Clinical Value of Prognosis Gene Expression Signatures in Colorectal Cancer: A Systematic Review

PubMed Central

Cordero, David; Riccadonna, Samantha; Solé, Xavier; Crous-Bou, Marta; Guinó, Elisabet; Sanjuan, Xavier; Biondo, Sebastiano; Soriano, Antonio; Jurman, Giuseppe; Capella, Gabriel; Furlanello, Cesare; Moreno, Victor

2012-01-01

Introduction The traditional staging system is inadequate to identify those patients with stage II colorectal cancer (CRC) at high risk of recurrence or with stage III CRC at low risk. A number of gene expression signatures to predict CRC prognosis have been proposed, but none is routinely used in the clinic. The aim of this work was to assess the prediction ability and potential clinical usefulness of these signatures in a series of independent datasets. Methods A literature review identified 31 gene expression signatures that used gene expression data to predict prognosis in CRC tissue. The search was based on the PubMed database and was restricted to papers published from January 2004 to December 2011. Eleven CRC gene expression datasets with outcome information were identified and downloaded from public repositories. Random Forest classifier was used to build predictors from the gene lists. Matthews correlation coefficient was chosen as a measure of classification accuracy and its associated p-value was used to assess association with prognosis. For clinical usefulness evaluation, positive and negative post-tests probabilities were computed in stage II and III samples. Results Five gene signatures showed significant association with prognosis and provided reasonable prediction accuracy in their own training datasets. Nevertheless, all signatures showed low reproducibility in independent data. Stratified analyses by stage or microsatellite instability status showed significant association but limited discrimination ability, especially in stage II tumors. From a clinical perspective, the most predictive signatures showed a minor but significant improvement over the classical staging system. Conclusions The published signatures show low prediction accuracy but moderate clinical usefulness. Although gene expression data may inform prognosis, better strategies for signature validation are needed to encourage their widespread use in the clinic. PMID:23145004

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

Inflammatory macrophage-associated 3-gene signature predicts subclinical allograft injury and graft survival.

PubMed

Azad, Tej D; Donato, Michele; Heylen, Line; Liu, Andrew B; Shen-Orr, Shai S; Sweeney, Timothy E; Maltzman, Jonathan Scott; Naesens, Maarten; Khatri, Purvesh

2018-01-25

Late allograft failure is characterized by cumulative subclinical insults manifesting over many years. Although immunomodulatory therapies targeting host T cells have improved short-term survival rates, rates of chronic allograft loss remain high. We hypothesized that other immune cell types may drive subclinical injury, ultimately leading to graft failure. We collected whole-genome transcriptome profiles from 15 independent cohorts composed of 1,697 biopsy samples to assess the association of an inflammatory macrophage polarization-specific gene signature with subclinical injury. We applied penalized regression to a subset of the data sets and identified a 3-gene inflammatory macrophage-derived signature. We validated discriminatory power of the 3-gene signature in 3 independent renal transplant data sets with mean AUC of 0.91. In a longitudinal cohort, the 3-gene signature strongly correlated with extent of injury and accurately predicted progression of subclinical injury 18 months before clinical manifestation. The 3-gene signature also stratified patients at high risk of graft failure as soon as 15 days after biopsy. We found that the 3-gene signature also distinguished acute rejection (AR) accurately in 3 heart transplant data sets but not in lung transplant. Overall, we identified a parsimonious signature capable of diagnosing AR, recognizing subclinical injury, and risk-stratifying renal transplant patients. Our results strongly suggest that inflammatory macrophages may be a viable therapeutic target to improve long-term outcomes for organ transplantation patients.

Identification of Single- and Multiple-Class Specific Signature Genes from Gene Expression Profiles by Group Marker Index

PubMed Central

Tsai, Yu-Shuen; Aguan, Kripamoy; Pal, Nikhil R.; Chung, I-Fang

2011-01-01

Informative genes from microarray data can be used to construct prediction model and investigate biological mechanisms. Differentially expressed genes, the main targets of most gene selection methods, can be classified as single- and multiple-class specific signature genes. Here, we present a novel gene selection algorithm based on a Group Marker Index (GMI), which is intuitive, of low-computational complexity, and efficient in identification of both types of genes. Most gene selection methods identify only single-class specific signature genes and cannot identify multiple-class specific signature genes easily. Our algorithm can detect de novo certain conditions of multiple-class specificity of a gene and makes use of a novel non-parametric indicator to assess the discrimination ability between classes. Our method is effective even when the sample size is small as well as when the class sizes are significantly different. To compare the effectiveness and robustness we formulate an intuitive template-based method and use four well-known datasets. We demonstrate that our algorithm outperforms the template-based method in difficult cases with unbalanced distribution. Moreover, the multiple-class specific genes are good biomarkers and play important roles in biological pathways. Our literature survey supports that the proposed method identifies unique multiple-class specific marker genes (not reported earlier to be related to cancer) in the Central Nervous System data. It also discovers unique biomarkers indicating the intrinsic difference between subtypes of lung cancer. We also associate the pathway information with the multiple-class specific signature genes and cross-reference to published studies. We find that the identified genes participate in the pathways directly involved in cancer development in leukemia data. Our method gives a promising way to find genes that can involve in pathways of multiple diseases and hence opens up the possibility of using an existing

Hormone-induced protection against mammary tumorigenesis is conserved in multiple rat strains and identifies a core gene expression signature induced by pregnancy.

PubMed

Blakely, Collin M; Stoddard, Alexander J; Belka, George K; Dugan, Katherine D; Notarfrancesco, Kathleen L; Moody, Susan E; D'Cruz, Celina M; Chodosh, Lewis A

2006-06-15

Women who have their first child early in life have a substantially lower lifetime risk of breast cancer. The mechanism for this is unknown. Similar to humans, rats exhibit parity-induced protection against mammary tumorigenesis. To explore the basis for this phenomenon, we identified persistent pregnancy-induced changes in mammary gene expression that are tightly associated with protection against tumorigenesis in multiple inbred rat strains. Four inbred rat strains that exhibit marked differences in their intrinsic susceptibilities to carcinogen-induced mammary tumorigenesis were each shown to display significant protection against methylnitrosourea-induced mammary tumorigenesis following treatment with pregnancy levels of estradiol and progesterone. Microarray expression profiling of parous and nulliparous mammary tissue from these four strains yielded a common 70-gene signature. Examination of the genes constituting this signature implicated alterations in transforming growth factor-beta signaling, the extracellular matrix, amphiregulin expression, and the growth hormone/insulin-like growth factor I axis in pregnancy-induced alterations in breast cancer risk. Notably, related molecular changes have been associated with decreased mammographic density, which itself is strongly associated with decreased breast cancer risk. Our findings show that hormone-induced protection against mammary tumorigenesis is widely conserved among divergent rat strains and define a gene expression signature that is tightly correlated with reduced mammary tumor susceptibility as a consequence of a normal developmental event. Given the conservation of this signature, these pathways may contribute to pregnancy-induced protection against breast cancer.

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.

Identifying a gene expression signature of cluster headache in blood

PubMed Central

Eising, Else; Pelzer, Nadine; Vijfhuizen, Lisanne S.; Vries, Boukje de; Ferrari, Michel D.; ‘t Hoen, Peter A. C.; Terwindt, Gisela M.; van den Maagdenberg, Arn M. J. M.

2017-01-01

Cluster headache is a relatively rare headache disorder, typically characterized by multiple daily, short-lasting attacks of excruciating, unilateral (peri-)orbital or temporal pain associated with autonomic symptoms and restlessness. To better understand the pathophysiology of cluster headache, we used RNA sequencing to identify differentially expressed genes and pathways in whole blood of patients with episodic (n = 19) or chronic (n = 20) cluster headache in comparison with headache-free controls (n = 20). Gene expression data were analysed by gene and by module of co-expressed genes with particular attention to previously implicated disease pathways including hypocretin dysregulation. Only moderate gene expression differences were identified and no associations were found with previously reported pathogenic mechanisms. At the level of functional gene sets, associations were observed for genes involved in several brain-related mechanisms such as GABA receptor function and voltage-gated channels. In addition, genes and modules of co-expressed genes showed a role for intracellular signalling cascades, mitochondria and inflammation. Although larger study samples may be required to identify the full range of involved pathways, these results indicate a role for mitochondria, intracellular signalling and inflammation in cluster headache. PMID:28074859

A Prognostic Gene Signature for Metastasis-Free Survival of Triple Negative Breast Cancer Patients

PubMed Central

Yun, Jieun; Bevilacqua, Elena; Caldas, Carlos; Chin, Suet-Feung; Rueda, Oscar M.; Reinitz, John; Rosner, Marsha Rich

2013-01-01

Although triple negative breast cancers (TNBC) are the most aggressive subtype of breast cancer, they currently lack targeted therapies. Because this classification still includes a heterogeneous collection of tumors, new tools to classify TNBCs are urgently required in order to improve our prognostic capability for high risk patients and predict response to therapy. We previously defined a gene expression signature, RKIP Pathway Metastasis Signature (RPMS), based upon a metastasis-suppressive signaling pathway initiated by Raf Kinase Inhibitory Protein (RKIP). We have now generated a new BACH1 Pathway Metastasis gene signature (BPMS) that utilizes targets of the metastasis regulator BACH1. Specifically, we substituted experimentally validated target genes to generate a new BACH1 metagene, developed an approach to optimize patient tumor stratification, and reduced the number of signature genes to 30. The BPMS significantly and selectively stratified metastasis-free survival in basal-like and, in particular, TNBC patients. In addition, the BPMS further stratified patients identified as having a good or poor prognosis by other signatures including the Mammaprint® and Oncotype® clinical tests. The BPMS is thus complementary to existing signatures and is a prognostic tool for high risk ER-HER2- patients. We also demonstrate the potential clinical applicability of the BPMS as a single sample predictor. Together, these results reveal the potential of this pathway-based BPMS gene signature to identify high risk TNBC patients that can respond effectively to targeted therapy, and highlight BPMS genes as novel drug targets for therapeutic development. PMID:24349199

A prognostic gene signature for metastasis-free survival of triple negative breast cancer patients.

PubMed

Lee, Unjin; Frankenberger, Casey; Yun, Jieun; Bevilacqua, Elena; Caldas, Carlos; Chin, Suet-Feung; Rueda, Oscar M; Reinitz, John; Rosner, Marsha Rich

2013-01-01

Although triple negative breast cancers (TNBC) are the most aggressive subtype of breast cancer, they currently lack targeted therapies. Because this classification still includes a heterogeneous collection of tumors, new tools to classify TNBCs are urgently required in order to improve our prognostic capability for high risk patients and predict response to therapy. We previously defined a gene expression signature, RKIP Pathway Metastasis Signature (RPMS), based upon a metastasis-suppressive signaling pathway initiated by Raf Kinase Inhibitory Protein (RKIP). We have now generated a new BACH1 Pathway Metastasis gene signature (BPMS) that utilizes targets of the metastasis regulator BACH1. Specifically, we substituted experimentally validated target genes to generate a new BACH1 metagene, developed an approach to optimize patient tumor stratification, and reduced the number of signature genes to 30. The BPMS significantly and selectively stratified metastasis-free survival in basal-like and, in particular, TNBC patients. In addition, the BPMS further stratified patients identified as having a good or poor prognosis by other signatures including the Mammaprint® and Oncotype® clinical tests. The BPMS is thus complementary to existing signatures and is a prognostic tool for high risk ER-HER2- patients. We also demonstrate the potential clinical applicability of the BPMS as a single sample predictor. Together, these results reveal the potential of this pathway-based BPMS gene signature to identify high risk TNBC patients that can respond effectively to targeted therapy, and highlight BPMS genes as novel drug targets for therapeutic development.

Use of DNA Microarrays to Identify Diagnostic Signature Transcription Profiles for Host Responses to Infectious Agents

DTIC Science & Technology

2004-10-01

informative in this regard. Key signature genes will serve as the basis for rapid diagnostic approaches that could be accessed when an outbreak is suspected...AD Award Number: DAMD17-01-1-0787 TITLE: Use of DNA Microarrays to Identify Diagnostic Signature Transcription Profiles for Host Responses to...Sep 2004) 4. TITLE AND SUBTITLE 5. FUNDING NUMBERS Use of DNA Microarrays to Identify Diagnostic Signature DAMD17-01-1-0787 Transcription Profiles for

Gene expression signature in urine for diagnosing and assessing aggressiveness of bladder urothelial carcinoma.

PubMed

Mengual, Lourdes; Burset, Moisès; Ribal, María José; Ars, Elisabet; Marín-Aguilera, Mercedes; Fernández, Manuel; Ingelmo-Torres, Mercedes; Villavicencio, Humberto; Alcaraz, Antonio

2010-05-01

To develop an accurate and noninvasive method for bladder cancer diagnosis and prediction of disease aggressiveness based on the gene expression patterns of urine samples. Gene expression patterns of 341 urine samples from bladder urothelial cell carcinoma (UCC) patients and 235 controls were analyzed via TaqMan Arrays. In a first phase of the study, three consecutive gene selection steps were done to identify a gene set expression signature to detect and stratify UCC in urine. Subsequently, those genes more informative for UCC diagnosis and prediction of tumor aggressiveness were combined to obtain a classification system of bladder cancer samples. In a second phase, the obtained gene set signature was evaluated in a routine clinical scenario analyzing only voided urine samples. We have identified a 12+2 gene expression signature for UCC diagnosis and prediction of tumor aggressiveness on urine samples. Overall, this gene set panel had 98% sensitivity (SN) and 99% specificity (SP) in discriminating between UCC and control samples and 79% SN and 92% SP in predicting tumor aggressiveness. The translation of the model to the clinically applicable format corroborates that the 12+2 gene set panel described maintains a high accuracy for UCC diagnosis (SN = 89% and SP = 95%) and tumor aggressiveness prediction (SN = 79% and SP = 91%) in voided urine samples. The 12+2 gene expression signature described in urine is able to identify patients suffering from UCC and predict tumor aggressiveness. We show that a panel of molecular markers may improve the schedule for diagnosis and follow-up in UCC patients. Copyright 2010 AACR.

Exome sequencing of hepatocellular carcinomas identifies new mutational signatures and potential therapeutic targets

DOE PAGES

Schulze, Kornelius; Imbeaud, Sandrine; Letouzé, Eric; ...

2015-03-30

Our genomic analyses promise to improve tumor characterization to optimize personalized treatment for patients with hepatocellular carcinoma (HCC). Exome sequencing analysis of 243 liver tumors identified mutational signatures associated with specific risk factors, mainly combined alcohol and tobacco consumption and exposure to aflatoxin B1. We identified 161 putative driver genes associated with 11 recurrently altered pathways. Associations of mutations defined 3 groups of genes related to risk factors and centered on CTNNB1 (alcohol), TP53 (hepatitis B virus, HBV) and AXIN1. These analyses according to tumor stage progression identified TERT promoter mutation as an early event, whereasFGF3, FGF4, FGF19 or CCND1more » amplification and TP53 and CDKN2A alterations appeared at more advanced stages in aggressive tumors. In 28% of the tumors, we identified genetic alterations potentially targetable by US Food and Drug Administration (FDA)–approved drugs. Finally, we identified risk factor–specific mutational signatures and defined the extensive landscape of altered genes and pathways in HCC, which will be useful to design clinical trials for targeted therapy.« less

Exome sequencing of hepatocellular carcinomas identifies new mutational signatures and potential therapeutic targets

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

Schulze, Kornelius; Imbeaud, Sandrine; Letouzé, Eric

Our genomic analyses promise to improve tumor characterization to optimize personalized treatment for patients with hepatocellular carcinoma (HCC). Exome sequencing analysis of 243 liver tumors identified mutational signatures associated with specific risk factors, mainly combined alcohol and tobacco consumption and exposure to aflatoxin B1. We identified 161 putative driver genes associated with 11 recurrently altered pathways. Associations of mutations defined 3 groups of genes related to risk factors and centered on CTNNB1 (alcohol), TP53 (hepatitis B virus, HBV) and AXIN1. These analyses according to tumor stage progression identified TERT promoter mutation as an early event, whereasFGF3, FGF4, FGF19 or CCND1more » amplification and TP53 and CDKN2A alterations appeared at more advanced stages in aggressive tumors. In 28% of the tumors, we identified genetic alterations potentially targetable by US Food and Drug Administration (FDA)–approved drugs. Finally, we identified risk factor–specific mutational signatures and defined the extensive landscape of altered genes and pathways in HCC, which will be useful to design clinical trials for targeted therapy.« less

Selection signature analysis in Holstein cattle identified genes known to affect reproduction

USDA-ARS?s Scientific Manuscript database

Using direct comparison of 45,878 SNPs between a group of Holstein cattle unselected since 1964 and contemporary Holsteins that on average take 30 days longer for successful conception than the 1964 Holsteins, we conducted selection signature analyses to identify genomic regions associated with dair...

Joint-specific DNA methylation and transcriptome signatures in rheumatoid arthritis identify distinct pathogenic processes

PubMed Central

Ai, Rizi; Hammaker, Deepa; Boyle, David L.; Morgan, Rachel; Walsh, Alice M.; Fan, Shicai; Firestein, Gary S.; Wang, Wei

2016-01-01

Stratifying patients on the basis of molecular signatures could facilitate development of therapeutics that target pathways specific to a particular disease or tissue location. Previous studies suggest that pathogenesis of rheumatoid arthritis (RA) is similar in all affected joints. Here we show that distinct DNA methylation and transcriptome signatures not only discriminate RA fibroblast-like synoviocytes (FLS) from osteoarthritis FLS, but also distinguish RA FLS isolated from knees and hips. Using genome-wide methods, we show differences between RA knee and hip FLS in the methylation of genes encoding biological pathways, such as IL-6 signalling via JAK-STAT pathway. Furthermore, differentially expressed genes are identified between knee and hip FLS using RNA-sequencing. Double-evidenced genes that are both differentially methylated and expressed include multiple HOX genes. Joint-specific DNA signatures suggest that RA disease mechanisms might vary from joint to joint, thus potentially explaining some of the diversity of drug responses in RA patients. PMID:27282753

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

Background Several gene sets for prediction of breast cancer survival have been derived from whole-genome mRNA expression profiles. Here, we develop a statistical framework to explore whether combination of the information from such sets may improve prediction of recurrence and breast cancer specific death in early-stage breast cancers. Microarray data from two clinically similar cohorts of breast cancer patients are used as training (n = 123) and test set (n = 81), respectively. Gene sets from eleven previously published gene signatures are included in the study. Principal Findings To investigate the relationship between breast cancer survival and gene expression on a particular gene set, a Cox proportional hazards model is applied using partial likelihood regression with an L2 penalty to avoid overfitting and using cross-validation to determine the penalty weight. The fitted models are applied to an independent test set to obtain a predicted risk for each individual and each gene set. Hierarchical clustering of the test individuals on the basis of the vector of predicted risks results in two clusters with distinct clinical characteristics in terms of the distribution of molecular subtypes, ER, PR status, TP53 mutation status and histological grade category, and associated with significantly different survival probabilities (recurrence: p = 0.005; breast cancer death: p = 0.014). Finally, principal components analysis of the gene signatures is used to derive combined predictors used to fit a new Cox model. This model classifies test individuals into two risk groups with distinct survival characteristics (recurrence: p = 0.003; breast cancer death: p = 0.001). The latter classifier outperforms all the individual gene signatures, as well as Cox models based on traditional clinical parameters and the Adjuvant! Online for survival prediction. Conclusion Combining the predictive strength of multiple gene signatures improves prediction of breast

Analysis of Gene Expression Profiles of Multiple Skin Diseases Identifies a Conserved Signature of Disrupted Homeostasis.

PubMed

Mills, Kevin J; Robinson, Michael K; Sherrill, Joseph D; Schnell, Daniel J; Xu, Jun

2018-05-28

Triggers of skin disease pathogenesis vary, but events associated with the elicitation of a lesion share many features in common. Our objective was to examine gene expression patterns in skin disease to develop a molecular signature of disruption of cutaneous homeostasis. Gene expression data from common inflammatory skin diseases (e.g., psoriasis, atopic dermatitis, seborrheic dermatitis and acne), and a novel statistical algorithm were used to define a unifying molecular signature referred to as the "Unhealthy Skin Signature" (USS). Using a pattern matching algorithm, analysis of public data repositories revealed that the USS is found in diverse epithelial diseases. Studies of milder disruptions of epidermal homeostasis have also shown that these conditions converge, to varying degrees, on the USS and that the degree of convergence is related directly to the severity of homeostatic disruption. The USS contains genes that had no prior published association with skin, but that play important roles in many different disease processes, supporting the importance of the USS to homeostasis. Finally, we show through pattern matching that the USS can be used to discover new potential dermatologic therapeutics. The USS provides a new means to further interrogate epithelial homeostasis and potentially develop novel therapeutics with efficacy across a spectrum of skin conditions. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Compendium of Immune Signatures Identifies Conserved and Species-Specific Biology in Response to Inflammation.

