific therapy, and therefore a better therapeutic response.

  10. The Cancer Genome Atlas Clinical Explorer: a web and mobile interface for identifying clinical-genomic driver associations.

    PubMed

    Lee, HoJoon; Palm, Jennifer; Grimes, Susan M; Ji, Hanlee P

    2015-10-27

    The Cancer Genome Atlas (TCGA) project has generated genomic data sets covering over 20 malignancies. These data provide valuable insights into the underlying genetic and genomic basis of cancer. However, exploring the relationship among TCGA genomic results and clinical phenotype remains a challenge, particularly for individuals lacking formal bioinformatics training. Overcoming this hurdle is an important step toward the wider clinical translation of cancer genomic/proteomic data and implementation of precision cancer medicine. Several websites such as the cBio portal or University of California Santa Cruz genome browser make TCGA data accessible but lack interactive features for querying clinically relevant phenotypic associations with cancer drivers. To enable exploration of the clinical-genomic driver associations from TCGA data, we developed the Cancer Genome Atlas Clinical Explorer. The Cancer Genome Atlas Clinical Explorer interface provides a straightforward platform to query TCGA data using one of the following methods: (1) searching for clinically relevant genes, micro RNAs, and proteins by name, cancer types, or clinical parameters; (2) searching for genomic/proteomic profile changes by clinical parameters in a cancer type; or (3) testing two-hit hypotheses. SQL queries run in the background and results are displayed on our portal in an easy-to-navigate interface according to user's input. To derive these associations, we relied on elastic-net estimates of optimal multiple linear regularized regression and clinical parameters in the space of multiple genomic/proteomic features provided by TCGA data. Moreover, we identified and ranked gene/micro RNA/protein predictors of each clinical parameter for each cancer. The robustness of the results was estimated by bootstrapping. Overall, we identify associations of potential clinical relevance among genes/micro RNAs/proteins using our statistical analysis from 25 cancer types and 18 clinical parameters that

  11. Differential expression patterns of housekeeping genes increase diagnostic and prognostic value in lung cancer

    PubMed Central

    Chang, Yu-Chun; Ding, Yan; Dong, Lingsheng; Zhu, Lang-Jing; Jensen, Roderick V.

    2018-01-01

    Background Using DNA microarrays, we previously identified 451 genes expressed in 19 different human tissues. Although ubiquitously expressed, the variable expression patterns of these “housekeeping genes” (HKGs) could separate one normal human tissue type from another. Current focus on identifying “specific disease markers” is problematic as single gene expression in a given sample represents the specific cellular states of the sample at the time of collection. In this study, we examine the diagnostic and prognostic potential of the variable expressions of HKGs in lung cancers. Methods Microarray and RNA-seq data for normal lungs, lung adenocarcinomas (AD), squamous cell carcinomas of the lung (SQCLC), and small cell carcinomas of the lung (SCLC) were collected from online databases. Using 374 of 451 HKGs, differentially expressed genes between pairs of sample types were determined via two-sided, homoscedastic t-test. Principal component analysis and hierarchical clustering classified normal lung and lung cancers subtypes according to relative gene expression variations. We used uni- and multi-variate cox-regressions to identify significant predictors of overall survival in AD patients. Classifying genes were selected using a set of training samples and then validated using an independent test set. Gene Ontology was examined by PANTHER. Results This study showed that the differential expression patterns of 242, 245, and 99 HKGs were able to distinguish normal lung from AD, SCLC, and SQCLC, respectively. From these, 70 HKGs were common across the three lung cancer subtypes. These HKGs have low expression variation compared to current lung cancer markers (e.g., EGFR, KRAS) and were involved in the most common biological processes (e.g., metabolism, stress response). In addition, the expression pattern of 106 HKGs alone was a significant classifier of AD versus SQCLC. We further highlighted that a panel of 13 HKGs was an independent predictor of overall

  12. Robust Principal Component Analysis Regularized by Truncated Nuclear Norm for Identifying Differentially Expressed Genes.

    PubMed

    Wang, Ya-Xuan; Gao, Ying-Lian; Liu, Jin-Xing; Kong, Xiang-Zhen; Li, Hai-Jun

    2017-09-01

    Identifying differentially expressed genes from the thousands of genes is a challenging task. Robust principal component analysis (RPCA) is an efficient method in the identification of differentially expressed genes. RPCA method uses nuclear norm to approximate the rank function. However, theoretical studies showed that the nuclear norm minimizes all singular values, so it may not be the best solution to approximate the rank function. The truncated nuclear norm is defined as the sum of some smaller singular values, which may achieve a better approximation of the rank function than nuclear norm. In this paper, a novel method is proposed by replacing nuclear norm of RPCA with the truncated nuclear norm, which is named robust principal component analysis regularized by truncated nuclear norm (TRPCA). The method decomposes the observation matrix of genomic data into a low-rank matrix and a sparse matrix. Because the significant genes can be considered as sparse signals, the differentially expressed genes are viewed as the sparse perturbation signals. Thus, the differentially expressed genes can be identified according to the sparse matrix. The experimental results on The Cancer Genome Atlas data illustrate that the TRPCA method outperforms other state-of-the-art methods in the identification of differentially expressed genes.

  13. Adenovirus-Mediated p202 Gene Transfer in Breast Cancer Gene Therapy

    DTIC Science & Technology

    2005-05-01

    transcriptional regulation of genes important for cell cycle control, differentiation, and apoptosis (1, 3, 4). Our previous studies have shown that p202...leads to induction of p53 and activation of p53 target gene (e.g., p21 CIP 1). 10. The positive regulation of p53 by IFIXcd can be observed only in...cancers. Together, our data suggest that both Ad-p202 and IFIX may be further developed into efficient therapeutic agents for human cancer gene

  14. Combinations of SERPINB5 gene polymorphisms and environmental factors are associated with oral cancer risks.

    PubMed

    Tsai, Hsiu-Ting; Hsieh, Ming-Ju; Lin, Chiao-Wen; Su, Shih-Chi; Miao, Nae-Fang; Yang, Shun-Fa; Huang, Hui-Chuan; Lai, Fu-Chih; Liu, Yu-Fan

    2017-01-01

    We identified rs17071138 T/C, rs3744941 C/T, and rs8089104 T/C gene polymorphisms of SERPINB5 (mammary serine protease inhibitor) that are specific to patients with oral cancer susceptibility and their clinicopathological status. In total, 1342 participants, including 601 healthy controls and 741 patients with oral cancer, were recruited for this study. Allelic discrimination of rs17071138 T/C, rs3744941 C/T, and rs8089104 T/C of the SERPINB5 gene was assessed by a real-time PCR with a TaqMan assay. We found that individuals carrying the polymorphic rs17071138 and rs8089104 are more susceptible to oral cancer (OR, 1.57; 95% CI, 1.07~2.31 and OR, 1.58; 95% CI, 1.04~2.39, respectively). Among oral cancer-related risk factor exposures, the individuals carrying the polymorphic rs17071138 had 4.26- (95% CI: 1.65~11.01; p = 0.002), 2.34- (95% CI: 1.19~4.61; p = 0.01), and 2.34-fold (95% CI: 1.38~3.96; p = 0.001) higher risks of developing oral cancer. Heterozygous TC of the SERPINB5 rs17071138 polymorphism may be a factor that increases susceptibility to oral cancer. Interactions of gene-to-gene and gene-to-oral cancer-related environmental risk factors have a synergetic effect that can further enhance oral cancer development.

  15. Cancer genes mutation profiling in calcifying epithelial odontogenic tumour.

    PubMed

    de Sousa, Sílvia Ferreira; Diniz, Marina Gonçalves; França, Josiane Alves; Fontes Pereira, Thaís Dos Santos; Moreira, Rennan Garcias; Santos, Jean Nunes Dos; Gomez, Ricardo Santiago; Gomes, Carolina Cavalieri

    2018-03-01

    To identify calcifying epithelial odontogenic tumour (CEOT) mutations in oncogenes and tumour suppressor genes. A panel of 50 genes commonly mutated in cancer was sequenced in CEOT by next-generation sequencing. Sanger sequencing was used to cover the region of the frameshift deletion identified in one sample. Missense single nucleotide variants (SNVs) with minor allele frequency (MAF) <1% were detected in PTEN , MET and JAK3 . A frameshift deletion in CDKN2A occurred in association with a missense mutation in the same gene region, suggesting a second hit in the inactivation of this gene. APC, KDR, KIT, PIK3CA and TP53 missense SNVs were identified; however, these are common SNVs, showing MAF >1%. CEOT harbours mutations in the tumour suppressor PTEN and CDKN2A and in the oncogenes JAK3 and MET . As these mutations occurred in only one case each, they are probably not driver mutations for these tumours. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

  16. Modifier locus mapping of a transgenic F2 mouse population identifies CCDC115 as a novel aggressive prostate cancer modifier gene in humans.

    PubMed

    Winter, Jean M; Curry, Natasha L; Gildea, Derek M; Williams, Kendra A; Lee, Minnkyong; Hu, Ying; Crawford, Nigel P S

    2018-06-11

    It is well known that development of prostate cancer (PC) can be attributed to somatic mutations of the genome, acquired within proto-oncogenes or tumor-suppressor genes. What is less well understood is how germline variation contributes to disease aggressiveness in PC patients. To map germline modifiers of aggressive neuroendocrine PC, we generated a genetically diverse F2 intercross population using the transgenic TRAMP mouse model and the wild-derived WSB/EiJ (WSB) strain. The relevance of germline modifiers of aggressive PC identified in these mice was extensively correlated in human PC datasets and functionally validated in cell lines. Aggressive PC traits were quantified in a population of 30 week old (TRAMP x WSB) F2 mice (n = 307). Correlation of germline genotype with aggressive disease phenotype revealed seven modifier loci that were significantly associated with aggressive disease. RNA-seq were analyzed using cis-eQTL and trait correlation analyses to identify candidate genes within each of these loci. Analysis of 92 (TRAMP x WSB) F2 prostates revealed 25 candidate genes that harbored both a significant cis-eQTL and mRNA expression correlations with an aggressive PC trait. We further delineated these candidate genes based on their clinical relevance, by interrogating human PC GWAS and PC tumor gene expression datasets. We identified four genes (CCDC115, DNAJC10, RNF149, and STYXL1), which encompassed all of the following characteristics: 1) one or more germline variants associated with aggressive PC traits; 2) differential mRNA levels associated with aggressive PC traits; and 3) differential mRNA expression between normal and tumor tissue. Functional validation studies of these four genes using the human LNCaP prostate adenocarcinoma cell line revealed ectopic overexpression of CCDC115 can significantly impede cell growth in vitro and tumor growth in vivo. Furthermore, CCDC115 human prostate tumor expression was associated with better survival

  17. Identification of Human HK Genes and Gene Expression Regulation Study in Cancer from Transcriptomics Data Analysis

    PubMed Central

    Zhang, Zhang; Liu, Jingxing; Wu, Jiayan; Yu, Jun

    2013-01-01

    The regulation of gene expression is essential for eukaryotes, as it drives the processes of cellular differentiation and morphogenesis, leading to the creation of different cell types in multicellular organisms. RNA-Sequencing (RNA-Seq) provides researchers with a powerful toolbox for characterization and quantification of transcriptome. Many different human tissue/cell transcriptome datasets coming from RNA-Seq technology are available on public data resource. The fundamental issue here is how to develop an effective analysis method to estimate expression pattern similarities between different tumor tissues and their corresponding normal tissues. We define the gene expression pattern from three directions: 1) expression breadth, which reflects gene expression on/off status, and mainly concerns ubiquitously expressed genes; 2) low/high or constant/variable expression genes, based on gene expression level and variation; and 3) the regulation of gene expression at the gene structure level. The cluster analysis indicates that gene expression pattern is higher related to physiological condition rather than tissue spatial distance. Two sets of human housekeeping (HK) genes are defined according to cell/tissue types, respectively. To characterize the gene expression pattern in gene expression level and variation, we firstly apply improved K-means algorithm and a gene expression variance model. We find that cancer-associated HK genes (a HK gene is specific in cancer group, while not in normal group) are expressed higher and more variable in cancer condition than in normal condition. Cancer-associated HK genes prefer to AT-rich genes, and they are enriched in cell cycle regulation related functions and constitute some cancer signatures. The expression of large genes is also avoided in cancer group. These studies will help us understand which cell type-specific patterns of gene expression differ among different cell types, and particularly for cancer. PMID:23382867

  18. Investigation of MACC1 Gene Expression in Head and Neck Cancer and Cancer Stem Cells.

    PubMed

    Evran, Ebru; Şahin, Hilal; Akbaş, Kübra; Çiğdem, Sadik; Gündüz, Esra

    2016-12-01

    By investigating the MACC1 gene (metastasis-associated in colon cancer 1) in cancer stem cells (CSC) resistant to chemotherapy and in cancer stem cells (CSC) resistant to chemotherapy and in cancer cells (CS) sensitive to chemotherapy we determineda steady expression in both types of cells in head and neck cancer. In conformity with the result we examined if this gene could be a competitor gene for chemotherapy. According to literature, the MACC1 gene shows a clear expression in head and neck cancer cells [1]. Here we examined MACC1 expression in CSC and investigated it as a possible biomarker. Our experiments were performed in the UT -SCC -74 in primary head and neck cancer cell line. We examined the MACC -1 gene expression by Real Time PCR from both isolated CSC and CS. Expression of MACC -1 gene of cancer stem cells showed an two-fold increase compared with cancer cells. Based on the positive expression of MACC1 in both CS and CSC, this gene may serve as a potential biomarker in head and neck cancer. By comparing the results of this study with the novel features of MACC1, two important hypotheses could be examined. The first hypothesis is that MACC1 is a possible transcripton factor in colon cancer, which influences a high expression of CSC in head and neck and affects the expression of three biomarkers of the CSC control group biomarkers. The second hypothesisis is that the positive expression of MACC1 in patients with a malignant prognosis of tongue cancer, which belongs to head and neck cancer types, operates a faster development of CSC to cancer cells.

  19. Telomere structure and maintenance gene variants and risk of five cancer types

    PubMed Central

    Karami, Sara; Han, Younghun; Pande, Mala; Cheng, Iona; Rudd, James; Pierce, Brandon L.; Nutter, Ellen L.; Schumacher, Fredrick R.; Kote-Jarai, Zsofia; Lindstrom, Sara; Witte, John S.; Fang, Shenying; Han, Jiali; Kraft, Peter; Hunter, David; Song, Fengju; Hung, Rayjean J.; McKay, James; Gruber, Stephen B.; Chanock, Stephen J.; Risch, Angela; Shen, Hongbing; Haiman, Christopher A.; Boardman, Lisa; Ulrich, Cornelia M.; Casey, Graham; Peters, Ulrike; Al Olama, Ali Amin; Berchuck, Andrew; Berndt, Sonja I.; Bezieau, Stephane; Brennan, Paul; Brenner, Hermann; Brinton, Louise; Caporaso, Neil; Chan, Andrew T.; Chang-Claude, Jenny; Christiani, David C.; Cunningham, Julie M.; Easton, Douglas; Eeles, Rosalind A.; Eisen, Timothy; Gala, Manish; Gallinger, Steven J.; Gayther, Simon A.; Goode, Ellen L.; Grönberg, Henrik; Henderson, Brian E.; Houlston, Richard; Joshi, Amit D.; Küry, Sébastien; Landi, Mari T.; Le Marchand, Loic; Muir, Kenneth; Newcomb, Polly A.; Permuth-Wey, Jenny; Pharoah, Paul; Phelan, Catherine; Potter, John D.; Ramus, Susan J.; Risch, Harvey; Schildkraut, Joellen; Slattery, Martha L.; Song, Honglin; Wentzensen, Nicolas; White, Emily; Wiklund, Fredrik; Zanke, Brent W.; Sellers, Thomas A.; Zheng, Wei; Chatterjee, Nilanjan; Amos, Christopher I.; Doherty, Jennifer A.

    2016-01-01

    Telomeres cap chromosome ends, protecting them from degradation, double-strand breaks, and end-to-end fusions. Telomeres are maintained by telomerase, a reverse transcriptase encoded by TERT, and an RNA template encoded by TERC. Loci in the TERT and adjoining CLPTM1L region are associated with risk of multiple cancers. We therefore investigated associations between variants in 22 telomere structure and maintenance gene regions and colorectal, breast, prostate, ovarian, and lung cancer risk. We performed subset-based meta-analyses of 204,993 directly-measured and imputed SNPs among 61,851 cancer cases and 74,457 controls of European descent. Independent associations for SNP minor alleles were identified using sequential conditional analysis (with gene-level P-value cutoffs ≤3.08×10−5). Of the thirteen independent SNPs observed to be associated with cancer risk, novel findings were observed for seven loci. Across the TERT-CLPTML1 region, rs12655062 was associated positively with prostate cancer, and inversely with colorectal and ovarian cancers, and rs115960372 was associated positively with prostate cancer. Across the TERC region, rs75316749 was positively associated with colorectal, breast, ovarian, and lung cancers. Across the DCLRE1B region, rs974404 and rs12144215 were inversely associated with prostate and lung cancers, and colorectal, breast, and ovarian cancers, respectively. Near POT1, rs116895242 was inversely associated with colorectal, ovarian, and lung cancers, and RTEL1 rs34978822 was inversely associated with prostate and lung cancers. The complex association patterns in telomere-related genes across cancer types may provide insight into mechanisms through which telomere dysfunction in different tissues influences cancer risk. PMID:27459707

  20. Mutational signature analysis identifies MUTYH deficiency in colorectal cancers and adrenocortical carcinomas: Mutational signature associated with MUTYH deficiency in cancers

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Pilati, Camilla; Shinde, Jayendra; Alexandrov, Ludmil B.

    Germline alterations in DNA repair genes are implicated in cancer predisposition and can result in characteristic mutational signatures. However, specific mutational signatures associated with base excision repair (BER) defects remain to be characterized. Here, by analysing a series of colorectal cancers (CRCs) using exome sequencing, we identified a particular spectrum of somatic mutations characterized by an enrichment of C > A transversions in NpCpA or NpCpT contexts in three tumours from a MUTYH-associated polyposis (MAP) patient and in two cases harbouring pathogenic germline MUTYH mutations. In two series of adrenocortical carcinomas (ACCs), we identified four tumours with a similar signaturemore » also presenting germline MUTYH mutations. Altogether, these findings demonstrate that MUTYH inactivation results in a particular mutational signature, which may serve as a useful marker of BER-related genomic instability in new cancer types.« less

  1. Mutational signature analysis identifies MUTYH deficiency in colorectal cancers and adrenocortical carcinomas: Mutational signature associated with MUTYH deficiency in cancers

    DOE PAGES

    Pilati, Camilla; Shinde, Jayendra; Alexandrov, Ludmil B.; ...

    2017-03-29

    Germline alterations in DNA repair genes are implicated in cancer predisposition and can result in characteristic mutational signatures. However, specific mutational signatures associated with base excision repair (BER) defects remain to be characterized. Here, by analysing a series of colorectal cancers (CRCs) using exome sequencing, we identified a particular spectrum of somatic mutations characterized by an enrichment of C > A transversions in NpCpA or NpCpT contexts in three tumours from a MUTYH-associated polyposis (MAP) patient and in two cases harbouring pathogenic germline MUTYH mutations. In two series of adrenocortical carcinomas (ACCs), we identified four tumours with a similar signaturemore » also presenting germline MUTYH mutations. Altogether, these findings demonstrate that MUTYH inactivation results in a particular mutational signature, which may serve as a useful marker of BER-related genomic instability in new cancer types.« less

  2. Systematic Search for Gene-Gene Interaction Effect on Prostate Cancer Risk

    DTIC Science & Technology

    2013-07-01

    Systematic Search for Gene-Gene Interaction 5a. CONTRACT NUMBER Effect on Prostate Cancer Risk 5b. GRANT NUMBER W81XWH-09-1-0488 5c. PROGRAM...Supported by this grant ) 1. Tao S, Wang Z, Feng J, Hsu FC, Jin G, Kin ST, Zhang Z, Gronberg H, Zheng, SL, Isaacs WB, XU J, Sun J. A Genome-Wide Search for...order interactions among estrogen- metabolism genes in sporadic breast cancer. Am J Hum Genet, 69, 138-47. 48. Marchini, J., Donnelly, P. and Cardon

  3. Depletion of Mediator Kinase Module Subunits Represses Superenhancer-Associated Genes in Colon Cancer Cells.

    PubMed

    Kuuluvainen, Emilia; Domènech-Moreno, Eva; Niemelä, Elina H; Mäkelä, Tomi P

    2018-06-01

    In cancer, oncogene activation is partly mediated by acquired superenhancers, which therefore represent potential targets for inhibition. Superenhancers are enriched for BRD4 and Mediator, and both BRD4 and the Mediator MED12 subunit are disproportionally required for expression of superenhancer-associated genes in stem cells. Here we show that depletion of Mediator kinase module subunit MED12 or MED13 together with MED13L can be used to reduce expression of cancer-acquired superenhancer genes, such as the MYC gene, in colon cancer cells, with a concomitant decrease in proliferation. Whereas depletion of MED12 or MED13/MED13L caused a disproportional decrease of superenhancer gene expression, this was not seen with depletion of the kinases cyclin-dependent kinase 9 (CDK8) and CDK19. MED12-MED13/MED13L-dependent superenhancer genes were coregulated by β-catenin, which has previously been shown to associate with MED12. Importantly, β-catenin depletion caused reduced binding of MED12 at the MYC superenhancer. The effect of MED12 or MED13/MED13L depletion on cancer-acquired superenhancer gene expression was more specific than and partially distinct from that of BRD4 depletion, with the most efficient inhibition seen with combined targeting. These results identify a requirement of MED12 and MED13/MED13L for expression of acquired superenhancer genes in colon cancer, implicating these Mediator subunits as potential therapeutic targets for colon cancer, alone or together with BRD4. Copyright © 2018 American Society for Microbiology.

  4. Screening for large genomic rearrangements in the FANCA gene reveals extensive deletion in a Finnish breast cancer family.

    PubMed

    Solyom, Szilvia; Winqvist, Robert; Nikkilä, Jenni; Rapakko, Katrin; Hirvikoski, Pasi; Kokkonen, Hannaleena; Pylkäs, Katri

    2011-03-28

    A portion of familial breast cancer cases are caused by mutations in the same genes that are inactivated in the downstream part of Fanconi anemia (FA) signaling pathway. Here we have assessed the FANCA gene for breast cancer susceptibility by examining blood DNA for aberrations from 100 Northern Finnish breast cancer families using the MLPA method. We identified a novel heterozygous deletion, removing the promoter and 12 exons of the gene in one family. This allele was absent from 124 controls. We conclude that FANCA deletions might contribute to breast cancer susceptibility, potentially in combination with other germline mutations. To our knowledge, this is the first study reporting a large deletion in an upstream FA gene in familial breast cancer. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

  5. Bayesian logistic regression in detection of gene-steroid interaction for cancer at PDLIM5 locus.

    PubMed

    Wang, Ke-Sheng; Owusu, Daniel; Pan, Yue; Xie, Changchun

    2016-06-01

    The PDZ and LIM domain 5 (PDLIM5) gene may play a role in cancer, bipolar disorder, major depression, alcohol dependence and schizophrenia; however, little is known about the interaction effect of steroid and PDLIM5 gene on cancer. This study examined 47 single-nucleotide polymorphisms (SNPs) within the PDLIM5 gene in the Marshfield sample with 716 cancer patients (any diagnosed cancer, excluding minor skin cancer) and 2848 noncancer controls. Multiple logistic regression model in PLINK software was used to examine the association of each SNP with cancer. Bayesian logistic regression in PROC GENMOD in SAS statistical software, ver. 9.4 was used to detect gene- steroid interactions influencing cancer. Single marker analysis using PLINK identified 12 SNPs associated with cancer (P< 0.05); especially, SNP rs6532496 revealed the strongest association with cancer (P = 6.84 × 10⁻³); while the next best signal was rs951613 (P = 7.46 × 10⁻³). Classic logistic regression in PROC GENMOD showed that both rs6532496 and rs951613 revealed strong gene-steroid interaction effects (OR=2.18, 95% CI=1.31-3.63 with P = 2.9 × 10⁻³ for rs6532496 and OR=2.07, 95% CI=1.24-3.45 with P = 5.43 × 10⁻³ for rs951613, respectively). Results from Bayesian logistic regression showed stronger interaction effects (OR=2.26, 95% CI=1.2-3.38 for rs6532496 and OR=2.14, 95% CI=1.14-3.2 for rs951613, respectively). All the 12 SNPs associated with cancer revealed significant gene-steroid interaction effects (P < 0.05); whereas 13 SNPs showed gene-steroid interaction effects without main effect on cancer. SNP rs4634230 revealed the strongest gene-steroid interaction effect (OR=2.49, 95% CI=1.5-4.13 with P = 4.0 × 10⁻⁴ based on the classic logistic regression and OR=2.59, 95% CI=1.4-3.97 from Bayesian logistic regression; respectively). This study provides evidence of common genetic variants within the PDLIM5 gene and interactions between PLDIM5 gene polymorphisms and steroid use

  6. Large-scale integrative network-based analysis identifies common pathways disrupted by copy number alterations across cancers

    PubMed Central

    2013-01-01

    Background Many large-scale studies analyzed high-throughput genomic data to identify altered pathways essential to the development and progression of specific types of cancer. However, no previous study has been extended to provide a comprehensive analysis of pathways disrupted by copy number alterations across different human cancers. Towards this goal, we propose a network-based method to integrate copy number alteration data with human protein-protein interaction networks and pathway databases to identify pathways that are commonly disrupted in many different types of cancer. Results We applied our approach to a data set of 2,172 cancer patients across 16 different types of cancers, and discovered a set of commonly disrupted pathways, which are likely essential for tumor formation in majority of the cancers. We also identified pathways that are only disrupted in specific cancer types, providing molecular markers for different human cancers. Analysis with independent microarray gene expression datasets confirms that the commonly disrupted pathways can be used to identify patient subgroups with significantly different survival outcomes. We also provide a network view of disrupted pathways to explain how copy number alterations affect pathways that regulate cell growth, cycle, and differentiation for tumorigenesis. Conclusions In this work, we demonstrated that the network-based integrative analysis can help to identify pathways disrupted by copy number alterations across 16 types of human cancers, which are not readily identifiable by conventional overrepresentation-based and other pathway-based methods. All the results and source code are available at http://compbio.cs.umn.edu/NetPathID/. PMID:23822816

  7. Integrative analysis identifies targetable CREB1/FoxA1 transcriptional co-regulation as a predictor of prostate cancer recurrence.

    PubMed

    Sunkel, Benjamin; Wu, Dayong; Chen, Zhong; Wang, Chiou-Miin; Liu, Xiangtao; Ye, Zhenqing; Horning, Aaron M; Liu, Joseph; Mahalingam, Devalingam; Lopez-Nicora, Horacio; Lin, Chun-Lin; Goodfellow, Paul J; Clinton, Steven K; Jin, Victor X; Chen, Chun-Liang; Huang, Tim H-M; Wang, Qianben

    2016-05-19

    Identifying prostate cancer-driving transcription factors (TFs) in addition to the androgen receptor promises to improve our ability to effectively diagnose and treat this disease. We employed an integrative genomics analysis of master TFs CREB1 and FoxA1 in androgen-dependent prostate cancer (ADPC) and castration-resistant prostate cancer (CRPC) cell lines, primary prostate cancer tissues and circulating tumor cells (CTCs) to investigate their role in defining prostate cancer gene expression profiles. Combining genome-wide binding site and gene expression profiles we define CREB1 as a critical driver of pro-survival, cell cycle and metabolic transcription programs. We show that CREB1 and FoxA1 co-localize and mutually influence each other's binding to define disease-driving transcription profiles associated with advanced prostate cancer. Gene expression analysis in human prostate cancer samples found that CREB1/FoxA1 target gene panels predict prostate cancer recurrence. Finally, we showed that this signaling pathway is sensitive to compounds that inhibit the transcription co-regulatory factor MED1. These findings not only reveal a novel, global transcriptional co-regulatory function of CREB1 and FoxA1, but also suggest CREB1/FoxA1 signaling is a targetable driver of prostate cancer progression and serves as a biomarker of poor clinical outcomes. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

  8. Signaling, Gene Regulation and Cancer | Center for Cancer Research

    Cancer.gov

    Although there have been tremendous progress in cancer research and treatment, the mortality caused by this disease is still very high. Cancer is the leading cause of death worldwide and second leading cause of death in the United States of America. Signaling, Gene Regulation and Cancer covers topics including the role of various signaling pathways in development, regulation

  9. Glycosyltransferase Gene Expression Profiles Classify Cancer Types and Propose Prognostic Subtypes

    NASA Astrophysics Data System (ADS)

    Ashkani, Jahanshah; Naidoo, Kevin J.

    2016-05-01

    Aberrant glycosylation in tumours stem from altered glycosyltransferase (GT) gene expression but can the expression profiles of these signature genes be used to classify cancer types and lead to cancer subtype discovery? The differential structural changes to cellular glycan structures are predominantly regulated by the expression patterns of GT genes and are a hallmark of neoplastic cell metamorphoses. We found that the expression of 210 GT genes taken from 1893 cancer patient samples in The Cancer Genome Atlas (TCGA) microarray data are able to classify six cancers; breast, ovarian, glioblastoma, kidney, colon and lung. The GT gene expression profiles are used to develop cancer classifiers and propose subtypes. The subclassification of breast cancer solid tumour samples illustrates the discovery of subgroups from GT genes that match well against basal-like and HER2-enriched subtypes and correlates to clinical, mutation and survival data. This cancer type glycosyltransferase gene signature finding provides foundational evidence for the centrality of glycosylation in cancer.

  10. Telomere structure and maintenance gene variants and risk of five cancer types.

    PubMed

    Karami, Sara; Han, Younghun; Pande, Mala; Cheng, Iona; Rudd, James; Pierce, Brandon L; Nutter, Ellen L; Schumacher, Fredrick R; Kote-Jarai, Zsofia; Lindstrom, Sara; Witte, John S; Fang, Shenying; Han, Jiali; Kraft, Peter; Hunter, David J; Song, Fengju; Hung, Rayjean J; McKay, James; Gruber, Stephen B; Chanock, Stephen J; Risch, Angela; Shen, Hongbing; Haiman, Christopher A; Boardman, Lisa; Ulrich, Cornelia M; Casey, Graham; Peters, Ulrike; Amin Al Olama, Ali; Berchuck, Andrew; Berndt, Sonja I; Bezieau, Stephane; Brennan, Paul; Brenner, Hermann; Brinton, Louise; Caporaso, Neil; Chan, Andrew T; Chang-Claude, Jenny; Christiani, David C; Cunningham, Julie M; Easton, Douglas; Eeles, Rosalind A; Eisen, Timothy; Gala, Manish; Gallinger, Steven J; Gayther, Simon A; Goode, Ellen L; Grönberg, Henrik; Henderson, Brian E; Houlston, Richard; Joshi, Amit D; Küry, Sébastien; Landi, Mari T; Le Marchand, Loic; Muir, Kenneth; Newcomb, Polly A; Permuth-Wey, Jenny; Pharoah, Paul; Phelan, Catherine; Potter, John D; Ramus, Susan J; Risch, Harvey; Schildkraut, Joellen; Slattery, Martha L; Song, Honglin; Wentzensen, Nicolas; White, Emily; Wiklund, Fredrik; Zanke, Brent W; Sellers, Thomas A; Zheng, Wei; Chatterjee, Nilanjan; Amos, Christopher I; Doherty, Jennifer A

    2016-12-15

    Telomeres cap chromosome ends, protecting them from degradation, double-strand breaks, and end-to-end fusions. Telomeres are maintained by telomerase, a reverse transcriptase encoded by TERT, and an RNA template encoded by TERC. Loci in the TERT and adjoining CLPTM1L region are associated with risk of multiple cancers. We therefore investigated associations between variants in 22 telomere structure and maintenance gene regions and colorectal, breast, prostate, ovarian, and lung cancer risk. We performed subset-based meta-analyses of 204,993 directly-measured and imputed SNPs among 61,851 cancer cases and 74,457 controls of European descent. Independent associations for SNP minor alleles were identified using sequential conditional analysis (with gene-level p value cutoffs ≤3.08 × 10 -5 ). Of the thirteen independent SNPs observed to be associated with cancer risk, novel findings were observed for seven loci. Across the DCLRE1B region, rs974494 and rs12144215 were inversely associated with prostate and lung cancers, and colorectal, breast, and prostate cancers, respectively. Across the TERC region, rs75316749 was positively associated with colorectal, breast, ovarian, and lung cancers. Across the DCLRE1B region, rs974404 and rs12144215 were inversely associated with prostate and lung cancers, and colorectal, breast, and prostate cancers, respectively. Near POT1, rs116895242 was inversely associated with colorectal, ovarian, and lung cancers, and RTEL1 rs34978822 was inversely associated with prostate and lung cancers. The complex association patterns in telomere-related genes across cancer types may provide insight into mechanisms through which telomere dysfunction in different tissues influences cancer risk. © 2016 UICC.

  11. Alternative splicing and differential gene expression in colon cancer detected by a whole genome exon array

    PubMed Central

    Gardina, Paul J; Clark, Tyson A; Shimada, Brian; Staples, Michelle K; Yang, Qing; Veitch, James; Schweitzer, Anthony; Awad, Tarif; Sugnet, Charles; Dee, Suzanne; Davies, Christopher; Williams, Alan; Turpaz, Yaron

    2006-01-01

    Background Alternative splicing is a mechanism for increasing protein diversity by excluding or including exons during post-transcriptional processing. Alternatively spliced proteins are particularly relevant in oncology since they may contribute to the etiology of cancer, provide selective drug targets, or serve as a marker set for cancer diagnosis. While conventional identification of splice variants generally targets individual genes, we present here a new exon-centric array (GeneChip Human Exon 1.0 ST) that allows genome-wide identification of differential splice variation, and concurrently provides a flexible and inclusive analysis of gene expression. Results We analyzed 20 paired tumor-normal colon cancer samples using a microarray designed to detect over one million putative exons that can be virtually assembled into potential gene-level transcripts according to various levels of prior supporting evidence. Analysis of high confidence (empirically supported) transcripts identified 160 differentially expressed genes, with 42 genes occupying a network impacting cell proliferation and another twenty nine genes with unknown functions. A more speculative analysis, including transcripts based solely on computational prediction, produced another 160 differentially expressed genes, three-fourths of which have no previous annotation. We also present a comparison of gene signal estimations from the Exon 1.0 ST and the U133 Plus 2.0 arrays. Novel splicing events were predicted by experimental algorithms that compare the relative contribution of each exon to the cognate transcript intensity in each tissue. The resulting candidate splice variants were validated with RT-PCR. We found nine genes that were differentially spliced between colon tumors and normal colon tissues, several of which have not been previously implicated in cancer. Top scoring candidates from our analysis were also found to substantially overlap with EST-based bioinformatic predictions of alternative

  12. Gene Expression Profiling of Liver Cancer Stem Cells by RNA-Sequencing

    PubMed Central

    Lam, Chi Tat; Ng, Michael N. P.; Yu, Wan Ching; Lau, Joyce; Wan, Timothy; Wang, Xiaoqi; Yan, Zhixiang; Liu, Hang; Fan, Sheung Tat

    2012-01-01

    Background Accumulating evidence supports that tumor growth and cancer relapse are driven by cancer stem cells. Our previous work has demonstrated the existence of CD90+ liver cancer stem cells (CSCs) in hepatocellular carcinoma (HCC). Nevertheless, the characteristics of these cells are still poorly understood. In this study, we employed a more sensitive RNA-sequencing (RNA-Seq) to compare the gene expression profiling of CD90+ cells sorted from tumor (CD90+CSCs) with parallel non-tumorous liver tissues (CD90+NTSCs) and elucidate the roles of putative target genes in hepatocarcinogenesis. Methodology/Principal Findings CD90+ cells were sorted respectively from tumor and adjacent non-tumorous human liver tissues using fluorescence-activated cell sorting. The amplified RNAs of CD90+ cells from 3 HCC patients were subjected to RNA-Seq analysis. A differential gene expression profile was established between CD90+CSCs and CD90+NTSCs, and validated by quantitative real-time PCR (qRT-PCR) on the same set of amplified RNAs, and further confirmed in an independent cohort of 12 HCC patients. Five hundred genes were differentially expressed (119 up-regulated and 381 down-regulated genes) between CD90+CSCs and CD90+NTSCs. Gene ontology analysis indicated that the over-expressed genes in CD90+CSCs were associated with inflammation, drug resistance and lipid metabolism. Among the differentially expressed genes, glypican-3 (GPC3), a member of glypican family, was markedly elevated in CD90+CSCs compared to CD90+NTSCs. Immunohistochemistry demonstrated that GPC3 was highly expressed in forty-two human liver tumor tissues but absent in adjacent non-tumorous liver tissues. Flow cytometry indicated that GPC3 was highly expressed in liver CD90+CSCs and mature cancer cells in liver cancer cell lines and human liver tumor tissues. Furthermore, GPC3 expression was positively correlated with the number of CD90+CSCs in liver tumor tissues. Conclusions/Significance The identified genes

  13. Alu distribution and mutation types of cancer genes

    PubMed Central

    2011-01-01

    Background Alu elements are the most abundant retrotransposable elements comprising ~11% of the human genome. Many studies have highlighted the role that Alu elements have in genetic instability and how their contribution to the assortment of mutagenic events can lead to cancer. As of yet, little has been done to quantitatively assess the association between Alu distribution and genes that are causally implicated in oncogenesis. Results We have investigated the effect of various Alu densities on the mutation type based classifications of cancer genes. In order to establish the direct relationship between Alus and the cancer genes of interest, genome wide Alu-related densities were measured using genes rather than the sliding windows of fixed length as the units. Several novel genomic features, such as the density of the adjacent Alu pairs and the number of Alu-Exon-Alu triplets, were developed in order to extend the investigation via the multivariate statistical analysis toward more advanced biological insight. In addition, we characterized the genome-wide intron Alu distribution with a mixture model that distinguished genes containing Alu elements from those with no Alus, and evaluated the gene-level effect of the 5'-TTAAAA motif associated with Alu insertion sites using a two-step regression analysis method. Conclusions The study resulted in several novel findings worthy of further investigation. They include: (1) Recessive cancer genes (tumor suppressor genes) are enriched with Alu elements (p < 0.01) compared to dominant cancer genes (oncogenes) and the entire set of genes in the human genome; (2) Alu-related genomic features can be used to cluster cancer genes into biological meaningful groups; (3) The retention of exon Alus has been restricted in the human genome development, and an upper limit to the chromosome-level exon Alu densities is suggested by the distribution profile; (4) For the genes with at least one intron Alu repeat in individual chromosomes

  14. Development and validation of a gene profile predicting benefit of postmastectomy radiotherapy in patients with high-risk breast cancer: a study of gene expression in the DBCG82bc cohort.

    PubMed

    Tramm, Trine; Mohammed, Hayat; Myhre, Simen; Kyndi, Marianne; Alsner, Jan; Børresen-Dale, Anne-Lise; Sørlie, Therese; Frigessi, Arnoldo; Overgaard, Jens

    2014-10-15

    To identify genes predicting benefit of radiotherapy in patients with high-risk breast cancer treated with systemic therapy and randomized to receive or not receive postmastectomy radiotherapy (PMRT). The study was based on the Danish Breast Cancer Cooperative Group (DBCG82bc) cohort. Gene-expression analysis was performed in a training set of frozen tumor tissue from 191 patients. Genes were identified through the Lasso method with the endpoint being locoregional recurrence (LRR). A weighted gene-expression index (DBCG-RT profile) was calculated and transferred to quantitative real-time PCR (qRT-PCR) in corresponding formalin-fixed, paraffin-embedded (FFPE) samples, before validation in FFPE from 112 additional patients. Seven genes were identified, and the derived DBCG-RT profile divided the 191 patients into "high LRR risk" and "low LRR risk" groups. PMRT significantly reduced risk of LRR in "high LRR risk" patients, whereas "low LRR risk" patients showed no additional reduction in LRR rate. Technical transfer of the DBCG-RT profile to FFPE/qRT-PCR was successful, and the predictive impact was successfully validated in another 112 patients. A DBCG-RT gene profile was identified and validated, identifying patients with very low risk of LRR and no benefit from PMRT. The profile may provide a method to individualize treatment with PMRT. ©2014 American Association for Cancer Research.

  15. Identification of constrained cancer driver genes based on mutation timing.

    PubMed

    Sakoparnig, Thomas; Fried, Patrick; Beerenwinkel, Niko

    2015-01-01

    Cancer drivers are genomic alterations that provide cells containing them with a selective advantage over their local competitors, whereas neutral passengers do not change the somatic fitness of cells. Cancer-driving mutations are usually discriminated from passenger mutations by their higher degree of recurrence in tumor samples. However, there is increasing evidence that many additional driver mutations may exist that occur at very low frequencies among tumors. This observation has prompted alternative methods for driver detection, including finding groups of mutually exclusive mutations and incorporating prior biological knowledge about gene function or network structure. Dependencies among drivers due to epistatic interactions can also result in low mutation frequencies, but this effect has been ignored in driver detection so far. Here, we present a new computational approach for identifying genomic alterations that occur at low frequencies because they depend on other events. Unlike passengers, these constrained mutations display punctuated patterns of occurrence in time. We test this driver-passenger discrimination approach based on mutation timing in extensive simulation studies, and we apply it to cross-sectional copy number alteration (CNA) data from ovarian cancer, CNA and single-nucleotide variant (SNV) data from breast tumors and SNV data from colorectal cancer. Among the top ranked predicted drivers, we find low-frequency genes that have already been shown to be involved in carcinogenesis, as well as many new candidate drivers. The mutation timing approach is orthogonal and complementary to existing driver prediction methods. It will help identifying from cancer genome data the alterations that drive tumor progression.

  16. Identification of Constrained Cancer Driver Genes Based on Mutation Timing

    PubMed Central

    Sakoparnig, Thomas; Fried, Patrick; Beerenwinkel, Niko

    2015-01-01

    Cancer drivers are genomic alterations that provide cells containing them with a selective advantage over their local competitors, whereas neutral passengers do not change the somatic fitness of cells. Cancer-driving mutations are usually discriminated from passenger mutations by their higher degree of recurrence in tumor samples. However, there is increasing evidence that many additional driver mutations may exist that occur at very low frequencies among tumors. This observation has prompted alternative methods for driver detection, including finding groups of mutually exclusive mutations and incorporating prior biological knowledge about gene function or network structure. Dependencies among drivers due to epistatic interactions can also result in low mutation frequencies, but this effect has been ignored in driver detection so far. Here, we present a new computational approach for identifying genomic alterations that occur at low frequencies because they depend on other events. Unlike passengers, these constrained mutations display punctuated patterns of occurrence in time. We test this driver–passenger discrimination approach based on mutation timing in extensive simulation studies, and we apply it to cross-sectional copy number alteration (CNA) data from ovarian cancer, CNA and single-nucleotide variant (SNV) data from breast tumors and SNV data from colorectal cancer. Among the top ranked predicted drivers, we find low-frequency genes that have already been shown to be involved in carcinogenesis, as well as many new candidate drivers. The mutation timing approach is orthogonal and complementary to existing driver prediction methods. It will help identifying from cancer genome data the alterations that drive tumor progression. PMID:25569148

  17. FGF receptor genes and breast cancer susceptibility: results from the Breast Cancer Association Consortium

    PubMed Central

    Agarwal, D; Pineda, S; Michailidou, K; Herranz, J; Pita, G; Moreno, L T; Alonso, M R; Dennis, J; Wang, Q; Bolla, M K; Meyer, K B; Menéndez-Rodríguez, P; Hardisson, D; Mendiola, M; González-Neira, A; Lindblom, A; Margolin, S; Swerdlow, A; Ashworth, A; Orr, N; Jones, M; Matsuo, K; Ito, H; Iwata, H; Kondo, N; Hartman, M; Hui, M; Lim, W Y; T-C Iau, P; Sawyer, E; Tomlinson, I; Kerin, M; Miller, N; Kang, D; Choi, J-Y; Park, S K; Noh, D-Y; Hopper, J L; Schmidt, D F; Makalic, E; Southey, M C; Teo, S H; Yip, C H; Sivanandan, K; Tay, W-T; Brauch, H; Brüning, T; Hamann, U; Dunning, A M; Shah, M; Andrulis, I L; Knight, J A; Glendon, G; Tchatchou, S; Schmidt, M K; Broeks, A; Rosenberg, E H; van't Veer, L J; Fasching, P A; Renner, S P; Ekici, A B; Beckmann, M W; Shen, C-Y; Hsiung, C-N; Yu, J-C; Hou, M-F; Blot, W; Cai, Q; Wu, A H; Tseng, C-C; Van Den Berg, D; Stram, D O; Cox, A; Brock, I W; Reed, M W R; Muir, K; Lophatananon, A; Stewart-Brown, S; Siriwanarangsan, P; Zheng, W; Deming-Halverson, S; Shrubsole, M J; Long, J; Shu, X-O; Lu, W; Gao, Y-T; Zhang, B; Radice, P; Peterlongo, P; Manoukian, S; Mariette, F; Sangrajrang, S; McKay, J; Couch, F J; Toland, A E; Yannoukakos, D; Fletcher, O; Johnson, N; Silva, I dos Santos; Peto, J; Marme, F; Burwinkel, B; Guénel, P; Truong, T; Sanchez, M; Mulot, C; Bojesen, S E; Nordestgaard, B G; Flyer, H; Brenner, H; Dieffenbach, A K; Arndt, V; Stegmaier, C; Mannermaa, A; Kataja, V; Kosma, V-M; Hartikainen, J M; Lambrechts, D; Yesilyurt, B T; Floris, G; Leunen, K; Chang-Claude, J; Rudolph, A; Seibold, P; Flesch-Janys, D; Wang, X; Olson, J E; Vachon, C; Purrington, K; Giles, G G; Severi, G; Baglietto, L; Haiman, C A; Henderson, B E; Schumacher, F; Le Marchand, L; Simard, J; Dumont, M; Goldberg, M S; Labrèche, F; Winqvist, R; Pylkäs, K; Jukkola-Vuorinen, A; Grip, M; Devilee, P; Tollenaar, R A E M; Seynaeve, C; García-Closas, M; Chanock, S J; Lissowska, J; Figueroa, J D; Czene, K; Eriksson, M; Humphreys, K; Darabi, H; Hooning, M J; Kriege, M; Collée, J M; Tilanus-Linthorst, M; Li, J; Jakubowska, A; Lubinski, J; Jaworska-Bieniek, K; Durda, K; Nevanlinna, H; Muranen, T A; Aittomäki, K; Blomqvist, C; Bogdanova, N; Dörk, T; Hall, P; Chenevix-Trench, G; Easton, D F; Pharoah, P D P; Arias-Perez, J I; Zamora, P; Benítez, J; Milne, R L

    2014-01-01

    Background: Breast cancer is one of the most common malignancies in women. Genome-wide association studies have identified FGFR2 as a breast cancer susceptibility gene. Common variation in other fibroblast growth factor (FGF) receptors might also modify risk. We tested this hypothesis by studying genotyped single-nucleotide polymorphisms (SNPs) and imputed SNPs in FGFR1, FGFR3, FGFR4 and FGFRL1 in the Breast Cancer Association Consortium. Methods: Data were combined from 49 studies, including 53 835 cases and 50 156 controls, of which 89 050 (46 450 cases and 42 600 controls) were of European ancestry, 12 893 (6269 cases and 6624 controls) of Asian and 2048 (1116 cases and 932 controls) of African ancestry. Associations with risk of breast cancer, overall and by disease sub-type, were assessed using unconditional logistic regression. Results: Little evidence of association with breast cancer risk was observed for SNPs in the FGF receptor genes. The strongest evidence in European women was for rs743682 in FGFR3; the estimated per-allele odds ratio was 1.05 (95% confidence interval=1.02–1.09, P=0.0020), which is substantially lower than that observed for SNPs in FGFR2. Conclusion: Our results suggest that common variants in the other FGF receptors are not associated with risk of breast cancer to the degree observed for FGFR2. PMID:24548884

  18. A network-based drug repositioning infrastructure for precision cancer medicine through targeting significantly mutated genes in the human cancer genomes.

    PubMed

    Cheng, Feixiong; Zhao, Junfei; Fooksa, Michaela; Zhao, Zhongming

    2016-07-01

    Development of computational approaches and tools to effectively integrate multidomain data is urgently needed for the development of newly targeted cancer therapeutics. We proposed an integrative network-based infrastructure to identify new druggable targets and anticancer indications for existing drugs through targeting significantly mutated genes (SMGs) discovered in the human cancer genomes. The underlying assumption is that a drug would have a high potential for anticancer indication if its up-/down-regulated genes from the Connectivity Map tended to be SMGs or their neighbors in the human protein interaction network. We assembled and curated 693 SMGs in 29 cancer types and found 121 proteins currently targeted by known anticancer or noncancer (repurposed) drugs. We found that the approved or experimental cancer drugs could potentially target these SMGs in 33.3% of the mutated cancer samples, and this number increased to 68.0% by drug repositioning through surveying exome-sequencing data in approximately 5000 normal-tumor pairs from The Cancer Genome Atlas. Furthermore, we identified 284 potential new indications connecting 28 cancer types and 48 existing drugs (adjusted P < .05), with a 66.7% success rate validated by literature data. Several existing drugs (e.g., niclosamide, valproic acid, captopril, and resveratrol) were predicted to have potential indications for multiple cancer types. Finally, we used integrative analysis to showcase a potential mechanism-of-action for resveratrol in breast and lung cancer treatment whereby it targets several SMGs (ARNTL, ASPM, CTTN, EIF4G1, FOXP1, and STIP1). In summary, we demonstrated that our integrative network-based infrastructure is a promising strategy to identify potential druggable targets and uncover new indications for existing drugs to speed up molecularly targeted cancer therapeutics. © The Author 2016. Published by Oxford University Press on behalf of the American Medical Informatics Association. All

  19. Selected approaches for rational drug design and high throughput screening to identify anti-cancer molecules.

    PubMed

    Hedvat, Michael; Emdad, Luni; Das, Swadesh K; Kim, Keetae; Dasgupta, Santanu; Thomas, Shibu; Hu, Bin; Zhu, Shan; Dash, Rupesh; Quinn, Bridget A; Oyesanya, Regina A; Kegelman, Timothy P; Sokhi, Upneet K; Sarkar, Siddik; Erdogan, Eda; Menezes, Mitchell E; Bhoopathi, Praveen; Wang, Xiang-Yang; Pomper, Martin G; Wei, Jun; Wu, Bainan; Stebbins, John L; Diaz, Paul W; Reed, John C; Pellecchia, Maurizio; Sarkar, Devanand; Fisher, Paul B

    2012-11-01

    Structure-based modeling combined with rational drug design, and high throughput screening approaches offer significant potential for identifying and developing lead compounds with therapeutic potential. The present review focuses on these two approaches using explicit examples based on specific derivatives of Gossypol generated through rational design and applications of a cancer-specificpromoter derived from Progression Elevated Gene-3. The Gossypol derivative Sabutoclax (BI-97C1) displays potent anti-tumor activity against a diverse spectrum of human tumors. The model of the docked structure of Gossypol bound to Bcl-XL provided a virtual structure-activity-relationship where appropriate modifications were predicted on a rational basis. These structure-based studies led to the isolation of Sabutoclax, an optically pure isomer of Apogossypol displaying superior efficacy and reduced toxicity. These studies illustrate the power of combining structure-based modeling with rational design to predict appropriate derivatives of lead compounds to be empirically tested and evaluated for bioactivity. Another approach to cancer drug discovery utilizes a cancer-specific promoter as readouts of the transformed state. The promoter region of Progression Elevated Gene-3 is such a promoter with cancer-specific activity. The specificity of this promoter has been exploited as a means of constructing cancer terminator viruses that selectively kill cancer cells and as a systemic imaging modality that specifically visualizes in vivo cancer growth with no background from normal tissues. Screening of small molecule inhibitors that suppress the Progression Elevated Gene-3-promoter may provide relevant lead compounds for cancer therapy that can be combined with further structure-based approaches leading to the development of novel compounds for cancer therapy.