PubMed

Godec, Jernej; Tan, Yan; Liberzon, Arthur; Tamayo, Pablo; Bhattacharya, Sanchita; Butte, Atul J; Mesirov, Jill P; Haining, W Nicholas

2016-01-19

Gene-expression profiling has become a mainstay in immunology, but subtle changes in gene networks related to biological processes are hard to discern when comparing various datasets. For instance, conservation of the transcriptional response to sepsis in mouse models and human disease remains controversial. To improve transcriptional analysis in immunology, we created ImmuneSigDB: a manually annotated compendium of ∼5,000 gene-sets from diverse cell states, experimental manipulations, and genetic perturbations in immunology. Analysis using ImmuneSigDB identified signatures induced in activated myeloid cells and differentiating lymphocytes that were highly conserved between humans and mice. Sepsis triggered conserved patterns of gene expression in humans and mouse models. However, we also identified species-specific biological processes in the sepsis transcriptional response: although both species upregulated phagocytosis-related genes, a mitosis signature was specific to humans. ImmuneSigDB enables granular analysis of transcriptomic data to improve biological understanding of immune processes of the human and mouse immune systems. Copyright © 2016 Elsevier Inc. All rights reserved.

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

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

Oxidative stress/reactive metabolite gene expression signature in rat liver detects idiosyncratic hepatotoxicants

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

Leone, Angelique; Nie, Alex; Brandon Parker, J.

Previously we reported a gene expression signature in rat liver for detecting a specific type of oxidative stress (OS) related to reactive metabolites (RM). High doses of the drugs disulfiram, ethinyl estradiol and nimesulide were used with another dozen paradigm OS/RM compounds, and three other drugs flutamide, phenacetin and sulindac were identified by this signature. In a second study, antiepileptic drugs were compared for covalent binding and their effects on OS/RM; felbamate, carbamazepine, and phenobarbital produced robust OS/RM gene expression. In the present study, liver RNA samples from drug-treated rats from more recent experiments were examined for statistical fit tomore » the OS/RM signature. Of all 97 drugs examined, in addition to the nine drugs noted above, 19 more were identified as OS/RM-producing compounds—chlorpromazine, clozapine, cyproterone acetate, dantrolene, dipyridamole, glibenclamide, isoniazid, ketoconazole, methapyrilene, naltrexone, nifedipine, sulfamethoxazole, tamoxifen, coumarin, ritonavir, amitriptyline, valproic acid, enalapril, and chloramphenicol. Importantly, all of the OS/RM drugs listed above have been linked to idiosyncratic hepatotoxicity, excepting chloramphenicol, which does not have a package label for hepatotoxicity, but does have a black box warning for idiosyncratic bone marrow suppression. Most of these drugs are not acutely toxic in the rat. The OS/RM signature should be useful to avoid idiosyncratic hepatotoxicity of drug candidates. - Highlights: • 28 of 97 drugs gave a positive OS/RM gene expression signature in rat liver. • The specificity of the signature for human idiosyncratic hepatotoxicants was 98%. • The sensitivity of the signature for human idiosyncratic hepatotoxicants was 75%. • The signature can help eliminate hepatotoxicants from drug development.« less

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.

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

Integration of ATAC-seq and RNA-seq identifies human alpha cell and beta cell signature genes.

PubMed

Ackermann, Amanda M; Wang, Zhiping; Schug, Jonathan; Naji, Ali; Kaestner, Klaus H

2016-03-01

human α- and β-cells based on chromatin accessibility and transcript levels, which allowed for detection of novel α- and β-cell signature genes not previously known to be expressed in islets. Using fine-mapping of open chromatin, we have identified thousands of potential cis-regulatory elements that operate in an endocrine cell type-specific fashion.

Experimentally-Derived Fibroblast Gene Signatures Identify Molecular Pathways Associated with Distinct Subsets of Systemic Sclerosis Patients in Three Independent Cohorts

PubMed Central

Johnson, Michael E.; Mahoney, J. Matthew; Taroni, Jaclyn; Sargent, Jennifer L.; Marmarelis, Eleni; Wu, Ming-Ru; Varga, John; Hinchcliff, Monique E.; Whitfield, Michael L.

2015-01-01

Genome-wide expression profiling in systemic sclerosis (SSc) has identified four ‘intrinsic’ subsets of disease (fibroproliferative, inflammatory, limited, and normal-like), each of which shows deregulation of distinct signaling pathways; however, the full set of pathways contributing to this differential gene expression has not been fully elucidated. Here we examine experimentally derived gene expression signatures in dermal fibroblasts for thirteen different signaling pathways implicated in SSc pathogenesis. These data show distinct and overlapping sets of genes induced by each pathway, allowing for a better understanding of the molecular relationship between profibrotic and immune signaling networks. Pathway-specific gene signatures were analyzed across a compendium of microarray datasets consisting of skin biopsies from three independent cohorts representing 80 SSc patients, 4 morphea, and 26 controls. IFNα signaling showed a strong association with early disease, while TGFβ signaling spanned the fibroproliferative and inflammatory subsets, was associated with worse MRSS, and was higher in lesional than non-lesional skin. The fibroproliferative subset was most strongly associated with PDGF signaling, while the inflammatory subset demonstrated strong activation of innate immune pathways including TLR signaling upstream of NF-κB. The limited and normal-like subsets did not show associations with fibrotic and inflammatory mediators such as TGFβ and TNFα. The normal-like subset showed high expression of genes associated with lipid signaling, which was absent in the inflammatory and limited subsets. Together, these data suggest a model by which IFNα is involved in early disease pathology, and disease severity is associated with active TGFβ signaling. PMID:25607805

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

Gene-Expression Signature Predicts Postoperative Recurrence in Stage I Non-Small Cell Lung Cancer Patients

PubMed Central

Lu, Yan; Wang, Liang; Liu, Pengyuan; Yang, Ping; You, Ming

2012-01-01

About 30% stage I non-small cell lung cancer (NSCLC) patients undergoing resection will recur. Robust prognostic markers are required to better manage therapy options. The purpose of this study is to develop and validate a novel gene-expression signature that can predict tumor recurrence of stage I NSCLC patients. Cox proportional hazards regression analysis was performed to identify recurrence-related genes and a partial Cox regression model was used to generate a gene signature of recurrence in the training dataset −142 stage I lung adenocarcinomas without adjunctive therapy from the Director's Challenge Consortium. Four independent validation datasets, including GSE5843, GSE8894, and two other datasets provided by Mayo Clinic and Washington University, were used to assess the prediction accuracy by calculating the correlation between risk score estimated from gene expression and real recurrence-free survival time and AUC of time-dependent ROC analysis. Pathway-based survival analyses were also performed. 104 probesets correlated with recurrence in the training dataset. They are enriched in cell adhesion, apoptosis and regulation of cell proliferation. A 51-gene expression signature was identified to distinguish patients likely to develop tumor recurrence (Dxy = −0.83, P<1e-16) and this signature was validated in four independent datasets with AUC >85%. Multiple pathways including leukocyte transendothelial migration and cell adhesion were highly correlated with recurrence-free survival. The gene signature is highly predictive of recurrence in stage I NSCLC patients, which has important prognostic and therapeutic implications for the future management of these patients. PMID:22292069

A signature inferred from Drosophila mitotic genes predicts survival of breast cancer patients.

PubMed

Damasco, Christian; Lembo, Antonio; Somma, Maria Patrizia; Gatti, Maurizio; Di Cunto, Ferdinando; Provero, Paolo

2011-02-28

The classification of breast cancer patients into risk groups provides a powerful tool for the identification of patients who will benefit from aggressive systemic therapy. The analysis of microarray data has generated several gene expression signatures that improve diagnosis and allow risk assessment. There is also evidence that cell proliferation-related genes have a high predictive power within these signatures. We thus constructed a gene expression signature (the DM signature) using the human orthologues of 108 Drosophila melanogaster genes required for either the maintenance of chromosome integrity (36 genes) or mitotic division (72 genes). The DM signature has minimal overlap with the extant signatures and is highly predictive of survival in 5 large breast cancer datasets. In addition, we show that the DM signature outperforms many widely used breast cancer signatures in predictive power, and performs comparably to other proliferation-based signatures. For most genes of the DM signature, an increased expression is negatively correlated with patient survival. The genes that provide the highest contribution to the predictive power of the DM signature are those involved in cytokinesis. This finding highlights cytokinesis as an important marker in breast cancer prognosis and as a possible target for antimitotic therapies.

Quantitative comparison of microarray experiments with published leukemia related gene expression signatures.

PubMed

Klein, Hans-Ulrich; Ruckert, Christian; Kohlmann, Alexander; Bullinger, Lars; Thiede, Christian; Haferlach, Torsten; Dugas, Martin

2009-12-15

Multiple gene expression signatures derived from microarray experiments have been published in the field of leukemia research. A comparison of these signatures with results from new experiments is useful for verification as well as for interpretation of the results obtained. Currently, the percentage of overlapping genes is frequently used to compare published gene signatures against a signature derived from a new experiment. However, it has been shown that the percentage of overlapping genes is of limited use for comparing two experiments due to the variability of gene signatures caused by different array platforms or assay-specific influencing parameters. Here, we present a robust approach for a systematic and quantitative comparison of published gene expression signatures with an exemplary query dataset. A database storing 138 leukemia-related published gene signatures was designed. Each gene signature was manually annotated with terms according to a leukemia-specific taxonomy. Two analysis steps are implemented to compare a new microarray dataset with the results from previous experiments stored and curated in the database. First, the global test method is applied to assess gene signatures and to constitute a ranking among them. In a subsequent analysis step, the focus is shifted from single gene signatures to chromosomal aberrations or molecular mutations as modeled in the taxonomy. Potentially interesting disease characteristics are detected based on the ranking of gene signatures associated with these aberrations stored in the database. Two example analyses are presented. An implementation of the approach is freely available as web-based application. The presented approach helps researchers to systematically integrate the knowledge derived from numerous microarray experiments into the analysis of a new dataset. By means of example leukemia datasets we demonstrate that this approach detects related experiments as well as related molecular mutations and may

Exploring signatures of positive selection in pigmentation candidate genes in populations of East Asian ancestry

PubMed Central

2013-01-01

Background Currently, there is very limited knowledge about the genes involved in normal pigmentation variation in East Asian populations. We carried out a genome-wide scan of signatures of positive selection using the 1000 Genomes Phase I dataset, in order to identify pigmentation genes showing putative signatures of selective sweeps in East Asia. We applied a broad range of methods to detect signatures of selection including: 1) Tests designed to identify deviations of the Site Frequency Spectrum (SFS) from neutral expectations (Tajima’s D, Fay and Wu’s H and Fu and Li’s D* and F*), 2) Tests focused on the identification of high-frequency haplotypes with extended linkage disequilibrium (iHS and Rsb) and 3) Tests based on genetic differentiation between populations (LSBL). Based on the results obtained from a genome wide analysis of 25 kb windows, we constructed an empirical distribution for each statistic across all windows, and identified pigmentation genes that are outliers in the distribution. Results Our tests identified twenty genes that are relevant for pigmentation biology. Of these, eight genes (ATRN, EDAR, KLHL7, MITF, OCA2, TH, TMEM33 and TRPM1,) were extreme outliers (top 0.1% of the empirical distribution) for at least one statistic, and twelve genes (ADAM17, BNC2, CTSD, DCT, EGFR, LYST, MC1R, MLPH, OPRM1, PDIA6, PMEL (SILV) and TYRP1) were in the top 1% of the empirical distribution for at least one statistic. Additionally, eight of these genes (BNC2, EGFR, LYST, MC1R, OCA2, OPRM1, PMEL (SILV) and TYRP1) have been associated with pigmentary traits in association studies. Conclusions We identified a number of putative pigmentation genes showing extremely unusual patterns of genetic variation in East Asia. Most of these genes are outliers for different tests and/or different populations, and have already been described in previous scans for positive selection, providing strong support to the hypothesis that recent selective sweeps left a

Exploring signatures of positive selection in pigmentation candidate genes in populations of East Asian ancestry.

PubMed

Hider, Jessica L; Gittelman, Rachel M; Shah, Tapan; Edwards, Melissa; Rosenbloom, Arnold; Akey, Joshua M; Parra, Esteban J

2013-07-12

Currently, there is very limited knowledge about the genes involved in normal pigmentation variation in East Asian populations. We carried out a genome-wide scan of signatures of positive selection using the 1000 Genomes Phase I dataset, in order to identify pigmentation genes showing putative signatures of selective sweeps in East Asia. We applied a broad range of methods to detect signatures of selection including: 1) Tests designed to identify deviations of the Site Frequency Spectrum (SFS) from neutral expectations (Tajima's D, Fay and Wu's H and Fu and Li's D* and F*), 2) Tests focused on the identification of high-frequency haplotypes with extended linkage disequilibrium (iHS and Rsb) and 3) Tests based on genetic differentiation between populations (LSBL). Based on the results obtained from a genome wide analysis of 25 kb windows, we constructed an empirical distribution for each statistic across all windows, and identified pigmentation genes that are outliers in the distribution. Our tests identified twenty genes that are relevant for pigmentation biology. Of these, eight genes (ATRN, EDAR, KLHL7, MITF, OCA2, TH, TMEM33 and TRPM1,) were extreme outliers (top 0.1% of the empirical distribution) for at least one statistic, and twelve genes (ADAM17, BNC2, CTSD, DCT, EGFR, LYST, MC1R, MLPH, OPRM1, PDIA6, PMEL (SILV) and TYRP1) were in the top 1% of the empirical distribution for at least one statistic. Additionally, eight of these genes (BNC2, EGFR, LYST, MC1R, OCA2, OPRM1, PMEL (SILV) and TYRP1) have been associated with pigmentary traits in association studies. We identified a number of putative pigmentation genes showing extremely unusual patterns of genetic variation in East Asia. Most of these genes are outliers for different tests and/or different populations, and have already been described in previous scans for positive selection, providing strong support to the hypothesis that recent selective sweeps left a signature in these regions. However, it will

FARO server: Meta-analysis of gene expression by matching gene expression signatures to a compendium of public gene expression data.

PubMed

Manijak, Mieszko P; Nielsen, Henrik B

2011-06-11

Although, systematic analysis of gene annotation is a powerful tool for interpreting gene expression data, it sometimes is blurred by incomplete gene annotation, missing expression response of key genes and secondary gene expression responses. These shortcomings may be partially circumvented by instead matching gene expression signatures to signatures of other experiments. To facilitate this we present the Functional Association Response by Overlap (FARO) server, that match input signatures to a compendium of 242 gene expression signatures, extracted from more than 1700 Arabidopsis microarray experiments. Hereby we present a publicly available tool for robust characterization of Arabidopsis gene expression experiments which can point to similar experimental factors in other experiments. The server is available at http://www.cbs.dtu.dk/services/faro/.

Gene signature associated with benign neurofibroma transformation to malignant peripheral nerve sheath tumors

PubMed Central

Sorzano, Carlos O. S.; Pascual-Montano, Alberto; Carazo, Jose M.

2017-01-01

Benign neurofibromas, the main phenotypic manifestations of the rare neurological disorder neurofibromatosis type 1, degenerate to malignant tumors associated to poor prognosis in about 10% of patients. Despite efforts in the field of (epi)genomics, the lack of prognostic biomarkers with which to predict disease evolution frustrates the adoption of appropriate early therapeutic measures. To identify potential biomarkers of malignant neurofibroma transformation, we integrated four human experimental studies and one for mouse, using a gene score-based meta-analysis method, from which we obtained a score-ranked signature of 579 genes. Genes with the highest absolute scores were classified as promising disease biomarkers. By grouping genes with similar neurofibromatosis-related profiles, we derived panels of potential biomarkers. The addition of promoter methylation data to gene profiles indicated a panel of genes probably silenced by hypermethylation. To identify possible therapeutic treatments, we used the gene signature to query drug expression databases. Trichostatin A and other histone deacetylase inhibitors, as well as cantharidin and tamoxifen, were retrieved as putative therapeutic means to reverse the aberrant regulation that drives to malignant cell proliferation and metastasis. This in silico prediction corroborated reported experimental results that suggested the inclusion of these compounds in clinical trials. This experimental validation supported the suitability of the meta-analysis method used to integrate several sources of public genomic information, and the reliability of the gene signature associated to the malignant evolution of neurofibromas to generate working hypotheses for prognostic and drug-responsive biomarkers or therapeutic measures, thus showing the potential of this in silico approach for biomarker discovery. PMID:28542306

A Host-Based RT-PCR Gene Expression Signature to Identify Acute Respiratory Viral Infection

PubMed Central

Zaas, Aimee K.; Burke, Thomas; Chen, Minhua; McClain, Micah; Nicholson, Bradly; Veldman, Timothy; Tsalik, Ephraim L.; Fowler, Vance; Rivers, Emanuel P.; Otero, Ronny; Kingsmore, Stephen F.; Voora, Deepak; Lucas, Joseph; Hero, Alfred O.; Carin, Lawrence; Woods, Christopher W.; Ginsburg, Geoffrey S.

2014-01-01

Improved ways to diagnose acute respiratory viral infections could decrease inappropriate antibacterial use and serve as a vital triage mechanism in the event of a potential viral pandemic. Measurement of the host response to infection is an alternative to pathogen-based diagnostic testing and may improve diagnostic accuracy. We have developed a host-based assay with a reverse transcription polymerase chain reaction (RT-PCR) TaqMan low-density array (TLDA) platform for classifying respiratory viral infection. We developed the assay using two cohorts experimentally infected with influenza A H3N2/Wisconsin or influenza A H1N1/Brisbane, and validated the assay in a sample of adults presenting to the emergency department with fever (n = 102) and in healthy volunteers (n = 41). Peripheral blood RNA samples were obtained from individuals who underwent experimental viral challenge or who presented to the emergency department and had microbiologically proven viral respiratory infection or systemic bacterial infection. The selected gene set on the RT-PCR TLDA assay classified participants with experimentally induced influenza H3N2 and H1N1 infection with 100 and 87% accuracy, respectively. We validated this host gene expression signature in a cohort of 102 individuals arriving at the emergency department. The sensitivity of the RT-PCR test was 89% [95% confidence interval (CI), 72 to 98%], and the specificity was 94% (95% CI, 86 to 99%). These results show that RT-PCR–based detection of a host gene expression signature can classify individuals with respiratory viral infection and sets the stage for prospective evaluation of this diagnostic approach in a clinical setting. PMID:24048524

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.

Twenty-four signature genes predict the prognosis of oral squamous cell carcinoma with high accuracy and repeatability

PubMed Central

Gao, Jianyong; Tian, Gang; Han, Xu; Zhu, Qiang

2018-01-01

Oral squamous cell carcinoma (OSCC) is the sixth most common type cancer worldwide, with poor prognosis. The present study aimed to identify gene signatures that could classify OSCC and predict prognosis in different stages. A training data set (GSE41613) and two validation data sets (GSE42743 and GSE26549) were acquired from the online Gene Expression Omnibus database. In the training data set, patients were classified based on the tumor-node-metastasis staging system, and subsequently grouped into low stage (L) or high stage (H). Signature genes between L and H stages were selected by disparity index analysis, and classification was performed by the expression of these signature genes. The established classification was compared with the L and H classification, and fivefold cross validation was used to evaluate the stability. Enrichment analysis for the signature genes was implemented by the Database for Annotation, Visualization and Integration Discovery. Two validation data sets were used to determine the precise of classification. Survival analysis was conducted followed each classification using the package ‘survival’ in R software. A set of 24 signature genes was identified based on the classification model with the Fi value of 0.47, which was used to distinguish OSCC samples in two different stages. Overall survival of patients in the H stage was higher than those in the L stage. Signature genes were primarily enriched in ‘ether lipid metabolism’ pathway and biological processes such as ‘positive regulation of adaptive immune response’ and ‘apoptotic cell clearance’. The results provided a novel 24-gene set that may be used as biomarkers to predict OSCC prognosis with high accuracy, which may be used to determine an appropriate treatment program for patients with OSCC in addition to the traditional evaluation index. PMID:29257303

A Temporal Chromatin Signature in Human Embryonic Stem Cells Identifies Regulators of Cardiac Development

PubMed Central

Paige, Sharon L.; Thomas, Sean; Stoick-Cooper, Cristi L.; Wang, Hao; Maves, Lisa; Sandstrom, Richard; Pabon, Lil; Reinecke, Hans; Pratt, Gabriel; Keller, Gordon; Moon, Randall T.; Stamatoyannopoulos, John; Murry, Charles E.