  20. Gene Expression Analysis in Human Breast Cancer Associated Blood Vessels

    PubMed Central

    Jones, Dylan T.; Lechertier, Tanguy; Mitter, Richard; Herbert, John M. J.; Bicknell, Roy; Jones, J. Louise; Li, Ji-Liang; Buffa, Francesca; Harris, Adrian L.; Hodivala-Dilke, Kairbaan

    2012-01-01

    Angiogenesis is essential for solid tumour growth, whilst the molecular profiles of tumour blood vessels have been reported to be different between cancer types. Although presently available anti-angiogenic strategies are providing some promise for the treatment of some cancers it is perhaps not surprisingly that, none of the anti-angiogenic agents available work on all tumours. Thus, the discovery of novel anti-angiogenic targets, relevant to individual cancer types, is required. Using Affymetrix microarray analysis of laser-captured, CD31-positive blood vessels we have identified 63 genes that are upregulated significantly (5–72 fold) in angiogenic blood vessels associated with human invasive ductal carcinoma (IDC) of the breast as compared with blood vessels in normal human breast. We tested the angiogenic capacity of a subset of these genes. Genes were selected based on either their known cellular functions, their enriched expression in endothelial cells and/or their sensitivity to anti-VEGF treatment; all features implicating their involvement in angiogenesis. For example, RRM2, a ribonucleotide reductase involved in DNA synthesis, was upregulated 32-fold in IDC-associated blood vessels; ATF1, a nuclear activating transcription factor involved in cellular growth and survival was upregulated 23-fold in IDC-associated blood vessels and HEX-B, a hexosaminidase involved in the breakdown of GM2 gangliosides, was upregulated 8-fold in IDC-associated blood vessels. Furthermore, in silico analysis confirmed that AFT1 and HEX-B also were enriched in endothelial cells when compared with non-endothelial cells. None of these genes have been reported previously to be involved in neovascularisation. However, our data establish that siRNA depletion of Rrm2, Atf1 or Hex-B had significant anti-angiogenic effects in VEGF-stimulated ex vivo mouse aortic ring assays. Overall, our results provide proof-of-principle that our approach can identify a cohort of potentially novel

  1. Systematic screening of isogenic cancer cells identifies DUSP6 as context-specific synthetic lethal target in melanoma

    PubMed Central

    Wittig-Blaich, Stephanie; Wittig, Rainer; Schmidt, Steffen; Lyer, Stefan; Bewerunge-Hudler, Melanie; Gronert-Sum, Sabine; Strobel-Freidekind, Olga; Müller, Carolin; List, Markus; Jaskot, Aleksandra; Christiansen, Helle; Hafner, Mathias; Schadendorf, Dirk; Block, Ines; Mollenhauer, Jan

    2017-01-01

    Next-generation sequencing has dramatically increased genome-wide profiling options and conceptually initiates the possibility for personalized cancer therapy. State-of-the-art sequencing studies yield large candidate gene sets comprising dozens or hundreds of mutated genes. However, few technologies are available for the systematic downstream evaluation of these results to identify novel starting points of future cancer therapies. We improved and extended a site-specific recombination-based system for systematic analysis of the individual functions of a large number of candidate genes. This was facilitated by a novel system for the construction of isogenic constitutive and inducible gain- and loss-of-function cell lines. Additionally, we demonstrate the construction of isogenic cell lines with combinations of the traits for advanced functional in vitro analyses. In a proof-of-concept experiment, a library of 108 isogenic melanoma cell lines was constructed and 8 genes were identified that significantly reduced viability in a discovery screen and in an independent validation screen. Here, we demonstrate the broad applicability of this recombination-based method and we proved its potential to identify new drug targets via the identification of the tumor suppressor DUSP6 as potential synthetic lethal target in melanoma cell lines with BRAF V600E mutations and high DUSP6 expression. PMID:28423600

  2. Identification of Differentially Expressed IGFBP5-Related Genes in Breast Cancer Tumor Tissues Using cDNA Microarray Experiments.

    PubMed

    Akkiprik, Mustafa; Peker, İrem; Özmen, Tolga; Amuran, Gökçe Güllü; Güllüoğlu, Bahadır M; Kaya, Handan; Özer, Ayşe

    2015-11-10

    IGFBP5 is an important regulatory protein in breast cancer progression. We tried to identify differentially expressed genes (DEGs) between breast tumor tissues with IGFBP5 overexpression and their adjacent normal tissues. In this study, thirty-eight breast cancer and adjacent normal breast tissue samples were used to determine IGFBP5 expression by qPCR. cDNA microarrays were applied to the highest IGFBP5 overexpressed tumor samples compared to their adjacent normal breast tissue. Microarray analysis revealed that a total of 186 genes were differentially expressed in breast cancer compared with normal breast tissues. Of the 186 genes, 169 genes were downregulated and 17 genes were upregulated in the tumor samples. KEGG pathway analyses showed that protein digestion and absorption, focal adhesion, salivary secretion, drug metabolism-cytochrome P450, and phenylalanine metabolism pathways are involved. Among these DEGs, the prominent top two genes (MMP11 and COL1A1) which potentially correlated with IGFBP5 were selected for validation using real time RT-qPCR. Only COL1A1 expression showed a consistent upregulation with IGFBP5 expression and COL1A1 and MMP11 were significantly positively correlated. We concluded that the discovery of coordinately expressed genes related with IGFBP5 might contribute to understanding of the molecular mechanism of the function of IGFBP5 in breast cancer. Further functional studies on DEGs and association with IGFBP5 may identify novel biomarkers for clinical applications in breast cancer.

  3. Prospectively-Identified Incident Testicular Cancer Risk in a Familial Testicular Cancer Cohort

    PubMed Central

    Pathak, Anand; Adams, Charleen D.; Loud, Jennifer T.; Nichols, Kathryn; Stewart, Douglas R.; Greene, Mark H.

    2015-01-01

    Background Human testicular germ cell tumors (TGCT) have a strong genetic component and a high familial relative risk. However, linkage analyses have not identified a rare, highly-penetrant familial TGCT (FTGCT) susceptibility locus. Currently, multiple low-penetrance genes are hypothesized to underlie the familial multiple-case phenotype. The observation that two is the most common number of affected individuals per family presents an impediment to FTGCT gene discovery. Clinically, the prospective TGCT risk in the multiple-case family context is unknown. Methods We performed a prospective analysis of TGCT incidence in a cohort of multiple-affected-person families and sporadic-bilateral-case families; 1,260 men from 140 families (10,207 person-years of follow-up) met our inclusion criteria. Age-, gender-, and calendar time-specific standardized incidence ratios (SIR) for TGCT relative to the general population were calculated using SEER*Stat. Results Eight incident TGCTs occurred during prospective FTGCT cohort follow-up (versus 0.67 expected; SIR=11.9; 95% confidence interval [CI]=5.1–23.4; excess absolute risk=7.2/10,000). We demonstrate that the incidence rate of TGCT is greater among bloodline male relatives from multiple-case testicular cancer families than that expected in the general population, a pattern characteristic of adult-onset Mendelian cancer susceptibility disorders. Two of these incident TGCTs occurred in relatives of sporadic-bilateral cases (0.15 expected; SIR=13.4; 95%CI=1.6–48.6). Conclusions Our data are the first indicating that despite relatively low numbers of affected individuals per family, members of both multiple-affected-person FTGCT families and sporadic-bilateral TGCT families comprise high-risk groups for incident testicular cancer. Impact Men at high TGCT risk might benefit from tailored risk stratification and surveillance strategies. PMID:26265202

  4. Whole exome sequencing identifies driver mutations in asymptomatic computed tomography-detected lung cancers with normal karyotype.

    PubMed

    Belloni, Elena; Veronesi, Giulia; Rotta, Luca; Volorio, Sara; Sardella, Domenico; Bernard, Loris; Pece, Salvatore; Di Fiore, Pier Paolo; Fumagalli, Caterina; Barberis, Massimo; Spaggiari, Lorenzo; Pelicci, Pier Giuseppe; Riva, Laura

    2015-04-01

    The efficacy of curative surgery for lung cancer could be largely improved by non-invasive screening programs, which can detect the disease at early stages. We previously showed that 18% of screening-identified lung cancers demonstrate a normal karyotype and, following high-density genome scanning, can be subdivided into samples with 1) numerous; 2) none; and 3) few copy number alterations. Whole exome sequencing was applied to the two normal karyotype, screening-detected lung cancers, constituting group 2, as well as normal controls. We identified mutations in both tumors, including KEAP1 (commonly mutated in lung cancers) in one, and TP53, PMS1, and MSH3 (well-characterized DNA-repair genes) in the other. The two normal karyotype screening-detected lung tumors displayed a typical lung cancer mutational profile that only next generation sequencing could reveal, which offered an additional contribution to the over-diagnosis bias concept hypothesized within lung cancer screening programs. Copyright © 2015 Elsevier Inc. All rights reserved.

  5. Controllability analysis of the directed human protein interaction network identifies disease genes and drug targets

    PubMed Central

    Vinayagam, Arunachalam; Gibson, Travis E.; Lee, Ho-Joon; Yilmazel, Bahar; Roesel, Charles; Hu, Yanhui; Kwon, Young; Sharma, Amitabh; Liu, Yang-Yu; Perrimon, Norbert; Barabási, Albert-László

    2016-01-01

    The protein–protein interaction (PPI) network is crucial for cellular information processing and decision-making. With suitable inputs, PPI networks drive the cells to diverse functional outcomes such as cell proliferation or cell death. Here, we characterize the structural controllability of a large directed human PPI network comprising 6,339 proteins and 34,813 interactions. This network allows us to classify proteins as “indispensable,” “neutral,” or “dispensable,” which correlates to increasing, no effect, or decreasing the number of driver nodes in the network upon removal of that protein. We find that 21% of the proteins in the PPI network are indispensable. Interestingly, these indispensable proteins are the primary targets of disease-causing mutations, human viruses, and drugs, suggesting that altering a network’s control property is critical for the transition between healthy and disease states. Furthermore, analyzing copy number alterations data from 1,547 cancer patients reveals that 56 genes that are frequently amplified or deleted in nine different cancers are indispensable. Among the 56 genes, 46 of them have not been previously associated with cancer. This suggests that controllability analysis is very useful in identifying novel disease genes and potential drug targets. PMID:27091990

  6. Gene Methylation and Cytological Atypia in Random Fine Needle Aspirates for Assessment of Breast Cancer Risk

    PubMed Central

    Hafeez, Sidra; Bujanda, Zoila Lopez; Chatterton, Robert T.; Jacobs, Lisa K.; Khouri, Nagi F.; Ivancic, David; Kenney, Kara; Shehata, Christina; Jeter, Stacie C.; Wolfman, Judith A.; Zalles, Carola M.; Huang, Peng

    2016-01-01

    Methods to determine individualized breast cancer risk lack sufficient sensitivity to select women most likely to benefit from preventive strategies. Alterations in DNA methylation occur early in breast cancer. We hypothesized that cancer-specific methylation markers could enhance breast cancer risk assessment. We evaluated 380 women without a history of breast cancer. We determined their menopausal status or menstrual cycle phase, risk of developing breast cancer (Gail model), and breast density, and obtained random fine needle aspiration (rFNA) samples for assessment of cytopathology and cumulative methylation index (CMI). Eight methylated gene markers were identified through whole genome methylation analysis and included novel and previously established breast cancer detection genes. We performed correlative and multivariate linear regression analyses to evaluate DNA methylation of a gene panel as a function of clinical factors associated with breast cancer risk. CMI and individual gene methylation were independent of age, menopausal status or menstrual phase, lifetime Gail risk score, and breast density. CMI and individual gene methylation for the eight genes increased significantly (p<0.001) with increasing cytological atypia. The findings were verified with multivariate analyses correcting for age, log (Gail), log (percent density), rFNA cell number and BMI. Our results demonstrate a significant association between cytological atypia and high CMI, which does not vary with menstrual phase or menopause and is independent of Gail risk and mammographic density. Thus CMI is an excellent candidate breast cancer risk biomarker, warranting larger prospective studies to establish its utility for cancer risk assessment. PMID:27261491

  7. Interleukin gene polymorphisms and breast cancer: a case control study and systematic literature review

    PubMed Central

    Balasubramanian, SP; Azmy, IAF; Higham, SE; Wilson, AG; Cross, SS; Cox, A; Brown, NJ; Reed, MW

    2006-01-01

    Background Interleukins and cytokines play an important role in the pathogenesis of many solid cancers. Several single nucleotide polymorphisms (SNPs) identified in cytokine genes are thought to influence the expression or function of these proteins and many have been evaluated for their role in inflammatory disease and cancer predisposition. The aim of this study was to evaluate any role of specific SNPs in the interleukin genes IL1A, IL1B, IL1RN, IL4R, IL6 and IL10 in predisposition to breast cancer susceptibility and severity. Methods Candidate single nucleotide polymorphisms (SNPs) in key cytokine genes were genotyped in breast cancer patients and in appropriate healthy volunteers who were similar in age, race and sex. Genotyping was performed using a high throughput allelic discrimination method. Data on clinico-pathological details and survival were collected. A systematic review of Medline English literature was done to retrieve previous studies of these polymorphisms in breast cancer. Results None of the polymorphisms studied showed any overall predisposition to breast cancer susceptibility, severity or to time to death or occurrence of distant metastases. The results of the systematic review are summarised. Conclusion Polymorphisms within key interleukin genes (IL1A, IL1B, IL1RN, IL4R, IL6 and IL10 do not appear to play a significant overall role in breast cancer susceptibility or severity. PMID:16842617

  8. miRNA-Processing Gene Methylation and Cancer Risk.

    PubMed

    Joyce, Brian T; Zheng, Yinan; Zhang, Zhou; Liu, Lei; Kocherginsky, Masha; Murphy, Robert; Achenbach, Chad J; Musa, Jonah; Wehbe, Firas; Just, Allan; Shen, Jincheng; Vokonas, Pantel; Schwartz, Joel; Baccarelli, Andrea A; Hou, Lifang

    2018-05-01

    Background: Dysregulation of miRNA and methylation levels are epigenetic hallmarks of cancer, potentially linked via miRNA-processing genes. Studies have found genetic alterations to miRNA-processing genes in cancer cells and human population studies. Our objective was to prospectively examine changes in DNA methylation of miRNA-processing genes and their associations with cancer risk. Methods: We examined cohort data from the Department of Veterans' Affairs Normative Aging Study. Participants were assessed every 3 to 5 years starting in 1999 through 2013 including questionnaires, medical record review, and blood collection. Blood from 686 consenting participants was analyzed using the Illumina 450K BeadChip array to measure methylation at CpG sites throughout the genome. We selected 19 genes based on a literature review, with 519 corresponding CpG sites. We then used Cox proportional hazards models to examine associations with cancer incidence, and generalized estimating equations to examine associations with cancer prevalence. Associations at false discovery rate < 0.05 were considered statistically significant. Results: Methylation of three CpGs ( DROSHA : cg23230564, TNRC6B : cg06751583, and TNRC6B : cg21034183) was prospectively associated with time to cancer development (positively for cg06751583, inversely for cg23230564 and cg21034183), whereas methylation of one CpG site ( DROSHA : cg16131300) was positively associated with cancer prevalence. Conclusions: DNA methylation of DROSHA , a key miRNA-processing gene, and TNRC6B may play a role in early carcinogenesis. Impact: Changes in miRNA processing may exert multiple effects on cancer development, including protecting against it via altered global miRNAs, and may be a useful early detection biomarker of cancer. Cancer Epidemiol Biomarkers Prev; 27(5); 550-7. ©2018 AACR . ©2018 American Association for Cancer Research.

  9. Comprehensive Analysis of Cancer-Proteogenome to Identify Biomarkers for the Early Diagnosis and Prognosis of Cancer.

    PubMed

    Shukla, Hem D

    2017-10-25

    data, are indispensable to glean into the cancer genome and proteome and these approaches have generated multidimensional universal studies of genes and proteins (OMICS) data which has the potential to facilitate precision medicine. However, due to slow progress in computational technologies, the translation of big omics data into their clinical aspects have been slow. In this review, attempts have been made to describe the role of high-throughput genomic and proteomic technologies in identifying a panel of biomarkers which could be used for the early diagnosis and prognosis of cancer.

  10. Gene Methylation and Cytological Atypia in Random Fine-Needle Aspirates for Assessment of Breast Cancer Risk.

    PubMed

    Stearns, Vered; Fackler, Mary Jo; Hafeez, Sidra; Bujanda, Zoila Lopez; Chatterton, Robert T; Jacobs, Lisa K; Khouri, Nagi F; Ivancic, David; Kenney, Kara; Shehata, Christina; Jeter, Stacie C; Wolfman, Judith A; Zalles, Carola M; Huang, Peng; Khan, Seema A; Sukumar, Saraswati

    2016-08-01

    Methods to determine individualized breast cancer risk lack sufficient sensitivity to select women most likely to benefit from preventive strategies. Alterations in DNA methylation occur early in breast cancer. We hypothesized that cancer-specific methylation markers could enhance breast cancer risk assessment. We evaluated 380 women without a history of breast cancer. We determined their menopausal status or menstrual cycle phase, risk of developing breast cancer (Gail model), and breast density and obtained random fine-needle aspiration (rFNA) samples for assessment of cytopathology and cumulative methylation index (CMI). Eight methylated gene markers were identified through whole-genome methylation analysis and included novel and previously established breast cancer detection genes. We performed correlative and multivariate linear regression analyses to evaluate DNA methylation of a gene panel as a function of clinical factors associated with breast cancer risk. CMI and individual gene methylation were independent of age, menopausal status or menstrual phase, lifetime Gail risk score, and breast density. CMI and individual gene methylation for the eight genes increased significantly (P < 0.001) with increasing cytological atypia. The findings were verified with multivariate analyses correcting for age, log (Gail), log (percent density), rFNA cell number, and body mass index. Our results demonstrate a significant association between cytological atypia and high CMI, which does not vary with menstrual phase or menopause and is independent of Gail risk and mammographic density. Thus, CMI is an excellent candidate breast cancer risk biomarker, warranting larger prospective studies to establish its utility for cancer risk assessment. Cancer Prev Res; 9(8); 673-82. ©2016 AACR. ©2016 American Association for Cancer Research.

  11. Almost 2% of Spanish breast cancer families are associated to germline pathogenic mutations in the ATM gene.

    PubMed

    Tavera-Tapia, A; Pérez-Cabornero, L; Macías, J A; Ceballos, M I; Roncador, G; de la Hoya, M; Barroso, A; Felipe-Ponce, V; Serrano-Blanch, R; Hinojo, C; Miramar-Gallart, M D; Urioste, M; Caldés, T; Santillan-Garzón, S; Benitez, J; Osorio, A

    2017-02-01

    There is still a considerable percentage of hereditary breast and ovarian cancer (HBOC) cases not explained by BRCA1 and BRCA2 genes. In this report, next-generation sequencing (NGS) techniques were applied to identify novel variants and/or genes involved in HBOC susceptibility. Using whole exome sequencing, we identified a novel germline mutation in the moderate-risk gene ATM (c.5441delT; p.Leu1814Trpfs*14) in a family negative for mutations in BRCA1/2 (BRCAX). A case-control association study was performed to establish its prevalence in Spanish population, in a series of 1477 BRCAX families and 589 controls further screened, and NGS panels were used for ATM mutational screening in a cohort of 392 HBOC Spanish BRCAX families and 350 patients affected with diseases not related to breast cancer. Although the interrogated mutation was not prevalent in case-control association study, a comprehensive mutational analysis of the ATM gene revealed 1.78% prevalence of mutations in the ATM gene in HBOC and 1.94% in breast cancer-only BRCAX families in Spanish population, where data about ATM mutations were very limited. ATM mutation prevalence in Spanish population highlights the importance of considering ATM pathogenic variants linked to breast cancer susceptibility.

  12. Identification of Novel Gene Targets and Putative Regulators of Arsenic-Associated DNA Methylation in Human Urothelial Cells and Bladder Cancer

    PubMed Central

    Rager, Julia E.; Miller, Sloane; Tulenko, Samantha E.; Smeester, Lisa; Ray, Paul D.; Yosim, Andrew; Currier, Jenna M.; Ishida, María C.; González-Horta, Maria del Carmen; Sánchez-Ramírez, Blanca; Ballinas-Casarrubias, Lourdes; Gutiérrez-Torres, Daniela S.; Drobná, Zuzana; Del Razo, Luz M.; García-Vargas, Gonzalo G.; Kim, William Y.; Zhou, Yi-Hui; Wright, Fred A.; Stýblo, Miroslav; Fry, Rebecca C.

    2016-01-01

    There is strong epidemiologic evidence linking chronic exposure to inorganic arsenic (iAs) to a myriad of adverse health effects, including cancer of the bladder. The present study set out to identify DNA methylation patterns associated with iAs and its metabolites in exfoliated urothelial cells (EUCs) that originate primarily from the urinary bladder, one of the targets of arsenic (As)-induced carcinogenesis. Genome-wide, gene-specific promoter DNA methylation levels were assessed in EUCs from 46 residents of Chihuahua, Mexico, and the relationship was examined between promoter methylation profiles and the intracellular concentrations of total As (tAs) and As species. A set of 49 differentially methylated genes was identified with increased promoter methylation associated with EUC tAs, iAs, and/or monomethylated As (MMAs) enriched for their roles in metabolic disease and cancer. Notably, no genes had differential methylation associated with EUC dimethylated As (DMAs), suggesting that DMAs may influence DNA methylation-mediated urothelial cell responses to a lesser extent than iAs or MMAs. Further analysis showed that 22 of the 49 As-associated genes (45%) are also differentially methylated in bladder cancer tissue identified using The Cancer Genome Atlas repository. Both the As- and cancer-associated genes are enriched for the binding sites of common transcription factors known to play roles in carcinogenesis, demonstrating a novel potential mechanistic link between iAs exposure and bladder cancer. PMID:26039340

  13. Deregulation of an imprinted gene network in prostate cancer

    PubMed Central

    Ribarska, Teodora; Goering, Wolfgang; Droop, Johanna; Bastian, Klaus-Marius; Ingenwerth, Marc; Schulz, Wolfgang A

    2014-01-01

    Multiple epigenetic alterations contribute to prostate cancer progression by deregulating gene expression. Epigenetic mechanisms, especially differential DNA methylation at imprinting control regions (termed DMRs), normally ensure the exclusive expression of imprinted genes from one specific parental allele. We therefore wondered to which extent imprinted genes become deregulated in prostate cancer and, if so, whether deregulation is due to altered DNA methylation at DMRs. Therefore, we selected presumptive deregulated imprinted genes from a previously conducted in silico analysis and from the literature and analyzed their expression in prostate cancer tissues by qRT-PCR. We found significantly diminished expression of PLAGL1/ZAC1, MEG3, NDN, CDKN1C, IGF2, and H19, while LIT1 was significantly overexpressed. The PPP1R9A gene, which is imprinted in selected tissues only, was strongly overexpressed, but was expressed biallelically in benign and cancerous prostatic tissues. Expression of many of these genes was strongly correlated, suggesting co-regulation, as in an imprinted gene network (IGN) reported in mice. Deregulation of the network genes also correlated with EZH2 and HOXC6 overexpression. Pyrosequencing analysis of all relevant DMRs revealed generally stable DNA methylation between benign and cancerous prostatic tissues, but frequent hypo- and hyper-methylation was observed at the H19 DMR in both benign and cancerous tissues. Re-expression of the ZAC1 transcription factor induced H19, CDKN1C and IGF2, supporting its function as a nodal regulator of the IGN. Our results indicate that a group of imprinted genes are coordinately deregulated in prostate cancers, independently of DNA methylation changes. PMID:24513574

  14. Deregulation of an imprinted gene network in prostate cancer.

    PubMed

    Ribarska, Teodora; Goering, Wolfgang; Droop, Johanna; Bastian, Klaus-Marius; Ingenwerth, Marc; Schulz, Wolfgang A

    2014-05-01

    Multiple epigenetic alterations contribute to prostate cancer progression by deregulating gene expression. Epigenetic mechanisms, especially differential DNA methylation at imprinting control regions (termed DMRs), normally ensure the exclusive expression of imprinted genes from one specific parental allele. We therefore wondered to which extent imprinted genes become deregulated in prostate cancer and, if so, whether deregulation is due to altered DNA methylation at DMRs. Therefore, we selected presumptive deregulated imprinted genes from a previously conducted in silico analysis and from the literature and analyzed their expression in prostate cancer tissues by qRT-PCR. We found significantly diminished expression of PLAGL1/ZAC1, MEG3, NDN, CDKN1C, IGF2, and H19, while LIT1 was significantly overexpressed. The PPP1R9A gene, which is imprinted in selected tissues only, was strongly overexpressed, but was expressed biallelically in benign and cancerous prostatic tissues. Expression of many of these genes was strongly correlated, suggesting co-regulation, as in an imprinted gene network (IGN) reported in mice. Deregulation of the network genes also correlated with EZH2 and HOXC6 overexpression. Pyrosequencing analysis of all relevant DMRs revealed generally stable DNA methylation between benign and cancerous prostatic tissues, but frequent hypo- and hyper-methylation was observed at the H19 DMR in both benign and cancerous tissues. Re-expression of the ZAC1 transcription factor induced H19, CDKN1C and IGF2, supporting its function as a nodal regulator of the IGN. Our results indicate that a group of imprinted genes are coordinately deregulated in prostate cancers, independently of DNA methylation changes.

  15. Germline mutations in candidate predisposition genes in individuals with cutaneous melanoma and at least two independent additional primary cancers.

    PubMed

    Pritchard, Antonia L; Johansson, Peter A; Nathan, Vaishnavi; Howlie, Madeleine; Symmons, Judith; Palmer, Jane M; Hayward, Nicholas K

    2018-01-01

    While a number of autosomal dominant and autosomal recessive cancer syndromes have an associated spectrum of cancers, the prevalence and variety of cancer predisposition mutations in patients with multiple primary cancers have not been extensively investigated. An understanding of the variants predisposing to more than one cancer type could improve patient care, including screening and genetic counselling, as well as advancing the understanding of tumour development. A cohort of 57 patients ascertained due to their cutaneous melanoma (CM) diagnosis and with a history of two or more additional non-cutaneous independent primary cancer types were recruited for this study. Patient blood samples were assessed by whole exome or whole genome sequencing. We focussed on variants in 525 pre-selected genes, including 65 autosomal dominant and 31 autosomal recessive cancer predisposition genes, 116 genes involved in the DNA repair pathway, and 313 commonly somatically mutated in cancer. The same genes were analysed in exome sequence data from 1358 control individuals collected as part of non-cancer studies (UK10K). The identified variants were classified for pathogenicity using online databases, literature and in silico prediction tools. No known pathogenic autosomal dominant or previously described compound heterozygous mutations in autosomal recessive genes were observed in the multiple cancer cohort. Variants typically found somatically in haematological malignancies (in JAK1, JAK2, SF3B1, SRSF2, TET2 and TYK2) were present in lymphocyte DNA of patients with multiple primary cancers, all of whom had a history of haematological malignancy and cutaneous melanoma, as well as colorectal cancer and/or prostate cancer. Other potentially pathogenic variants were discovered in BUB1B, POLE2, ROS1 and DNMT3A. Compared to controls, multiple cancer cases had significantly more likely damaging mutations (nonsense, frameshift ins/del) in tumour suppressor and tyrosine kinase genes and

  16. Nanoparticles for cancer gene therapy: Recent advances, challenges, and strategies.

    PubMed

    Wang, Kui; Kievit, Forrest M; Zhang, Miqin

    2016-12-01

    Compared to conventional treatments, gene therapy offers a variety of advantages for cancer treatment including high potency and specificity, low off-target toxicity, and delivery of multiple genes that concurrently target cancer tumorigenesis, recurrence, and drug resistance. In the past decades, gene therapy has undergone remarkable progress, and is now poised to become a first line therapy for cancer. Among various gene delivery systems, nanoparticles have attracted much attention because of their desirable characteristics including low toxicity profiles, well-controlled and high gene delivery efficiency, and multi-functionalities. This review provides an overview on gene therapeutics and gene delivery technologies, and highlight recent advances, challenges and insights into the design and the utility of nanoparticles in gene therapy for cancer treatment. Copyright © 2016. Published by Elsevier Ltd.

  17. Transposon mutagenesis identifies genes and cellular processes driving epithelial-mesenchymal transition in hepatocellular carcinoma

    PubMed Central

    Kodama, Takahiro; Newberg, Justin Y.; Kodama, Michiko; Rangel, Roberto; Yoshihara, Kosuke; Tien, Jean C.; Parsons, Pamela H.; Wu, Hao; Finegold, Milton J.; Copeland, Neal G.; Jenkins, Nancy A.

    2016-01-01

    Epithelial-mesenchymal transition (EMT) is thought to contribute to metastasis and chemoresistance in patients with hepatocellular carcinoma (HCC), leading to their poor prognosis. The genes driving EMT in HCC are not yet fully understood, however. Here, we show that mobilization of Sleeping Beauty (SB) transposons in immortalized mouse hepatoblasts induces mesenchymal liver tumors on transplantation to nude mice. These tumors show significant down-regulation of epithelial markers, along with up-regulation of mesenchymal markers and EMT-related transcription factors (EMT-TFs). Sequencing of transposon insertion sites from tumors identified 233 candidate cancer genes (CCGs) that were enriched for genes and cellular processes driving EMT. Subsequent trunk driver analysis identified 23 CCGs that are predicted to function early in tumorigenesis and whose mutation or alteration in patients with HCC is correlated with poor patient survival. Validation of the top trunk drivers identified in the screen, including MET (MET proto-oncogene, receptor tyrosine kinase), GRB2-associated binding protein 1 (GAB1), HECT, UBA, and WWE domain containing 1 (HUWE1), lysine-specific demethylase 6A (KDM6A), and protein-tyrosine phosphatase, nonreceptor-type 12 (PTPN12), showed that deregulation of these genes activates an EMT program in human HCC cells that enhances tumor cell migration. Finally, deregulation of these genes in human HCC was found to confer sorafenib resistance through apoptotic tolerance and reduced proliferation, consistent with recent studies showing that EMT contributes to the chemoresistance of tumor cells. Our unique cell-based transposon mutagenesis screen appears to be an excellent resource for discovering genes involved in EMT in human HCC and potentially for identifying new drug targets. PMID:27247392

  18. Association of -330 interleukin-2 gene polymorphism with oral cancer.

    PubMed

    Singh, Prithvi Kumar; Kumar, Vijay; Ahmad, Mohammad Kaleem; Gupta, Rajni; Mahdi, Abbas Ali; Jain, Amita; Bogra, Jaishri; Chandra, Girish

    2017-12-01

    Cytokines play an important role in the development of cancer. Several single-nucleotide polymorphisms (SNPs) of cytokine genes have been reported to be associated with the development and severity of inflammatory diseases and cancer predisposition. This study was undertaken to evaluate a possible association of interleukin 2 (IL-2) (- 330A>C) gene polymorphisms with the susceptibility to oral cancer. The SNP in IL-2 (-330A>C) gene was genotyped in 300 oral cancer patients and in similar number of healthy volunteers by polymerase chain reaction (PCR)-restriction fragment length polymorphism and the association of the gene with the disease was evaluated. IL-2 (-330A>C) gene polymorphism was significantly associated with oral cancer whereas it was neither associated with clinicopathological status nor with cancer pain. The AC heterozygous genotype was significantly associated with oral cancer patients as compared to controls [odds ratio (OR): 3.0; confidence interval (CI): 2.14-4.20; P<0.001]. The C allele frequency was also significantly associated with oral cancer (OR: 1.80; CI: 1.39-2.33; P<0.001). IL-2 (-330A>C) gene polymorphism was also associated with oral cancer in tobacco smokers and chewers. Our results showed that oral cancer patients had significantly higher frequency of AA genotype but significantly lower frequency of AC genotype and C allele compared to controls. The IL-2 AC genotype and C allele of IL-2 (-330A>C) gene polymorphisms could be potential protective factors and might reduce the risk of oral cancer in Indian population.

  19. Integrative analysis of gene expression and DNA methylation using unsupervised feature extraction for detecting candidate cancer biomarkers.

    PubMed

    Moon, Myungjin; Nakai, Kenta

    2018-04-01

    Currently, cancer biomarker discovery is one of the important research topics worldwide. In particular, detecting significant genes related to cancer is an important task for early diagnosis and treatment of cancer. Conventional studies mostly focus on genes that are differentially expressed in different states of cancer; however, noise in gene expression datasets and insufficient information in limited datasets impede precise analysis of novel candidate biomarkers. In this study, we propose an integrative analysis of gene expression and DNA methylation using normalization and unsupervised feature extractions to identify candidate biomarkers of cancer using renal cell carcinoma RNA-seq datasets. Gene expression and DNA methylation datasets are normalized by Box-Cox transformation and integrated into a one-dimensional dataset that retains the major characteristics of the original datasets by unsupervised feature extraction methods, and differentially expressed genes are selected from the integrated dataset. Use of the integrated dataset demonstrated improved performance as compared with conventional approaches that utilize gene expression or DNA methylation datasets alone. Validation based on the literature showed that a considerable number of top-ranked genes from the integrated dataset have known relationships with cancer, implying that novel candidate biomarkers can also be acquired from the proposed analysis method. Furthermore, we expect that the proposed method can be expanded for applications involving various types of multi-omics datasets.

  20. Analysis of the gene coding for the BRCA2-interacting protein PALB2 in hereditary prostate cancer.

    PubMed

    Tischkowitz, Marc; Sabbaghian, Nelly; Ray, Anna M; Lange, Ethan M; Foulkes, William D; Cooney, Kathleen A

    2008-05-01

    The genetic basis of susceptibility to prostate cancer (PRCA) remains elusive. Mutations in BRCA2 have been associated with increased prostate cancer risk and account for around 2% of young onset (<56 years) prostate cancer cases. PALB2 is a recently identified breast cancer susceptibility gene whose protein is closely associated with BRCA2 and is essential for BRCA2 anchorage to nuclear structures. This functional relationship made PALB2 a candidate PRCA susceptibility gene. We sequenced PALB2 in probands from 95 PRCA families, 77 of which had two or more cases of early onset PRCA (age at diagnosis <55 years), and the remaining 18 had one case of early onset PRCA and five or more total cases of PRCA. Two previously unreported variants, K18R and V925L were identified, neither of which is in a known PALB2 functional domain and both of which are unlikely to be pathogenic. No truncating mutations were identified. These results indicate that deleterious PALB2 mutations are unlikely to play a significant role in hereditary prostate cancer.

  1. Interleukin gene polymorphisms in Chinese Han population with breast cancer, a case-control study.

    PubMed

    Zuo, Xiaoxiao; Li, Miao; Yang, Ya; Liang, Tiansong; Yang, Hongyao; Zhao, Xinhan; Yang, Daoke

    2018-04-06

    Cytokines are known as important regulators of the cancer involved in inflammatory and immunological responses. This fact and plethora of gene polymorphism data prompted us to investigate IL1 gene polymorphisms in breast cancer (BC) patients. Totally, 530 patients with BC and 628 healthy control women were studied. The genetic polymorphisms for IL1 were analyzed by Massarray Sequencing method. Three single nucleotide polymorphisms (SNPs) identified in IL1B, IL1R1 gene are thought to influence breast cancer risk. The results of the association between IL-1B, IL1R1 polymorphisms and breast cancer risk have significant. We found that the variant TT genotype of rs10490571 was associated with a significantly increased breast cancer risk (TT vs. CC: OR = 2.82, 95% CI = 1.12-7.08, P = 0.047 for the codominant model). For rs16944 (AG vs. GG: OR = 0.60, 95% CI = 0.41-0.90, P = 0.034 for the codominant model) and rs1143623 (CG vs. CC: OR = 0.65, 95% CI = 0.45-0.94, P = 0.023 for the codominant model) have significant associations were found in genetic models. In conclusion, the present analysis suggests a correlation of polymorphic markers within the IL-1 gene locus with the risk in developing breast cancer. Taken together with our finding that IL1B, IL1R1 gene three SNP are also associated with the risk for the disease, we suggest that inflammation via innate and adaptive immunity contributes to multifactorial hereditary predisposition to pathogenesis of the breast cancer.

  2. Cancer-associated fibroblasts affect breast cancer cell gene expression, invasion and angiogenesis.

    PubMed

    Eiro, Noemi; González, Lucía; Martínez-Ordoñez, Anxo; Fernandez-Garcia, Belen; González, Luis O; Cid, Sandra; Dominguez, Francisco; Perez-Fernandez, Román; Vizoso, Francisco J

    2018-03-01

    It has been reported that stromal cell features may affect the clinical outcome of breast cancer patients. Cancer associated fibroblasts (CAFs) represent one of the most abundant cell types within the breast cancer stroma. Here, we aimed to explore the influence of CAFs on breast cancer gene expression, as well as on invasion and angiogenesis. qRT-PCR was used to evaluate the expression of several cancer progression related genes (S100A4, TGFβ, FGF2, FGF7, PDGFA, PDGFB, VEGFA, IL-6, IL-8, uPA, MMP2, MMP9, MMP11 and TIMP1) in the human breast cancer-derived cell lines MCF-7 and MDA-MB-231, before and after co-culture with CAFs. Stromal mononuclear inflammatory cell (MIC) MMP11 expression was used to stratify primary tumors. In addition, we assessed the in vitro effects of CAFs on both MDA-MB-231 breast cancer cell invasion and endothelial cell (HUVEC) tube formation. We found that the expression levels of most of the genes tested were significantly increased in both breast cancer-derived cell lines after co-culture with CAFs from either MMP11+ or MMP11- MIC tumors. IL-6 and IL-8 showed an increased expression in both cancer-derived cell lines after co-culture with CAFs from MMP11+ MIC tumors. We also found that the invasive and angiogenic capacities of, respectively, MDA-MB-231 and HUVEC cells were increased after co-culture with CAFs, especially those from MMP11+ MIC tumors. Our data indicate that tumor-derived CAFs can induce up-regulation of genes involved in breast cancer progression. Our data additionally indicate that CAFs, especially those derived from MMP11+ MIC tumors, can promote breast cancer cell invasion and angiogenesis.

  3. Candidate genes for panhypopituitarism identified by gene expression profiling

    PubMed Central

    Mortensen, Amanda H.; MacDonald, James W.; Ghosh, Debashis

    2011-01-01

    Mutations in the transcription factors PROP1 and PIT1 (POU1F1) lead to pituitary hormone deficiency and hypopituitarism in mice and humans. The dysmorphology of developing Prop1 mutant pituitaries readily distinguishes them from those of Pit1 mutants and normal mice. This and other features suggest that Prop1 controls the expression of genes besides Pit1 that are important for pituitary cell migration, survival, and differentiation. To identify genes involved in these processes we used microarray analysis of gene expression to compare pituitary RNA from newborn Prop1 and Pit1 mutants and wild-type littermates. Significant differences in gene expression were noted between each mutant and their normal littermates, as well as between Prop1 and Pit1 mutants. Otx2, a gene critical for normal eye and pituitary development in humans and mice, exhibited elevated expression specifically in Prop1 mutant pituitaries. We report the spatial and temporal regulation of Otx2 in normal mice and Prop1 mutants, and the results suggest Otx2 could influence pituitary development by affecting signaling from the ventral diencephalon and regulation of gene expression in Rathke's pouch. The discovery that Otx2 expression is affected by Prop1 deficiency provides support for our hypothesis that identifying molecular differences in mutants will contribute to understanding the molecular mechanisms that control pituitary organogenesis and lead to human pituitary disease. PMID:21828248

  4. [Genetic basis of head and neck cancers and gene therapy].

    PubMed

    Özel, Halil Erdem; Özkırış, Mahmut; Gencer, Zeliha Kapusuz; Saydam, Levent

    2013-01-01

    Surgery and combinations of traditional treatments are not successful enough particularly for advanced stage head and neck cancer. The major disadvantages of chemotherapy and radiation therapy are the lack of specificity for the target tissue and toxicity to the patient. As a result, gene therapy may offer a more specific approach. The aim of gene therapy is to present therapeutic genes into cancer cells which selectively eliminate malignant cells with no systemic toxicity to the patient. This article reviews the genetic basis of head and neck cancers and important concepts in cancer gene therapy: (i) inhibition of oncogenes; (ii) tumor suppressor gene replacement; (iii) regulation of immune response against malignant cells; (iv) genetic prodrug activation; and (v) antiangiogenic gene therapy. Currently, gene therapy is not sufficient to replace the traditional treatments of head and neck cancers, however there is no doubt that it will have an important role in the near future.

  5. Genes with mutation significance were highly associated with the clinical pattern of patients with breast cancer.

    PubMed

    Ding, Wan-Jun; Zeng, Tao; Wang, Li-Jun; Lei, Hong-Bo; Ge, Wei; Wang, Zhi

    2017-11-17

    In the United States, breast cancer is the second leading cause of cancer death in women. Over the past 20 years, breast cancer incidence and mortality rates increased rapidly in developing regions. We aimed to identify the gene mutation patterns that associated with the clinical patterns, including survival status, histo-pathological classes and so forth, of breast cancer. We retrieved 1098 cases of the clinical information, and level-3 legacy data of mRNA expression level, protein expression data and mutation files from GDC data portal. The genes with mutation significance were obtained. We studied the impacts of mutation types on the expression levels of mRNA and protein. Different statistics methods were used to calculate the correlation between the mutation types and the expression data or histo-clinical measures. There were 24 genes with mutation significance identified. The most mutated genes were selected to study the role of specific mutations played on the patients with breast cancer. One interesting finding was the missense mutations on TP53 were related with high expression levels of mRNA and protein. The missense mutations on TP53 were highly related with the morphology, race, ER status, PR status and HER2 Status, while the truncated mutations were only related with the morphology, ER status and PR status. The missense mutation on PIK3CA was highly associated with the morphology, race, ER status and PR status. The mutants with different mutants and the wild type of the most mutated genes had different impacts on the histo-clinical measures that might help personalized therapy.

  6. Meta-analysis of gene expression profiles associated with histological classification and survival in 829 ovarian cancer samples.

    PubMed

    Fekete, Tibor; Rásó, Erzsébet; Pete, Imre; Tegze, Bálint; Liko, István; Munkácsy, Gyöngyi; Sipos, Norbert; Rigó, János; Györffy, Balázs

    2012-07-01

    Transcriptomic analysis of global gene expression in ovarian carcinoma can identify dysregulated genes capable to serve as molecular markers for histology subtypes and survival. The aim of our study was to validate previous candidate signatures in an independent setting and to identify single genes capable to serve as biomarkers for ovarian cancer progression. As several datasets are available in the GEO today, we were able to perform a true meta-analysis. First, 829 samples (11 datasets) were downloaded, and the predictive power of 16 previously published gene sets was assessed. Of these, eight were capable to discriminate histology subtypes, and none was capable to predict survival. To overcome the differences in previous studies, we used the 829 samples to identify new predictors. Then, we collected 64 ovarian cancer samples (median relapse-free survival 24.5 months) and performed TaqMan Real Time Polimerase Chain Reaction (RT-PCR) analysis for the best 40 genes associated with histology subtypes and survival. Over 90% of subtype-associated genes were confirmed. Overall survival was effectively predicted by hormone receptors (PGR and ESR2) and by TSPAN8. Relapse-free survival was predicted by MAPT and SNCG. In summary, we successfully validated several gene sets in a meta-analysis in large datasets of ovarian samples. Additionally, several individual genes identified were validated in a clinical cohort. Copyright © 2011 UICC.

  7. Clinical omics analysis of colorectal cancer incorporating copy number aberrations and gene expression data.

    PubMed

    Yoshida, Tsuyoshi; Kobayashi, Takumi; Itoda, Masaya; Muto, Taika; Miyaguchi, Ken; Mogushi, Kaoru; Shoji, Satoshi; Shimokawa, Kazuro; Iida, Satoru; Uetake, Hiroyuki; Ishikawa, Toshiaki; Sugihara, Kenichi; Mizushima, Hiroshi; Tanaka, Hiroshi

    2010-07-29

    Colorectal cancer (CRC) is one of the most frequently occurring cancers in Japan, and thus a wide range of methods have been deployed to study the molecular mechanisms of CRC. In this study, we performed a comprehensive analysis of CRC, incorporating copy number aberration (CRC) and gene expression data. For the last four years, we have been collecting data from CRC cases and organizing the information as an "omics" study by integrating many kinds of analysis into a single comprehensive investigation. In our previous studies, we had experienced difficulty in finding genes related to CRC, as we observed higher noise levels in the expression data than in the data for other cancers. Because chromosomal aberrations are often observed in CRC, here, we have performed a combination of CNA analysis and expression analysis in order to identify some new genes responsible for CRC. This study was performed as part of the Clinical Omics Database Project at Tokyo Medical and Dental University. The purpose of this study was to investigate the mechanism of genetic instability in CRC by this combination of expression analysis and CNA, and to establish a new method for the diagnosis and treatment of CRC. Comprehensive gene expression analysis was performed on 79 CRC cases using an Affymetrix Gene Chip, and comprehensive CNA analysis was performed using an Affymetrix DNA Sty array. To avoid the contamination of cancer tissue with normal cells, laser micro-dissection was performed before DNA/RNA extraction. Data analysis was performed using original software written in the R language. We observed a high percentage of CNA in colorectal cancer, including copy number gains at 7, 8q, 13 and 20q, and copy number losses at 8p, 17p and 18. Gene expression analysis provided many candidates for CRC-related genes, but their association with CRC did not reach the level of statistical significance. The combination of CNA and gene expression analysis, together with the clinical information

  8. Identifying molecular subtypes related to clinicopathologic factors in pancreatic cancer

    PubMed Central

    2014-01-01

    Background Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal tumors and usually presented with locally advanced and distant metastasis disease, which prevent curative resection or treatments. In this regard, we considered identifying molecular subtypes associated with clinicopathological factor as prognosis factors to stratify PDAC for appropriate treatment of patients. Results In this study, we identified three molecular subtypes which were significant on survival time and metastasis. We also identified significant genes and enriched pathways represented for each molecular subtype. Considering R0 resection patients included in each subtype, metastasis and survival times are significantly associated with subtype 1 and subtype 2. Conclusions We observed three PDAC molecular subtypes and demonstrated that those subtypes were significantly related with metastasis and survival time. The study may have utility in stratifying patients for cancer treatment. PMID:25560450

  9. Multi-dimensional genomic analysis of myoepithelial carcinoma identifies prevalent oncogenic gene fusions.

    PubMed

    Dalin, Martin G; Katabi, Nora; Persson, Marta; Lee, Ken-Wing; Makarov, Vladimir; Desrichard, Alexis; Walsh, Logan A; West, Lyndsay; Nadeem, Zaineb; Ramaswami, Deepa; Havel, Jonathan J; Kuo, Fengshen; Chadalavada, Kalyani; Nanjangud, Gouri J; Ganly, Ian; Riaz, Nadeem; Ho, Alan L; Antonescu, Cristina R; Ghossein, Ronald; Stenman, Göran; Chan, Timothy A; Morris, Luc G T

    2017-10-30

    Myoepithelial carcinoma (MECA) is an aggressive salivary gland cancer with largely unknown genetic features. Here we comprehensively analyze molecular alterations in 40 MECAs using integrated genomic analyses. We identify a low mutational load, and high prevalence (70%) of oncogenic gene fusions. Most fusions involve the PLAG1 oncogene, which is associated with PLAG1 overexpression. We find FGFR1-PLAG1 in seven (18%) cases, and the novel TGFBR3-PLAG1 fusion in six (15%) cases. TGFBR3-PLAG1 promotes a tumorigenic phenotype in vitro, and is absent in 723 other salivary gland tumors. Other novel PLAG1 fusions include ND4-PLAG1; a fusion between mitochondrial and nuclear DNA. We also identify higher number of copy number alterations as a risk factor for recurrence, independent of tumor stage at diagnosis. Our findings indicate that MECA is a fusion-driven disease, nominate TGFBR3-PLAG1 as a hallmark of MECA, and provide a framework for future diagnostic and therapeutic research in this lethal cancer.

  10. A Genetic Interaction Screen for Breast Cancer Progression Driver Genes

    DTIC Science & Technology

    2013-06-01

    analysis of genetic alterations in human breast cancers has revealed that individual tumors accumulate mutations in approximately ninety different genes ...cancer. We performed a screen to test the roles of seventy breast cancer mutated genes in mouse mammary tumorigenesis using the MMTV-PyVT mouse breast...cancer model and piggyBac insertional mutation strains. We found that insertional mutations in 23 genes altered the onset of tumor formation and four

  11. Cost-effectiveness of using a gene expression profiling test to aid in identifying the primary tumour in patients with cancer of unknown primary.

    PubMed

    Hannouf, M B; Winquist, E; Mahmud, S M; Brackstone, M; Sarma, S; Rodrigues, G; Rogan, P; Hoch, J S; Zaric, G S

    2017-06-01

    We aimed to investigate the cost-effectiveness of a 2000-gene-expression profiling (GEP) test to help identify the primary tumor site when clinicopathological diagnostic evaluation was inconclusive in patients with cancer of unknown primary (CUP). We built a decision-analytic-model to project the lifetime clinical and economic consequences of different clinical management strategies for CUP. The model was parameterized using follow-up data from the Manitoba Cancer Registry, cost data from Manitoba Health administrative databases and secondary sources. The 2000-GEP-based strategy compared to current clinical practice resulted in an incremental cost-effectiveness ratio (ICER) of $44,151 per quality-adjusted life years (QALY) gained. The total annual-budget impact was $36.2 million per year. A value-of-information analysis revealed that the expected value of perfect information about the test's clinical impact was $4.2 million per year. The 2000-GEP test should be considered for adoption in CUP. Field evaluations of the test are associated with a large societal benefit.

  12. Low Prevalence of CHEK2 Gene Mutations in Multiethnic Cohorts of Breast Cancer Patients in Malaysia

    PubMed Central

    Mohamad, Suriati; Isa, Nurismah Md; Muhammad, Rohaizak; Emran, Nor Aina; Kitan, Nor Mayah; Kang, Peter; Kang, In Nee; Taib, Nur Aishah Mohd; Teo, Soo Hwang; Akmal, Sharifah Noor

    2015-01-01

    CHEK2 is a protein kinase that is involved in cell-cycle checkpoint control after DNA damage. Germline mutations in CHEK2 gene have been associated with increase in breast cancer risk. The aim of this study is to identify the CHEK2 gene germline mutations among high-risk breast cancer patients and its contribution to the multiethnic population in Malaysia. We screened the entire coding region of CHEK2 gene on 59 high-risk breast cancer patients who tested negative for BRCA1/2 germline mutations from UKM Medical Centre (UKMMC), Hospital Kuala Lumpur (HKL) and Hospital Putrajaya (HPJ). Sequence variants identified were screened further in case-control cohorts consisting of 878 unselected invasive breast cancer patients (180 Malays, 526 Chinese and 172 Indian) and 270 healthy individuals (90 Malays, 90 Chinese and 90 Indian). By screening the entire coding region of the CHEK2 gene, two missense mutations, c.480A>G (p.I160M) and c.538C>T (p.R180C) were identified in two unrelated patients (3.4%). Further screening of these missense mutations on the case-control cohorts unveiled the variant p.I160M in 2/172 (1.1%) Indian cases and 1/90 (1.1%) Indian control, variant p.R180C in 2/526 (0.38%) Chinese cases and 0/90 Chinese control, and in 2/180 (1.1%) of Malay cases and 1/90 (1.1%) of Malay control. The results of this study suggest that CHEK2 mutations are rare among high-risk breast cancer patients and may play a minor contributing role in breast carcinogenesis among Malaysian population. PMID:25629968

  13. Low prevalence of CHEK2 gene mutations in multiethnic cohorts of breast cancer patients in Malaysia.

    PubMed

    Mohamad, Suriati; Isa, Nurismah Md; Muhammad, Rohaizak; Emran, Nor Aina; Kitan, Nor Mayah; Kang, Peter; Kang, In Nee; Taib, Nur Aishah Mohd; Teo, Soo Hwang; Akmal, Sharifah Noor

    2015-01-01

    CHEK2 is a protein kinase that is involved in cell-cycle checkpoint control after DNA damage. Germline mutations in CHEK2 gene have been associated with increase in breast cancer risk. The aim of this study is to identify the CHEK2 gene germline mutations among high-risk breast cancer patients and its contribution to the multiethnic population in Malaysia. We screened the entire coding region of CHEK2 gene on 59 high-risk breast cancer patients who tested negative for BRCA1/2 germline mutations from UKM Medical Centre (UKMMC), Hospital Kuala Lumpur (HKL) and Hospital Putrajaya (HPJ). Sequence variants identified were screened further in case-control cohorts consisting of 878 unselected invasive breast cancer patients (180 Malays, 526 Chinese and 172 Indian) and 270 healthy individuals (90 Malays, 90 Chinese and 90 Indian). By screening the entire coding region of the CHEK2 gene, two missense mutations, c.480A>G (p.I160M) and c.538C>T (p.R180C) were identified in two unrelated patients (3.4%). Further screening of these missense mutations on the case-control cohorts unveiled the variant p.I160M in 2/172 (1.1%) Indian cases and 1/90 (1.1%) Indian control, variant p.R180C in 2/526 (0.38%) Chinese cases and 0/90 Chinese control, and in 2/180 (1.1%) of Malay cases and 1/90 (1.1%) of Malay control. The results of this study suggest that CHEK2 mutations are rare among high-risk breast cancer patients and may play a minor contributing role in breast carcinogenesis among Malaysian population.

  14. Id-1 gene and gene products as therapeutic targets for treatment of breast cancer and other types of carcinoma

    DOEpatents

    Desprez, Pierre-Yves; Campisi, Judith

    2014-08-19

    A method for treatment of breast cancer and other types of cancer. The method comprises targeting and modulating Id-1 gene expression, if any, for the Id-1 gene, or gene products in breast or other epithelial cancers in a patient by delivering products that modulate Id-1 gene expression. When expressed, Id-1 gene is a prognostic indicator that cancer cells are invasive and metastatic.

  15. A comparative analysis of gene-expression data of multiple cancer types.

    PubMed

    Xu, Kun; Cui, Juan; Olman, Victor; Yang, Qing; Puett, David; Xu, Ying

    2010-10-27

    A comparative study of public gene-expression data of seven types of cancers (breast, colon, kidney, lung, pancreatic, prostate and stomach cancers) was conducted with the aim of deriving marker genes, along with associated pathways, that are either common to multiple types of cancers or specific to individual cancers. The analysis results indicate that (a) each of the seven cancer types can be distinguished from its corresponding control tissue based on the expression patterns of a small number of genes, e.g., 2, 3 or 4; (b) the expression patterns of some genes can distinguish multiple cancer types from their corresponding control tissues, potentially serving as general markers for all or some groups of cancers; (c) the proteins encoded by some of these genes are predicted to be blood secretory, thus providing potential cancer markers in blood; (d) the numbers of differentially expressed genes across different cancer types in comparison with their control tissues correlate well with the five-year survival rates associated with the individual cancers; and (e) some metabolic and signaling pathways are abnormally activated or deactivated across all cancer types, while other pathways are more specific to certain cancers or groups of cancers. The novel findings of this study offer considerable insight into these seven cancer types and have the potential to provide exciting new directions for diagnostic and therapeutic development.