2012-01-01

Summary Directed differentiation of human embryonic stem cells (ESCs) into cardiovascular cells provides a model for studying molecular mechanisms of human cardiovascular development. Though it is known that chromatin modification patterns in ESCs differ markedly from those in lineage-committed progenitors and differentiated cells, the temporal dynamics of chromatin alterations during differentiation along a defined lineage have not been studied. We show that differentiation of human ESCs into cardiovascular cells is accompanied by programmed temporal alterations in chromatin structure that distinguish key regulators of cardiovascular development from other genes. We used this temporal chromatin signature to identify regulators of cardiac development, including the homeobox gene MEIS2. We demonstrate using the zebrafish model that MEIS2 is critical for proper heart tube formation and subsequent cardiac looping. Temporal chromatin signatures should be broadly applicable to other models of stem cell differentiation to identify regulators and provide key insights into major developmental decisions. PMID:22981225

Aging-dependent alterations in gene expression and a mitochondrial signature of responsiveness to human influenza vaccination.

PubMed

Thakar, Juilee; Mohanty, Subhasis; West, A Phillip; Joshi, Samit R; Ueda, Ikuyo; Wilson, Jean; Meng, Hailong; Blevins, Tamara P; Tsang, Sui; Trentalange, Mark; Siconolfi, Barbara; Park, Koonam; Gill, Thomas M; Belshe, Robert B; Kaech, Susan M; Shadel, Gerald S; Kleinstein, Steven H; Shaw, Albert C

2015-01-01

To elucidate gene expression pathways underlying age-associated impairment in influenza vaccine response, we screened young (age 21-30) and older (age≥65) adults receiving influenza vaccine in two consecutive seasons and identified those with strong or absent response to vaccine, including a subset of older adults meeting criteria for frailty. PBMCs obtained prior to vaccination (Day 0) and at day 2 or 4, day 7 and day 28 post-vaccine were subjected to gene expression microarray analysis. We defined a response signature and also detected induction of a type I interferon response at day 2 and a plasma cell signature at day 7 post-vaccine in young responders. The response signature was dysregulated in older adults, with the plasma cell signature induced at day 2, and was never induced in frail subjects (who were all non-responders). We also identified a mitochondrial signature in young vaccine responders containing genes mediating mitochondrial biogenesis and oxidative phosphorylation that was consistent in two different vaccine seasons and verified by analyses of mitochondrial content and protein expression. These results represent the first genome-wide transcriptional profiling analysis of age-associated dynamics following influenza vaccination, and implicate changes in mitochondrial biogenesis and function as a critical factor in human vaccine responsiveness.

Polycomb repressive complex 2 epigenomic signature defines age-associated hypermethylation and gene expression changes

PubMed Central

Dozmorov, Mikhail G

2015-01-01

Although age-associated gene expression and methylation changes have been reported throughout the literature, the unifying epigenomic principles of aging remain poorly understood. Recent explosion in availability and resolution of functional/regulatory genome annotation data (epigenomic data), such as that provided by the ENCODE and Roadmap Epigenomics projects, provides an opportunity for the identification of epigenomic mechanisms potentially altered by age-associated differentially methylated regions (aDMRs) and regulatory signatures in the promoters of age-associated genes (aGENs). In this study we found that aDMRs and aGENs identified in multiple independent studies share a common Polycomb Repressive Complex 2 signature marked by EZH2, SUZ12, CTCF binding sites, repressive H3K27me3, and activating H3K4me1 histone modification marks, and a “poised promoter” chromatin state. This signature is depleted in RNA Polymerase II-associated transcription factor binding sites, activating H3K79me2, H3K36me3, H3K27ac marks, and an “active promoter” chromatin state. The PRC2 signature was shown to be generally stable across cell types. When considering the directionality of methylation changes, we found the PRC2 signature to be associated with aDMRs hypermethylated with age, while hypomethylated aDMRs were associated with enhancers. In contrast, aGENs were associated with the PRC2 signature independently of the directionality of gene expression changes. In this study we demonstrate that the PRC2 signature is the common epigenomic context of genomic regions associated with hypermethylation and gene expression changes in aging. PMID:25880792

Systematic computation with functional gene-sets among leukemic and hematopoietic stem cells reveals a favorable prognostic signature for acute myeloid leukemia.

PubMed

Yang, Xinan Holly; Li, Meiyi; Wang, Bin; Zhu, Wanqi; Desgardin, Aurelie; Onel, Kenan; de Jong, Jill; Chen, Jianjun; Chen, Luonan; Cunningham, John M

2015-03-24

Genes that regulate stem cell function are suspected to exert adverse effects on prognosis in malignancy. However, diverse cancer stem cell signatures are difficult for physicians to interpret and apply clinically. To connect the transcriptome and stem cell biology, with potential clinical applications, we propose a novel computational "gene-to-function, snapshot-to-dynamics, and biology-to-clinic" framework to uncover core functional gene-sets signatures. This framework incorporates three function-centric gene-set analysis strategies: a meta-analysis of both microarray and RNA-seq data, novel dynamic network mechanism (DNM) identification, and a personalized prognostic indicator analysis. This work uses complex disease acute myeloid leukemia (AML) as a research platform. We introduced an adjustable "soft threshold" to a functional gene-set algorithm and found that two different analysis methods identified distinct gene-set signatures from the same samples. We identified a 30-gene cluster that characterizes leukemic stem cell (LSC)-depleted cells and a 25-gene cluster that characterizes LSC-enriched cells in parallel; both mark favorable-prognosis in AML. Genes within each signature significantly share common biological processes and/or molecular functions (empirical p = 6e-5 and 0.03 respectively). The 25-gene signature reflects the abnormal development of stem cells in AML, such as AURKA over-expression. We subsequently determined that the clinical relevance of both signatures is independent of known clinical risk classifications in 214 patients with cytogenetically normal AML. We successfully validated the prognosis of both signatures in two independent cohorts of 91 and 242 patients respectively (log-rank p < 0.0015 and 0.05; empirical p < 0.015 and 0.08). The proposed algorithms and computational framework will harness systems biology research because they efficiently translate gene-sets (rather than single genes) into biological discoveries about

Genome-wide methylomic and transcriptomic analyses identify subtype-specific epigenetic signatures commonly dysregulated in glioma stem cells and glioblastoma.

PubMed

Pangeni, Rajendra P; Zhang, Zhou; Alvarez, Angel A; Wan, Xuechao; Sastry, Namratha; Lu, Songjian; Shi, Taiping; Huang, Tianzhi; Lei, Charles X; James, C David; Kessler, John A; Brennan, Cameron W; Nakano, Ichiro; Lu, Xinghua; Hu, Bo; Zhang, Wei; Cheng, Shi-Yuan

2018-06-21

Glioma stem cells (GSCs), a subpopulation of tumor cells, contribute to tumor heterogeneity and therapy resistance. Gene expression profiling classified glioblastoma (GBM) and GSCs into four transcriptomically-defined subtypes. Here, we determined the DNA methylation signatures in transcriptomically pre-classified GSC and GBM bulk tumors subtypes. We hypothesized that these DNA methylation signatures correlate with gene expression and are uniquely associated either with only GSCs or only GBM bulk tumors. Additional methylation signatures may be commonly associated with both GSCs and GBM bulk tumors, i.e., common to non-stem-like and stem-like tumor cell populations and correlating with the clinical prognosis of glioma patients. We analyzed Illumina 450K methylation array and expression data from a panel of 23 patient-derived GSCs. We referenced these results with The Cancer Genome Atlas (TCGA) GBM datasets to generate methylomic and transcriptomic signatures for GSCs and GBM bulk tumors of each transcriptomically pre-defined tumor subtype. Survival analyses were carried out for these signature genes using publicly available datasets, including from TCGA. We report that DNA methylation signatures in proneural and mesenchymal tumor subtypes are either unique to GSCs, unique to GBM bulk tumors, or common to both. Further, dysregulated DNA methylation correlates with gene expression and clinical prognoses. Additionally, many previously identified transcriptionally-regulated markers are also dysregulated due to DNA methylation. The subtype-specific DNA methylation signatures described in this study could be useful for refining GBM sub-classification, improving prognostic accuracy, and making therapeutic decisions.

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.

Comparative analyses identify molecular signature of MRI-classified SVZ-associated glioblastoma

PubMed Central

Lin, Chin-Hsing Annie; Rhodes, Christopher T.; Lin, ChenWei; Phillips, Joanna J.; Berger, Mitchel S.

2017-01-01

ABSTRACT Glioblastoma (GBM) is a highly aggressive brain cancer with limited therapeutic options. While efforts to identify genes responsible for GBM have revealed mutations and aberrant gene expression associated with distinct types of GBM, patients with GBM are often diagnosed and classified based on MRI features. Therefore, we seek to identify molecular representatives in parallel with MRI classification for group I and group II primary GBM associated with the subventricular zone (SVZ). As group I and II GBM contain stem-like signature, we compared gene expression profiles between these 2 groups of primary GBM and endogenous neural stem progenitor cells to reveal dysregulation of cell cycle, chromatin status, cellular morphogenesis, and signaling pathways in these 2 types of MRI-classified GBM. In the absence of IDH mutation, several genes associated with metabolism are differentially expressed in these subtypes of primary GBM, implicating metabolic reprogramming occurs in tumor microenvironment. Furthermore, histone lysine methyltransferase EZH2 was upregulated while histone lysine demethylases KDM2 and KDM4 were downregulated in both group I and II primary GBM. Lastly, we identified 9 common genes across large data sets of gene expression profiles among MRI-classified group I/II GBM, a large cohort of GBM subtypes from TCGA, and glioma stem cells by unsupervised clustering comparison. These commonly upregulated genes have known functions in cell cycle, centromere assembly, chromosome segregation, and mitotic progression. Our findings highlight altered expression of genes important in chromosome integrity across all GBM, suggesting a common mechanism of disrupted fidelity of chromosome structure in GBM. PMID:28278055

Prognostic breast cancer signature identified from 3D culture model accurately predicts clinical outcome across independent datasets

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

Martin, Katherine J.; Patrick, Denis R.; Bissell, Mina J.

2008-10-20

One of the major tenets in breast cancer research is that early detection is vital for patient survival by increasing treatment options. To that end, we have previously used a novel unsupervised approach to identify a set of genes whose expression predicts prognosis of breast cancer patients. The predictive genes were selected in a well-defined three dimensional (3D) cell culture model of non-malignant human mammary epithelial cell morphogenesis as down-regulated during breast epithelial cell acinar formation and cell cycle arrest. Here we examine the ability of this gene signature (3D-signature) to predict prognosis in three independent breast cancer microarray datasetsmore » having 295, 286, and 118 samples, respectively. Our results show that the 3D-signature accurately predicts prognosis in three unrelated patient datasets. At 10 years, the probability of positive outcome was 52, 51, and 47 percent in the group with a poor-prognosis signature and 91, 75, and 71 percent in the group with a good-prognosis signature for the three datasets, respectively (Kaplan-Meier survival analysis, p<0.05). Hazard ratios for poor outcome were 5.5 (95% CI 3.0 to 12.2, p<0.0001), 2.4 (95% CI 1.6 to 3.6, p<0.0001) and 1.9 (95% CI 1.1 to 3.2, p = 0.016) and remained significant for the two larger datasets when corrected for estrogen receptor (ER) status. Hence the 3D-signature accurately predicts breast cancer outcome in both ER-positive and ER-negative tumors, though individual genes differed in their prognostic ability in the two subtypes. Genes that were prognostic in ER+ patients are AURKA, CEP55, RRM2, EPHA2, FGFBP1, and VRK1, while genes prognostic in ER patients include ACTB, FOXM1 and SERPINE2 (Kaplan-Meier p<0.05). Multivariable Cox regression analysis in the largest dataset showed that the 3D-signature was a strong independent factor in predicting breast cancer outcome. The 3D-signature accurately predicts breast cancer outcome across multiple datasets and holds

A Gene Signature to Determine Metastatic Behavior in Thymomas

PubMed Central

Gökmen-Polar, Yesim; Wilkinson, Jeff; Maetzold, Derek; Stone, John F.; Oelschlager, Kristen M.; Vladislav, Ioan Tudor; Shirar, Kristen L.; Kesler, Kenneth A.; Loehrer, Patrick J.; Badve, Sunil

2013-01-01

Purpose Thymoma represents one of the rarest of all malignancies. Stage and completeness of resection have been used to ascertain postoperative therapeutic strategies albeit with limited prognostic accuracy. A molecular classifier would be useful to improve the assessment of metastatic behaviour and optimize patient management. Methods qRT-PCR assay for 23 genes (19 test and four reference genes) was performed on multi-institutional archival primary thymomas (n = 36). Gene expression levels were used to compute a signature, classifying tumors into classes 1 and 2, corresponding to low or high likelihood for metastases. The signature was validated in an independent multi-institutional cohort of patients (n = 75). Results A nine-gene signature that can predict metastatic behavior of thymomas was developed and validated. Using radial basis machine modeling in the training set, 5-year and 10-year metastasis-free survival rates were 77% and 26% for predicted low (class 1) and high (class 2) risk of metastasis (P = 0.0047, log-rank), respectively. For the validation set, 5-year metastasis-free survival rates were 97% and 30% for predicted low- and high-risk patients (P = 0.0004, log-rank), respectively. The 5-year metastasis-free survival rates for the validation set were 49% and 41% for Masaoka stages I/II and III/IV (P = 0.0537, log-rank), respectively. In univariate and multivariate Cox models evaluating common prognostic factors for thymoma metastasis, the nine-gene signature was the only independent indicator of metastases (P = 0.036). Conclusion A nine-gene signature was established and validated which predicts the likelihood of metastasis more accurately than traditional staging. This further underscores the biologic determinants of the clinical course of thymoma and may improve patient management. PMID:23894276

Radiation Gene-expression Signatures in Primary Breast Cancer Cells.

PubMed

Minafra, Luigi; Bravatà, Valentina; Cammarata, Francesco P; Russo, Giorgio; Gilardi, Maria C; Forte, Giusi I

2018-05-01

In breast cancer (BC) care, radiation therapy (RT) is an efficient treatment to control localized tumor. Radiobiological research is needed to understand molecular differences that affect radiosensitivity of different tumor subtypes and the response variability. The aim of this study was to analyze gene expression profiling (GEP) in primary BC cells following irradiation with doses of 9 Gy and 23 Gy delivered by intraoperative electron radiation therapy (IOERT) in order to define gene signatures of response to high doses of ionizing radiation. We performed GEP by cDNA microarrays and evaluated cell survival after IOERT treatment in primary BC cell cultures. Real-time quantitative reverse transcription polymerase chain reaction (qRT-PCR) was performed to validate candidate genes. We showed, for the first time, a 4-gene and a 6-gene signature, as new molecular biomarkers, in two primary BC cell cultures after exposure at 9 Gy and 23 Gy respectively, for which we observed a significantly high survival rate. Gene signatures activated by different doses of ionizing radiation may predict response to RT and contribute to defining a personalized biological-driven treatment plan. Copyright© 2018, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.

Liverome: a curated database of liver cancer-related gene signatures with self-contained context information.

PubMed

Lee, Langho; Wang, Kai; Li, Gang; Xie, Zhi; Wang, Yuli; Xu, Jiangchun; Sun, Shaoxian; Pocalyko, David; Bhak, Jong; Kim, Chulhong; Lee, Kee-Ho; Jang, Ye Jin; Yeom, Young Il; Yoo, Hyang-Sook; Hwang, Seungwoo

2011-11-30

Hepatocellular carcinoma (HCC) is the fifth most common cancer worldwide. A number of molecular profiling studies have investigated the changes in gene and protein expression that are associated with various clinicopathological characteristics of HCC and generated a wealth of scattered information, usually in the form of gene signature tables. A database of the published HCC gene signatures would be useful to liver cancer researchers seeking to retrieve existing differential expression information on a candidate gene and to make comparisons between signatures for prioritization of common genes. A challenge in constructing such database is that a direct import of the signatures as appeared in articles would lead to a loss or ambiguity of their context information that is essential for a correct biological interpretation of a gene's expression change. This challenge arises because designation of compared sample groups is most often abbreviated, ad hoc, or even missing from published signature tables. Without manual curation, the context information becomes lost, leading to uninformative database contents. Although several databases of gene signatures are available, none of them contains informative form of signatures nor shows comprehensive coverage on liver cancer. Thus we constructed Liverome, a curated database of liver cancer-related gene signatures with self-contained context information. Liverome's data coverage is more than three times larger than any other signature database, consisting of 143 signatures taken from 98 HCC studies, mostly microarray and proteome, and involving 6,927 genes. The signatures were post-processed into an informative and uniform representation and annotated with an itemized summary so that all context information is unambiguously self-contained within the database. The signatures were further informatively named and meaningfully organized according to ten functional categories for guided browsing. Its web interface enables a

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

Gene Expression Signatures Based on Variability can Robustly Predict Tumor Progression and Prognosis

PubMed Central

Dinalankara, Wikum; Bravo, Héctor Corrada

2015-01-01

Gene expression signatures are commonly used to create cancer prognosis and diagnosis methods, yet only a small number of them are successfully deployed in the clinic since many fail to replicate performance on subsequent validation. A primary reason for this lack of reproducibility is the fact that these signatures attempt to model the highly variable and unstable genomic behavior of cancer. Our group recently introduced gene expression anti-profiles as a robust methodology to derive gene expression signatures based on the observation that while gene expression measurements are highly heterogeneous across tumors of a specific cancer type relative to the normal tissue, their degree of deviation from normal tissue expression in specific genes involved in tissue differentiation is a stable tumor mark that is reproducible across experiments and cancer types. Here we show that constructing gene expression signatures based on variability and the anti-profile approach yields classifiers capable of successfully distinguishing benign growths from cancerous growths based on deviation from normal expression. We then show that this same approach generates stable and reproducible signatures that predict probability of relapse and survival based on tumor gene expression. These results suggest that using the anti-profile framework for the discovery of genomic signatures is an avenue leading to the development of reproducible signatures suitable for adoption in clinical settings. PMID:26078586

Gene Expression Profiling Specifies Chemokine, Mitochondrial and Lipid Metabolism Signatures in Leprosy

PubMed Central

Guerreiro, Luana Tatiana Albuquerque; Robottom-Ferreira, Anna Beatriz; Ribeiro-Alves, Marcelo; Toledo-Pinto, Thiago Gomes; Rosa Brito, Tiana; Rosa, Patrícia Sammarco; Sandoval, Felipe Galvan; Jardim, Márcia Rodrigues; Antunes, Sérgio Gomes; Shannon, Edward J.; Sarno, Euzenir Nunes; Pessolani, Maria Cristina Vidal; Williams, Diana Lynn; Moraes, Milton Ozório

2013-01-01

Herein, we performed microarray experiments in Schwann cells infected with live M. leprae and identified novel differentially expressed genes (DEG) in M. leprae infected cells. Also, we selected candidate genes associated or implicated with leprosy in genetic studies and biological experiments. Forty-seven genes were selected for validation in two independent types of samples by multiplex qPCR. First, an in vitro model using THP-1 cells was infected with live Mycobacterium leprae and M. bovis bacillus Calmette-Guérin (BCG). In a second situation, mRNA obtained from nerve biopsies from patients with leprosy or other peripheral neuropathies was tested. We detected DEGs that discriminate M. bovis BCG from M. leprae infection. Specific signatures of susceptible responses after M. leprae infection when compared to BCG lead to repression of genes, including CCL2, CCL3, IL8 and SOD2. The same 47-gene set was screened in nerve biopsies, which corroborated the down-regulation of CCL2 and CCL3 in leprosy, but also evidenced the down-regulation of genes involved in mitochondrial metabolism, and the up-regulation of genes involved in lipid metabolism and ubiquitination. Finally, a gene expression signature from DEG was identified in patients confirmed of having leprosy. A classification tree was able to ascertain 80% of the cases as leprosy or non-leprous peripheral neuropathy based on the expression of only LDLR and CCL4. A general immune and mitochondrial hypo-responsive state occurs in response to M. leprae infection. Also, the most important genes and pathways have been highlighted providing new tools for early diagnosis and treatment of leprosy. PMID:23798993

Early signatures of regime shifts in gene expression dynamics

NASA Astrophysics Data System (ADS)

Pal, Mainak; Pal, Amit Kumar; Ghosh, Sayantari; Bose, Indrani

2013-06-01

Recently, a large number of studies have been carried out on the early signatures of sudden regime shifts in systems as diverse as ecosystems, financial markets, population biology and complex diseases. The signatures of regime shifts in gene expression dynamics are less systematically investigated. In this paper, we consider sudden regime shifts in the gene expression dynamics described by a fold-bifurcation model involving bistability and hysteresis. We consider two alternative models, models 1 and 2, of competence development in the bacterial population B. subtilis and determine some early signatures of the regime shifts between competence and noncompetence. We use both deterministic and stochastic formalisms for the purpose of our study. The early signatures studied include the critical slowing down as a transition point is approached, rising variance and the lag-1 autocorrelation function, skewness and a ratio of two mean first passage times. Some of the signatures could provide the experimental basis for distinguishing between bistability and excitability as the correct mechanism for the development of competence.