  16. Gene expression analysis in MCF-7 breast cancer cells treated with recombinant bromelain.

    PubMed

    Fouz, Nour; Amid, Azura; Hashim, Yumi Zuhanis Has-Yun

    2014-08-01

    The contributing molecular pathways underlying the pathogenesis of breast cancer need to be better characterized. The principle of our study was to better understand the genetic mechanism of oncogenesis for human breast cancer and to discover new possible tumor markers for use in clinical practice. We used complimentary DNA (cDNA) microarrays to compare gene expression profiles of treated Michigan Cancer Foundation-7 (MCF-7) with recombinant bromelain and untreated MCF-7. SpringGene analysis was carried out of differential expression followed by Ingenuity Pathway Analysis (IPA), to understand the underlying consequence in developing disease and disorders. We identified 1,102 known genes differentially expressed to a significant degree (p<0.001) changed between the treatment. Within this gene set, 20 genes were significantly changed between treated cells and the control cells with cutoff fold change of more than 1.5. These genes are RNA-binding motif, single-stranded interacting protein 1 (RBMS1), ribosomal protein L29 (RPL29), glutathione S-transferase mu 2 (GSTM2), C15orf32, Akt3, B cell translocation gene 1 (BTG1), C6orf62, C7orf60, kinesin-associated protein 3 (KIFAP3), FBXO11, AT-rich interactive domain 4A (ARID4A), COPS2, TBPL1|SLC2A12, TMEM59, SNORD46, glioma tumor suppressor candidate region gene 2 (GLTSCR2), and LRRFIP. Our observation on gene expression indicated that recombinant bromelain produces a unique signature affecting different pathways, specific for each congener. The microarray results give a molecular mechanistic insight and functional effects, following recombinant bromelain treatment. The extent of changes in genes is related to and involved significantly in gap junction signaling, amyloid processing, cell cycle regulation by BTG family proteins, and breast cancer regulation by stathmin1 that play major roles.

  17. CCDB: a curated database of genes involved in cervix cancer.

    PubMed

    Agarwal, Subhash M; Raghav, Dhwani; Singh, Harinder; Raghava, G P S

    2011-01-01

    The Cervical Cancer gene DataBase (CCDB, http://crdd.osdd.net/raghava/ccdb) is a manually curated catalog of experimentally validated genes that are thought, or are known to be involved in the different stages of cervical carcinogenesis. In spite of the large women population that is presently affected from this malignancy still at present, no database exists that catalogs information on genes associated with cervical cancer. Therefore, we have compiled 537 genes in CCDB that are linked with cervical cancer causation processes such as methylation, gene amplification, mutation, polymorphism and change in expression level, as evident from published literature. Each record contains details related to gene like architecture (exon-intron structure), location, function, sequences (mRNA/CDS/protein), ontology, interacting partners, homology to other eukaryotic genomes, structure and links to other public databases, thus augmenting CCDB with external data. Also, manually curated literature references have been provided to support the inclusion of the gene in the database and establish its association with cervix cancer. In addition, CCDB provides information on microRNA altered in cervical cancer as well as search facility for querying, several browse options and an online tool for sequence similarity search, thereby providing researchers with easy access to the latest information on genes involved in cervix cancer.

  18. Gene therapy for prostate cancer: where are we now?

    PubMed

    Steiner, M S; Gingrich, J R

    2000-10-01

    The ability to recombine specifically and alter DNA sequences followed by techniques to transfer these sequences or even whole genes into normal and diseased cells has revolutionized medical research and ushered the clinicians of today into the age of gene therapy. We provide urologists a review of relevant background information, outline current treatment strategies and clinical trials, and delineate current challenges facing the field of gene therapy for advanced prostate cancer. We comprehensively reviewed the literature, including PubMed and recent abstract proceedings from national meetings, relevant to gene therapy and advanced prostate cancer. We selected for review literature representative of the principal scientific background for current gene therapy strategies and National Institutes of Health Recombinant DNA Advisory Committee approved clinical trials. Current prostate cancer gene therapy strategies include correcting aberrant gene expression, exploiting programmed cell death pathways, targeting critical cell biological functions, introducing toxic or cell lytic suicide genes, enhancing the immune system antitumor response and combining treatment with conventional cytotoxic chemotherapy or radiation therapy. Many challenges lie ahead for gene therapy, including improving DNA transfer efficiency to cells locally and at distant sites, enhancing levels of gene expression and overcoming immune responses that limit the time that genes are expressed. Nevertheless, despite these current challenges it is almost certain that gene therapy will be part of the urological armamentarium against prostate cancer in this century.

  19. Gene expression information improves reliability of receptor status in breast cancer patients

    PubMed Central

    Kenn, Michael; Schlangen, Karin; Castillo-Tong, Dan Cacsire; Singer, Christian F.; Cibena, Michael; Koelbl, Heinz; Schreiner, Wolfgang

    2017-01-01

    Immunohistochemical (IHC) determination of receptor status in breast cancer patients is frequently inaccurate. Since it directs the choice of systemic therapy, it is essential to increase its reliability. We increase the validity of IHC receptor expression by additionally considering gene expression (GE) measurements. Crisp therapeutic decisions are based on IHC estimates, even if they are borderline reliable. We further improve decision quality by a responsibility function, defining a critical domain for gene expression. Refined normalization is devised to file any newly diagnosed patient into existing data bases. Our approach renders receptor estimates more reliable by identifying patients with questionable receptor status. The approach is also more efficient since the rate of conclusive samples is increased. We have curated and evaluated gene expression data, together with clinical information, from 2880 breast cancer patients. Combining IHC with gene expression information yields a method more reliable and also more efficient as compared to common practice up to now. Several types of possibly suboptimal treatment allocations, based on IHC receptor status alone, are enumerated. A ‘therapy allocation check’ identifies patients possibly miss-classified. Estrogen: false negative 8%, false positive 6%. Progesterone: false negative 14%, false positive 11%. HER2: false negative 2%, false positive 50%. Possible implications are discussed. We propose an ‘expression look-up-plot’, allowing for a significant potential to improve the quality of precision medicine. Methods are developed and exemplified here for breast cancer patients, but they may readily be transferred to diagnostic data relevant for therapeutic decisions in other fields of oncology. PMID:29100391

  20. Weighted gene co-expression network analysis of gene modules for the prognosis of esophageal cancer.

    PubMed

    Zhang, Cong; Sun, Qian

    2017-06-01

    Esophageal cancer is a common malignant tumor, whose pathogenesis and prognosis factors are not fully understood. This study aimed to discover the gene clusters that have similar functions and can be used to predict the prognosis of esophageal cancer. The matched microarray and RNA sequencing data of 185 patients with esophageal cancer were downloaded from The Cancer Genome Atlas (TCGA), and gene co-expression networks were built without distinguishing between squamous carcinoma and adenocarcinoma. The result showed that 12 modules were associated with one or more survival data such as recurrence status, recurrence time, vital status or vital time. Furthermore, survival analysis showed that 5 out of the 12 modules were related to progression-free survival (PFS) or overall survival (OS). As the most important module, the midnight blue module with 82 genes was related to PFS, apart from the patient age, tumor grade, primary treatment success, and duration of smoking and tumor histological type. Gene ontology enrichment analysis revealed that "glycoprotein binding" was the top enriched function of midnight blue module genes. Additionally, the blue module was the exclusive gene clusters related to OS. Platelet activating factor receptor (PTAFR) and feline Gardner-Rasheed (FGR) were the top hub genes in both modeling datasets and the STRING protein interaction database. In conclusion, our study provides novel insights into the prognosis-associated genes and screens out candidate biomarkers for esophageal cancer.

  1. Genes associated with metabolic syndrome predict disease-free survival in stage II colorectal cancer patients. A novel link between metabolic dysregulation and colorectal cancer.

    PubMed

    Vargas, Teodoro; Moreno-Rubio, Juan; Herranz, Jesús; Cejas, Paloma; Molina, Susana; González-Vallinas, Margarita; Ramos, Ricardo; Burgos, Emilio; Aguayo, Cristina; Custodio, Ana B; Reglero, Guillermo; Feliu, Jaime; Ramírez de Molina, Ana

    2014-12-01

    Studies have recently suggested that metabolic syndrome and its components increase the risk of colorectal cancer. Both diseases are increasing in most countries, and the genetic association between them has not been fully elucidated. The objective of this study was to assess the association between genetic risk factors of metabolic syndrome or related conditions (obesity, hyperlipidaemia, diabetes mellitus type 2) and clinical outcome in stage II colorectal cancer patients. Expression levels of several genes related to metabolic syndrome and associated alterations were analysed by real-time qPCR in two equivalent but independent sets of stage II colorectal cancer patients. Using logistic regression models and cross-validation analysis with all tumour samples, we developed a metabolic syndrome-related gene expression profile to predict clinical outcome in stage II colorectal cancer patients. The results showed that a gene expression profile constituted by genes previously related to metabolic syndrome was significantly associated with clinical outcome of stage II colorectal cancer patients. This metabolic profile was able to identify patients with a low risk and high risk of relapse. Its predictive value was validated using an independent set of stage II colorectal cancer patients. The identification of a set of genes related to metabolic syndrome that predict survival in intermediate-stage colorectal cancer patients allows delineation of a high-risk group that may benefit from adjuvant therapy and avoid the toxic and unnecessary chemotherapy in patients classified as low risk. Our results also confirm the linkage between metabolic disorder and colorectal cancer and suggest the potential for cancer prevention and/or treatment by targeting these genes. Copyright © 2014 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.

  2. Identification of Genes Involved in Breast Cancer Metastasis by Integrating Protein-Protein Interaction Information with Expression Data.

    PubMed

    Tian, Xin; Xin, Mingyuan; Luo, Jian; Liu, Mingyao; Jiang, Zhenran

    2017-02-01

    The selection of relevant genes for breast cancer metastasis is critical for the treatment and prognosis of cancer patients. Although much effort has been devoted to the gene selection procedures by use of different statistical analysis methods or computational techniques, the interpretation of the variables in the resulting survival models has been limited so far. This article proposes a new Random Forest (RF)-based algorithm to identify important variables highly related with breast cancer metastasis, which is based on the important scores of two variable selection algorithms, including the mean decrease Gini (MDG) criteria of Random Forest and the GeneRank algorithm with protein-protein interaction (PPI) information. The new gene selection algorithm can be called PPIRF. The improved prediction accuracy fully illustrated the reliability and high interpretability of gene list selected by the PPIRF approach.

  3. Multi-gene fluorescence in situ hybridization to detect cell cycle gene copy number aberrations in young breast cancer patients

    PubMed Central

    Li, Chunyan; Bai, Jingchao; Hao, Xiaomeng; Zhang, Sheng; Hu, Yunhui; Zhang, Xiaobei; Yuan, Weiping; Hu, Linping; Cheng, Tao; Zetterberg, Anders; Lee, Mong-Hong; Zhang, J

    2014-01-01

    Breast cancer is a disease of cell cycle, and the dysfunction of cell cycle checkpoints plays a vital role in the occurrence and development of breast cancer. We employed multi-gene fluorescence in situ hybridization (M-FISH) to investigate gene copy number aberrations (CNAs) of 4 genes (Rb1, CHEK2, c-Myc, CCND1) that are involved in the regulation of cell cycle, in order to analyze the impact of gene aberrations on prognosis in the young breast cancer patients. Gene copy number aberrations of these 4 genes were more frequently observed in young breast cancer patients when compared with the older group. Further, these CNAs were more frequently seen in Luminal B type, Her2 overexpression, and tiple-negative breast cancer (TNBC) type in young breast cancer patients. The variations of CCND1, Rb1, and CHEK2 were significantly correlated with poor survival in the young breast cancer patient group, while the amplification of c-Myc was not obviously correlated with poor survival in young breast cancer patients. Thus, gene copy number aberrations (CNAs) of cell cycle-regulated genes can serve as an important tool for prognosis in young breast cancer patients. PMID:24621502

  4. Identification of downstream metastasis-associated target genes regulated by LSD1 in colon cancer cells.

    PubMed

    Chen, Jiang; Ding, Jie; Wang, Ziwei; Zhu, Jian; Wang, Xuejian; Du, Jiyi

    2017-03-21

    This study aims to identify downstream target genes regulated by lysine-specific demethylase 1 (LSD1) in colon cancer cells and investigate the molecular mechanisms of LSD1 influencing invasion and metastasis of colon cancer. We obtained the expression changes of downstream target genes regulated by small-interfering RNA-LSD1 and LSD1-overexpression via gene expression profiling in two human colon cancer cell lines. An Affymetrix Human Transcriptome Array 2.0 was used to identify differentially expressed genes (DEGs). We screened out LSD1-target gene associated with proliferation, metastasis, and invasion from DEGs via Gene Ontology and Pathway Studio. Subsequently, four key genes (CABYR, FOXF2, TLE4, and CDH1) were computationally predicted as metastasis-related LSD1-target genes. ChIp-PCR was applied after RT-PCR and Western blot validations to detect the occupancy of LSD1-target gene promoter-bound LSD1. A total of 3633 DEGs were significantly upregulated, and 4642 DEGs were downregulated in LSD1-silenced SW620 cells. A total of 4047 DEGs and 4240 DEGs were upregulated and downregulated in LSD1-overexpressed HT-29 cells, respectively. RT-PCR and Western blot validated the microarray analysis results. ChIP assay results demonstrated that LSD1 might be negative regulators for target genes CABYR and CDH1. The expression level of LSD1 is negatively correlated with mono- and dimethylation of histone H3 lysine4(H3K4) at LSD1- target gene promoter region. No significant mono-methylation and dimethylation of H3 lysine9 methylation was detected at the promoter region of CABYR and CDH1. LSD1- depletion contributed to the upregulation of CABYR and CDH1 through enhancing the dimethylation of H3K4 at the LSD1-target genes promoter. LSD1- overexpression mediated the downregulation of CABYR and CDH1expression through decreasing the mono- and dimethylation of H3K4 at LSD1-target gene promoter in colon cancer cells. CABYR and CDH1 might be potential LSD1-target genes in colon

  5. Analyzing the differentially expressed genes and pathway cross-talk in aggressive breast cancer.

    PubMed

    Chen, Wen-Yan; Wu, Fang; You, Zhen-Yu; Zhang, Zhan-Min; Guo, Yu-Ling; Zhong, Lu-Xing

    2015-01-01

    The aim of this study was to explore the genes and pathways involved in the aggressive breast cancer cells. The gene expression profiles of GSE40057, including four aggressive breast cell lines and six less aggressive cell lines, were downloaded from the Gene Expression Omnibus (GEO) database. The gene differential expression analysis was carried out with limma software with the method of Bayes for multiple tests. The gene ontology (GO) term enrichment and pathway cross-talk analysis were performed with the online tool of DAVID and Cytoscape software. A total of 401 differentially expressed genes (DEG), such as pentraxin 3 (PTX3), snail family zinc finger 2 (SNAI2), interleukin-8/6 (IL-8/6), osteonectin (SPARC), matrix metallopeptidase-1 (MMP-1) and Ras-related protein Rab-25 (Rab 25), were identified between aggressive and less aggressive cell lines. They were mainly enriched in the GO terms of response to wounding, negative regulation of cell proliferation and calcium binding. Pathways in cancer dysfunctionally interacted with glyoxylate and dicarboxylate metabolism (P < 0.0001), basal transcription factors (P < 0.0001), tyrosine metabolism (P < 0.0001), calcium signaling pathway (P = 0.0021), FcγR-mediated phagocytosis (P = 0.0022), metabolism of xenobiotics by cytochrome P450 (P = 0.0097) and phagosome (P = 0.0102). The screened aggressive cancer-associated DEG (PTX3, SNAI2, IL-8/6, SPARC, MMP-1 and Rab25) and significant pathways (calcium signaling pathway, tyrosine metabolism, alanine, aspartate and glutamate metabolism) give us new insights into the mechanism of aggressive breast cancer cells, and these DEG may become promising target genes in the treatment of metastatic breast cancer. © 2014 The Authors. Journal of Obstetrics and Gynaecology Research © 2014 Japan Society of Obstetrics and Gynecology.

  6. Turning the gene tap off; implications of regulating gene expression for cancer therapeutics

    PubMed Central

    Curtin, James F.; Candolfi, Marianela; Xiong, Weidong; Lowenstein, Pedro R.; Castro, Maria G.

    2008-01-01

    Cancer poses a tremendous therapeutic challenge worldwide, highlighting the critical need for developing novel therapeutics. A promising cancer treatment modality is gene therapy, which is a form of molecular medicine designed to introduce into target cells genetic material with therapeutic intent. Anticancer gene therapy strategies currently used in preclinical models, and in some cases in the clinic, include proapoptotic genes, oncolytic/replicative vectors, conditional cytotoxic approaches, inhibition of angiogenesis, inhibition of growth factor signaling, inactivation of oncogenes, inhibition of tumor invasion and stimulation of the immune system. The translation of these novel therapeutic modalities from the preclinical setting to the clinic has been driven by encouraging preclinical efficacy data and advances in gene delivery technologies. One area of intense research involves the ability to accurately regulate the levels of therapeutic gene expression to achieve enhanced efficacy and provide the capability to switch gene expression off completely if adverse side effects should arise. This feature could also be implemented to switch gene expression off when a successful therapeutic outcome ensues. Here, we will review recent developments related to the engineering of transcriptional switches within gene delivery systems, which could be implemented in clinical gene therapy applications directed at the treatment of cancer. PMID:18347132

  7. An automated procedure to identify biomedical articles that contain cancer-associated gene variants.

    PubMed

    McDonald, Ryan; Scott Winters, R; Ankuda, Claire K; Murphy, Joan A; Rogers, Amy E; Pereira, Fernando; Greenblatt, Marc S; White, Peter S

    2006-09-01

    The proliferation of biomedical literature makes it increasingly difficult for researchers to find and manage relevant information. However, identifying research articles containing mutation data, a requisite first step in integrating large and complex mutation data sets, is currently tedious, time-consuming and imprecise. More effective mechanisms for identifying articles containing mutation information would be beneficial both for the curation of mutation databases and for individual researchers. We developed an automated method that uses information extraction, classifier, and relevance ranking techniques to determine the likelihood of MEDLINE abstracts containing information regarding genomic variation data suitable for inclusion in mutation databases. We targeted the CDKN2A (p16) gene and the procedure for document identification currently used by CDKN2A Database curators as a measure of feasibility. A set of abstracts was manually identified from a MEDLINE search as potentially containing specific CDKN2A mutation events. A subset of these abstracts was used as a training set for a maximum entropy classifier to identify text features distinguishing "relevant" from "not relevant" abstracts. Each document was represented as a set of indicative word, word pair, and entity tagger-derived genomic variation features. When applied to a test set of 200 candidate abstracts, the classifier predicted 88 articles as being relevant; of these, 29 of 32 manuscripts in which manual curation found CDKN2A sequence variants were positively predicted. Thus, the set of potentially useful articles that a manual curator would have to review was reduced by 56%, maintaining 91% recall (sensitivity) and more than doubling precision (positive predictive value). Subsequent expansion of the training set to 494 articles yielded similar precision and recall rates, and comparison of the original and expanded trials demonstrated that the average precision improved with the larger data set

  8. A comparison of 12-gene colon cancer assay gene expression in African American and Caucasian patients with stage II colon cancer.

    PubMed

    Govindarajan, Rangaswamy; Posey, James; Chao, Calvin Y; Lu, Ruixiao; Jadhav, Trafina; Javed, Ahmed Y; Javed, Awais; Mahmoud, Fade A; Osarogiagbon, Raymond U; Manne, Upender

    2016-06-18

    African American (AA) colon cancer patients have a worse prognosis than Caucasian (CA) colon cancer patients, however, reasons for this disparity are not well understood. To determine if tumor biology might contribute to differential prognosis, we measured recurrence risk and gene expression using the Oncotype DX® Colon Cancer Assay (12-gene assay) and compared the Recurrence Score results and gene expression profiles between AA patients and CA patients with stage II colon cancer. We retrieved demographic, clinical, and archived tumor tissues from stage II colon cancer patients at four institutions. The 12-gene assay and mismatch repair (MMR) status were performed by Genomic Health (Redwood City, California). Student's t-test and the Wilcoxon rank sum test were used to compare Recurrence Score data and gene expression data from AA and CA patients (SAS Enterprise Guide 5.1). Samples from 122 AA and 122 CA patients were analyzed. There were 118 women (63 AA, 55 CA) and 126 men (59 AA, 67 CA). Median age was 66 years for AA patients and 68 for CA patients. Age, gender, year of surgery, pathologic T-stage, tumor location, the number of lymph nodes examined, lymphovascular invasion, and MMR status were not significantly different between groups (p = 0.93). The mean Recurrence Score result for AA patients (27.9 ± 12.8) and CA patients (28.1 ± 11.8) was not significantly different and the proportions of patients with high Recurrence Score values (≥41) were similar between the groups (17/122 AA; 15/122 CA). None of the gene expression variables, either single genes or gene groups (cell cycle group, stromal group, BGN1, FAP, INHBA1, Ki67, MYBL2, cMYC and GADD45B), was significantly different between the racial groups. After controlling for clinical and pathologic covariates, the means and distributions of Recurrence Score results and gene expression profiles showed no statistically significant difference between patient groups. The distribution of

  9. Breast cancer prognosis by combinatorial analysis of gene expression data.

    PubMed

    Alexe, Gabriela; Alexe, Sorin; Axelrod, David E; Bonates, Tibérius O; Lozina, Irina I; Reiss, Michael; Hammer, Peter L

    2006-01-01

    The potential of applying data analysis tools to microarray data for diagnosis and prognosis is illustrated on the recent breast cancer dataset of van 't Veer and coworkers. We re-examine that dataset using the novel technique of logical analysis of data (LAD), with the double objective of discovering patterns characteristic for cases with good or poor outcome, using them for accurate and justifiable predictions; and deriving novel information about the role of genes, the existence of special classes of cases, and other factors. Data were analyzed using the combinatorics and optimization-based method of LAD, recently shown to provide highly accurate diagnostic and prognostic systems in cardiology, cancer proteomics, hematology, pulmonology, and other disciplines. LAD identified a subset of 17 of the 25,000 genes, capable of fully distinguishing between patients with poor, respectively good prognoses. An extensive list of 'patterns' or 'combinatorial biomarkers' (that is, combinations of genes and limitations on their expression levels) was generated, and 40 patterns were used to create a prognostic system, shown to have 100% and 92.9% weighted accuracy on the training and test sets, respectively. The prognostic system uses fewer genes than other methods, and has similar or better accuracy than those reported in other studies. Out of the 17 genes identified by LAD, three (respectively, five) were shown to play a significant role in determining poor (respectively, good) prognosis. Two new classes of patients (described by similar sets of covering patterns, gene expression ranges, and clinical features) were discovered. As a by-product of the study, it is shown that the training and the test sets of van 't Veer have differing characteristics. The study shows that LAD provides an accurate and fully explanatory prognostic system for breast cancer using genomic data (that is, a system that, in addition to predicting good or poor prognosis, provides an individualized

  10. CDKN2D-WDFY2 is a cancer-specific fusion gene recurrent in high-grade serous ovarian carcinoma.

    PubMed

    Kannan, Kalpana; Coarfa, Cristian; Rajapakshe, Kimal; Hawkins, Shannon M; Matzuk, Martin M; Milosavljevic, Aleksandar; Yen, Laising

    2014-03-01

    Ovarian cancer is the fifth leading cause of cancer death in women. Almost 70% of ovarian cancer deaths are due to the high-grade serous subtype, which is typically detected only after it has metastasized. Characterization of high-grade serous cancer is further complicated by the significant heterogeneity and genome instability displayed by this cancer. Other than mutations in TP53, which is common to many cancers, highly recurrent recombinant events specific to this cancer have yet to be identified. Using high-throughput transcriptome sequencing of seven patient samples combined with experimental validation at DNA, RNA and protein levels, we identified a cancer-specific and inter-chromosomal fusion gene CDKN2D-WDFY2 that occurs at a frequency of 20% among sixty high-grade serous cancer samples but is absent in non-cancerous ovary and fallopian tube samples. This is the most frequent recombinant event identified so far in high-grade serous cancer implying a major cellular lineage in this highly heterogeneous cancer. In addition, the same fusion transcript was also detected in OV-90, an established high-grade serous type cell line. The genomic breakpoint was identified in intron 1 of CDKN2D and intron 2 of WDFY2 in patient tumor, providing direct evidence that this is a fusion gene. The parental gene, CDKN2D, is a cell-cycle modulator that is also involved in DNA repair, while WDFY2 is known to modulate AKT interactions with its substrates. Transfection of cloned fusion construct led to loss of wildtype CDKN2D and wildtype WDFY2 protein expression, and a gain of a short WDFY2 protein isoform that is presumably under the control of the CDKN2D promoter. The expression of short WDFY2 protein in transfected cells appears to alter the PI3K/AKT pathway that is known to play a role in oncogenesis. CDKN2D-WDFY2 fusion could be an important molecular signature for understanding and classifying sub-lineages among heterogeneous high-grade serous ovarian carcinomas.

  11. Transcriptional regulation of core autophagy and lysosomal genes by the androgen receptor promotes prostate cancer progression

    PubMed Central

    Blessing, Alicia M.; Rajapakshe, Kimal; Reddy Bollu, Lakshmi; Shi, Yan; White, Mark A.; Pham, Alexander H.; Lin, Chenchu; Jonsson, Philip; Cortes, Constanza J.; Cheung, Edwin; La Spada, Albert R.; Bast, Robert C.; Merchant, Fatima A.; Coarfa, Cristian; Frigo, Daniel E.

    2017-01-01

    ABSTRACT AR (androgen receptor) signaling is crucial for the development and maintenance of the prostate as well as the initiation and progression of prostate cancer. Despite the AR's central role in prostate cancer progression, it is still unclear which AR-mediated processes drive the disease. Here, we identified 4 core autophagy genes: ATG4B, ATG4D, ULK1, and ULK2, in addition to the transcription factor TFEB, a master regulator of lysosomal biogenesis and function, as transcriptional targets of AR in prostate cancer. These findings were significant in light of our recent observation that androgens promoted prostate cancer cell growth in part through the induction of autophagy. Expression of these 5 genes was essential for maximal androgen-mediated autophagy and cell proliferation. In addition, expression of each of these 5 genes alone or in combination was sufficient to increase prostate cancer cell growth independent of AR activity. Further, bioinformatic analysis demonstrated that the expression of these genes correlated with disease progression in 3 separate clinical cohorts. Collectively, these findings demonstrate a functional role for increased autophagy in prostate cancer progression, provide a mechanism for how autophagy is augmented, and highlight the potential of targeting this process for the treatment of advanced prostate cancer. PMID:27977328

  12. Transcriptional regulation of core autophagy and lysosomal genes by the androgen receptor promotes prostate cancer progression.