CRC-113 gene expression signature for predicting prognosis in patients with colorectal cancer

PubMed Central

Nguyen, Dinh Truong; Kim, Jin-Hwan; Jo, Yong Hwa; Shahid, Muhammad; Akter, Salima; Aryal, Saurav Nath; Yoo, Ji Youn; Ahn, Yong-Joo; Cho, Kyoung Min; Lee, Ju-Seog; Choe, Wonchae; Kang, Insug; Ha, Joohun; Kim, Sung Soo

2015-01-01

Colorectal cancer (CRC) is the third leading cause of global cancer mortality. Recent studies have proposed several gene signatures to predict CRC prognosis, but none of those have proven reliable for predicting prognosis in clinical practice yet due to poor reproducibility and molecular heterogeneity. Here, we have established a prognostic signature of 113 probe sets (CRC-113) that include potential biomarkers and reflect the biological and clinical characteristics. Robustness and accuracy were significantly validated in external data sets from 19 centers in five countries. In multivariate analysis, CRC-113 gene signature showed a stronger prognostic value for survival and disease recurrence in CRC patients than current clinicopathological risk factors and molecular alterations. We also demonstrated that the CRC-113 gene signature reflected both genetic and epigenetic molecular heterogeneity in CRC patients. Furthermore, incorporation of the CRC-113 gene signature into a clinical context and molecular markers further refined the selection of the CRC patients who might benefit from postoperative chemotherapy. Conclusively, CRC-113 gene signature provides new possibilities for improving prognostic models and personalized therapeutic strategies. PMID:26397224

CRC-113 gene expression signature for predicting prognosis in patients with colorectal cancer.

PubMed

Nguyen, Minh Nam; Choi, Tae Gyu; Nguyen, Dinh Truong; Kim, Jin-Hwan; Jo, Yong Hwa; Shahid, Muhammad; Akter, Salima; Aryal, Saurav Nath; Yoo, Ji Youn; Ahn, Yong-Joo; Cho, Kyoung Min; Lee, Ju-Seog; Choe, Wonchae; Kang, Insug; Ha, Joohun; Kim, Sung Soo

2015-10-13

Colorectal cancer (CRC) is the third leading cause of global cancer mortality. Recent studies have proposed several gene signatures to predict CRC prognosis, but none of those have proven reliable for predicting prognosis in clinical practice yet due to poor reproducibility and molecular heterogeneity. Here, we have established a prognostic signature of 113 probe sets (CRC-113) that include potential biomarkers and reflect the biological and clinical characteristics. Robustness and accuracy were significantly validated in external data sets from 19 centers in five countries. In multivariate analysis, CRC-113 gene signature showed a stronger prognostic value for survival and disease recurrence in CRC patients than current clinicopathological risk factors and molecular alterations. We also demonstrated that the CRC-113 gene signature reflected both genetic and epigenetic molecular heterogeneity in CRC patients. Furthermore, incorporation of the CRC-113 gene signature into a clinical context and molecular markers further refined the selection of the CRC patients who might benefit from postoperative chemotherapy. Conclusively, CRC-113 gene signature provides new possibilities for improving prognostic models and personalized therapeutic strategies.

A four-gene signature predicts survival in clear-cell renal-cell carcinoma.

PubMed

Dai, Jun; Lu, Yuchao; Wang, Jinyu; Yang, Lili; Han, Yingyan; Wang, Ying; Yan, Dan; Ruan, Qiurong; Wang, Shaogang

2016-12-13

Clear-cell renal-cell carcinoma (ccRCC) is the most common pathological subtype of renal cell carcinoma (RCC), accounting for about 80% of RCC. In order to find potential prognostic biomarkers in ccRCC, we presented a four-gene signature to evaluate the prognosis of ccRCC. SurvExpress and immunohistochemical (IHC) staining of tissue microarrays were used to analyze the association between the four genes and the prognosis of ccRCC. Data from TCGA dataset revealed a prognostic prompt function of the four genes (PTEN, PIK3C2A, ITPA and BCL3). Further discovery suggested that the four-gene signature predicted survival better than any of the four genes alone. Moreover, IHC staining demonstrated a consistent result with TCGA, indicating that the signature was an independent prognostic factor of survival in ccRCC. Univariate and multivariate Cox proportional hazard regression analysis were conducted to verify the association of clinicopathological variables and the four genes' expression levels with survival. The results further testified that the risk (four-gene signature) was an independent prognostic factors of both Overall Survival (OS) and Disease-free Survival (DFS) (P<0.05). In conclusion, the four-gene signature was correlated with the survival of ccRCC, and therefore, may help to provide significant clinical implications for predicting the prognosis of patients.

Prioritizing Therapeutics for Lung Cancer: An Integrative Meta-analysis of Cancer Gene Signatures and Chemogenomic Data

PubMed Central

Fortney, Kristen; Griesman, Joshua; Kotlyar, Max; Pastrello, Chiara; Angeli, Marc; Sound-Tsao, Ming; Jurisica, Igor

2015-01-01

Repurposing FDA-approved drugs with the aid of gene signatures of disease can accelerate the development of new therapeutics. A major challenge to developing reliable drug predictions is heterogeneity. Different gene signatures of the same disease or drug treatment often show poor overlap across studies, as a consequence of both biological and technical variability, and this can affect the quality and reproducibility of computational drug predictions. Existing algorithms for signature-based drug repurposing use only individual signatures as input. But for many diseases, there are dozens of signatures in the public domain. Methods that exploit all available transcriptional knowledge on a disease should produce improved drug predictions. Here, we adapt an established meta-analysis framework to address the problem of drug repurposing using an ensemble of disease signatures. Our computational pipeline takes as input a collection of disease signatures, and outputs a list of drugs predicted to consistently reverse pathological gene changes. We apply our method to conduct the largest and most systematic repurposing study on lung cancer transcriptomes, using 21 signatures. We show that scaling up transcriptional knowledge significantly increases the reproducibility of top drug hits, from 44% to 78%. We extensively characterize drug hits in silico, demonstrating that they slow growth significantly in nine lung cancer cell lines from the NCI-60 collection, and identify CALM1 and PLA2G4A as promising drug targets for lung cancer. Our meta-analysis pipeline is general, and applicable to any disease context; it can be applied to improve the results of signature-based drug repurposing by leveraging the large number of disease signatures in the public domain. PMID:25786242

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

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

Importance of correlation between gene expression levels: application to the type I interferon signature in rheumatoid arthritis.

PubMed

Reynier, Frédéric; Petit, Fabien; Paye, Malick; Turrel-Davin, Fanny; Imbert, Pierre-Emmanuel; Hot, Arnaud; Mougin, Bruno; Miossec, Pierre

2011-01-01

The analysis of gene expression data shows that many genes display similarity in their expression profiles suggesting some co-regulation. Here, we investigated the co-expression patterns in gene expression data and proposed a correlation-based research method to stratify individuals. Using blood from rheumatoid arthritis (RA) patients, we investigated the gene expression profiles from whole blood using Affymetrix microarray technology. Co-expressed genes were analyzed by a biclustering method, followed by gene ontology analysis of the relevant biclusters. Taking the type I interferon (IFN) pathway as an example, a classification algorithm was developed from the 102 RA patients and extended to 10 systemic lupus erythematosus (SLE) patients and 100 healthy volunteers to further characterize individuals. We developed a correlation-based algorithm referred to as Classification Algorithm Based on a Biological Signature (CABS), an alternative to other approaches focused specifically on the expression levels. This algorithm applied to the expression of 35 IFN-related genes showed that the IFN signature presented a heterogeneous expression between RA, SLE and healthy controls which could reflect the level of global IFN signature activation. Moreover, the monitoring of the IFN-related genes during the anti-TNF treatment identified changes in type I IFN gene activity induced in RA patients. In conclusion, we have proposed an original method to analyze genes sharing an expression pattern and a biological function showing that the activation levels of a biological signature could be characterized by its overall state of correlation.

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.

Gene-expression signature regulated by the KEAP1-NRF2-CUL3 axis is associated with a poor prognosis in head and neck squamous cell cancer.

PubMed

Namani, Akhileshwar; Matiur Rahaman, Md; Chen, Ming; Tang, Xiuwen

2018-01-06

NRF2 is the key regulator of oxidative stress in normal cells and aberrant expression of the NRF2 pathway due to genetic alterations in the KEAP1 (Kelch-like ECH-associated protein 1)-NRF2 (nuclear factor erythroid 2 like 2)-CUL3 (cullin 3) axis leads to tumorigenesis and drug resistance in many cancers including head and neck squamous cell cancer (HNSCC). The main goal of this study was to identify specific genes regulated by the KEAP1-NRF2-CUL3 axis in HNSCC patients, to assess the prognostic value of this gene signature in different cohorts, and to reveal potential biomarkers. RNA-Seq V2 level 3 data from 279 tumor samples along with 37 adjacent normal samples from patients enrolled in the The Cancer Genome Atlas (TCGA)-HNSCC study were used to identify upregulated genes using two methods (altered KEAP1-NRF2-CUL3 versus normal, and altered KEAP1-NRF2-CUL3 versus wild-type). We then used a new approach to identify the combined gene signature by integrating both datasets and subsequently tested this signature in 4 independent HNSCC datasets to assess its prognostic value. In addition, functional annotation using the DAVID v6.8 database and protein-protein interaction (PPI) analysis using the STRING v10 database were performed on the signature. A signature composed of a subset of 17 genes regulated by the KEAP1-NRF2-CUL3 axis was identified by overlapping both the upregulated genes of altered versus normal (251 genes) and altered versus wild-type (25 genes) datasets. We showed that increased expression was significantly associated with poor survival in 4 independent HNSCC datasets, including the TCGA-HNSCC dataset. Furthermore, Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, and PPI analysis revealed that most of the genes in this signature are associated with drug metabolism and glutathione metabolic pathways. Altogether, our study emphasizes the discovery of a gene signature regulated by the KEAP1-NRF2-CUL3 axis which is strongly associated with

A 7-Gene Signature Depicts the Biochemical Profile of Early Prefibrotic Myelofibrosis

PubMed Central

Skov, Vibe; Burton, Mark; Thomassen, Mads; Stauffer Larsen, Thomas; Riley, Caroline H.; Brinch Madelung, Ann; Kjær, Lasse; Bondo, Henrik; Stamp, Inger; Ehinger, Mats; Dahl-Sørensen, Rasmus; Brochmann, Nana; Nielsen, Karsten; Thiele, Jürgen; Jensen, Morten K.; Weis Bjerrum, Ole; Kruse, Torben A.; Hasselbalch, Hans Carl

2016-01-01

Recent studies have shown that a large proportion of patients classified as essential thrombocythemia (ET) actually have early primary prefibrotic myelofibrosis (prePMF), which implies an inferior prognosis as compared to patients being diagnosed with so-called genuine or true ET. According to the World Health Organization (WHO) 2008 classification, bone marrow histology is a major component in the distinction between these disease entities. However, the differential diagnosis between them may be challenging and several studies have not been able to distinguish between them. Most lately, it has been argued that simple blood tests, including the leukocyte count and plasma lactate dehydrogenase (LDH) may be useful tools to separate genuine ET from prePMF, the latter disease entity more often being featured by anemia, leukocytosis and elevated LDH. Whole blood gene expression profiling was performed in 17 and 9 patients diagnosed with ET and PMF, respectively. Using elevated LDH obtained at the time of diagnosis as a marker of prePMF, a 7-gene signature was identified which correctly predicted the prePMF group with a sensitivity of 100% and a specificity of 89%. The 7 genes included MPO, CEACAM8, CRISP3, MS4A3, CEACAM6, HEMGN, and MMP8, which are genes known to be involved in inflammation, cell adhesion, differentiation and proliferation. Evaluation of bone marrow biopsies and the 7-gene signature showed a concordance rate of 71%, 79%, 62%, and 38%. Our 7-gene signature may be a useful tool to differentiate between genuine ET and prePMF but needs to be validated in a larger cohort of “ET” patients. PMID:27579896

Common disease signatures from gene expression analysis in Huntington's disease human blood and brain.

PubMed

Mina, Eleni; van Roon-Mom, Willeke; Hettne, Kristina; van Zwet, Erik; Goeman, Jelle; Neri, Christian; A C 't Hoen, Peter; Mons, Barend; Roos, Marco

2016-08-01

Huntington's disease (HD) is a devastating brain disorder with no effective treatment or cure available. The scarcity of brain tissue makes it hard to study changes in the brain and impossible to perform longitudinal studies. However, peripheral pathology in HD suggests that it is possible to study the disease using peripheral tissue as a monitoring tool for disease progression and/or efficacy of novel therapies. In this study, we investigated if blood can be used to monitor disease severity and progression in brain. Since previous attempts using only gene expression proved unsuccessful, we compared blood and brain Huntington's disease signatures in a functional context. Microarray HD gene expression profiles from three brain regions were compared to the transcriptome of HD blood generated by next generation sequencing. The comparison was performed with a combination of weighted gene co-expression network analysis and literature based functional analysis (Concept Profile Analysis). Uniquely, our comparison of blood and brain datasets was not based on (the very limited) gene overlap but on the similarity between the gene annotations in four different semantic categories: "biological process", "cellular component", "molecular function" and "disease or syndrome". We identified signatures in HD blood reflecting a broad pathophysiological spectrum, including alterations in the immune response, sphingolipid biosynthetic processes, lipid transport, cell signaling, protein modification, spliceosome, RNA splicing, vesicle transport, cell signaling and synaptic transmission. Part of this spectrum was reminiscent of the brain pathology. The HD signatures in caudate nucleus and BA4 exhibited the highest similarity with blood, irrespective of the category of semantic annotations used. BA9 exhibited an intermediate similarity, while cerebellum had the least similarity. We present two signatures that were shared between blood and brain: immune response and spinocerebellar ataxias

A gene expression inflammatory signature specifically predicts multiple myeloma evolution and patients survival.

PubMed

Botta, C; Di Martino, M T; Ciliberto, D; Cucè, M; Correale, P; Rossi, M; Tagliaferri, P; Tassone, P

2016-12-16

Multiple myeloma (MM) is closely dependent on cross-talk between malignant plasma cells and cellular components of the inflammatory/immunosuppressive bone marrow milieu, which promotes disease progression, drug resistance, neo-angiogenesis, bone destruction and immune-impairment. We investigated the relevance of inflammatory genes in predicting disease evolution and patient survival. A bioinformatics study by Ingenuity Pathway Analysis on gene expression profiling dataset of monoclonal gammopathy of undetermined significance, smoldering and symptomatic-MM, identified inflammatory and cytokine/chemokine pathways as the most progressively affected during disease evolution. We then selected 20 candidate genes involved in B-cell inflammation and we investigated their role in predicting clinical outcome, through univariate and multivariate analyses (log-rank test, logistic regression and Cox-regression model). We defined an 8-genes signature (IL8, IL10, IL17A, CCL3, CCL5, VEGFA, EBI3 and NOS2) identifying each condition (MGUS/smoldering/symptomatic-MM) with 84% accuracy. Moreover, six genes (IFNG, IL2, LTA, CCL2, VEGFA, CCL3) were found independently correlated with patients' survival. Patients whose MM cells expressed high levels of Th1 cytokines (IFNG/LTA/IL2/CCL2) and low levels of CCL3 and VEGFA, experienced the longest survival. On these six genes, we built a prognostic risk score that was validated in three additional independent datasets. In this study, we provide proof-of-concept that inflammation has a critical role in MM patient progression and survival. The inflammatory-gene prognostic signature validated in different datasets clearly indicates novel opportunities for personalized anti-MM treatment.

Triazole induced concentration-related gene signatures in rat whole embryo culture.

PubMed

Robinson, Joshua F; Tonk, Elisa C M; Verhoef, Aart; Piersma, Aldert H

2012-09-01

Commonly used as antifungal agents in agriculture and medicine, triazoles have been shown to cause teratogenicity in a diverse set of animal models. Here, we evaluated the dose-dependent impacts of flusilazole, cyproconazole and triadimefon, on global gene expression in relation to effects on embryonic development using the rat whole embryo culture (WEC) model. After 4 h exposure, we identified changes in gene expression due to triazole exposure which preceded morphological alterations observed at 48 h. In general, across the three triazoles, we observed similar directionality of regulation in gene expression and the magnitude of effects on gene expression correlated with the degree of induced developmental toxicity. Significantly regulated genes included key members of steroid/cholesterol and retinoic acid metabolism and hindbrain developmental pathways. Direct comparisons with previous studies suggest that triazole-gene signatures identified in the WEC overlap with zebrafish and mouse, and furthermore, triazoles impact gene expression in a similar manner as retinoic acid exposures in rat embryos. In summary, we further differentiate pathways underlying triazole-developmental toxicity using WEC and demonstrate the conservation of these response-pathways across model systems. Copyright © 2012 Elsevier Inc. All rights reserved.

Prognostic Power of a Tumor Differentiation Gene Signature for Bladder Urothelial Carcinomas.

PubMed

Mo, Qianxing; Nikolos, Fotis; Chen, Fengju; Tramel, Zoe; Lee, Yu-Cheng; Hayashi, Kazukuni; Xiao, Jing; Shen, Jianjun; Chan, Keith Syson

2018-05-01

Muscle-invasive bladder cancers (MIBCs) cause approximately 150 000 deaths per year worldwide. Survival for MIBC patients is heterogeneous, with no clinically validated molecular markers that predict clinical outcome. Non-MIBCs (NMIBCs) generally have favorable outcome; however, a portion progress to MIBC. Hence, development of a prognostic tool that can guide decision-making is crucial for improving clinical management of bladder urothelial carcinomas. Tumor grade is defined by pathologic evaluation of tumor cell differentiation, and it often associates with clinical outcome. The current study extrapolates this conventional wisdom and combines it with molecular profiling. We developed an 18-gene signature that molecularly defines urothelial cellular differentiation, thus classifying MIBCs and NMIBCs into two subgroups: basal and differentiated. We evaluated the prognostic capability of this "tumor differentiation signature" and three other existing gene signatures including the The Cancer Genome Atlas (TCGA; 2707 genes), MD Anderson Cancer Center (MDA; 2252 genes/2697 probes), and University of North Carolina at Chapel Hill (UNC; 47 genes) using five gene expression data sets derived from MIBC and NMIBC patients. All statistical tests were two-sided. The tumor differentiation signature demonstrated consistency and statistical robustness toward stratifying MIBC patients into different overall survival outcomes (TCGA cohort 1, P = .03; MDA discovery, P = .009; MDA validation, P = .01), while the other signatures were not as consistent. In addition, we analyzed the progression (Ta/T1 progressing to ≥T2) probability of NMIBCs. NMIBC patients with a basal tumor differentiation signature associated with worse progression outcome (P = .008). Gene functional term enrichment and gene set enrichment analyses revealed that genes involved in the biologic process of immune response and inflammatory response are among the most elevated within basal bladder cancers

Establishment of a 12-gene expression signature to predict colon cancer prognosis

PubMed Central

Zhao, Guangxi; Dong, Pingping; Wu, Bingrui

2018-01-01

A robust and accurate gene expression signature is essential to assist oncologists to determine which subset of patients at similar Tumor-Lymph Node-Metastasis (TNM) stage has high recurrence risk and could benefit from adjuvant therapies. Here we applied a two-step supervised machine-learning method and established a 12-gene expression signature to precisely predict colon adenocarcinoma (COAD) prognosis by using COAD RNA-seq transcriptome data from The Cancer Genome Atlas (TCGA). The predictive performance of the 12-gene signature was validated with two independent gene expression microarray datasets: GSE39582 includes 566 COAD cases for the development of six molecular subtypes with distinct clinical, molecular and survival characteristics; GSE17538 is a dataset containing 232 colon cancer patients for the generation of a metastasis gene expression profile to predict recurrence and death in COAD patients. The signature could effectively separate the poor prognosis patients from good prognosis group (disease specific survival (DSS): Kaplan Meier (KM) Log Rank p = 0.0034; overall survival (OS): KM Log Rank p = 0.0336) in GSE17538. For patients with proficient mismatch repair system (pMMR) in GSE39582, the signature could also effectively distinguish high risk group from low risk group (OS: KM Log Rank p = 0.005; Relapse free survival (RFS): KM Log Rank p = 0.022). Interestingly, advanced stage patients were significantly enriched in high 12-gene score group (Fisher’s exact test p = 0.0003). After stage stratification, the signature could still distinguish poor prognosis patients in GSE17538 from good prognosis within stage II (Log Rank p = 0.01) and stage II & III (Log Rank p = 0.017) in the outcome of DFS. Within stage III or II/III pMMR patients treated with Adjuvant Chemotherapies (ACT) and patients with higher 12-gene score showed poorer prognosis (III, OS: KM Log Rank p = 0.046; III & II, OS: KM Log Rank p = 0.041). Among stage II/III pMMR patients with

A 16 Yin Yang gene expression ratio signature for ER+/node- breast cancer.

PubMed

Xu, Wayne; Jia, Gaofeng; Cai, Nianguang; Huang, Shujun; Davie, James R; Pitz, Marshall; Banerji, Shantanu; Murphy, Leigh

2017-03-15

Breast cancer is one of the leading causes of cancer death in women. It is a complex and heterogeneous disease with different clinical outcomes. Stratifying patients into subgroups with different outcomes could help guide clinical decision making. In this study, we used two opposing groups of genes, Yin and Yang, to develop a prognostic expression ratio signature. Using the METABRIC cohort we identified a16-gene signature capable of stratifying breast cancer patients into four risk levels with intention that low-risk patients would not undergo adjuvant systemic therapy, intermediate-low-risk patients will be treated with hormonal therapy only, and intermediate-high- and high-risk groups will be treated by chemotherapy in addition to the hormonal therapy. The 16-gene signature for four risk level stratifications of breast cancer patients has been validated using 14 independent datasets. Notably, the low-risk group (n = 51) of 205 estrogen receptor-positive and node negative (ER+/node-) patients from three different datasets who had not had any systemic adjuvant therapy had 100% 15-year disease-specific survival rate. The Concordance Index of YMR for ER+/node negative patients is close to the commercially available signatures. However, YMR showed more significance (HR = 3.7, p = 8.7e-12) in stratifying ER+/node- subgroup than OncotypeDx (HR = 2.7, p = 1.3e-7), MammaPrint (HR = 2.5, p = 5.8e-7), rorS (HR = 2.4, p = 1.4e-6), and NPI (HR = 2.6, p = 1.2e-6). YMR signature may be developed as a clinical tool to select a subgroup of low-risk ER+/node- patients who do not require any adjuvant hormonal therapy (AHT). © 2016 UICC.

Selection signatures in Shetland ponies.

PubMed

Frischknecht, M; Flury, C; Leeb, T; Rieder, S; Neuditschko, M

2016-06-01

Shetland ponies were selected for numerous traits including small stature, strength, hardiness and longevity. Despite the different selection criteria, Shetland ponies are well known for their small stature. We performed a selection signature analysis including genome-wide SNPs of 75 Shetland ponies and 76 large-sized horses. Based upon this dataset, we identified a selection signature on equine chromosome (ECA) 1 between 103.8 Mb and 108.5 Mb. A total of 33 annotated genes are located within this interval including the IGF1R gene at 104.2 Mb and the ADAMTS17 gene at 105.4 Mb. These two genes are well known to have a major impact on body height in numerous species including humans. Homozygosity mapping in the Shetland ponies identified a region with increased homozygosity between 107.4 Mb and 108.5 Mb. None of the annotated genes in this region have so far been associated with height. Thus, we cannot exclude the possibility that the identified selection signature on ECA1 is associated with some trait other than height, for which Shetland ponies were selected. © 2016 Stichting International Foundation for Animal Genetics.

Building predictive gene signatures through simultaneous assessment of transcription factor activation and gene expression.

EPA Science Inventory

Building predictive gene signatures through simultaneous assessment of transcription factor activation and gene expression Exposure to many drugs and environmentally-relevant chemicals can cause adverse outcomes. These adverse outcomes, such as cancer, have been linked to mol...

Clinical Application of Prognostic Gene Expression Signature in Fusion Gene-Negative Rhabdomyosarcoma: A Report from the Children's Oncology Group.

PubMed

Hingorani, Pooja; Missiaglia, Edoardo; Shipley, Janet; Anderson, James R; Triche, Timothy J; Delorenzi, Mauro; Gastier-Foster, Julie; Wing, Michele; Hawkins, Douglas S; Skapek, Stephen X

2015-10-15

Pediatric rhabdomyosarcoma (RMS) has two common histologic subtypes: embryonal (ERMS) and alveolar (ARMS). PAX-FOXO1 fusion gene status is a more reliable prognostic marker than alveolar histology, whereas fusion gene-negative (FN) ARMS patients are clinically similar to ERMS patients. A five-gene expression signature (MG5) previously identified two diverse risk groups within the fusion gene-negative RMS (FN-RMS) patients, but this has not been independently validated. The goal of this study was to test whether expression of the MG5 metagene, measured using a technical platform that can be applied to routine pathology material, would correlate with outcome in a new cohort of patients with FN-RMS. Cases were taken from the Children's Oncology Group (COG) D9803 study of children with intermediate-risk RMS, and gene expression profiling for the MG5 genes was performed using the nCounter assay. The MG5 score was correlated with clinical and pathologic characteristics as well as overall and event-free survival. MG5 standardized score showed no significant association with any of the available clinicopathologic variables. The MG5 signature score showed a significant correlation with overall (N = 57; HR, 7.3; 95% CI, 1.9-27.0; P = 0.003) and failure-free survival (N = 57; HR, 6.1; 95% CI, 1.9-19.7; P = 0.002). This represents the first, validated molecular prognostic signature for children with FN-RMS who otherwise have intermediate-risk disease. The capacity to measure the expression of a small number of genes in routine pathology material and apply a simple mathematical formula to calculate the MG5 metagene score provides a clear path toward better risk stratification in future prospective clinical trials. ©2015 American Association for Cancer Research.

Development of phoH as a Novel Signature Gene for Assessing Marine Phage Diversity▿

PubMed Central

Goldsmith, Dawn B.; Crosti, Giuseppe; Dwivedi, Bhakti; McDaniel, Lauren D.; Varsani, Arvind; Suttle, Curtis A.; Weinbauer, Markus G.; Sandaa, Ruth-Anne; Breitbart, Mya

2011-01-01

Phages play a key role in the marine environment by regulating the transfer of energy between trophic levels and influencing global carbon and nutrient cycles. The diversity of marine phage communities remains difficult to characterize because of the lack of a signature gene common to all phages. Recent studies have demonstrated the presence of host-derived auxiliary metabolic genes in phage genomes, such as those belonging to the Pho regulon, which regulates phosphate uptake and metabolism under low-phosphate conditions. Among the completely sequenced phage genomes in GenBank, this study identified Pho regulon genes in nearly 40% of the marine phage genomes, while only 4% of nonmarine phage genomes contained these genes. While several Pho regulon genes were identified, phoH was the most prevalent, appearing in 42 out of 602 completely sequenced phage genomes. Phylogenetic analysis demonstrated that phage phoH sequences formed a cluster distinct from those of their bacterial hosts. PCR primers designed to amplify a region of the phoH gene were used to determine the diversity of phage phoH sequences throughout a depth profile in the Sargasso Sea and at six locations worldwide. phoH was present at all sites examined, and a high diversity of phoH sequences was recovered. Most phoH sequences belonged to clusters without any cultured representatives. Each depth and geographic location had a distinct phoH composition, although most phoH clusters were recovered from multiple sites. Overall, phoH is an effective signature gene for examining phage diversity in the marine environment. PMID:21926220

Identifying signatures of positive selection in pigmentation genes in two South Asian populations.

PubMed

Jonnalagadda, Manjari; Bharti, Neeraj; Patil, Yatish; Ozarkar, Shantanu; K, Sunitha Manjari; Joshi, Rajendra; Norton, Heather

2017-09-10

Skin pigmentation is a polygenic trait showing wide phenotypic variations among global populations. While numerous pigmentation genes have been identified to be under positive selection among European and East populations, genes contributing to phenotypic variation in skin pigmentation within and among South Asian populations are still poorly understood. The present study uses data from the Phase 3 of the 1000 genomes project focusing on two South Asian populations-GIH (Gujarati Indian from Houston, Texas) and ITU (Indian Telugu from UK), so as to decode the genetic architecture involved in adaptation to ultraviolet radiation in South Asian populations. Statistical tests included were (1) tests to identify deviations of the Site Frequency Spectrum (SFS) from neutral expectations (Tajima's D, Fay and Wu's H and Fu and Li's D* and F*), (2) tests focused on the identification of high-frequency haplotypes with extended linkage disequilibrium (iHS and Rsb), and (3) tests based on genetic differentiation between populations (LSBL). Twenty-two pigmentation genes fall in the top 1% for at least one statistic in the GIH population, 5 of which (LYST, OCA2, SLC24A5, SLC45A2, and TYR) have been previously associated with normal variation in skin, hair, or eye color. In comparison, 17 genes fall in the top 1% for at least one statistic in the ITU population. Twelve loci which are identified as outliers in the ITU scan were also identified in the GIH population. These results suggest that selection may have affected these loci broadly across the region. © 2017 Wiley Periodicals, Inc.

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

EG-05COMBINATION OF GENE COPY GAIN AND EPIGENETIC DEREGULATION ARE ASSOCIATED WITH THE ABERRANT EXPRESSION OF A STEM CELL RELATED HOX-SIGNATURE IN GLIOBLASTOMA

PubMed Central

Kurscheid, Sebastian; Bady, Pierre; Sciuscio, Davide; Samarzija, Ivana; Shay, Tal; Vassallo, Irene; Van Criekinge, Wim; Domany, Eytan; Stupp, Roger; Delorenzi, Mauro; Hegi, Monika

2014-01-01

We previously reported a stem cell related HOX gene signature associated with resistance to chemo-radiotherapy (TMZ/RT- > TMZ) in glioblastoma. However, underlying mechanisms triggering overexpression remain mostly elusive. Interestingly, HOX genes are neither involved in the developing brain, nor expressed in normal brain, suggestive of an acquired gene expression signature during gliomagenesis. HOXA genes are located on CHR 7 that displays trisomy in most glioblastoma which strongly impacts gene expression on this chromosome, modulated by local regulatory elements. Furthermore we observed more pronounced DNA methylation across the HOXA locus as compared to non-tumoral brain (Human methylation 450K BeadChip Illumina; 59 glioblastoma, 5 non-tumoral brain sampes). CpG probes annotated for HOX-signature genes, contributing most to the variability, served as input into the analysis of DNA methylation and expression to identify key regulatory regions. The structural similarity of the observed correlation matrices between DNA methylation and gene expression in our cohort and an independent data-set from TCGA (106 glioblastoma) was remarkable (RV-coefficient, 0.84; p-value < 0.0001). We identified a CpG located in the promoter region of the HOXA10 locus exerting the strongest mean negative correlation between methylation and expression of the whole HOX-signature. Applying this analysis the same CpG emerged in the external set. We then determined the contribution of both, gene copy aberration (CNA) and methylation at the selected probe to explain expression of the HOX-signature using a linear model. Statistically significant results suggested an additive effect between gene dosage and methylation at the key CpG identified. Similarly, such an additive effect was also observed in the external data-set. Taken together, we hypothesize that overexpression of the stem-cell related HOX signature is triggered by gain of trisomy 7 and escape from compensatory DNA methylation at

An eleven gene molecular signature for extra-capsular spread in oral squamous cell carcinoma serves as a prognosticator of outcome in patients without nodal metastases.

PubMed

Wang, Weining; Lim, Weng Khong; Leong, Hui Sun; Chong, Fui Teen; Lim, Tony K H; Tan, Daniel S W; Teh, Bin Tean; Iyer, N Gopalakrishna

2015-04-01

Extracapsular spread (ECS) is an important prognostic factor for oral squamous cell carcinoma (OSCC) and is used to guide management. In this study, we aimed to identify an expression profile signature for ECS in node-positive OSCC using data derived from two different sources: a cohort of OSCC patients from our institution (National Cancer Centre Singapore) and The Cancer Genome Atlas (TCGA) head and neck squamous cell carcinoma (HNSCC) cohort. We also sought to determine if this signature could serve as a prognostic factor in node negative cancers. Patients with a histological diagnosis of OSCC were identified from an institutional database and fresh tumor samples were retrieved. RNA was extracted and gene expression profiling was performed using the Affymetrix GeneChip Human Genome U133 Plus 2.0 microarray platform. RNA sequence data and corresponding clinical data for the TCGA HNSCC cohort were downloaded from the TCGA Data Portal. All data analyses were conducted using R package and SPSS. We identified an 11 gene signature (GGH, MTFR1, CDKN3, PSRC1, SMIM3, CA9, IRX4, CPA3, ZSCAN16, CBX7 and ZFP3) which was robust in segregating tumors by ECS status. In node negative patients, patients harboring this ECS signature had a significantly worse overall survival (p=0.04). An eleven gene signature for ECS was derived. Our results also suggest that this signature is prognostic in a separate subset of patients with no nodal metastasis Further validation of this signature on other datasets and immunohistochemical studies are required to establish utility of this signature in stratifying early stage OSCC patients. Copyright © 2014 Elsevier Ltd. All rights reserved.

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.

Signatures from Tissue-specific MPSS Libraries Identify Transcripts Preferentially Expressed in the Mouse Inner Ear

PubMed Central

Peters, Linda M.; Belyantseva, Inna A.; Lagziel, Ayala; Battey, James F.; Friedman, Thomas B.; Morell, Robert J.

2007-01-01

Specialization in cell function and morphology is influenced by the differential expression of mRNAs, many of which are expressed at low abundance and restricted to certain cell types. Detecting such transcripts in cDNA libraries may require sequencing millions of clones. Massively parallel signature sequencing (MPSS) is well-suited for identifying transcripts that are expressed in discrete cell types and in low abundance. We have made MPSS libraries from microdissections of three inner ear tissues. By comparing these MPSS libraries to those of 87 other tissues included in the Mouse Reference Transcriptome (MRT) online resource, we have identified genes that are highly enriched in, or specific to, the inner ear. We show by RT-PCR and in situ hybridization that signatures unique to the inner ear libraries identify transcripts with highly specific cell-type localizations. These transcripts serve to illustrate the utility of a resource that is available to the research community. Utilization of these resources will increase the number of known transcription units and expand our knowledge of the tissue-specific regulation of the transcriptome. PMID:17049805

Minimising Immunohistochemical False Negative ER Classification Using a Complementary 23 Gene Expression Signature of ER Status

PubMed Central

Li, Qiyuan; Eklund, Aron C.; Juul, Nicolai; Haibe-Kains, Benjamin; Workman, Christopher T.; Richardson, Andrea L.; Szallasi, Zoltan; Swanton, Charles

2010-01-01

Background Expression of the oestrogen receptor (ER) in breast cancer predicts benefit from endocrine therapy. Minimising the frequency of false negative ER status classification is essential to identify all patients with ER positive breast cancers who should be offered endocrine therapies in order to improve clinical outcome. In routine oncological practice ER status is determined by semi-quantitative methods such as immunohistochemistry (IHC) or other immunoassays in which the ER expression level is compared to an empirical threshold[1], [2]. The clinical relevance of gene expression-based ER subtypes as compared to IHC-based determination has not been systematically evaluated. Here we attempt to reduce the frequency of false negative ER status classification using two gene expression approaches and compare these methods to IHC based ER status in terms of predictive and prognostic concordance with clinical outcome. Methodology/Principal Findings Firstly, ER status was discriminated by fitting the bimodal expression of ESR1 to a mixed Gaussian model. The discriminative power of ESR1 suggested bimodal expression as an efficient way to stratify breast cancer; therefore we identified a set of genes whose expression was both strongly bimodal, mimicking ESR expression status, and highly expressed in breast epithelial cell lines, to derive a 23-gene ER expression signature-based classifier. We assessed our classifiers in seven published breast cancer cohorts by comparing the gene expression-based ER status to IHC-based ER status as a predictor of clinical outcome in both untreated and tamoxifen treated cohorts. In untreated breast cancer cohorts, the 23 gene signature-based ER status provided significantly improved prognostic power compared to IHC-based ER status (P = 0.006). In tamoxifen-treated cohorts, the 23 gene ER expression signature predicted clinical outcome (HR = 2.20, P = 0.00035). These complementary ER signature-based strategies estimated that

Human relevance of an in vitro gene signature in HaCaT for skin sensitization.

PubMed

van der Veen, Jochem W; Hodemaekers, Henny; Reus, Astrid A; Maas, Wilfred J M; van Loveren, Henk; Ezendam, Janine

2015-02-01

The skin sensitizing potential of chemicals is mainly assessed using animal methods, such as the murine local lymph node assay. Recently, an in vitro assay based on a gene expression signature in the HaCaT keratinocyte cell line was proposed as an alternative to these animal methods. Here, the human relevance of this gene signature is assessed through exposure of freshly isolated human skin to the chemical allergens dinitrochlorobenzene (DNCB) and diphenylcyclopropenone (DCP). In human skin, the gene signature shows similar direction of regulation as was previously observed in vitro, suggesting that the molecular processes that drive expression of these genes are similar between the HaCaT cell line and freshly isolated skin, providing evidence for the human relevance of the gene signature. Copyright © 2014 Elsevier Ltd. All rights reserved.

Gene Expression Signatures Characterized by Longitudinal Stability and Interindividual Variability Delineate Baseline Phenotypic Groups with Distinct Responses to Immune Stimulation.

PubMed

Scheid, Adam D; Van Keulen, Virginia P; Felts, Sara J; Neier, Steven C; Middha, Sumit; Nair, Asha A; Techentin, Robert W; Gilbert, Barry K; Jen, Jin; Neuhauser, Claudia; Zhang, Yuji; Pease, Larry R

2018-03-01

Human immunity exhibits remarkable heterogeneity among individuals, which engenders variable responses to immune perturbations in human populations. Population studies reveal that, in addition to interindividual heterogeneity, systemic immune signatures display longitudinal stability within individuals, and these signatures may reliably dictate how given individuals respond to immune perturbations. We hypothesize that analyzing relationships among these signatures at the population level may uncover baseline immune phenotypes that correspond with response outcomes to immune stimuli. To test this, we quantified global gene expression in peripheral blood CD4 + cells from healthy individuals at baseline and following CD3/CD28 stimulation at two time points 1 mo apart. Systemic CD4 + cell baseline and poststimulation molecular immune response signatures (MIRS) were defined by identifying genes expressed at levels that were stable between time points within individuals and differential among individuals in each state. Iterative differential gene expression analyses between all possible phenotypic groupings of at least three individuals using the baseline and stimulated MIRS gene sets revealed shared baseline and response phenotypic groupings, indicating the baseline MIRS contained determinants of immune responsiveness. Furthermore, significant numbers of shared phenotype-defining sets of determinants were identified in baseline data across independent healthy cohorts. Combining the cohorts and repeating the analyses resulted in identification of over 6000 baseline immune phenotypic groups, implying that the MIRS concept may be useful in many immune perturbation contexts. These findings demonstrate that patterns in complex gene expression variability can be used to define immune phenotypes and discover determinants of immune responsiveness. Copyright © 2018 by The American Association of Immunologists, Inc.

Evolutionary analysis of vision genes identifies potential drivers of visual differences between giraffe and okapi

PubMed Central

Agaba, Morris; Cavener, Douglas R.