    PubMed

    Blessing, Alicia M; Rajapakshe, Kimal; Reddy Bollu, Lakshmi; Shi, Yan; White, Mark A; Pham, Alexander H; Lin, Chenchu; Jonsson, Philip; Cortes, Constanza J; Cheung, Edwin; La Spada, Albert R; Bast, Robert C; Merchant, Fatima A; Coarfa, Cristian; Frigo, Daniel E

    2017-03-04

    AR (androgen receptor) signaling is crucial for the development and maintenance of the prostate as well as the initiation and progression of prostate cancer. Despite the AR's central role in prostate cancer progression, it is still unclear which AR-mediated processes drive the disease. Here, we identified 4 core autophagy genes: ATG4B, ATG4D, ULK1, and ULK2, in addition to the transcription factor TFEB, a master regulator of lysosomal biogenesis and function, as transcriptional targets of AR in prostate cancer. These findings were significant in light of our recent observation that androgens promoted prostate cancer cell growth in part through the induction of autophagy. Expression of these 5 genes was essential for maximal androgen-mediated autophagy and cell proliferation. In addition, expression of each of these 5 genes alone or in combination was sufficient to increase prostate cancer cell growth independent of AR activity. Further, bioinformatic analysis demonstrated that the expression of these genes correlated with disease progression in 3 separate clinical cohorts. Collectively, these findings demonstrate a functional role for increased autophagy in prostate cancer progression, provide a mechanism for how autophagy is augmented, and highlight the potential of targeting this process for the treatment of advanced prostate cancer.

  13. Epidermal growth factor receptor and AKT1 gene copy numbers by multi-gene fluorescence in situ hybridization impact on prognosis in breast cancer.

    PubMed

    Li, Jiao; Su, Wei; Zhang, Sheng; Hu, Yunhui; Liu, Jingjing; Zhang, Xiaobei; Bai, Jingchao; Yuan, Weiping; Hu, Linping; Cheng, Tao; Zetterberg, Anders; Lei, Zhenmin; Zhang, Jin

    2015-05-01

    The epidermal growth factor receptor (EGFR)/PI3K/AKT signaling pathway aberrations play significant roles in breast cancer occurrence and development. However, the status of EGFR and AKT1 gene copy numbers remains unclear. In this study, we showed that the rates of EGFR and AKT1 gene copy number alterations were associated with the prognosis of breast cancer. Among 205 patients, high EGFR and AKT1 gene copy numbers were observed in 34.6% and 27.8% of cases by multi-gene fluorescence in situ hybridization, respectively. Co-heightened EGFR/AKT1 gene copy numbers were identified in 11.7% cases. No changes were found in 49.3% of patients. Although changes in EGFR and AKT1 gene copy numbers had no correlation with patients' age, tumor stage, histological grade and the expression status of other molecular makers, high EGFR (P = 0.0002) but not AKT1 (P = 0.1177) gene copy numbers correlated with poor 5-year overall survival. The patients with co-heightened EGFR/AKT1 gene copy numbers displayed a poorer prognosis than those with tumors with only high EGFR gene copy numbers (P = 0.0383). Both Univariate (U) and COX multivariate (C) analyses revealed that high EGFR and AKT1 gene copy numbers (P = 0.000 [U], P = 0.0001 [C]), similar to histological grade (P = 0.001 [U], P = 0.012 [C]) and lymph node metastasis (P = 0.046 [U], P = 0.158 [C]), were independent prognostic indicators of 5-year overall survival. These results indicate that high EGFR and AKT1 gene copy numbers were relatively frequent in breast cancer. Co-heightened EGFR/AKT1 gene copy numbers had a worse outcome than those with only high EGFR gene copy numbers, suggesting that evaluation of these two genes together may be useful for selecting patients for anti-EGFR-targeted therapy or anti-EGFR/AKT1-targeted therapy and for predicting outcomes. © 2015 The Authors. Cancer Science published by Wiley Publishing Asia Pty Ltd on behalf of Japanese Cancer Association.

  14. An integrated genomic approach identifies persistent tumor suppressive effects of transforming growth factor-β in human breast cancer

    PubMed Central

    2014-01-01

    Introduction Transforming growth factor-βs (TGF-βs) play a dual role in breast cancer, with context-dependent tumor-suppressive or pro-oncogenic effects. TGF-β antagonists are showing promise in early-phase clinical oncology trials to neutralize the pro-oncogenic effects. However, there is currently no way to determine whether the tumor-suppressive effects of TGF-β are still active in human breast tumors at the time of surgery and treatment, a situation that could lead to adverse therapeutic responses. Methods Using a breast cancer progression model that exemplifies the dual role of TGF-β, promoter-wide chromatin immunoprecipitation and transcriptomic approaches were applied to identify a core set of TGF-β-regulated genes that specifically reflect only the tumor-suppressor arm of the pathway. The clinical significance of this signature and the underlying biology were investigated using bioinformatic analyses in clinical breast cancer datasets, and knockdown validation approaches in tumor xenografts. Results TGF-β-driven tumor suppression was highly dependent on Smad3, and Smad3 target genes that were specifically enriched for involvement in tumor suppression were identified. Patterns of Smad3 binding reflected the preexisting active chromatin landscape, and target genes were frequently regulated in opposite directions in vitro and in vivo, highlighting the strong contextuality of TGF-β action. An in vivo-weighted TGF-β/Smad3 tumor-suppressor signature was associated with good outcome in estrogen receptor-positive breast cancer cohorts. TGF-β/Smad3 effects on cell proliferation, differentiation and ephrin signaling contributed to the observed tumor suppression. Conclusions Tumor-suppressive effects of TGF-β persist in some breast cancer patients at the time of surgery and affect clinical outcome. Carefully tailored in vitro/in vivo genomic approaches can identify such patients for exclusion from treatment with TGF-β antagonists. PMID:24890385

  15. Identifying potential maternal genes of Bombyx mori using digital gene expression profiling

    PubMed Central

    Xu, Pingzhen

    2018-01-01

    Maternal genes present in mature oocytes play a crucial role in the early development of silkworm. Although maternal genes have been widely studied in many other species, there has been limited research in Bombyx mori. High-throughput next generation sequencing provides a practical method for gene discovery on a genome-wide level. Herein, a transcriptome study was used to identify maternal-related genes from silkworm eggs. Unfertilized eggs from five different stages of early development were used to detect the changing situation of gene expression. The expressed genes showed different patterns over time. Seventy-six maternal genes were annotated according to homology analysis with Drosophila melanogaster. More than half of the differentially expressed maternal genes fell into four expression patterns, while the expression patterns showed a downward trend over time. The functional annotation of these material genes was mainly related to transcription factor activity, growth factor activity, nucleic acid binding, RNA binding, ATP binding, and ion binding. Additionally, twenty-two gene clusters including maternal genes were identified from 18 scaffolds. Altogether, we plotted a profile for the maternal genes of Bombyx mori using a digital gene expression profiling method. This will provide the basis for maternal-specific signature research and improve the understanding of the early development of silkworm. PMID:29462160

  16. HFE gene C282Y variant is associated with colorectal cancer in Caucasians: a meta-analysis.

    PubMed

    Chen, Weidong; Zhao, Hua; Li, Tiegang; Yao, Hongliang

    2013-08-01

    The HFE gene has been suggested to play an important role in the pathogenesis of colorectal cancer. However, the results have been conflicting. In this study, we performed a meta-analysis to clarify the association of HFE gene C282Y variant with colorectal cancer. PubMed and Embase were retrieved to identify the potential literature. Pooled odds ratio (OR) with 95 % confidence interval (CI) was calculated using fixed- or random-effects model. A total of eight papers including nine studies (7,588 colorectal cancer cases and 81,571 controls) for HFE gene C282Y variant were included in the meta-analysis. The result indicated that HFE gene C282Y variant was significantly associated with colorectal cancer under recessive model (OR = 2.00, 95 % CI = 1.32-3.04), with no evidence of between-study heterogeneity (I (2) = 0.2 %, p = 0.432). Further subgroup analysis by number of cases suggested the effect was significant in studies with more than 500 cases (OR = 2.51, 95 % CI = 1.58-3.98, I (2) = 0.0 %, p = 0.921), but not in studies with less than 500 cases (OR = 0.75, 95 % CI = 0.28-1.97, I (2) = 0.0 %, p = 0.622). The current meta-analysis supported the positive association of HFE gene C282Y variant with colorectal cancer. Further large-scale studies with the consideration for gene-gene/gene-environment interactions should be conducted to investigate the association.

  17. Interleukin gene polymorphisms in Chinese Han population with breast cancer, a case-control study

    PubMed Central

    Yang, Ya; Liang, Tiansong; Yang, Hongyao; Zhao, Xinhan; Yang, Daoke

    2018-01-01

    Cytokines are known as important regulators of the cancer involved in inflammatory and immunological responses. This fact and plethora of gene polymorphism data prompted us to investigate IL1 gene polymorphisms in breast cancer (BC) patients. Totally, 530 patients with BC and 628 healthy control women were studied. The genetic polymorphisms for IL1 were analyzed by Massarray Sequencing method. Three single nucleotide polymorphisms (SNPs) identified in IL1B, IL1R1 gene are thought to influence breast cancer risk. The results of the association between IL-1B, IL1R1 polymorphisms and breast cancer risk have significant. We found that the variant TT genotype of rs10490571 was associated with a significantly increased breast cancer risk (TT vs. CC: OR = 2.82, 95% CI = 1.12–7.08, P = 0.047 for the codominant model). For rs16944 (AG vs. GG: OR = 0.60, 95% CI = 0.41–0.90, P = 0.034 for the codominant model) and rs1143623 (CG vs. CC: OR = 0.65, 95% CI = 0.45–0.94, P = 0.023 for the codominant model) have significant associations were found in genetic models. In conclusion, the present analysis suggests a correlation of polymorphic markers within the IL-1 gene locus with the risk in developing breast cancer. Taken together with our finding that IL1B, IL1R1 gene three SNP are also associated with the risk for the disease, we suggest that inflammation via innate and adaptive immunity contributes to multifactorial hereditary predisposition to pathogenesis of the breast cancer. PMID:29719585

  18. Novel KRAS Gene Mutations in Sporadic Colorectal Cancer

    PubMed Central

    Naser, Walid M.; Shawarby, Mohamed A.; Al-Tamimi, Dalal M.; Seth, Arun; Al-Quorain, Abdulaziz; Nemer, Areej M. Al; Albagha, Omar M. E.

    2014-01-01

    Introduction In this article, we report 7 novel KRAS gene mutations discovered while retrospectively studying the prevalence and pattern of KRAS mutations in cancerous tissue obtained from 56 Saudi sporadic colorectal cancer patients from the Eastern Province. Methods Genomic DNA was extracted from formalin-fixed, paraffin-embedded cancerous and noncancerous colorectal tissues. Successful and specific PCR products were then bi-directionally sequenced to detect exon 4 mutations while Mutector II Detection Kits were used for identifying mutations in codons 12, 13 and 61. The functional impact of the novel mutations was assessed using bioinformatics tools and molecular modeling. Results KRAS gene mutations were detected in the cancer tissue of 24 cases (42.85%). Of these, 11 had exon 4 mutations (19.64%). They harbored 8 different mutations all of which except two altered the KRAS protein amino acid sequence and all except one were novel as revealed by COSMIC database. The detected novel mutations were found to be somatic. One mutation is predicted to be benign. The remaining mutations are predicted to cause substantial changes in the protein structure. Of these, the Q150X nonsense mutation is the second truncating mutation to be reported in colorectal cancer in the literature. Conclusions Our discovery of novel exon 4 KRAS mutations that are, so far, unique to Saudi colorectal cancer patients may be attributed to environmental factors and/or racial/ethnic variations due to genetic differences. Alternatively, it may be related to paucity of clinical studies on mutations other than those in codons 12, 13, 61 and 146. Further KRAS testing on a large number of patients of various ethnicities, particularly beyond the most common hotspot alleles in exons 2 and 3 is needed to assess the prevalence and explore the exact prognostic and predictive significance of the discovered novel mutations as well as their possible role in colorectal carcinogenesis. PMID:25412182

  19. Screening for common copy-number variants in cancer genes.

    PubMed

    Tyson, Jess; Majerus, Tamsin M O; Walker, Susan; Armour, John A L

    2010-12-01

    For most cases of colorectal cancer that arise without a family history of the disease, it is proposed that an appreciable heritable component of predisposition is the result of contributions from many loci. Although progress has been made in identifying single nucleotide variants associated with colorectal cancer risk, the involvement of low-penetrance copy number variants is relatively unexplored. We have used multiplex amplifiable probe hybridization (MAPH) in a fourfold multiplex (QuadMAPH), positioned at an average resolution of one probe per 2 kb, to screen a total of 1.56 Mb of genomic DNA for copy number variants around the genes APC, AXIN1, BRCA1, BRCA2, CTNNB1, HRAS, MLH1, MSH2, and TP53. Two deletion events were detected, one upstream of MLH1 in a control individual and the other in APC in a colorectal cancer patient, but these do not seem to correspond to copy number polymorphisms with measurably high population frequencies. In summary, by means of our QuadMAPH assay, copy number measurement data were of sufficient resolution and accuracy to detect any copy number variants with high probability. However, this study has demonstrated a very low incidence of deletion and duplication variants within intronic and flanking regions of these nine genes, in both control individuals and colorectal cancer patients. Copyright © 2010 Elsevier Inc. All rights reserved.

  20. PCR-free Quantification of Multiple Splice Variants in Cancer Gene by Surface Enhanced Raman Spectroscopy

    PubMed Central

    Sun, Lan; Irudayaraj, Joseph

    2009-01-01

    We demonstrate a surface enhanced Raman spectroscopy (SERS) based array platform to monitor gene expression in cancer cells in a multiplex and quantitative format without amplification steps. A strategy comprising of DNA/RNA hybridization, S1 nuclease digestion, and alkaline hydrolysis was adopted to obtain DNA targets specific to two splice junction variants Δ(9, 10) and Δ(5) of the breast cancer susceptibility gene 1 (BRCA1) from MCF-7 and MDA-MB-231 breast cancer cell lines. These two targets were identified simultaneously and their absolute quantities were estimated by a SERS strategy utilizing the inherent plasmon-phonon Raman mode of gold nanoparticle probes as a self-referencing standard to correct for variability in surface enhancement. Results were then validated by reverse transcription PCR (RT-PCR). Our proposed methodology could be expanded to a higher level of multiplexing for quantitative gene expression analysis of any gene without any amplification steps. PMID:19780515

  1. NCG 4.0: the network of cancer genes in the era of massive mutational screenings of cancer genomes

    PubMed Central

    An, Omer; Pendino, Vera; D’Antonio, Matteo; Ratti, Emanuele; Gentilini, Marco; Ciccarelli, Francesca D.

    2014-01-01

    NCG 4.0 is the latest update of the Network of Cancer Genes, a web-based repository of systems-level properties of cancer genes. In its current version, the database collects information on 537 known (i.e. experimentally supported) and 1463 candidate (i.e. inferred using statistical methods) cancer genes. Candidate cancer genes derive from the manual revision of 67 original publications describing the mutational screening of 3460 human exomes and genomes in 23 different cancer types. For all 2000 cancer genes, duplicability, evolutionary origin, expression, functional annotation, interaction network with other human proteins and with microRNAs are reported. In addition to providing a substantial update of cancer-related information, NCG 4.0 also introduces two new features. The first is the annotation of possible false-positive cancer drivers, defined as candidate cancer genes inferred from large-scale screenings whose association with cancer is likely to be spurious. The second is the description of the systems-level properties of 64 human microRNAs that are causally involved in cancer progression (oncomiRs). Owing to the manual revision of all information, NCG 4.0 constitutes a complete and reliable resource on human coding and non-coding genes whose deregulation drives cancer onset and/or progression. NCG 4.0 can also be downloaded as a free application for Android smart phones. Database URL: http://bio.ieo.eu/ncg/ PMID:24608173

  2. Associations between RNA splicing regulatory variants of stemness-related genes and racial disparities in susceptibility to prostate cancer.

    PubMed

    Wang, Yanru; Freedman, Jennifer A; Liu, Hongliang; Moorman, Patricia G; Hyslop, Terry; George, Daniel J; Lee, Norman H; Patierno, Steven R; Wei, Qingyi

    2017-08-15

    Evidence suggests that cells with a stemness phenotype play a pivotal role in oncogenesis, and prostate cells exhibiting this phenotype have been identified. We used two genome-wide association study (GWAS) datasets of African descendants, from the Multiethnic/Minority Cohort Study of Diet and Cancer (MEC) and the Ghana Prostate Study, and two GWAS datasets of non-Hispanic whites, from the Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial and the Breast and Prostate Cancer Cohort Consortium (BPC3), to analyze the associations between genetic variants of stemness-related genes and racial disparities in susceptibility to prostate cancer. We evaluated associations of single-nucleotide polymorphisms (SNPs) in 25 stemness-related genes with prostate cancer risk in 1,609 cases and 2,550 controls of non-Hispanic whites (4,934 SNPs) and 1,144 cases and 1,116 controls of African descendants (5,448 SNPs) with correction by false discovery rate ≤0.2. We identified 32 SNPs in five genes (TP63, ALDH1A1, WNT1, MET and EGFR) that were significantly associated with prostate cancer risk, of which six SNPs in three genes (TP63, ALDH1A1 and WNT1) and eight EGFR SNPs showed heterogeneity in susceptibility between these two racial groups. In addition, 13 SNPs in MET and one in ALDH1A1 were found only in African descendants. The in silico bioinformatics analyses revealed that EGFR rs2072454 and SNPs in linkage with the identified SNPs in MET and ALDH1A1 (r 2  > 0.6) were predicted to regulate RNA splicing. These variants may serve as novel biomarkers for racial disparities in prostate cancer risk. © 2017 UICC.

  3. A functional in vivo screen for regulators of tumor progression identifies HOXB2 as a regulator of tumor growth in breast cancer

    PubMed Central

    Boimel, Pamela J.; Cruz, Cristian; Segall, Jeffrey E.

    2011-01-01

    Microarray profiling in breast cancer patients have identified genes correlated with prognosis whose functions are unknown. The purpose of this study was to develop an in vivo assay for functionally screening regulators of tumor progression using a mouse model. Transductant shRNA cell lines were made in the MDA-MB-231 breast cancer line. A pooled population of 25 transductants was injected into the mammary fat pads and tail veins of mice to evaluate tumor growth, and experimental metastasis. The proportions of transductants were evaluated in the tumor and metastases using barcodes specific to each shRNA transductant. We characterized the homeobox 2 transcription factor as a negative regulator, decreasing tumor growth in MDA-MB-231, T47D, and MTLn3 mammary adenocarcinoma cell lines. Homeobox genes have been correlated with cancer patient prognosis and tumorigenesis. Here we use a novel in vivo shRNA screen to identify a new role for a homeobox gene in human mammary adenocarcinoma. PMID:21672623

  4. Genetic basis and gene therapy trials for thyroid cancer.

    PubMed

    Al-Humadi, Hussam; Zarros, Apostolos; Al-Saigh, Rafal; Liapi, Charis

    2010-01-01

    Gene therapy is regarded as one of the most promising novel therapeutic approaches for hopeless cases of thyroid cancer and those not responding to traditional treatment. In the last two decades, many studies have focused on the genetic factors behind the origin and the development of thyroid cancer, in order to investigate and shed more light on the molecular pathways implicated in different differentiated or undifferentiated types of thyroid tumors. We, herein, review the current data on the main genes that have been proven to (or thought to) be implicated in thyroid cancer etiology, and which are involved in several well-known signaling pathways (such as the mitogen-activated protein kinase and phosphatidylinositol-3-kinase/Akt pathways). Moreover, we review the results of the efforts made through multiple gene therapy trials, via several gene therapy approaches/strategies, on different thyroid carcinomas. Our review leads to the conclusion that future research efforts should seriously consider gene therapy for the treatment of thyroid cancer, and, thus, should: (a) shed more light on the molecular basis of thyroid cancer tumorigenesis, (b) focus on the development of novel gene therapy approaches that can achieve the required antitumoral efficacy with minimum normal tissue toxicity, as well as (c) perform more gene therapy clinical trials, in order to acquire more data on the efficacy of the examined approaches and to record the provoked adverse effects.

  5. A VEGF-dependent gene signature enriched in mesenchymal ovarian cancer predicts patient prognosis.

    PubMed

    Yin, Xia; Wang, Xiaojie; Shen, Boqiang; Jing, Ying; Li, Qing; Cai, Mei-Chun; Gu, Zhuowei; Yang, Qi; Zhang, Zhenfeng; Liu, Jin; Li, Hongxia; Di, Wen; Zhuang, Guanglei

    2016-08-08

    We have previously reported surrogate biomarkers of VEGF pathway activities with the potential to provide predictive information for anti-VEGF therapies. The aim of this study was to systematically evaluate a new VEGF-dependent gene signature (VDGs) in relation to molecular subtypes of ovarian cancer and patient prognosis. Using microarray profiling and cross-species analysis, we identified 140-gene mouse VDGs and corresponding 139-gene human VDGs, which displayed enrichment of vasculature and basement membrane genes. In patients who received bevacizumab therapy and showed partial response, the expressions of VDGs (summarized to yield VDGs scores) were markedly decreased in post-treatment biopsies compared with pre-treatment baselines. In contrast, VDGs scores were not significantly altered following bevacizumab treatment in patients with stable or progressive disease. Analysis of VDGs in ovarian cancer showed that VDGs as a prognostic signature was able to predict patient outcome. Correlation estimation of VDGs scores and molecular features revealed that VDGs was overrepresented in mesenchymal subtype and BRCA mutation carriers. These findings highlighted the prognostic role of VEGF-mediated angiogenesis in ovarian cancer, and proposed a VEGF-dependent gene signature as a molecular basis for developing novel diagnostic strategies to aid patient selection for VEGF-targeted agents.

  6. Systems Biology-Based Investigation of Cellular Antiviral Drug Targets Identified by Gene-Trap Insertional Mutagenesis.

    PubMed

    Cheng, Feixiong; Murray, James L; Zhao, Junfei; Sheng, Jinsong; Zhao, Zhongming; Rubin, Donald H

    2016-09-01

    Viruses require host cellular factors for successful replication. A comprehensive systems-level investigation of the virus-host interactome is critical for understanding the roles of host factors with the end goal of discovering new druggable antiviral targets. Gene-trap insertional mutagenesis is a high-throughput forward genetics approach to randomly disrupt (trap) host genes and discover host genes that are essential for viral replication, but not for host cell survival. In this study, we used libraries of randomly mutagenized cells to discover cellular genes that are essential for the replication of 10 distinct cytotoxic mammalian viruses, 1 gram-negative bacterium, and 5 toxins. We herein reported 712 candidate cellular genes, characterizing distinct topological network and evolutionary signatures, and occupying central hubs in the human interactome. Cell cycle phase-specific network analysis showed that host cell cycle programs played critical roles during viral replication (e.g. MYC and TAF4 regulating G0/1 phase). Moreover, the viral perturbation of host cellular networks reflected disease etiology in that host genes (e.g. CTCF, RHOA, and CDKN1B) identified were frequently essential and significantly associated with Mendelian and orphan diseases, or somatic mutations in cancer. Computational drug repositioning framework via incorporating drug-gene signatures from the Connectivity Map into the virus-host interactome identified 110 putative druggable antiviral targets and prioritized several existing drugs (e.g. ajmaline) that may be potential for antiviral indication (e.g. anti-Ebola). In summary, this work provides a powerful methodology with a tight integration of gene-trap insertional mutagenesis testing and systems biology to identify new antiviral targets and drugs for the development of broadly acting and targeted clinical antiviral therapeutics.

  7. Epsin Family Member 3 and Ribosome-Related Genes Are Associated with Late Metastasis in Estrogen Receptor-Positive Breast Cancer and Long-Term Survival in Non-Small Cell Lung Cancer Using a Genome-Wide Identification and Validation Strategy.

    PubMed

    Hellwig, Birte; Madjar, Katrin; Edlund, Karolina; Marchan, Rosemarie; Cadenas, Cristina; Heimes, Anne-Sophie; Almstedt, Katrin; Lebrecht, Antje; Sicking, Isabel; Battista, Marco J; Micke, Patrick; Schmidt, Marcus; Hengstler, Jan G; Rahnenführer, Jörg

    2016-01-01

    In breast cancer, gene signatures that predict the risk of metastasis after surgical tumor resection are mainly indicative of early events. The purpose of this study was to identify genes linked to metastatic recurrence more than three years after surgery. Affymetrix HG U133A and Plus 2.0 array datasets with information on metastasis-free, disease-free or overall survival were accessed via public repositories. Time restricted Cox regression models were used to identify genes associated with metastasis during or after the first three years post-surgery (early- and late-type genes). A sequential validation study design, with two non-adjuvantly treated discovery cohorts (n = 409) and one validation cohort (n = 169) was applied and identified genes were further evaluated in tamoxifen-treated breast cancer patients (n = 923), as well as in patients with non-small cell lung (n = 1779), colon (n = 893) and ovarian (n = 922) cancer. Ten late- and 243 early-type genes were identified in adjuvantly untreated breast cancer. Adjustment to clinicopathological factors and an established proliferation-related signature markedly reduced the number of early-type genes to 16, whereas nine late-type genes still remained significant. These nine genes were associated with metastasis-free survival (MFS) also in a non-time restricted model, but not in the early period alone, stressing that their prognostic impact was primarily based on MFS more than three years after surgery. Four of the ten late-type genes, the ribosome-related factors EIF4B, RPL5, RPL3, and the tumor angiogenesis modifier EPN3 were significantly associated with MFS in the late period also in a meta-analysis of tamoxifen-treated breast cancer cohorts. In contrast, only one late-type gene (EPN3) showed consistent survival associations in more than one cohort in the other cancer types, being associated with worse outcome in two non-small cell lung cancer cohorts. No late-type gene was validated in ovarian and colon cancer

  8. Speckle-type POZ (pox virus and zinc finger protein) protein gene deletion in ovarian cancer: Fluorescence in situ hybridization analysis of a tissue microarray.

    PubMed

    Hu, Xiaoyu; Yang, Zhu; Zeng, Manman; Liu, Y I; Yang, Xiaotao; Li, Yanan; Li, X U; Yu, Qiubo

    2016-07-01

    The aim of the present study was to investigate the status of speckle-type POZ (pox virus and zinc finger protein) protein (SPOP) gene located on chromosome 17q21 in ovarian cancer (OC). The present study evaluated a tissue microarray, which contained 90 samples of ovarian cancer and 10 samples of normal ovarian tissue, using fluorescence in situ hybridization (FISH). FISH is a method where a SPOP-specific DNA red fluorescence probe was used for the experimental group and a centromere-specific DNA green fluorescence probe for chromosome 17 was used for the control group. The present study demonstrated that a deletion of the SPOP gene was observed in 52.27% (46/88) of the ovarian cancer tissues, but was not identified in normal ovarian tissues. Simultaneously, monosomy 17 was frequently identified in the ovarian cancer tissues, but not in the normal ovarian tissues. Furthermore, the present data revealed that the ovarian cancer histological subtype and grade were significantly associated with a deletion of the SPOP gene, which was assessed by the appearance of monosomy 17 in the ovarian cancer samples; the deletion of the SPOP gene was observed in a large proportion of serous epithelial ovarian cancer (41/61; 67.21%), particularly in grade 3 (31/37; 83.78%). In conclusion, deletion of the SPOP gene on chromosome 17 in ovarian cancer samples, which results from monosomy 17, indicates that the SPOP gene may serve as a tumor suppressor gene in ovarian cancer.