2017-01-01

Background The capacity of visually oriented species to perceive and respond to visual signal is integral to their evolutionary success. Giraffes are closely related to okapi, but the two species have broad range of phenotypic differences including their visual capacities. Vision studies rank giraffe’s visual acuity higher than all other artiodactyls despite sharing similar vision ecological determinants with many of them. The extent to which the giraffe’s unique visual capacity and its difference with okapi is reflected by changes in their vision genes is not understood. Methods The recent availability of giraffe and okapi genomes provided opportunity to identify giraffe and okapi vision genes. Multiple strategies were employed to identify thirty-six candidate mammalian vision genes in giraffe and okapi genomes. Quantification of selection pressure was performed by a combination of branch-site tests of positive selection and clade models of selection divergence through comparing giraffe and okapi vision genes and orthologous sequences from other mammals. Results Signatures of selection were identified in key genes that could potentially underlie giraffe and okapi visual adaptations. Importantly, some genes that contribute to optical transparency of the eye and those that are critical in light signaling pathway were found to show signatures of adaptive evolution or selection divergence. Comparison between giraffe and other ruminants identifies significant selection divergence in CRYAA and OPN1LW. Significant selection divergence was identified in SAG while positive selection was detected in LUM when okapi is compared with ruminants and other mammals. Sequence analysis of OPN1LW showed that at least one of the sites known to affect spectral sensitivity of the red pigment is uniquely divergent between giraffe and other ruminants. Discussion By taking a systemic approach to gene function in vision, the results provide the first molecular clues associated with

Evolutionary analysis of vision genes identifies potential drivers of visual differences between giraffe and okapi.

PubMed

Ishengoma, Edson; Agaba, Morris; Cavener, Douglas R

2017-01-01

The capacity of visually oriented species to perceive and respond to visual signal is integral to their evolutionary success. Giraffes are closely related to okapi, but the two species have broad range of phenotypic differences including their visual capacities. Vision studies rank giraffe's visual acuity higher than all other artiodactyls despite sharing similar vision ecological determinants with many of them. The extent to which the giraffe's unique visual capacity and its difference with okapi is reflected by changes in their vision genes is not understood. The recent availability of giraffe and okapi genomes provided opportunity to identify giraffe and okapi vision genes. Multiple strategies were employed to identify thirty-six candidate mammalian vision genes in giraffe and okapi genomes. Quantification of selection pressure was performed by a combination of branch-site tests of positive selection and clade models of selection divergence through comparing giraffe and okapi vision genes and orthologous sequences from other mammals. Signatures of selection were identified in key genes that could potentially underlie giraffe and okapi visual adaptations. Importantly, some genes that contribute to optical transparency of the eye and those that are critical in light signaling pathway were found to show signatures of adaptive evolution or selection divergence. Comparison between giraffe and other ruminants identifies significant selection divergence in CRYAA and OPN1LW . Significant selection divergence was identified in SAG while positive selection was detected in LUM when okapi is compared with ruminants and other mammals. Sequence analysis of OPN1LW showed that at least one of the sites known to affect spectral sensitivity of the red pigment is uniquely divergent between giraffe and other ruminants. By taking a systemic approach to gene function in vision, the results provide the first molecular clues associated with giraffe and okapi vision adaptations. At

Gene-expression signatures of Atlantic salmon's plastic life cycle.

PubMed

Aubin-Horth, Nadia; Letcher, Benjamin H; Hofmann, Hans A

2009-09-15

How genomic expression differs as a function of life history variation is largely unknown. Atlantic salmon exhibits extreme alternative life histories. We defined the gene-expression signatures of wild-caught salmon at two different life stages by comparing the brain expression profiles of mature sneaker males and immature males, and early migrants and late migrants. In addition to life-stage-specific signatures, we discovered a surprisingly large gene set that was differentially regulated-at similar magnitudes, yet in opposite direction-in both life history transitions. We suggest that this co-variation is not a consequence of many independent cellular and molecular switches in the same direction but rather represents the molecular equivalent of a physiological shift orchestrated by one or very few master regulators.

Ontology based molecular signatures for immune cell types via gene expression analysis

PubMed Central

2013-01-01

Background New technologies are focusing on characterizing cell types to better understand their heterogeneity. With large volumes of cellular data being generated, innovative methods are needed to structure the resulting data analyses. Here, we describe an ‘Ontologically BAsed Molecular Signature’ (OBAMS) method that identifies novel cellular biomarkers and infers biological functions as characteristics of particular cell types. This method finds molecular signatures for immune cell types based on mapping biological samples to the Cell Ontology (CL) and navigating the space of all possible pairwise comparisons between cell types to find genes whose expression is core to a particular cell type’s identity. Results We illustrate this ontological approach by evaluating expression data available from the Immunological Genome project (IGP) to identify unique biomarkers of mature B cell subtypes. We find that using OBAMS, candidate biomarkers can be identified at every strata of cellular identity from broad classifications to very granular. Furthermore, we show that Gene Ontology can be used to cluster cell types by shared biological processes in order to find candidate genes responsible for somatic hypermutation in germinal center B cells. Moreover, through in silico experiments based on this approach, we have identified genes sets that represent genes overexpressed in germinal center B cells and identify genes uniquely expressed in these B cells compared to other B cell types. Conclusions This work demonstrates the utility of incorporating structured ontological knowledge into biological data analysis – providing a new method for defining novel biomarkers and providing an opportunity for new biological insights. PMID:24004649

Similar NF-κB Gene Signatures in TNF-α Treated Human Endothelial Cells and Breast Tumor Biopsies

PubMed Central

Perrot-Applanat, Martine; Vacher, Sophie; Toullec, Aurore; Pelaez, Irma; Velasco, Guillaume; Cormier, Françoise; Saad, Hanan El Sheikh; Lidereau, Rosette; Baud, Véronique; Bièche, Ivan

2011-01-01

Background Endothelial dysfunction has been implicated in the pathogenesis of diverse pathologies ranging from vascular and immune diseases to cancer. TNF-α is one of the mediators of endothelial dysfunction through the activation of transcription factors, including NF-κB. While HUVEC (macrovascular cells) have been largely used in the past, here, we documented an NF-κB gene signature in TNFα-stimulated microvascular endothelial cells HMEC often used in tumor angiogenesis studies. Methodology/Principal Findings We measured mRNA expression of 55 NF-κB related genes using quantitative RT-PCR in HUVEC and HMEC. Our study identified twenty genes markedly up-regulated in response to TNFα, including adhesion molecules, cytokines, chemokines, and apoptosis regulators, some of them being identified as TNF-α-inducible genes for the first time in endothelial cells (two apoptosis regulators, TNFAIP3 and TNFRSF10B/Trail R2 (DR5), the chemokines GM-CSF/CSF2 and MCF/CSF1, and CD40 and TNF-α itself, as well as NF-κB components (RELB, NFKB1or 50/p105 and NFKB2 or p52/p100). For eight genes, the fold induction was much higher in HMEC, as compared to HUVEC. Most importantly, our study described for the first time a connection between NF-κB activation and the induction of most, if not all, of these genes in HMEC as evaluated by pharmacological inhibition and RelA expression knock-down by RNA interference. Moreover, since TNF-α is highly expressed in tumors, we further applied the NF-κB gene signature documented in TNFα-stimulated endothelial cells to human breast tumors. We found a significant positive correlation between TNF and the majority (85 %) of the identified endothelial TNF-induced genes in a well-defined series of 96 (48 ERα positive and 48 ERα negative) breast tumors. Conclusion/Significance Taken together these data suggest the potential use of this NF-κB gene signature in analyzing the role of TNF-α in the endothelial dysfunction, as well as in breast

Real time gamma-ray signature identifier

DOEpatents

Rowland, Mark [Alamo, CA; Gosnell, Tom B [Moraga, CA; Ham, Cheryl [Livermore, CA; Perkins, Dwight [Livermore, CA; Wong, James [Dublin, CA

2012-05-15

A real time gamma-ray signature/source identification method and system using principal components analysis (PCA) for transforming and substantially reducing one or more comprehensive spectral libraries of nuclear materials types and configurations into a corresponding concise representation/signature(s) representing and indexing each individual predetermined spectrum in principal component (PC) space, wherein an unknown gamma-ray signature may be compared against the representative signature to find a match or at least characterize the unknown signature from among all the entries in the library with a single regression or simple projection into the PC space, so as to substantially reduce processing time and computing resources and enable real-time characterization and/or identification.

Cancer-cell intrinsic gene expression signatures overcome intratumoural heterogeneity bias in colorectal cancer patient classification

PubMed Central

Dunne, Philip D.; Alderdice, Matthew; O'Reilly, Paul G.; Roddy, Aideen C.; McCorry, Amy M. B.; Richman, Susan; Maughan, Tim; McDade, Simon S.; Johnston, Patrick G.; Longley, Daniel B.; Kay, Elaine; McArt, Darragh G.; Lawler, Mark

2017-01-01

Stromal-derived intratumoural heterogeneity (ITH) has been shown to undermine molecular stratification of patients into appropriate prognostic/predictive subgroups. Here, using several clinically relevant colorectal cancer (CRC) gene expression signatures, we assessed the susceptibility of these signatures to the confounding effects of ITH using gene expression microarray data obtained from multiple tumour regions of a cohort of 24 patients, including central tumour, the tumour invasive front and lymph node metastasis. Sample clustering alongside correlative assessment revealed variation in the ability of each signature to cluster samples according to patient-of-origin rather than region-of-origin within the multi-region dataset. Signatures focused on cancer-cell intrinsic gene expression were found to produce more clinically useful, patient-centred classifiers, as exemplified by the CRC intrinsic signature (CRIS), which robustly clustered samples by patient-of-origin rather than region-of-origin. These findings highlight the potential of cancer-cell intrinsic signatures to reliably stratify CRC patients by minimising the confounding effects of stromal-derived ITH. PMID:28561046

Genome-wide detection of selection signatures in Chinese indigenous Laiwu pigs revealed candidate genes regulating fat deposition in muscle.

PubMed

Chen, Minhui; Wang, Jiying; Wang, Yanping; Wu, Ying; Fu, Jinluan; Liu, Jian-Feng

2018-05-18

Currently, genome-wide scans for positive selection signatures in commercial breed have been investigated. However, few studies have focused on selection footprints of indigenous breeds. Laiwu pig is an invaluable Chinese indigenous pig breed with extremely high proportion of intramuscular fat (IMF), and an excellent model to detect footprint as the result of natural and artificial selection for fat deposition in muscle. In this study, based on GeneSeek Genomic profiler Porcine HD data, three complementary methods, F ST , iHS (integrated haplotype homozygosity score) and CLR (composite likelihood ratio), were implemented to detect selection signatures in the whole genome of Laiwu pigs. Totally, 175 candidate selected regions were obtained by at least two of the three methods, which covered 43.75 Mb genomic regions and corresponded to 1.79% of the genome sequence. Gene annotation of the selected regions revealed a list of functionally important genes for feed intake and fat deposition, reproduction, and immune response. Especially, in accordance to the phenotypic features of Laiwu pigs, among the candidate genes, we identified several genes, NPY1R, NPY5R, PIK3R1 and JAKMIP1, involved in the actions of two sets of neurons, which are central regulators in maintaining the balance between food intake and energy expenditure. Our results identified a number of regions showing signatures of selection, as well as a list of functionally candidate genes with potential effect on phenotypic traits, especially fat deposition in muscle. Our findings provide insights into the mechanisms of artificial selection of fat deposition and further facilitate follow-up functional studies.

Gene-expression signatures of Atlantic salmon's plastic life cycle

USGS Publications Warehouse

Aubin-Horth, N.; Letcher, B.H.; Hofmann, H.A.

2009-01-01

How genomic expression differs as a function of life history variation is largely unknown. Atlantic salmon exhibits extreme alternative life histories. We defined the gene-expression signatures of wild-caught salmon at two different life stages by comparing the brain expression profiles of mature sneaker males and immature males, and early migrants and late migrants. In addition to life-stage-specific signatures, we discovered a surprisingly large gene set that was differentially regulated-at similar magnitudes, yet in opposite direction-in both life history transitions. We suggest that this co-variation is not a consequence of many independent cellular and molecular switches in the same direction but rather represents the molecular equivalent of a physiological shift orchestrated by one or very few master regulators. ?? 2009 Elsevier Inc. All rights reserved.

An archaeal genomic signature

NASA Technical Reports Server (NTRS)

Graham, D. E.; Overbeek, R.; Olsen, G. J.; Woese, C. R.

2000-01-01

Comparisons of complete genome sequences allow the most objective and comprehensive descriptions possible of a lineage's evolution. This communication uses the completed genomes from four major euryarchaeal taxa to define a genomic signature for the Euryarchaeota and, by extension, the Archaea as a whole. The signature is defined in terms of the set of protein-encoding genes found in at least two diverse members of the euryarchaeal taxa that function uniquely within the Archaea; most signature proteins have no recognizable bacterial or eukaryal homologs. By this definition, 351 clusters of signature proteins have been identified. Functions of most proteins in this signature set are currently unknown. At least 70% of the clusters that contain proteins from all the euryarchaeal genomes also have crenarchaeal homologs. This conservative set, which appears refractory to horizontal gene transfer to the Bacteria or the Eukarya, would seem to reflect the significant innovations that were unique and fundamental to the archaeal "design fabric." Genomic protein signature analysis methods may be extended to characterize the evolution of any phylogenetically defined lineage. The complete set of protein clusters for the archaeal genomic signature is presented as supplementary material (see the PNAS web site, www.pnas.org).

Identification of gene expression signature for cigarette smoke exposure response--from man to mouse.

PubMed

Martin, F; Talikka, M; Hoeng, J; Peitsch, M C

2015-12-01

Gene expression profiling data can be used in toxicology to assess both the level and impact of toxicant exposure, aligned with a vision of 21st century toxicology. Here, we present a whole blood-derived gene signature that can distinguish current smokers from either nonsmokers or former smokers with high specificity and sensitivity. Such a signature that can be measured in a surrogate tissue (whole blood) may help in monitoring smoking exposure as well as discontinuation of exposure when the primarily impacted tissue (e.g., lung) is not readily accessible. The signature consisted of LRRN3, SASH1, PALLD, RGL1, TNFRSF17, CDKN1C, IGJ, RRM2, ID3, SERPING1, and FUCA1. Several members of this signature have been previously described in the context of smoking. The signature translated well across species and could distinguish mice that were exposed to cigarette smoke from ones exposed to air only or had been withdrawn from cigarette smoke exposure. Finally, the small signature of only 11 genes could be converted into a polymerase chain reaction-based assay that could serve as a marker to monitor compliance with a smoking abstinence protocol. © The Author(s) 2015.

Radiogenomics analysis identifies correlations of digital mammography with clinical molecular signatures in breast cancer.

PubMed

Tamez-Peña, Jose-Gerardo; Rodriguez-Rojas, Juan-Andrés; Gomez-Rueda, Hugo; Celaya-Padilla, Jose-Maria; Rivera-Prieto, Roxana-Alicia; Palacios-Corona, Rebeca; Garza-Montemayor, Margarita; Cardona-Huerta, Servando; Treviño, Victor

2018-01-01

In breast cancer, well-known gene expression subtypes have been related to a specific clinical outcome. However, their impact on the breast tissue phenotype has been poorly studied. Here, we investigate the association of imaging data of tumors to gene expression signatures from 71 patients with breast cancer that underwent pre-treatment digital mammograms and tumor biopsies. From digital mammograms, a semi-automated radiogenomics analysis generated 1,078 features describing the shape, signal distribution, and texture of tumors along their contralateral image used as control. From tumor biopsy, we estimated the OncotypeDX and PAM50 recurrence scores using gene expression microarrays. Then, we used multivariate analysis under stringent cross-validation to train models predicting recurrence scores. Few univariate features reached Spearman correlation coefficients above 0.4. Nevertheless, multivariate analysis yielded significantly correlated models for both signatures (correlation of OncotypeDX = 0.49 ± 0.07 and PAM50 = 0.32 ± 0.10 in stringent cross-validation and OncotypeDX = 0.83 and PAM50 = 0.78 for a unique model). Equivalent models trained from the unaffected contralateral breast were not correlated suggesting that the image signatures were tumor-specific and that overfitting was not a considerable issue. We also noted that models were improved by combining clinical information (triple negative status and progesterone receptor). The models used mostly wavelets and fractal features suggesting their importance to capture tumor information. Our results suggest that molecular-based recurrence risk and breast cancer subtypes have observable radiographic phenotypes. To our knowledge, this is the first study associating mammographic information to gene expression recurrence signatures.

Prognostic stratification improvement by integrating ID1/ID3/IGJ gene expression signature and immunophenotypic profile in adult patients with B-ALL.

PubMed

Cruz-Rodriguez, Nataly; Combita, Alba L; Enciso, Leonardo J; Raney, Lauren F; Pinzon, Paula L; Lozano, Olga C; Campos, Alba M; Peñaloza, Niyireth; Solano, Julio; Herrera, Maria V; Zabaleta, Jovanny; Quijano, Sandra

2017-02-28

Survival of adults with B-Acute Lymphoblastic Leukemia requires accurate risk stratification of patients in order to provide the appropriate therapy. Contemporary techniques, using clinical and cytogenetic variables are incomplete for prognosis prediction. To improve the classification of adult patients diagnosed with B-ALL into prognosis groups, two strategies were examined and combined: the expression of the ID1/ID3/IGJ gene signature by RT-PCR and the immunophenotypic profile of 19 markers proposed in the EuroFlow protocol by Flow Cytometry in bone marrow samples. Both techniques were correlated to stratify patients into prognostic groups. An inverse relationship between survival and expression of the three-genes signature was observed and an immunophenotypic profile associated with clinical outcome was identified. Markers CD10 and CD20 were correlated with simultaneous overexpression of ID1, ID3 and IGJ. Patients with simultaneous expression of the poor prognosis gene signature and overexpression of CD10 or CD20, had worse Event Free Survival and Overall Survival than patients who had either the poor prognosis gene expression signature or only CD20 or CD10 overexpressed. By utilizing the combined evaluation of these two immunophenotypic markers along with the poor prognosis gene expression signature, the risk stratification can be significantly strengthened. Further studies including a large number of patients are needed to confirm these findings.

Identification of Gene Expression Signatures in the Chicken Intestinal Intraepithelial Lymphocytes in Response to Herb Additive Supplementations

PubMed Central

Won, Kyeong-Hye; Song, Ki-Duk; Park, Jong-Eun; Kim, Duk-Kyung; Na, Chong-Sam

2016-01-01

Anethole and garlic have an immune modulatory effects on avian coccidiosis, and these effects are correlated with gene expression changes in intestinal epithelial lymphocytes (IELs). In this study, we integrated gene expression datasets from two independent experiments and investigated gene expression profile changes by anethole and garlic respectively, and identified gene expression signatures, which are common targets of these herbs as they might be used for the evaluation of the effect of plant herbs on immunity toward avian coccidiosis. We identified 4,382 and 371 genes, which were differentially expressed in IELs of chickens supplemented with garlic and anethole respectively. The gene ontology (GO) term of differentially expressed genes (DEGs) from garlic treatment resulted in the biological processes (BPs) related to proteolysis, e.g., “modification-dependent protein catabolic process”, “proteolysis involved in cellular protein catabolic process”, “cellular protein catabolic process”, “protein catabolic process”, and “ubiquitin-dependent protein catabolic process”. In GO analysis, one BP term, “Proteolysis”, was obtained. Among DEGs, 300 genes were differentially regulated in response to both garlic and anethole, and 234 and 59 genes were either up- or down-regulated in supplementation with both herbs. Pathway analysis resulted in enrichment of the pathways related to digestion such as “Starch and sucrose metabolism” and “Insulin signaling pathway”. Taken together, the results obtained in the present study could contribute to the effective development of evaluation system of plant herbs based on molecular signatures related with their immunological functions in chicken IELs. PMID:26954117

A predictive signature gene set for discriminating active from latent tuberculosis in Warao Amerindian children.