  9. Identifying significant genetic regulatory networks in the prostate cancer from microarray data based on transcription factor analysis and conditional independency.

    PubMed

    Yeh, Hsiang-Yuan; Cheng, Shih-Wu; Lin, Yu-Chun; Yeh, Cheng-Yu; Lin, Shih-Fang; Soo, Von-Wun

    2009-12-21

    Prostate cancer is a world wide leading cancer and it is characterized by its aggressive metastasis. According to the clinical heterogeneity, prostate cancer displays different stages and grades related to the aggressive metastasis disease. Although numerous studies used microarray analysis and traditional clustering method to identify the individual genes during the disease processes, the important gene regulations remain unclear. We present a computational method for inferring genetic regulatory networks from micorarray data automatically with transcription factor analysis and conditional independence testing to explore the potential significant gene regulatory networks that are correlated with cancer, tumor grade and stage in the prostate cancer. To deal with missing values in microarray data, we used a K-nearest-neighbors (KNN) algorithm to determine the precise expression values. We applied web services technology to wrap the bioinformatics toolkits and databases to automatically extract the promoter regions of DNA sequences and predicted the transcription factors that regulate the gene expressions. We adopt the microarray datasets consists of 62 primary tumors, 41 normal prostate tissues from Stanford Microarray Database (SMD) as a target dataset to evaluate our method. The predicted results showed that the possible biomarker genes related to cancer and denoted the androgen functions and processes may be in the development of the prostate cancer and promote the cell death in cell cycle. Our predicted results showed that sub-networks of genes SREBF1, STAT6 and PBX1 are strongly related to a high extent while ETS transcription factors ELK1, JUN and EGR2 are related to a low extent. Gene SLC22A3 may explain clinically the differentiation associated with the high grade cancer compared with low grade cancer. Enhancer of Zeste Homolg 2 (EZH2) regulated by RUNX1 and STAT3 is correlated to the pathological stage. We provide a computational framework to reconstruct

  10. Identifying significant genetic regulatory networks in the prostate cancer from microarray data based on transcription factor analysis and conditional independency

    PubMed Central

    2009-01-01

    Background Prostate cancer is a world wide leading cancer and it is characterized by its aggressive metastasis. According to the clinical heterogeneity, prostate cancer displays different stages and grades related to the aggressive metastasis disease. Although numerous studies used microarray analysis and traditional clustering method to identify the individual genes during the disease processes, the important gene regulations remain unclear. We present a computational method for inferring genetic regulatory networks from micorarray data automatically with transcription factor analysis and conditional independence testing to explore the potential significant gene regulatory networks that are correlated with cancer, tumor grade and stage in the prostate cancer. Results To deal with missing values in microarray data, we used a K-nearest-neighbors (KNN) algorithm to determine the precise expression values. We applied web services technology to wrap the bioinformatics toolkits and databases to automatically extract the promoter regions of DNA sequences and predicted the transcription factors that regulate the gene expressions. We adopt the microarray datasets consists of 62 primary tumors, 41 normal prostate tissues from Stanford Microarray Database (SMD) as a target dataset to evaluate our method. The predicted results showed that the possible biomarker genes related to cancer and denoted the androgen functions and processes may be in the development of the prostate cancer and promote the cell death in cell cycle. Our predicted results showed that sub-networks of genes SREBF1, STAT6 and PBX1 are strongly related to a high extent while ETS transcription factors ELK1, JUN and EGR2 are related to a low extent. Gene SLC22A3 may explain clinically the differentiation associated with the high grade cancer compared with low grade cancer. Enhancer of Zeste Homolg 2 (EZH2) regulated by RUNX1 and STAT3 is correlated to the pathological stage. Conclusions We provide a

  11. In silico analysis of stomach lineage specific gene set expression pattern in gastric cancer

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Pandi, Narayanan Sathiya, E-mail: sathiyapandi@gmail.com; Suganya, Sivagurunathan; Rajendran, Suriliyandi

    Highlights: •Identified stomach lineage specific gene set (SLSGS) was found to be under expressed in gastric tumors. •Elevated expression of SLSGS in gastric tumor is a molecular predictor of metabolic type gastric cancer. •In silico pathway scanning identified estrogen-α signaling is a putative regulator of SLSGS in gastric cancer. •Elevated expression of SLSGS in GC is associated with an overall increase in the survival of GC patients. -- Abstract: Stomach lineage specific gene products act as a protective barrier in the normal stomach and their expression maintains the normal physiological processes, cellular integrity and morphology of the gastric wall. However,more » the regulation of stomach lineage specific genes in gastric cancer (GC) is far less clear. In the present study, we sought to investigate the role and regulation of stomach lineage specific gene set (SLSGS) in GC. SLSGS was identified by comparing the mRNA expression profiles of normal stomach tissue with other organ tissue. The obtained SLSGS was found to be under expressed in gastric tumors. Functional annotation analysis revealed that the SLSGS was enriched for digestive function and gastric epithelial maintenance. Employing a single sample prediction method across GC mRNA expression profiles identified the under expression of SLSGS in proliferative type and invasive type gastric tumors compared to the metabolic type gastric tumors. Integrative pathway activation prediction analysis revealed a close association between estrogen-α signaling and SLSGS expression pattern in GC. Elevated expression of SLSGS in GC is associated with an overall increase in the survival of GC patients. In conclusion, our results highlight that estrogen mediated regulation of SLSGS in gastric tumor is a molecular predictor of metabolic type GC and prognostic factor in GC.« less

  12. New Wnt/β-catenin target genes promote experimental metastasis and migration of colorectal cancer cells through different signals.

    PubMed

    Qi, Jingjing; Yu, Yong; Akilli Öztürk, Özlem; Holland, Jane D; Besser, Daniel; Fritzmann, Johannes; Wulf-Goldenberg, Annika; Eckert, Klaus; Fichtner, Iduna; Birchmeier, Walter

    2016-10-01

    We have previously identified a 115-gene signature that characterises the metastatic potential of human primary colon cancers. The signature included the canonical Wnt target gene BAMBI, which promoted experimental metastasis in mice. Here, we identified three new direct Wnt target genes from the signature, and studied their functions in epithelial-mesenchymal transition (EMT), cell migration and experimental metastasis. We examined experimental liver metastases following injection of selected tumour cells into spleens of NOD/SCID mice. Molecular and cellular techniques were used to identify direct transcription target genes of Wnt/β-catenin signals. Microarray analyses and experiments that interfered with cell migration through inhibitors were performed to characterise downstream signalling systems. Three new genes from the colorectal cancer (CRC) metastasis signature, BOP1, CKS2 and NFIL3, were identified as direct transcription targets of β-catenin/TCF4. Overexpression and knocking down of these genes in CRC cells promoted and inhibited, respectively, experimental metastasis in mice, EMT and cell motility in culture. Cell migration was repressed by interfering with distinct signalling systems through inhibitors of PI3K, JNK, p38 mitogen-activated protein kinase and/or mTOR. Gene expression profiling identified a series of migration-promoting genes, which were induced by BOP1, CKS2 and NFIL3, and could be repressed by inhibitors that are specific to these pathways. We identified new direct Wnt/β-catenin target genes, BOP1, CKS2 and NFIL3, which induced EMT, cell migration and experimental metastasis of CRC cells. These genes crosstalk with different downstream signalling systems, and activate migration-promoting genes. These pathways and downstream genes may serve as therapeutic targets in the treatment of CRC metastasis. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

  13. Identifying kinase dependency in cancer cells by integrating high-throughput drug screening and kinase inhibition data.

    PubMed

    Ryall, Karen A; Shin, Jimin; Yoo, Minjae; Hinz, Trista K; Kim, Jihye; Kang, Jaewoo; Heasley, Lynn E; Tan, Aik Choon

    2015-12-01

    Targeted kinase inhibitors have dramatically improved cancer treatment, but kinase dependency for an individual patient or cancer cell can be challenging to predict. Kinase dependency does not always correspond with gene expression and mutation status. High-throughput drug screens are powerful tools for determining kinase dependency, but drug polypharmacology can make results difficult to interpret. We developed Kinase Addiction Ranker (KAR), an algorithm that integrates high-throughput drug screening data, comprehensive kinase inhibition data and gene expression profiles to identify kinase dependency in cancer cells. We applied KAR to predict kinase dependency of 21 lung cancer cell lines and 151 leukemia patient samples using published datasets. We experimentally validated KAR predictions of FGFR and MTOR dependence in lung cancer cell line H1581, showing synergistic reduction in proliferation after combining ponatinib and AZD8055. KAR can be downloaded as a Python function or a MATLAB script along with example inputs and outputs at: http://tanlab.ucdenver.edu/KAR/. aikchoon.tan@ucdenver.edu. Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  14. Validation and Interrogation of Differentially Expressed and Alternately Spliced Genes in African American Prostate Cancer

    DTIC Science & Technology

    2017-10-01

    aggressive disease. 15. SUBJECT TERMS Prostate cancer, health disparities among racial groups, molecular mechanisms, differential gene expression...identify molecular mechanisms of tumor aggressiveness. The studies proposed here address the urgent need to elucidate the molecular mechanisms underlying... genetic /epigenetic/post-transcriptional factors in AA prostate cancer and Gleason grade and 2) manipulate splicing using novel splice-switching

  15. Massive expression of germ cell-specific genes is a hallmark of cancer and a potential target for novel treatment development.

    PubMed

    Bruggeman, Jan Willem; Koster, Jan; Lodder, Paul; Repping, Sjoerd; Hamer, Geert

    2018-06-15

    Cancer cells have been found to frequently express genes that are normally restricted to the testis, often referred to as cancer/testis (CT) antigens or genes. Because germ cell-specific antigens are not recognized as "self" by the innate immune system, CT-genes have previously been suggested as ideal candidate targets for cancer therapy. The use of CT-genes in cancer therapy has thus far been unsuccessful, most likely because their identification has relied on gene expression in whole testis, including the testicular somatic cells, precluding the detection of true germ cell-specific genes. By comparing the transcriptomes of micro-dissected germ cell subtypes, representing the main developmental stages of human spermatogenesis, with the publicly accessible transcriptomes of 2617 samples from 49 different healthy somatic tissues and 9232 samples from 33 tumor types, we here discover hundreds of true germ cell-specific cancer expressed genes. Strikingly, we found these germ cell cancer genes (GC-genes) to be widely expressed in all analyzed tumors. Many GC-genes appeared to be involved in processes that are likely to actively promote tumor viability, proliferation and metastasis. Targeting these true GC-genes thus has the potential to inhibit tumor growth with infertility being the only possible side effect. Moreover, we identified a subset of GC-genes that are not expressed in spermatogonial stem cells. Targeting of this GC-gene subset is predicted to only lead to temporary infertility, as untargeted spermatogonial stem cells can recover spermatogenesis after treatment. Our GC-gene dataset enables improved understanding of tumor biology and provides multiple novel targets for cancer treatment.

  16. Data Mining of Gene Arrays for Biomarkers of Survival in Ovarian Cancer

    PubMed Central

    Coveney, Clare; Boocock, David J.; Rees, Robert C.; Deen, Suha; Ball, Graham R.

    2015-01-01

    The expected five-year survival rate from a stage III ovarian cancer diagnosis is a mere 22%; this applies to the 7000 new cases diagnosed yearly in the UK. Stratification of patients with this heterogeneous disease, based on active molecular pathways, would aid a targeted treatment improving the prognosis for many cases. While hundreds of genes have been associated with ovarian cancer, few have yet been verified by peer research for clinical significance. Here, a meta-analysis approach was applied to two carefully selected gene expression microarray datasets. Artificial neural networks, Cox univariate survival analyses and T-tests identified genes whose expression was consistently and significantly associated with patient survival. The rigor of this experimental design increases confidence in the genes found to be of interest. A list of 56 genes were distilled from a potential 37,000 to be significantly related to survival in both datasets with a FDR of 1.39859 × 10−11, the identities of which both verify genes already implicated with this disease and provide novel genes and pathways to pursue. Further investigation and validation of these may lead to clinical insights and have potential to predict a patient’s response to treatment or be used as a novel target for therapy. PMID:27600227

  17. RNA-based ovarian cancer research from 'a gene to systems biomedicine' perspective.

    PubMed

    Gov, Esra; Kori, Medi; Arga, Kazim Yalcin

    2017-08-01

    Ovarian cancer remains the leading cause of death from a gynecologic malignancy, and treatment of this disease is harder than any other type of female reproductive cancer. Improvements in the diagnosis and development of novel and effective treatment strategies for complex pathophysiologies, such as ovarian cancer, require a better understanding of disease emergence and mechanisms of progression through systems medicine approaches. RNA-level analyses generate new information that can help in understanding the mechanisms behind disease pathogenesis, to identify new biomarkers and therapeutic targets and in new drug discovery. Whole RNA sequencing and coding and non-coding RNA expression array datasets have shed light on the mechanisms underlying disease progression and have identified mRNAs, miRNAs, and lncRNAs involved in ovarian cancer progression. In addition, the results from these analyses indicate that various signalling pathways and biological processes are associated with ovarian cancer. Here, we present a comprehensive literature review on RNA-based ovarian cancer research and highlight the benefits of integrative approaches within the systems biomedicine concept for future ovarian cancer research. We invite the ovarian cancer and systems biomedicine research fields to join forces to achieve the interdisciplinary caliber and rigor required to find real-life solutions to common, devastating, and complex diseases such as ovarian cancer. CAF: cancer-associated fibroblasts; COG: Cluster of Orthologous Groups; DEA: disease enrichment analysis; EOC: epithelial ovarian carcinoma; ESCC: oesophageal squamous cell carcinoma; GSI: gamma secretase inhibitor; GO: Gene Ontology; GSEA: gene set enrichment analyzes; HAS: Hungarian Academy of Sciences; lncRNAs: long non-coding RNAs; MAPK/ERK: mitogen-activated protein kinase/extracellular signal-regulated kinases; NGS: next-generation sequencing; ncRNAs: non-coding RNAs; OvC: ovarian cancer; PI3K

  18. New genes emerging for colorectal cancer predisposition.

    PubMed

    Esteban-Jurado, Clara; Garre, Pilar; Vila, Maria; Lozano, Juan José; Pristoupilova, Anna; Beltrán, Sergi; Abulí, Anna; Muñoz, Jenifer; Balaguer, Francesc; Ocaña, Teresa; Castells, Antoni; Piqué, Josep M; Carracedo, Angel; Ruiz-Ponte, Clara; Bessa, Xavier; Andreu, Montserrat; Bujanda, Luis; Caldés, Trinidad; Castellví-Bel, Sergi

    2014-02-28

    Colorectal cancer (CRC) is one of the most frequent neoplasms and an important cause of mortality in the developed world. This cancer is caused by both genetic and environmental factors although 35% of the variation in CRC susceptibility involves inherited genetic differences. Mendelian syndromes account for about 5% of the total burden of CRC, with Lynch syndrome and familial adenomatous polyposis the most common forms. Excluding hereditary forms, there is an important fraction of CRC cases that present familial aggregation for the disease with an unknown germline genetic cause. CRC can be also considered as a complex disease taking into account the common disease-commom variant hypothesis with a polygenic model of inheritance where the genetic components of common complex diseases correspond mostly to variants of low/moderate effect. So far, 30 common, low-penetrance susceptibility variants have been identified for CRC. Recently, new sequencing technologies including exome- and whole-genome sequencing have permitted to add a new approach to facilitate the identification of new genes responsible for human disease predisposition. By using whole-genome sequencing, germline mutations in the POLE and POLD1 genes have been found to be responsible for a new form of CRC genetic predisposition called polymerase proofreading-associated polyposis.

  19. Identifying key genes in rheumatoid arthritis by weighted gene co-expression network analysis.

    PubMed

    Ma, Chunhui; Lv, Qi; Teng, Songsong; Yu, Yinxian; Niu, Kerun; Yi, Chengqin

    2017-08-01

    This study aimed to identify rheumatoid arthritis (RA) related genes based on microarray data using the WGCNA (weighted gene co-expression network analysis) method. Two gene expression profile datasets GSE55235 (10 RA samples and 10 healthy controls) and GSE77298 (16 RA samples and seven healthy controls) were downloaded from Gene Expression Omnibus database. Characteristic genes were identified using metaDE package. WGCNA was used to find disease-related networks based on gene expression correlation coefficients, and module significance was defined as the average gene significance of all genes used to assess the correlation between the module and RA status. Genes in the disease-related gene co-expression network were subject to functional annotation and pathway enrichment analysis using Database for Annotation Visualization and Integrated Discovery. Characteristic genes were also mapped to the Connectivity Map to screen small molecules. A total of 599 characteristic genes were identified. For each dataset, characteristic genes in the green, red and turquoise modules were most closely associated with RA, with gene numbers of 54, 43 and 79, respectively. These genes were enriched in totally enriched in 17 Gene Ontology terms, mainly related to immune response (CD97, FYB, CXCL1, IKBKE, CCR1, etc.), inflammatory response (CD97, CXCL1, C3AR1, CCR1, LYZ, etc.) and homeostasis (C3AR1, CCR1, PLN, CCL19, PPT1, etc.). Two small-molecule drugs sanguinarine and papaverine were predicted to have a therapeutic effect against RA. Genes related to immune response, inflammatory response and homeostasis presumably have critical roles in RA pathogenesis. Sanguinarine and papaverine have a potential therapeutic effect against RA. © 2017 Asia Pacific League of Associations for Rheumatology and John Wiley & Sons Australia, Ltd.

  20. Inherited variation in circadian rhythm genes and risks of prostate cancer and three other cancer sites in combined cancer consortia.

    PubMed

    Gu, Fangyi; Zhang, Han; Hyland, Paula L; Berndt, Sonja; Gapstur, Susan M; Wheeler, William; Ellipse Consortium, The; Amos, Christopher I; Bezieau, Stephane; Bickeböller, Heike; Brenner, Hermann; Brennan, Paul; Chang-Claude, Jenny; Conti, David V; Doherty, Jennifer Anne; Gruber, Stephen B; Harrison, Tabitha A; Hayes, Richard B; Hoffmeister, Michael; Houlston, Richard S; Hung, Rayjean J; Jenkins, Mark A; Kraft, Peter; Lawrenson, Kate; McKay, James; Markt, Sarah; Mucci, Lorelei; Phelan, Catherine M; Qu, Conghui; Risch, Angela; Rossing, Mary Anne; Wichmann, H-Erich; Shi, Jianxin; Schernhammer, Eva; Yu, Kai; Landi, Maria Teresa; Caporaso, Neil E

    2017-11-01

    Circadian disruption has been linked to carcinogenesis in animal models, but the evidence in humans is inconclusive. Genetic variation in circadian rhythm genes provides a tool to investigate such associations. We examined associations of genetic variation in nine core circadian rhythm genes and six melatonin pathway genes with risk of colorectal, lung, ovarian and prostate cancers using data from the Genetic Associations and Mechanisms in Oncology (GAME-ON) network. The major results for prostate cancer were replicated in the Prostate, Lung, Colorectal and Ovarian (PLCO) cancer screening trial, and for colorectal cancer in the Genetics and Epidemiology of Colorectal Cancer Consortium (GECCO). The total number of cancer cases and controls was 15,838/18,159 for colorectal, 14,818/14,227 for prostate, 12,537/17,285 for lung and 4,369/9,123 for ovary. For each cancer site, we conducted gene-based and pathway-based analyses by applying the summary-based Adaptive Rank Truncated Product method (sARTP) on the summary association statistics for each SNP within the candidate gene regions. Aggregate genetic variation in circadian rhythm and melatonin pathways were significantly associated with the risk of prostate cancer in data combining GAME-ON and PLCO, after Bonferroni correction (p pathway  < 0.00625). The two most significant genes were NPAS2 (p gene  = 0.0062) and AANAT (p gene  = 0.00078); the latter being significant after Bonferroni correction. For colorectal cancer, we observed a suggestive association with the circadian rhythm pathway in GAME-ON (p pathway  = 0.021); this association was not confirmed in GECCO (p pathway  = 0.76) or the combined data (p pathway  = 0.17). No significant association was observed for ovarian and lung cancer. These findings support a potential role for circadian rhythm and melatonin pathways in prostate carcinogenesis. Further functional studies are needed to better understand the underlying biologic

  1. Comprehensive genetic assessment of the ESR1 locus identifies a risk region for endometrial cancer.

    PubMed

    O'Mara, Tracy A; Glubb, Dylan M; Painter, Jodie N; Cheng, Timothy; Dennis, Joe; Attia, John; Holliday, Elizabeth G; McEvoy, Mark; Scott, Rodney J; Ashton, Katie; Proietto, Tony; Otton, Geoffrey; Shah, Mitul; Ahmed, Shahana; Healey, Catherine S; Gorman, Maggie; Martin, Lynn; Hodgson, Shirley; Fasching, Peter A; Hein, Alexander; Beckmann, Matthias W; Ekici, Arif B; Hall, Per; Czene, Kamila; Darabi, Hatef; Li, Jingmei; Dürst, Matthias; Runnebaum, Ingo; Hillemanns, Peter; Dörk, Thilo; Lambrechts, Diether; Depreeuw, Jeroen; Annibali, Daniela; Amant, Frederic; Zhao, Hui; Goode, Ellen L; Dowdy, Sean C; Fridley, Brooke L; Winham, Stacey J; Salvesen, Helga B; Njølstad, Tormund S; Trovik, Jone; Werner, Henrica M J; Tham, Emma; Liu, Tao; Mints, Miriam; Bolla, Manjeet K; Michailidou, Kyriaki; Tyrer, Jonathan P; Wang, Qin; Hopper, John L; Peto, Julian; Swerdlow, Anthony J; Burwinkel, Barbara; Brenner, Hermann; Meindl, Alfons; Brauch, Hiltrud; Lindblom, Annika; Chang-Claude, Jenny; Couch, Fergus J; Giles, Graham G; Kristensen, Vessela N; Cox, Angela; Pharoah, Paul D P; Dunning, Alison M; Tomlinson, Ian; Easton, Douglas F; Thompson, Deborah J; Spurdle, Amanda B

    2015-10-01

    Excessive exposure to estrogen is a well-established risk factor for endometrial cancer (EC), particularly for cancers of endometrioid histology. The physiological function of estrogen is primarily mediated by estrogen receptor alpha, encoded by ESR1. Consequently, several studies have investigated whether variation at the ESR1 locus is associated with risk of EC, with conflicting results. We performed comprehensive fine-mapping analyses of 3633 genotyped and imputed single nucleotide polymorphisms (SNPs) in 6607 EC cases and 37 925 controls. There was evidence of an EC risk signal located at a potential alternative promoter of the ESR1 gene (lead SNP rs79575945, P=1.86×10(-5)), which was stronger for cancers of endometrioid subtype (P=3.76×10(-6)). Bioinformatic analysis suggests that this risk signal is in a functionally important region targeting ESR1, and eQTL analysis found that rs79575945 was associated with expression of SYNE1, a neighbouring gene. In summary, we have identified a single EC risk signal located at ESR1, at study-wide significance. Given SNPs located at this locus have been associated with risk for breast cancer, also a hormonally driven cancer, this study adds weight to the rationale for performing informed candidate fine-scale genetic studies across cancer types. © 2015 Society for Endocrinology.

  2. Genome-wide DNA methylation analysis reveals estrogen-mediated epigenetic repression of metallothionein-1 gene cluster in breast cancer.

    PubMed

    Jadhav, Rohit R; Ye, Zhenqing; Huang, Rui-Lan; Liu, Joseph; Hsu, Pei-Yin; Huang, Yi-Wen; Rangel, Leticia B; Lai, Hung-Cheng; Roa, Juan Carlos; Kirma, Nameer B; Huang, Tim Hui-Ming; Jin, Victor X

    2015-01-01

    Recent genome-wide analysis has shown that DNA methylation spans long stretches of chromosome regions consisting of clusters of contiguous CpG islands or gene families. Hypermethylation of various gene clusters has been reported in many types of cancer. In this study, we conducted methyl-binding domain capture (MBDCap) sequencing (MBD-seq) analysis on a breast cancer cohort consisting of 77 patients and 10 normal controls, as well as a panel of 38 breast cancer cell lines. Bioinformatics analysis determined seven gene clusters with a significant difference in overall survival (OS) and further revealed a distinct feature that the conservation of a large gene cluster (approximately 70 kb) metallothionein-1 (MT1) among 45 species is much lower than the average of all RefSeq genes. Furthermore, we found that DNA methylation is an important epigenetic regulator contributing to gene repression of MT1 gene cluster in both ERα positive (ERα+) and ERα negative (ERα-) breast tumors. In silico analysis revealed much lower gene expression of this cluster in The Cancer Genome Atlas (TCGA) cohort for ERα + tumors. To further investigate the role of estrogen, we conducted 17β-estradiol (E2) and demethylating agent 5-aza-2'-deoxycytidine (DAC) treatment in various breast cancer cell types. Cell proliferation and invasion assays suggested MT1F and MT1M may play an anti-oncogenic role in breast cancer. Our data suggests that DNA methylation in large contiguous gene clusters can be potential prognostic markers of breast cancer. Further investigation of these clusters revealed that estrogen mediates epigenetic repression of MT1 cluster in ERα + breast cancer cell lines. In all, our studies identify thousands of breast tumor hypermethylated regions for the first time, in particular, discovering seven large contiguous hypermethylated gene clusters.