PubMed

Verhagen, Lilly M; Zomer, Aldert; Maes, Mailis; Villalba, Julian A; Del Nogal, Berenice; Eleveld, Marc; van Hijum, Sacha Aft; de Waard, Jacobus H; Hermans, Peter Wm

2013-02-01

Tuberculosis (TB) continues to cause a high toll of disease and death among children worldwide. The diagnosis of childhood TB is challenged by the paucibacillary nature of the disease and the difficulties in obtaining specimens. Whereas scientific and clinical research efforts to develop novel diagnostic tools have focused on TB in adults, childhood TB has been relatively neglected. Blood transcriptional profiling has improved our understanding of disease pathogenesis of adult TB and may offer future leads for diagnosis and treatment. No studies applying gene expression profiling of children with TB have been published so far. We identified a 116-gene signature set that showed an average prediction error of 11% for TB vs. latent TB infection (LTBI) and for TB vs. LTBI vs. healthy controls (HC) in our dataset. A minimal gene set of only 9 genes showed the same prediction error of 11% for TB vs. LTBI in our dataset. Furthermore, this minimal set showed a significant discriminatory value for TB vs. LTBI for all previously published adult studies using whole blood gene expression, with average prediction errors between 17% and 23%. In order to identify a robust representative gene set that would perform well in populations of different genetic backgrounds, we selected ten genes that were highly discriminative between TB, LTBI and HC in all literature datasets as well as in our dataset. Functional annotation of these genes highlights a possible role for genes involved in calcium signaling and calcium metabolism as biomarkers for active TB. These ten genes were validated by quantitative real-time polymerase chain reaction in an additional cohort of 54 Warao Amerindian children with LTBI, HC and non-TB pneumonia. Decision tree analysis indicated that five of the ten genes were sufficient to classify 78% of the TB cases correctly with no LTBI subjects wrongly classified as TB (100% specificity). Our data justify the further exploration of our signature set as biomarkers

A predictive signature gene set for discriminating active from latent tuberculosis in Warao Amerindian children

PubMed Central

2013-01-01

Background Tuberculosis (TB) continues to cause a high toll of disease and death among children worldwide. The diagnosis of childhood TB is challenged by the paucibacillary nature of the disease and the difficulties in obtaining specimens. Whereas scientific and clinical research efforts to develop novel diagnostic tools have focused on TB in adults, childhood TB has been relatively neglected. Blood transcriptional profiling has improved our understanding of disease pathogenesis of adult TB and may offer future leads for diagnosis and treatment. No studies applying gene expression profiling of children with TB have been published so far. Results We identified a 116-gene signature set that showed an average prediction error of 11% for TB vs. latent TB infection (LTBI) and for TB vs. LTBI vs. healthy controls (HC) in our dataset. A minimal gene set of only 9 genes showed the same prediction error of 11% for TB vs. LTBI in our dataset. Furthermore, this minimal set showed a significant discriminatory value for TB vs. LTBI for all previously published adult studies using whole blood gene expression, with average prediction errors between 17% and 23%. In order to identify a robust representative gene set that would perform well in populations of different genetic backgrounds, we selected ten genes that were highly discriminative between TB, LTBI and HC in all literature datasets as well as in our dataset. Functional annotation of these genes highlights a possible role for genes involved in calcium signaling and calcium metabolism as biomarkers for active TB. These ten genes were validated by quantitative real-time polymerase chain reaction in an additional cohort of 54 Warao Amerindian children with LTBI, HC and non-TB pneumonia. Decision tree analysis indicated that five of the ten genes were sufficient to classify 78% of the TB cases correctly with no LTBI subjects wrongly classified as TB (100% specificity). Conclusions Our data justify the further exploration of our

Identifying signatures of natural selection in Tibetan and Andean populations using dense genome scan data.

PubMed

Bigham, Abigail; Bauchet, Marc; Pinto, Dalila; Mao, Xianyun; Akey, Joshua M; Mei, Rui; Scherer, Stephen W; Julian, Colleen G; Wilson, Megan J; López Herráez, David; Brutsaert, Tom; Parra, Esteban J; Moore, Lorna G; Shriver, Mark D

2010-09-09

High-altitude hypoxia (reduced inspired oxygen tension due to decreased barometric pressure) exerts severe physiological stress on the human body. Two high-altitude regions where humans have lived for millennia are the Andean Altiplano and the Tibetan Plateau. Populations living in these regions exhibit unique circulatory, respiratory, and hematological adaptations to life at high altitude. Although these responses have been well characterized physiologically, their underlying genetic basis remains unknown. We performed a genome scan to identify genes showing evidence of adaptation to hypoxia. We looked across each chromosome to identify genomic regions with previously unknown function with respect to altitude phenotypes. In addition, groups of genes functioning in oxygen metabolism and sensing were examined to test the hypothesis that particular pathways have been involved in genetic adaptation to altitude. Applying four population genetic statistics commonly used for detecting signatures of natural selection, we identified selection-nominated candidate genes and gene regions in these two populations (Andeans and Tibetans) separately. The Tibetan and Andean patterns of genetic adaptation are largely distinct from one another, with both populations showing evidence of positive natural selection in different genes or gene regions. Interestingly, one gene previously known to be important in cellular oxygen sensing, EGLN1 (also known as PHD2), shows evidence of positive selection in both Tibetans and Andeans. However, the pattern of variation for this gene differs between the two populations. Our results indicate that several key HIF-regulatory and targeted genes are responsible for adaptation to high altitude in Andeans and Tibetans, and several different chromosomal regions are implicated in the putative response to selection. These data suggest a genetic role in high-altitude adaption and provide a basis for future genotype/phenotype association studies necessary

Identifying Signatures of Natural Selection in Tibetan and Andean Populations Using Dense Genome Scan Data

PubMed Central

Bigham, Abigail; Bauchet, Marc; Pinto, Dalila; Mao, Xianyun; Akey, Joshua M.; Mei, Rui; Scherer, Stephen W.; Julian, Colleen G.; Wilson, Megan J.; López Herráez, David; Brutsaert, Tom; Parra, Esteban J.; Moore, Lorna G.; Shriver, Mark D.

2010-01-01

High-altitude hypoxia (reduced inspired oxygen tension due to decreased barometric pressure) exerts severe physiological stress on the human body. Two high-altitude regions where humans have lived for millennia are the Andean Altiplano and the Tibetan Plateau. Populations living in these regions exhibit unique circulatory, respiratory, and hematological adaptations to life at high altitude. Although these responses have been well characterized physiologically, their underlying genetic basis remains unknown. We performed a genome scan to identify genes showing evidence of adaptation to hypoxia. We looked across each chromosome to identify genomic regions with previously unknown function with respect to altitude phenotypes. In addition, groups of genes functioning in oxygen metabolism and sensing were examined to test the hypothesis that particular pathways have been involved in genetic adaptation to altitude. Applying four population genetic statistics commonly used for detecting signatures of natural selection, we identified selection-nominated candidate genes and gene regions in these two populations (Andeans and Tibetans) separately. The Tibetan and Andean patterns of genetic adaptation are largely distinct from one another, with both populations showing evidence of positive natural selection in different genes or gene regions. Interestingly, one gene previously known to be important in cellular oxygen sensing, EGLN1 (also known as PHD2), shows evidence of positive selection in both Tibetans and Andeans. However, the pattern of variation for this gene differs between the two populations. Our results indicate that several key HIF-regulatory and targeted genes are responsible for adaptation to high altitude in Andeans and Tibetans, and several different chromosomal regions are implicated in the putative response to selection. These data suggest a genetic role in high-altitude adaption and provide a basis for future genotype/phenotype association studies necessary

Phosphorylated and sumoylation-deficient progesterone receptors drive proliferative gene signatures during breast cancer progression.

PubMed

Knutson, Todd P; Daniel, Andrea R; Fan, Danhua; Silverstein, Kevin At; Covington, Kyle R; Fuqua, Suzanne Aw; Lange, Carol A

2012-06-14

Progesterone receptors (PR) are emerging as important breast cancer drivers. Phosphorylation events common to breast cancer cells impact PR transcriptional activity, in part by direct phosphorylation. PR-B but not PR-A isoforms are phosphorylated on Ser294 by mitogen activated protein kinase (MAPK) and cyclin dependent kinase 2 (CDK2). Phospho-Ser294 PRs are resistant to ligand-dependent Lys388 SUMOylation (that is, a repressive modification). Antagonism of PR small ubiquitin-like modifier (SUMO)ylation by mitogenic protein kinases suggests a mechanism for derepression (that is, transcriptional activation) of target genes. As a broad range of PR protein expression is observed clinically, a PR gene signature would provide a valuable marker of PR contribution to early breast cancer progression. Global gene expression patterns were measured in T47D and MCF-7 breast cancer cells expressing either wild-type (SUMOylation-capable) or K388R (SUMOylation-deficient) PRs and subjected to pathway analysis. Gene sets were validated by RT-qPCR. Recruitment of coregulators and histone methylation levels were determined by chromatin immunoprecipitation. Changes in cell proliferation and survival were determined by 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assays and western blotting. Finally, human breast tumor cohort datasets were probed to identify PR-associated gene signatures; metagene analysis was employed to define survival rates in patients whose tumors express a PR gene signature. 'SUMO-sensitive' PR target genes primarily include genes required for proliferative and pro-survival signaling. DeSUMOylated K388R receptors are preferentially recruited to enhancer regions of derepressed genes (that is, MSX2, RGS2, MAP1A, and PDK4) with the steroid receptor coactivator, CREB-(cAMP-response element-binding protein)-binding protein (CBP), and mixed lineage leukemia 2 (MLL2), a histone methyltransferase mediator of nucleosome remodeling. PR SUMOylation

Microarray-based gene expression profiling in patients with cryopyrin-associated periodic syndromes defines a disease-related signature and IL-1-responsive transcripts.

PubMed

Balow, James E; Ryan, John G; Chae, Jae Jin; Booty, Matthew G; Bulua, Ariel; Stone, Deborah; Sun, Hong-Wei; Greene, James; Barham, Beverly; Goldbach-Mansky, Raphaela; Kastner, Daniel L; Aksentijevich, Ivona

2013-06-01

To analyse gene expression patterns and to define a specific gene expression signature in patients with the severe end of the spectrum of cryopyrin-associated periodic syndromes (CAPS). The molecular consequences of interleukin 1 inhibition were examined by comparing gene expression patterns in 16 CAPS patients before and after treatment with anakinra. We collected peripheral blood mononuclear cells from 22 CAPS patients with active disease and from 14 healthy children. Transcripts that passed stringent filtering criteria (p values≤false discovery rate 1%) were considered as differentially expressed genes (DEG). A set of DEG was validated by quantitative reverse transcription PCR and functional studies with primary cells from CAPS patients and healthy controls. We used 17 CAPS and 66 non-CAPS patient samples to create a set of gene expression models that differentiates CAPS patients from controls and from patients with other autoinflammatory conditions. Many DEG include transcripts related to the regulation of innate and adaptive immune responses, oxidative stress, cell death, cell adhesion and motility. A set of gene expression-based models comprising the CAPS-specific gene expression signature correctly classified all 17 samples from an independent dataset. This classifier also correctly identified 15 of 16 post-anakinra CAPS samples despite the fact that these CAPS patients were in clinical remission. We identified a gene expression signature that clearly distinguished CAPS patients from controls. A number of DEG were in common with other systemic inflammatory diseases such as systemic onset juvenile idiopathic arthritis. The CAPS-specific gene expression classifiers also suggest incomplete suppression of inflammation at low doses of anakinra.

Gene-expression signatures of Atlantic salmon’s plastic life cycle

PubMed Central

Aubin-Horth, Nadia; Letcher, Benjamin H.; Hofmann, Hans A.

2009-01-01

How genomic expression differs as a function of life history variation is largely unknown. Atlantic salmon exhibits extreme alternative life histories. We defined the gene-expression signatures of wild-caught salmon at two different life stages by comparing the brain expression profiles of mature sneaker males and immature males, and early migrants and late migrants. In addition to life-stage-specific signatures, we discovered a surprisingly large gene set that was differentially regulated - at similar magnitudes, yet in opposite direction - in both life history transitions. We suggest that this co-variation is not a consequence of many independent cellular and molecular switches in the same direction but rather represents the molecular equivalent of a physiological shift orchestrated by one or very few master regulators. PMID:19401203

Biological and Clinical Significance of MAD2L1 and BUB1, Genes Frequently Appearing in Expression Signatures for Breast Cancer Prognosis

PubMed Central

Wang, Zhanwei; Katsaros, Dionyssios; Shen, Yi; Fu, Yuanyuan; Canuto, Emilie Marion; Benedetto, Chiara; Lu, Lingeng; Chu, Wen-Ming; Risch, Harvey A.; Yu, Herbert

2015-01-01

To investigate the biologic relevance and clinical implication of genes involved in multiple gene expression signatures for breast cancer prognosis, we identified 16 published gene expression signatures, and selected two genes, MAD2L1 and BUB1. These genes appeared in 5 signatures and were involved in cell-cycle regulation. We analyzed the expression of these genes in relation to tumor features and disease outcomes. In vitro experiments were also performed in two breast cancer cell lines, MDA-MB-231 and MDA-MB-468, to assess cell proliferation, migration and invasion after knocking down the expression of these genes. High expression of these genes was found to be associated with aggressive tumors and poor disease-free survival of 203 breast cancer patients in our study, and the association with survival was confirmed in an online database consisting of 914 patients. In vitro experiments demonstrated that lowering the expression of these genes by siRNAs reduced tumor cell growth and inhibited cell migration and invasion. Our investigation suggests that MAD2L1 and BUB1 may play important roles in breast cancer progression, and measuring the expression of these genes may assist the prediction of breast cancer prognosis. PMID:26287798

Radiogenomics analysis identifies correlations of digital mammography with clinical molecular signatures in breast cancer

PubMed Central

Tamez-Peña, Jose-Gerardo; Rodriguez-Rojas, Juan-Andrés; Gomez-Rueda, Hugo; Celaya-Padilla, Jose-Maria; Rivera-Prieto, Roxana-Alicia; Palacios-Corona, Rebeca; Garza-Montemayor, Margarita; Cardona-Huerta, Servando

2018-01-01

In breast cancer, well-known gene expression subtypes have been related to a specific clinical outcome. However, their impact on the breast tissue phenotype has been poorly studied. Here, we investigate the association of imaging data of tumors to gene expression signatures from 71 patients with breast cancer that underwent pre-treatment digital mammograms and tumor biopsies. From digital mammograms, a semi-automated radiogenomics analysis generated 1,078 features describing the shape, signal distribution, and texture of tumors along their contralateral image used as control. From tumor biopsy, we estimated the OncotypeDX and PAM50 recurrence scores using gene expression microarrays. Then, we used multivariate analysis under stringent cross-validation to train models predicting recurrence scores. Few univariate features reached Spearman correlation coefficients above 0.4. Nevertheless, multivariate analysis yielded significantly correlated models for both signatures (correlation of OncotypeDX = 0.49 ± 0.07 and PAM50 = 0.32 ± 0.10 in stringent cross-validation and OncotypeDX = 0.83 and PAM50 = 0.78 for a unique model). Equivalent models trained from the unaffected contralateral breast were not correlated suggesting that the image signatures were tumor-specific and that overfitting was not a considerable issue. We also noted that models were improved by combining clinical information (triple negative status and progesterone receptor). The models used mostly wavelets and fractal features suggesting their importance to capture tumor information. Our results suggest that molecular-based recurrence risk and breast cancer subtypes have observable radiographic phenotypes. To our knowledge, this is the first study associating mammographic information to gene expression recurrence signatures. PMID:29596496

NF-κB gene signature predicts prostate cancer progression

PubMed Central

Jin, Renjie; Yi, Yajun; Yull, Fiona E.; Blackwell, Timothy S.; Clark, Peter E.; Koyama, Tatsuki; Smith, Joseph A.; Matusik, Robert J.

2014-01-01

In many prostate cancer (PCa) patients, the cancer will be recurrent and eventually progress to lethal metastatic disease after primary treatment, such as surgery or radiation therapy. Therefore, it would be beneficial to better predict which patients with early-stage PCa would progress or recur after primary definitive treatment. In addition, many studies indicate that activation of NF-κB signaling correlates with PCa progression; however, the precise underlying mechanism is not fully understood. Our studies show that activation of NF-κB signaling via deletion of one allele of its inhibitor, IκBα, did not induce prostatic tumorigenesis in our mouse model. However, activation of NF-κB signaling did increase the rate of tumor progression in the Hi-Myc mouse PCa model when compared to Hi-Myc alone. Using the non-malignant NF-κB activated androgen depleted mouse prostate, a NF-κB Activated Recurrence Predictor 21 (NARP21) gene signature was generated. The NARP21 signature successfully predicted disease-specific survival and distant metastases-free survival in patients with PCa. This transgenic mouse model derived gene signature provides a useful and unique molecular profile for human PCa prognosis, which could be used on a prostatic biopsy to predict indolent versus aggressive behavior of the cancer after surgery. PMID:24686169

Integrative ChIP-seq/microarray analysis identifies a CTNNB1 target signature enriched in intestinal stem cells and colon cancer.

PubMed

Watanabe, Kazuhide; Biesinger, Jacob; Salmans, Michael L; Roberts, Brian S; Arthur, William T; Cleary, Michele; Andersen, Bogi; Xie, Xiaohui; Dai, Xing

2014-01-01

Deregulation of canonical Wnt/CTNNB1 (beta-catenin) pathway is one of the earliest events in the pathogenesis of colon cancer. Mutations in APC or CTNNB1 are highly frequent in colon cancer and cause aberrant stabilization of CTNNB1, which activates the transcription of Wnt target genes by binding to chromatin via the TCF/LEF transcription factors. Here we report an integrative analysis of genome-wide chromatin occupancy of CTNNB1 by chromatin immunoprecipitation coupled with high-throughput sequencing (ChIP-seq) and gene expression profiling by microarray analysis upon RNAi-mediated knockdown of CTNNB1 in colon cancer cells. We observed 3629 CTNNB1 binding peaks across the genome and a significant correlation between CTNNB1 binding and knockdown-induced gene expression change. Our integrative analysis led to the discovery of a direct Wnt target signature composed of 162 genes. Gene ontology analysis of this signature revealed a significant enrichment of Wnt pathway genes, suggesting multiple feedback regulations of the pathway. We provide evidence that this gene signature partially overlaps with the Lgr5+ intestinal stem cell signature, and is significantly enriched in normal intestinal stem cells as well as in clinical colorectal cancer samples. Interestingly, while the expression of the CTNNB1 target gene set does not correlate with survival, elevated expression of negative feedback regulators within the signature predicts better prognosis. Our data provide a genome-wide view of chromatin occupancy and gene regulation of Wnt/CTNNB1 signaling in colon cancer cells.

Follow up of a robust meta-signature to identify Zika virus infection in Aedes aegypti: another brick in the wall.

PubMed

Fukutani, Eduardo; Rodrigues, Moreno; Kasprzykowski, José Irahe; Araujo, Cintia Figueiredo de; Paschoal, Alexandre Rossi; Ramos, Pablo Ivan Pereira; Fukutani, Kiyoshi Ferreira; Queiroz, Artur Trancoso Lopo de

2018-01-01

The mosquito Aedes aegypti is the main vector of several arthropod-borne diseases that have global impacts. In a previous meta-analysis, our group identified a vector gene set containing 110 genes strongly associated with infections of dengue, West Nile and yellow fever viruses. Of these 110 genes, four genes allowed a highly accurate classification of infected status. More recently, a new study of Ae. aegypti infected with Zika virus (ZIKV) was published, providing new data to investigate whether this "infection" gene set is also altered during a ZIKV infection. Our hypothesis is that the infection-associated signature may also serve as a proxy to classify the ZIKV infection in the vector. Raw data associated with the NCBI/BioProject were downloaded and re-analysed. A total of 18 paired-end replicates corresponding to three ZIKV-infected samples and three controls were included in this study. The nMDS technique with a logistic regression was used to obtain the probabilities of belonging to a given class. Thus, to compare both gene sets, we used the area under the curve and performed a comparison using the bootstrap method. Our meta-signature was able to separate the infected mosquitoes from the controls with good predictive power to classify the Zika-infected mosquitoes.

Gene Expression Signatures Diagnose Influenza and Other Symptomatic Respiratory Viral Infection in Humans

PubMed Central

Zaas, Aimee K.; Chen, Minhua; Varkey, Jay; Veldman, Timothy; Hero, Alfred O.; Lucas, Joseph; Huang, Yongsheng; Turner, Ronald; Gilbert, Anthony; Lambkin-Williams, Robert; Øien, N. Christine; Nicholson, Bradly; Kingsmore, Stephen; Carin, Lawrence; Woods, Christopher W.; Ginsburg, Geoffrey S.