  3. Hypermethylation of the TSLC1 Gene Promoter in Primary Gastric Cancers and Gastric Cancer Cell Lines

    PubMed Central

    Honda, Teiichiro; Waki, Takayoshi; Jin, Zhe; Sato, Kiyoshi; Motoyama, Teiichi; Kawata, Sumio; Kimura, Wataru; Nishizuka, Satoshi; Murakami, Yoshinori

    2002-01-01

    The TSLC1 (tumor suppressor in lung cancer–1) gene is a novel tumor suppressor gene on chromosomal region 11q23.2, and is frequently inactivated by concordant promoter hypermethylation and loss of heterozygosity (LOH) in non‐small cell lung cancer (NSCLC). Because LOH on 11q has also been observed frequently in other human neoplasms including gastric cancer, we investigated the promoter methylation status of TSLC1 in 10 gastric cancer cell lines and 97 primary gastric cancers, as well as the corresponding non‐cancerous gastric tissues, by bisulfite‐SSCP analysis followed by direct sequencing. Allelic status of the TSLC1 gene was also investigated in these cell lines and primary gastric cancers. The TSLC1 promoter was methylated in two gastric cancer cell lines, KATO‐III and ECC10, and in 15 out of 97 (16%) primary gastric cancers. It was not methylated in non‐cancerous gastric tissues, suggesting that this hypermethylation is a cancer‐specific alteration. KATO‐III and ECC10 cells retained two alleles of TSLC1, both of which showed hypermethylation, associated with complete loss of gene expression. Most of the primary gastric cancers with promoter methylation also retained heterozygosity at the TSLC1 locus on 11q23.2. These data indicate that bi‐allelic hypermethylation of the TSLC1 promoter and resulting gene silencing occur in a subset of primary gastric cancers. PMID:12716461

  4. A side-effect free method for identifying cancer drug targets.

    PubMed

    Ashraf, Md Izhar; Ong, Seng-Kai; Mujawar, Shama; Pawar, Shrikant; More, Pallavi; Paul, Somnath; Lahiri, Chandrajit

    2018-04-27

    Identifying effective drug targets, with little or no side effects, remains an ever challenging task. A potential pitfall of failing to uncover the correct drug targets, due to side effect of pleiotropic genes, might lead the potential drugs to be illicit and withdrawn. Simplifying disease complexity, for the investigation of the mechanistic aspects and identification of effective drug targets, have been done through several approaches of protein interactome analysis. Of these, centrality measures have always gained importance in identifying candidate drug targets. Here, we put forward an integrated method of analysing a complex network of cancer and depict the importance of k-core, functional connectivity and centrality (KFC) for identifying effective drug targets. Essentially, we have extracted the proteins involved in the pathways leading to cancer from the pathway databases which enlist real experimental datasets. The interactions between these proteins were mapped to build an interactome. Integrative analyses of the interactome enabled us to unearth plausible reasons for drugs being rendered withdrawn, thereby giving future scope to pharmaceutical industries to potentially avoid them (e.g. ESR1, HDAC2, F2, PLG, PPARA, RXRA, etc). Based upon our KFC criteria, we have shortlisted ten proteins (GRB2, FYN, PIK3R1, CBL, JAK2, LCK, LYN, SYK, JAK1 and SOCS3) as effective candidates for drug development.

  5. Integrated Molecular Profiling of Human Gastric Cancer Identifies DDR2 as a Potential Regulator of Peritoneal Dissemination.

    PubMed

    Kurashige, Junji; Hasegawa, Takanori; Niida, Atsushi; Sugimachi, Keishi; Deng, Niantao; Mima, Kosuke; Uchi, Ryutaro; Sawada, Genta; Takahashi, Yusuke; Eguchi, Hidetoshi; Inomata, Masashi; Kitano, Seigo; Fukagawa, Takeo; Sasako, Mitsuru; Sasaki, Hiroki; Sasaki, Shin; Mori, Masaki; Yanagihara, Kazuyoshi; Baba, Hideo; Miyano, Satoru; Tan, Patrick; Mimori, Koshi

    2016-03-03

    Peritoneal dissemination is the most frequent, incurable metastasis occurring in patients with advanced gastric cancer (GC). However, molecular mechanisms driving peritoneal dissemination still remain poorly understood. Here, we aimed to provide novel insights into the molecular mechanisms that drive the peritoneal dissemination of GC. We performed combined expression analysis with in vivo-selected metastatic cell lines and samples from 200 GC patients to identify driver genes of peritoneal dissemination. The driver-gene functions associated with GC dissemination were examined using a mouse xenograft model. We identified a peritoneal dissemination-associated expression signature, whose profile correlated with those of genes related to development, focal adhesion, and the extracellular matrix. Among the genes comprising the expression signature, we identified that discoidin-domain receptor 2 (DDR2) as a potential regulator of peritoneal dissemination. The DDR2 was upregulated by the loss of DNA methylation and that DDR2 knockdown reduced peritoneal metastasis in a xenograft model. Dasatinib, an inhibitor of the DDR2 signaling pathway, effectively suppressed peritoneal dissemination. DDR2 was identified as a driver gene for GC dissemination from the combined expression signature and can potentially serve as a novel therapeutic target for inhibiting GC peritoneal dissemination.

  6. Identifying gene networks underlying the neurobiology of ethanol and alcoholism.

    PubMed

    Wolen, Aaron R; Miles, Michael F

    2012-01-01

    For complex disorders such as alcoholism, identifying the genes linked to these diseases and their specific roles is difficult. Traditional genetic approaches, such as genetic association studies (including genome-wide association studies) and analyses of quantitative trait loci (QTLs) in both humans and laboratory animals already have helped identify some candidate genes. However, because of technical obstacles, such as the small impact of any individual gene, these approaches only have limited effectiveness in identifying specific genes that contribute to complex diseases. The emerging field of systems biology, which allows for analyses of entire gene networks, may help researchers better elucidate the genetic basis of alcoholism, both in humans and in animal models. Such networks can be identified using approaches such as high-throughput molecular profiling (e.g., through microarray-based gene expression analyses) or strategies referred to as genetical genomics, such as the mapping of expression QTLs (eQTLs). Characterization of gene networks can shed light on the biological pathways underlying complex traits and provide the functional context for identifying those genes that contribute to disease development.

  7. Ancient genes establish stress-induced mutation as a hallmark of cancer.

    PubMed

    Cisneros, Luis; Bussey, Kimberly J; Orr, Adam J; Miočević, Milica; Lineweaver, Charles H; Davies, Paul

    2017-01-01

    Cancer is sometimes depicted as a reversion to single cell behavior in cells adapted to live in a multicellular assembly. If this is the case, one would expect that mutation in cancer disrupts functional mechanisms that suppress cell-level traits detrimental to multicellularity. Such mechanisms should have evolved with or after the emergence of multicellularity. This leads to two related, but distinct hypotheses: 1) Somatic mutations in cancer will occur in genes that are younger than the emergence of multicellularity (1000 million years [MY]); and 2) genes that are frequently mutated in cancer and whose mutations are functionally important for the emergence of the cancer phenotype evolved within the past 1000 million years, and thus would exhibit an age distribution that is skewed to younger genes. In order to investigate these hypotheses we estimated the evolutionary ages of all human genes and then studied the probability of mutation and their biological function in relation to their age and genomic location for both normal germline and cancer contexts. We observed that under a model of uniform random mutation across the genome, controlled for gene size, genes less than 500 MY were more frequently mutated in both cases. Paradoxically, causal genes, defined in the COSMIC Cancer Gene Census, were depleted in this age group. When we used functional enrichment analysis to explain this unexpected result we discovered that COSMIC genes with recessive disease phenotypes were enriched for DNA repair and cell cycle control. The non-mutated genes in these pathways are orthologous to those underlying stress-induced mutation in bacteria, which results in the clustering of single nucleotide variations. COSMIC genes were less common in regions where the probability of observing mutational clusters is high, although they are approximately 2-fold more likely to harbor mutational clusters compared to other human genes. Our results suggest this ancient mutational response to

  8. Ancient genes establish stress-induced mutation as a hallmark of cancer

    PubMed Central

    Orr, Adam J.; Miočević, Milica; Lineweaver, Charles H.; Davies, Paul

    2017-01-01

    Cancer is sometimes depicted as a reversion to single cell behavior in cells adapted to live in a multicellular assembly. If this is the case, one would expect that mutation in cancer disrupts functional mechanisms that suppress cell-level traits detrimental to multicellularity. Such mechanisms should have evolved with or after the emergence of multicellularity. This leads to two related, but distinct hypotheses: 1) Somatic mutations in cancer will occur in genes that are younger than the emergence of multicellularity (1000 million years [MY]); and 2) genes that are frequently mutated in cancer and whose mutations are functionally important for the emergence of the cancer phenotype evolved within the past 1000 million years, and thus would exhibit an age distribution that is skewed to younger genes. In order to investigate these hypotheses we estimated the evolutionary ages of all human genes and then studied the probability of mutation and their biological function in relation to their age and genomic location for both normal germline and cancer contexts. We observed that under a model of uniform random mutation across the genome, controlled for gene size, genes less than 500 MY were more frequently mutated in both cases. Paradoxically, causal genes, defined in the COSMIC Cancer Gene Census, were depleted in this age group. When we used functional enrichment analysis to explain this unexpected result we discovered that COSMIC genes with recessive disease phenotypes were enriched for DNA repair and cell cycle control. The non-mutated genes in these pathways are orthologous to those underlying stress-induced mutation in bacteria, which results in the clustering of single nucleotide variations. COSMIC genes were less common in regions where the probability of observing mutational clusters is high, although they are approximately 2-fold more likely to harbor mutational clusters compared to other human genes. Our results suggest this ancient mutational response to

  9. A Synthetic Interaction Screen Identifies Factors Selectively Required for Proliferation and TERT Transcription in p53-Deficient Human Cancer Cells

    PubMed Central

    Park, Sung Mi; Zhu, Lihua J.; Debily, Marie-anne; Kittler, Ellen L. W.; Zapp, Maria L.; Lapointe, David; Gobeil, Stephane; Virbasius, Ching-Man; Green, Michael R.

    2012-01-01

    Numerous genetic and epigenetic alterations render cancer cells selectively dependent on specific genes and regulatory pathways, and represent potential vulnerabilities that can be therapeutically exploited. Here we describe an RNA interference (RNAi)–based synthetic interaction screen to identify genes preferentially required for proliferation of p53-deficient (p53−) human cancer cells. We find that compared to p53-competent (p53+) human cancer cell lines, diverse p53− human cancer cell lines are preferentially sensitive to loss of the transcription factor ETV1 and the DNA damage kinase ATR. In p53− cells, RNAi–mediated knockdown of ETV1 or ATR results in decreased expression of the telomerase catalytic subunit TERT leading to growth arrest, which can be reversed by ectopic TERT expression. Chromatin immunoprecipitation analysis reveals that ETV1 binds to a region downstream of the TERT transcriptional start-site in p53− but not p53+ cells. We find that the role of ATR is to phosphorylate and thereby stabilize ETV1. Our collective results identify a regulatory pathway involving ETV1, ATR, and TERT that is preferentially important for proliferation of diverse p53− cancer cells. PMID:23284306

  10. EGFR Gene Amplification and KRAS Mutation Predict Response to Combination Targeted Therapy in Metastatic Colorectal Cancer.

    PubMed

    Khan, Sajid A; Zeng, Zhaoshi; Shia, Jinru; Paty, Philip B

    2017-07-01

    Genetic variability in KRAS and EGFR predicts response to cetuximab in irinotecan refractory colorectal cancer. Whether these markers or others remain predictive in combination biologic therapies including bevacizumab is unknown. We identified predictive biomarkers from patients with irinotecan refractory metastatic colorectal cancer treated with cetuximab plus bevacizumab. Patients who received cetuximab plus bevacizumab for irinotecan refractory colorectal cancer in either of two Phase II trials conducted were identified. Tumor tissue was available for 33 patients. Genomic DNA was extracted and used for mutational analysis of KRAS, BRAF, and p53 genes. Fluorescence in situ hybridization was performed to assess EGFR copy number. The status of single genes and various combinations were tested for association with response. Seven of 33 patients responded to treatment. KRAS mutations were found in 14/33 cases, and 0 responded to treatment (p = 0.01). EGFR gene amplification was seen in 3/33 of tumors and in every case was associated with response to treatment (p < 0.001). TP53 and BRAF mutations were found in 18/33 and 0/33 tumors, respectively, and there were no associations with response to either gene. EGFR gene amplification and KRAS mutations are predictive markers for patients receiving combination biologic therapy of cetuximab plus bevacizumab for metastatic colorectal cancer. One marker or the other is present in the tumor of half of all patients allowing treatment response to be predicted with a high degree of certainty. The role for molecular markers in combination biologic therapy seems promising.

  11. Weak sharing of genetic association signals in three lung cancer subtypes: evidence at the SNP, gene, regulation, and pathway levels.

    PubMed

    O'Brien, Timothy D; Jia, Peilin; Caporaso, Neil E; Landi, Maria Teresa; Zhao, Zhongming

    2018-02-27

    There are two main types of lung cancer: small cell lung cancer (SCLC) and non-small cell lung cancer (NSCLC). NSCLC has many subtypes, but the two most common are lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC). These subtypes are mainly classified by physiological and pathological characteristics, although there is increasing evidence of genetic and molecular differences as well. Although some work has been done at the somatic level to explore the genetic and biological differences among subtypes, little work has been done that interrogates these differences at the germline level to characterize the unique and shared susceptibility genes for each subtype. We used single-nucleotide polymorphisms (SNPs) from a genome-wide association study (GWAS) of European samples to interrogate the similarity of the subtypes at the SNP, gene, pathway, and regulatory levels. We expanded these genotyped SNPs to include all SNPs in linkage disequilibrium (LD) using data from the 1000 Genomes Project. We mapped these SNPs to several lung tissue expression quantitative trait loci (eQTL) and enhancer datasets to identify regulatory SNPs and their target genes. We used these genes to perform a biological pathway analysis for each subtype. We identified 8295, 8734, and 8361 SNPs with moderate association signals for LUAD, LUSC, and SCLC, respectively. Those SNPs had p < 1 × 10 - 3 in the original GWAS or were within LD (r 2 > 0.8, Europeans) to the genotyped SNPs. We identified 215, 320, and 172 disease-associated genes for LUAD, LUSC, and SCLC, respectively. Only five genes (CHRNA5, IDH3A, PSMA4, RP11-650 L12.2, and TBC1D2B) overlapped all subtypes. Furthermore, we observed only two pathways from the Kyoto Encyclopedia of Genes and Genomes shared by all subtypes. At the regulatory level, only three eQTL target genes and two enhancer target genes overlapped between all subtypes. Our results suggest that the three lung cancer subtypes do not share much genetic signal

  12. A systematic study on drug-response associated genes using baseline gene expressions of the Cancer Cell Line Encyclopedia

    NASA Astrophysics Data System (ADS)

    Liu, Xiaoming; Yang, Jiasheng; Zhang, Yi; Fang, Yun; Wang, Fayou; Wang, Jun; Zheng, Xiaoqi; Yang, Jialiang

    2016-03-01

    We have studied drug-response associated (DRA) gene expressions by applying a systems biology framework to the Cancer Cell Line Encyclopedia data. More than 4,000 genes are inferred to be DRA for at least one drug, while the number of DRA genes for each drug varies dramatically from almost 0 to 1,226. Functional enrichment analysis shows that the DRA genes are significantly enriched in genes associated with cell cycle and plasma membrane. Moreover, there might be two patterns of DRA genes between genders. There are significantly shared DRA genes between male and female for most drugs, while very little DRA genes tend to be shared between the two genders for a few drugs targeting sex-specific cancers (e.g., PD-0332991 for breast cancer and ovarian cancer). Our analyses also show substantial difference for DRA genes between young and old samples, suggesting the necessity of considering the age effects for personalized medicine in cancers. Lastly, differential module and key driver analyses confirm cell cycle related modules as top differential ones for drug sensitivity. The analyses also reveal the role of TSPO, TP53, and many other immune or cell cycle related genes as important key drivers for DRA network modules. These key drivers provide new drug targets to improve the sensitivity of cancer therapy.

  13. Gene Expression Profiling of Evening Fatigue in Women Undergoing Chemotherapy for Breast Cancer

    PubMed Central

    Kober, Kord M.; Dunn, Laura; Mastick, Judy; Cooper, Bruce; Langford, Dale; Melisko, Michelle; Venook, Alan; Chen, Lee-May; Wright, Fay; Hammer, Marilyn J.; Schmidt, Brian L.; Levine, Jon; Miaskowski, Christine; Aouizerat, Bradley E.

    2017-01-01

    Moderate to severe fatigue occurs in 14% to 96% of oncology patients undergoing active treatment. Current interventions for fatigue are not efficacious. A major impediment to the development of effective treatments is a lack of understanding of the fundamental mechanisms underlying fatigue. In the current study, differences in phenotypic characteristics and gene expression profiles were evaluated in a sample of breast cancer patients undergoing chemotherapy (CTX) who reported low (n=19) and high (n=25) levels of evening fatigue. Compared to the low group, patients in the high evening fatigue group reported lower functional status scores, higher comorbidity scores, and fewer prior cancer treatments. One gene was identified as up-regulated and eleven genes were identified to be down-regulated in the high evening fatigue group. Gene set analysis found 24 down-regulated and 94 simultaneously up and down perturbed pathways between the two fatigue groups. Transcript Origin Analysis found that differential expression originated primarily from monocytes and dendritic cell types. Query of public data sources found 18 gene expression experiments with similar differential expression profiles. Our analyses revealed that inflammation, neurotransmitter regulation, and energy metabolism are likely mechanisms associated with evening fatigue severity; that CTX may contribute to fatigue seen in oncology patients; and that the patterns of gene expression may be shared with other models of fatigue (e.g., physical exercise, pathogen-induced sickness behavior). These results suggest that the mechanisms that underlie fatigue in oncology patients are multi-factorial. PMID:26957308

  14. Transcriptome-Wide Analysis of UTRs in Non-Small Cell Lung Cancer Reveals Cancer-Related Genes with SNV-Induced Changes on RNA Secondary Structure and miRNA Target Sites

    PubMed Central

    Novotny, Peter; Tang, Xiaojia; Kalari, Krishna R.; Gorodkin, Jan

    2014-01-01

    Traditional mutation assessment methods generally focus on predicting disruptive changes in protein-coding regions rather than non-coding regulatory regions like untranslated regions (UTRs) of mRNAs. The UTRs, however, are known to have many sequence and structural motifs that can regulate translational and transcriptional efficiency and stability of mRNAs through interaction with RNA-binding proteins and other non-coding RNAs like microRNAs (miRNAs). In a recent study, transcriptomes of tumor cells harboring mutant and wild-type KRAS (V-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog) genes in patients with non-small cell lung cancer (NSCLC) have been sequenced to identify single nucleotide variations (SNVs). About 40% of the total SNVs (73,717) identified were mapped to UTRs, but omitted in the previous analysis. To meet this obvious demand for analysis of the UTRs, we designed a comprehensive pipeline to predict the effect of SNVs on two major regulatory elements, secondary structure and miRNA target sites. Out of 29,290 SNVs in 6462 genes, we predict 472 SNVs (in 408 genes) affecting local RNA secondary structure, 490 SNVs (in 447 genes) affecting miRNA target sites and 48 that do both. Together these disruptive SNVs were present in 803 different genes, out of which 188 (23.4%) were previously known to be cancer-associated. Notably, this ratio is significantly higher (one-sided Fisher's exact test p-value = 0.032) than the ratio (20.8%) of known cancer-associated genes (n = 1347) in our initial data set (n = 6462). Network analysis shows that the genes harboring disruptive SNVs were involved in molecular mechanisms of cancer, and the signaling pathways of LPS-stimulated MAPK, IL-6, iNOS, EIF2 and mTOR. In conclusion, we have found hundreds of SNVs which are highly disruptive with respect to changes in the secondary structure and miRNA target sites within UTRs. These changes hold the potential to alter the expression of known cancer genes or genes

  15. Transcriptome-wide analysis of UTRs in non-small cell lung cancer reveals cancer-related genes with SNV-induced changes on RNA secondary structure and miRNA target sites.

    PubMed

    Sabarinathan, Radhakrishnan; Wenzel, Anne; Novotny, Peter; Tang, Xiaojia; Kalari, Krishna R; Gorodkin, Jan

    2014-01-01

    Traditional mutation assessment methods generally focus on predicting disruptive changes in protein-coding regions rather than non-coding regulatory regions like untranslated regions (UTRs) of mRNAs. The UTRs, however, are known to have many sequence and structural motifs that can regulate translational and transcriptional efficiency and stability of mRNAs through interaction with RNA-binding proteins and other non-coding RNAs like microRNAs (miRNAs). In a recent study, transcriptomes of tumor cells harboring mutant and wild-type KRAS (V-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog) genes in patients with non-small cell lung cancer (NSCLC) have been sequenced to identify single nucleotide variations (SNVs). About 40% of the total SNVs (73,717) identified were mapped to UTRs, but omitted in the previous analysis. To meet this obvious demand for analysis of the UTRs, we designed a comprehensive pipeline to predict the effect of SNVs on two major regulatory elements, secondary structure and miRNA target sites. Out of 29,290 SNVs in 6462 genes, we predict 472 SNVs (in 408 genes) affecting local RNA secondary structure, 490 SNVs (in 447 genes) affecting miRNA target sites and 48 that do both. Together these disruptive SNVs were present in 803 different genes, out of which 188 (23.4%) were previously known to be cancer-associated. Notably, this ratio is significantly higher (one-sided Fisher's exact test p-value = 0.032) than the ratio (20.8%) of known cancer-associated genes (n = 1347) in our initial data set (n = 6462). Network analysis shows that the genes harboring disruptive SNVs were involved in molecular mechanisms of cancer, and the signaling pathways of LPS-stimulated MAPK, IL-6, iNOS, EIF2 and mTOR. In conclusion, we have found hundreds of SNVs which are highly disruptive with respect to changes in the secondary structure and miRNA target sites within UTRs. These changes hold the potential to alter the expression of known cancer genes or genes

  16. TARGET Researchers Identify Mutations in SIX1/2 and microRNA Processing Genes in Favorable Histology Wilms Tumor | Office of Cancer Genomics

    Cancer.gov

    TARGET researchers molecularly characterized favorable histology Wilms tumor (FHWT), a pediatric renal cancer. Comprehensive genome and transcript analyses revealed single-nucleotide substitution/deletion mutations in microRNA processing genes (15% of FHWT patients) and Sine Oculis Homeobox Homolog 1/2 (SIX1/2) genes (7% of FHWT patients). SIX1/2 genes play a critical role in renal development and were not previously associated with FHWT, thus presenting a novel role for SIX1/2 pathway aberrations in this disease.

  17. Dosage analysis of cancer predisposition genes by multiplex ligation-dependent probe amplification

    PubMed Central

    Bunyan, D J; Eccles, D M; Sillibourne, J; Wilkins, E; Thomas, N Simon; Shea-Simonds, J; Duncan, P J; Curtis, C E; Robinson, D O; Harvey, J F; Cross, N C P

    2004-01-01

    Multiplex ligation-dependent probe amplification (MLPA) is a recently described method for detecting gross deletions or duplications of DNA sequences, aberrations which are commonly overlooked by standard diagnostic analysis. To determine the incidence of copy number variants in cancer predisposition genes from families in the Wessex region, we have analysed the hMLH1 and hMSH2 genes in patients with hereditary nonpolyposis colorectal cancer (HNPCC), BRCA1 and BRCA2 in families with hereditary breast/ovarian cancer (BRCA) and APC in patients with familial adenomatous polyposis coli (FAP). Hereditary nonpolyposis colorectal cancer (n=162) and FAP (n=74) probands were fully screened for small mutations, and cases for which no causative abnormality were found (HNPCC, n=122; FAP, n=24) were screened by MLPA. Complete or partial gene deletions were identified in seven cases for hMSH2 (5.7% of mutation-negative HNPCC; 4.3% of all HNPCC), no cases for hMLH1 and six cases for APC (25% of mutation negative FAP; 8% of all FAP). For BRCA1 and BRCA2, a partial mutation screen was performed and 136 mutation-negative cases were selected for MLPA. Five deletions and one duplication were found for BRCA1 (4.4% of mutation-negative BRCA cases) and one deletion for BRCA2 (0.7% of mutation-negative BRCA cases). Cost analysis indicates it is marginally more cost effective to perform MLPA prior to point mutation screening, but the main advantage gained by prescreening is a greatly reduced reporting time for the patients who are positive. These data demonstrate that dosage analysis is an essential component of genetic screening for cancer predisposition genes. PMID:15475941

  18. Multi-walled carbon nanotube-induced gene signatures in the mouse lung: potential predictive value for human lung cancer risk and prognosis

    PubMed Central

    Guo, Nancy L; Wan, Ying-Wooi; Denvir, James; Porter, Dale W; Pacurari, Maricica; Wolfarth, Michael G; Castranova, Vincent; Qian, Yong

    2012-01-01

    Concerns over the potential for multi-walled carbon nanotubes (MWCNT) to induce lung carcinogenesis have emerged. This study sought to (1) identify gene expression signatures in the mouse lungs following pharyngeal aspiration of well-dispersed MWCNT and (2) determine if these genes were associated with human lung cancer risk and progression. Genome-wide mRNA expression profiles were analyzed in mouse lungs (n=160) exposed to 0, 10, 20, 40, or 80 µg of MWCNT by pharyngeal aspiration at 1, 7, 28, and 56 days post-exposure. By using pairwise-Statistical Analysis of Microarray (SAM) and linear modeling, 24 genes were selected, which have significant changes in at least two time points, have a more than 1.5 fold change at all doses, and are significant in the linear model for the dose or the interaction of time and dose. Additionally, a 38-gene set was identified as related to cancer from 330 genes differentially expressed at day 56 post-exposure in functional pathway analysis. Using the expression profiles of the cancer-related gene set in 8 mice at day 56 post-exposure to 10 µg of MWCNT, a nearest centroid classification accurately predicts human lung cancer survival with a significant hazard ratio in training set (n=256) and test set (n=186). Furthermore, both gene signatures were associated with human lung cancer risk (n=164) with significant odds ratios. These results may lead to development of a surveillance approach for early detection of lung cancer and prognosis associated with MWCNT in the workplace. PMID:22891886

  19. Breast cancer risk-associated SNPs modulate the affinity of chromatin for FOXA1 and alter gene expression

    PubMed Central

    Cowper-Sal·lari, Richard; Zhang, Xiaoyang; Wright, Jason B.; Bailey, Swneke D.; Cole, Michael D.; Eeckhoute, Jerome; Moore, Jason H.; Lupien, Mathieu

    2012-01-01

    Genome-wide association studies (GWASs) have identified thousands of single nucleotide polymorphisms (SNPs) associated with human traits and diseases. But because the vast majority of these SNPs are located in the noncoding regions of the genome their risk promoting mechanisms are elusive. Employing a new methodology combining cistromics, epigenomics and genotype imputation we annotate the noncoding regions of the genome in breast cancer cells and systematically identify the functional nature of SNPs associated with breast cancer risk. Our results demonstrate that breast cancer risk-associated SNPs are enriched in the cistromes of FOXA1 and ESR1 and the epigenome of H3K4me1 in a cancer and cell-type-specific manner. Furthermore, the majority of these risk-associated SNPs modulate the affinity of chromatin for FOXA1 at distal regulatory elements, which results in allele-specific gene expression, exemplified by the effect of the rs4784227 SNP on the TOX3 gene found within the 16q12.1 risk locus. PMID:23001124

  20. Breast cancer and gene testing: risk, rationale, and responsibilities of primary care providers.

    PubMed

    Wilcox-Honnold, P M

    1998-01-01

    Family history is one of the known risk factors for breast cancer. Breast cancer susceptibility genes, BRCA-1 and BRCA-2, have been identified as accountable for less than 10% of all cases of breast cancer. Certain populations however, including native Icelanders and Ashkenazi Jews have a higher incidence of BRCA mutations than the general population. Genetic testing for these mutations is now available. Many ethical issues remain regarding who should be tested and what interventions should be carried out with positive test results. This article describes the patient assessment and counseling process for breast cancer testing to improve the knowledge base and confidence of the primary care provider.