2010-01-01

Summary Acute respiratory infections (ARI) are a common reason for seeking medical attention and the threat of pandemic influenza will likely add to these numbers. Using human viral challenge studies with live rhinovirus, respiratory syncytial virus, and influenza A, we developed peripheral blood gene expression signatures that distinguish individuals with symptomatic ARI from uninfected individuals with > 95% accuracy. We validated this “acute respiratory viral” signature - encompassing genes with a known role in host defense against viral infections - across each viral challenge. We also validated the signature in an independently acquired dataset for influenza A and classified infected individuals from healthy controls with 100% accuracy. In the same dataset, we could also distinguish viral from bacterial ARIs (93% accuracy). These results demonstrate that ARIs induce changes in human peripheral blood gene expression that can be used to diagnose a viral etiology of respiratory infection and triage symptomatic individuals. PMID:19664979

Data mining reveals a network of early-response genes as a consensus signature of drug-induced in vitro and in vivo toxicity.

PubMed

Zhang, J D; Berntenis, N; Roth, A; Ebeling, M

2014-06-01

Gene signatures of drug-induced toxicity are of broad interest, but they are often identified from small-scale, single-time point experiments, and are therefore of limited applicability. To address this issue, we performed multivariate analysis of gene expression, cell-based assays, and histopathological data in the TG-GATEs (Toxicogenomics Project-Genomics Assisted Toxicity Evaluation system) database. Data mining highlights four genes-EGR1, ATF3, GDF15 and FGF21-that are induced 2 h after drug administration in human and rat primary hepatocytes poised to eventually undergo cytotoxicity-induced cell death. Modelling and simulation reveals that these early stress-response genes form a functional network with evolutionarily conserved structure and intrinsic dynamics. This is underlined by the fact that early induction of this network in vivo predicts drug-induced liver and kidney pathology with high accuracy. Our findings demonstrate the value of early gene-expression signatures in predicting and understanding compound-induced toxicity. The identified network can empower first-line tests that reduce animal use and costs of safety evaluation.

Microbial signatures of oral dysbiosis, periodontitis and edentulism revealed by Gene Meter methodology.

PubMed

Hunter, M Colby; Pozhitkov, Alex E; Noble, Peter A

2016-12-01

Conceptual models suggest that certain microorganisms (e.g., the "red" complex) are indicative of a specific disease state (e.g., periodontitis); however, recent studies have questioned the validity of these models. Here, the abundances of 500+ microbial species were determined in 16 patients with clinical signs of one of the following oral conditions: periodontitis, established caries, edentulism, and oral health. Our goal was to determine if the abundances of certain microorganisms reflect dysbiosis or a specific clinical condition that could be used as a 'signature' for dental research. Microbial abundances were determined by the analysis of 138,718 calibrated probes using Gene Meter methodology. Each 16S rRNA gene was targeted by an average of 194 unique probes (n=25nt). The calibration involved diluting pooled gene target samples, hybridizing each dilution to a DNA microarray, and fitting the probe intensities to adsorption models. The fit of the model to the experimental data was used to assess individual and aggregate probe behavior; good fits (R 2 >0.90) were retained for back-calculating microbial abundances from patient samples. The abundance of a gene was determined from the median of all calibrated individual probes or from the calibrated abundance of all aggregated probes. With the exception of genes with low abundances (<2 arbitrary units), the abundances determined by the different calibrations were highly correlated (r~1.0). Seventeen genera were classified as 'signatures of dysbiosis' because they had significantly higher abundances in patients with periodontitis and edentulism when contrasted with health. Similarly, 13 genera were classified as 'signatures of periodontitis', and 14 genera were classified as 'signatures of edentulism'. The signatures could be used, individually or in combination, to assess the clinical status of a patient (e.g., evaluating treatments such as antibiotic therapies). Comparisons of the same patient samples revealed

Exploring the molecular mechanisms of Traditional Chinese Medicine components using gene expression signatures and connectivity map.

PubMed

Yoo, Minjae; Shin, Jimin; Kim, Hyunmin; Kim, Jihye; Kang, Jaewoo; Tan, Aik Choon

2018-04-04

Traditional Chinese Medicine (TCM) has been practiced over thousands of years in China and other Asian countries for treating various symptoms and diseases. However, the underlying molecular mechanisms of TCM are poorly understood, partly due to the "multi-component, multi-target" nature of TCM. To uncover the molecular mechanisms of TCM, we perform comprehensive gene expression analysis using connectivity map. We interrogated gene expression signatures obtained 102 TCM components using the next generation Connectivity Map (CMap) resource. We performed systematic data mining and analysis on the mechanism of action (MoA) of these TCM components based on the CMap results. We clustered the 102 TCM components into four groups based on their MoAs using next generation CMap resource. We performed gene set enrichment analysis on these components to provide additional supports for explaining these molecular mechanisms. We also provided literature evidence to validate the MoAs identified through this bioinformatics analysis. Finally, we developed the Traditional Chinese Medicine Drug Repurposing Hub (TCM Hub) - a connectivity map resource to facilitate the elucidation of TCM MoA for drug repurposing research. TCMHub is freely available in http://tanlab.ucdenver.edu/TCMHub. Molecular mechanisms of TCM could be uncovered by using gene expression signatures and connectivity map. Through this analysis, we identified many of the TCM components possess diverse MoAs, this may explain the applications of TCM in treating various symptoms and diseases. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

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.

Microarray-based gene expression profiling in patients with cryopyrin-associated periodic syndromes defines a disease-related signature and IL-1-responsive transcripts

PubMed Central

Balow, James E; Ryan, John G; Chae, Jae Jin; Booty, Matthew G; Bulua, Ariel; Stone, Deborah; Sun, Hong-Wei; Greene, James; Barham, Beverly; Goldbach-Mansky, Raphaela; Kastner, Daniel L; Aksentijevich, Ivona

2014-01-01

Objective To analyse gene expression patterns and to define a specific gene expression signature in patients with the severe end of the spectrum of cryopyrin-associated periodic syndromes (CAPS). The molecular consequences of interleukin 1 inhibition were examined by comparing gene expression patterns in 16 CAPS patients before and after treatment with anakinra. Methods We collected peripheral blood mononuclear cells from 22 CAPS patients with active disease and from 14 healthy children. Transcripts that passed stringent filtering criteria (p values ≤ false discovery rate 1%) were considered as differentially expressed genes (DEG). A set of DEG was validated by quantitative reverse transcription PCR and functional studies with primary cells from CAPS patients and healthy controls. We used 17 CAPS and 66 non-CAPS patient samples to create a set of gene expression models that differentiates CAPS patients from controls and from patients with other autoinflammatory conditions. Results Many DEG include transcripts related to the regulation of innate and adaptive immune responses, oxidative stress, cell death, cell adhesion and motility. A set of gene expression-based models comprising the CAPS-specific gene expression signature correctly classified all 17 samples from an independent dataset. This classifier also correctly identified 15 of 16 postanakinra CAPS samples despite the fact that these CAPS patients were in clinical remission. Conclusions We identified a gene expression signature that clearly distinguished CAPS patients from controls. A number of DEG were in common with other systemic inflammatory diseases such as systemic onset juvenile idiopathic arthritis. The CAPS-specific gene expression classifiers also suggest incomplete suppression of inflammation at low doses of anakinra. PMID:23223423

Integrative ChIP-seq/Microarray Analysis Identifies a CTNNB1 Target Signature Enriched in Intestinal Stem Cells and Colon Cancer

PubMed Central

Watanabe, Kazuhide; Biesinger, Jacob; Salmans, Michael L.; Roberts, Brian S.; Arthur, William T.; Cleary, Michele; Andersen, Bogi; Xie, Xiaohui; Dai, Xing

2014-01-01

Background Deregulation of canonical Wnt/CTNNB1 (beta-catenin) pathway is one of the earliest events in the pathogenesis of colon cancer. Mutations in APC or CTNNB1 are highly frequent in colon cancer and cause aberrant stabilization of CTNNB1, which activates the transcription of Wnt target genes by binding to chromatin via the TCF/LEF transcription factors. Here we report an integrative analysis of genome-wide chromatin occupancy of CTNNB1 by chromatin immunoprecipitation coupled with high-throughput sequencing (ChIP-seq) and gene expression profiling by microarray analysis upon RNAi-mediated knockdown of CTNNB1 in colon cancer cells. Results We observed 3629 CTNNB1 binding peaks across the genome and a significant correlation between CTNNB1 binding and knockdown-induced gene expression change. Our integrative analysis led to the discovery of a direct Wnt target signature composed of 162 genes. Gene ontology analysis of this signature revealed a significant enrichment of Wnt pathway genes, suggesting multiple feedback regulations of the pathway. We provide evidence that this gene signature partially overlaps with the Lgr5+ intestinal stem cell signature, and is significantly enriched in normal intestinal stem cells as well as in clinical colorectal cancer samples. Interestingly, while the expression of the CTNNB1 target gene set does not correlate with survival, elevated expression of negative feedback regulators within the signature predicts better prognosis. Conclusion Our data provide a genome-wide view of chromatin occupancy and gene regulation of Wnt/CTNNB1 signaling in colon cancer cells. PMID:24651522

A Microbial Signature Approach to Identify Fecal Pollution in the Waters Off an Urbanized Coast of Lake Michigan

PubMed Central

Newton, Ryan J.; Bootsma, Melinda J.; Morrison, Hilary G.; Sogin, Mitchell L.

2014-01-01

Urban coasts receive watershed drainage from ecosystems that include highly developed lands with sewer and stormwater infrastructure. In these complex ecosystems, coastal waters are often contaminated with fecal pollution, where multiple delivery mechanisms that often contain multiple fecal sources make it difficult to mitigate the pollution. Here, we exploit bacterial community sequencing of the V6 and V6V4 hypervariable regions of the bacterial 16S rRNA gene to identify bacterial distributions that signal the presence of sewer, fecal, and human fecal pollution. The sequences classified to three sewer infrastructure-associated bacterial genera, Acinetobacter, Arcobacter, and Trichococcus, and five fecal-associated bacterial families, Bacteroidaceae, Porphyromonadaceae, Clostridiaceae, Lachnospiraceae, and Ruminococcaceae, served as signatures of sewer and fecal contamination, respectively. The human fecal signature was determined with the Bayesian source estimation program SourceTracker, which we applied to a set of 40 sewage influent samples collected in Milwaukee, WI, USA to identify operational taxonomic units (≥97 % identity) that were most likely of human fecal origin. During periods of dry weather, the magnitudes of all three signatures were relatively low in Milwaukee's urban rivers and harbor and nearly zero in Lake Michigan. However, the relative contribution of the sewer and fecal signature frequently increased to >2 % of the measured surface water communities following sewer overflows. Also during combined sewer overflows, the ratio of the human fecal pollution signature to the fecal pollution signature in surface waters was generally close to that of sewage, but this ratio decreased dramatically during dry weather and rain events, suggesting that nonhuman fecal pollution was the dominant source during these weather-driven scenarios. The qPCR detection of two human fecal indicators, human Bacteroides and Lachno2, confirmed the urban fecal footprint in

ArrayVigil: a methodology for statistical comparison of gene signatures using segregated-one-tailed (SOT) Wilcoxon's signed-rank test.

PubMed

Khan, Haseeb Ahmad

2005-01-28

Due to versatile diagnostic and prognostic fidelity molecular signatures or fingerprints are anticipated as the most powerful tools for cancer management in the near future. Notwithstanding the experimental advancements in microarray technology, methods for analyzing either whole arrays or gene signatures have not been firmly established. Recently, an algorithm, ArraySolver has been reported by Khan for two-group comparison of microarray gene expression data using two-tailed Wilcoxon signed-rank test. Most of the molecular signatures are composed of two sets of genes (hybrid signatures) wherein up-regulation of one set and down-regulation of the other set collectively define the purpose of a gene signature. Since the direction of a selected gene's expression (positive or negative) with respect to a particular disease condition is known, application of one-tailed statistics could be a more relevant choice. A novel method, ArrayVigil, is described for comparing hybrid signatures using segregated-one-tailed (SOT) Wilcoxon signed-rank test and the results compared with integrated-two-tailed (ITT) procedures (SPSS and ArraySolver). ArrayVigil resulted in lower P values than those obtained from ITT statistics while comparing real data from four signatures.

Distinct Host Tropism Protein Signatures to Identify Possible Zoonotic Influenza A Viruses.

PubMed

Eng, Christine L P; Tong, Joo Chuan; Tan, Tin Wee

2016-01-01

Zoonotic influenza A viruses constantly pose a health threat to humans as novel strains occasionally emerge from the avian population to cause human infections. Many past epidemic as well as pandemic strains have originated from avian species. While most viruses are restricted to their primary hosts, zoonotic strains can sometimes arise from mutations or reassortment, leading them to acquire the capability to escape host species barrier and successfully infect a new host. Phylogenetic analyses and genetic markers are useful in tracing the origins of zoonotic infections, but there are still no effective means to identify high risk strains prior to an outbreak. Here we show that distinct host tropism protein signatures can be used to identify possible zoonotic strains in avian species which have the potential to cause human infections. We have discovered that influenza A viruses can now be classified into avian, human, or zoonotic strains based on their host tropism protein signatures. Analysis of all influenza A viruses with complete proteome using the host tropism prediction system, based on machine learning classifications of avian and human viral proteins has uncovered distinct signatures of zoonotic strains as mosaics of avian and human viral proteins. This is in contrast with typical avian or human strains where they show mostly avian or human viral proteins in their signatures respectively. Moreover, we have found that zoonotic strains from the same influenza outbreaks carry similar host tropism protein signatures characteristic of a common ancestry. Our results demonstrate that the distinct host tropism protein signature in zoonotic strains may prove useful in influenza surveillance to rapidly identify potential high risk strains circulating in avian species, which may grant us the foresight in anticipating an impending influenza outbreak.

Transcriptome profiling reveals novel BMI- and sex-specific gene expression signatures for human cardiac hypertrophy.

PubMed

Newman, Mackenzie S; Nguyen, Tina; Watson, Michael J; Hull, Robert W; Yu, Han-Gang

2017-07-01

How obesity or sex may affect the gene expression profiles of human cardiac hypertrophy is unknown. We hypothesized that body-mass index (BMI) and sex can affect gene expression profiles of cardiac hypertrophy. Human heart tissues were grouped according to sex (male, female), BMI (lean<25 kg/m 2 , obese>30 kg/m 2 ), or left ventricular hypertrophy (LVH) and non-LVH nonfailed controls (NF). We identified 24 differentially expressed (DE) genes comparing female with male samples. In obese subgroup, there were 236 DE genes comparing LVH with NF; in lean subgroup, there were seven DE genes comparing LVH with NF. In female subgroup, we identified 1,320 significant genes comparing LVH with NF; in male subgroup, there were 1,383 significant genes comparing LVH with NF. There were seven significant genes comparing obese LVH with lean NF; comparing male obese LVH with male lean NF samples we found 106 significant genes; comparing female obese LVH with male lean NF, we found no significant genes. Using absolute value of log 2 fold-change > 2 or extremely small P value (10 -20 ) as a criterion, we identified nine significant genes (HBA1, HBB, HIST1H2AC, GSTT1, MYL7, NPPA, NPPB, PDK4, PLA2G2A) in LVH, also found in published data set for ischemic and dilated cardiomyopathy in heart failure. We identified a potential gene expression signature that distinguishes between patients with high BMI or between men and women with cardiac hypertrophy. Expression of established biomarkers atrial natriuretic peptide A (NPPA) and B (NPPB) were already significantly increased in hypertrophy compared with controls. Copyright © 2017 the American Physiological Society.

Saliva Microbiota Carry Caries-Specific Functional Gene Signatures

PubMed Central

Chang, Xingzhi; Yuan, Xiao; Tu, Qichao; Yuan, Tong; Deng, Ye; Hemme, Christopher L.; Van Nostrand, Joy; Cui, Xinping; He, Zhili; Chen, Zhenggang; Guo, Dawei; Yu, Jiangbo; Zhang, Yue; Zhou, Jizhong; Xu, Jian

2014-01-01

Human saliva microbiota is phylogenetically divergent among host individuals yet their roles in health and disease are poorly appreciated. We employed a microbial functional gene microarray, HuMiChip 1.0, to reconstruct the global functional profiles of human saliva microbiota from ten healthy and ten caries-active adults. Saliva microbiota in the pilot population featured a vast diversity of functional genes. No significant distinction in gene number or diversity indices was observed between healthy and caries-active microbiota. However, co-presence network analysis of functional genes revealed that caries-active microbiota was more divergent in non-core genes than healthy microbiota, despite both groups exhibited a similar degree of conservation at their respective core genes. Furthermore, functional gene structure of saliva microbiota could potentially distinguish caries-active patients from healthy hosts. Microbial functions such as Diaminopimelate epimerase, Prephenate dehydrogenase, Pyruvate-formate lyase and N-acetylmuramoyl-L-alanine amidase were significantly linked to caries. Therefore, saliva microbiota carried disease-associated functional signatures, which could be potentially exploited for caries diagnosis. PMID:24533043

Saliva microbiota carry caries-specific functional gene signatures.

PubMed

Yang, Fang; Ning, Kang; Chang, Xingzhi; Yuan, Xiao; Tu, Qichao; Yuan, Tong; Deng, Ye; Hemme, Christopher L; Van Nostrand, Joy; Cui, Xinping; He, Zhili; Chen, Zhenggang; Guo, Dawei; Yu, Jiangbo; Zhang, Yue; Zhou, Jizhong; Xu, Jian

2014-01-01

Human saliva microbiota is phylogenetically divergent among host individuals yet their roles in health and disease are poorly appreciated. We employed a microbial functional gene microarray, HuMiChip 1.0, to reconstruct the global functional profiles of human saliva microbiota from ten healthy and ten caries-active adults. Saliva microbiota in the pilot population featured a vast diversity of functional genes. No significant distinction in gene number or diversity indices was observed between healthy and caries-active microbiota. However, co-presence network analysis of functional genes revealed that caries-active microbiota was more divergent in non-core genes than healthy microbiota, despite both groups exhibited a similar degree of conservation at their respective core genes. Furthermore, functional gene structure of saliva microbiota could potentially distinguish caries-active patients from healthy hosts. Microbial functions such as Diaminopimelate epimerase, Prephenate dehydrogenase, Pyruvate-formate lyase and N-acetylmuramoyl-L-alanine amidase were significantly linked to caries. Therefore, saliva microbiota carried disease-associated functional signatures, which could be potentially exploited for caries diagnosis.

Transforming RNA-Seq data to improve the performance of prognostic gene signatures.

PubMed

Zwiener, Isabella; Frisch, Barbara; Binder, Harald

2014-01-01

Gene expression measurements have successfully been used for building prognostic signatures, i.e for identifying a short list of important genes that can predict patient outcome. Mostly microarray measurements have been considered, and there is little advice available for building multivariable risk prediction models from RNA-Seq data. We specifically consider penalized regression techniques, such as the lasso and componentwise boosting, which can simultaneously consider all measurements and provide both, multivariable regression models for prediction and automated variable selection. However, they might be affected by the typical skewness, mean-variance-dependency or extreme values of RNA-Seq covariates and therefore could benefit from transformations of the latter. In an analytical part, we highlight preferential selection of covariates with large variances, which is problematic due to the mean-variance dependency of RNA-Seq data. In a simulation study, we compare different transformations of RNA-Seq data for potentially improving detection of important genes. Specifically, we consider standardization, the log transformation, a variance-stabilizing transformation, the Box-Cox transformation, and rank-based transformations. In addition, the prediction performance for real data from patients with kidney cancer and acute myeloid leukemia is considered. We show that signature size, identification performance, and prediction performance critically depend on the choice of a suitable transformation. Rank-based transformations perform well in all scenarios and can even outperform complex variance-stabilizing approaches. Generally, the results illustrate that the distribution and potential transformations of RNA-Seq data need to be considered as a critical step when building risk prediction models by penalized regression techniques.

Transforming RNA-Seq Data to Improve the Performance of Prognostic Gene Signatures

PubMed Central

Zwiener, Isabella; Frisch, Barbara; Binder, Harald

2014-01-01

Gene expression measurements have successfully been used for building prognostic signatures, i.e for identifying a short list of important genes that can predict patient outcome. Mostly microarray measurements have been considered, and there is little advice available for building multivariable risk prediction models from RNA-Seq data. We specifically consider penalized regression techniques, such as the lasso and componentwise boosting, which can simultaneously consider all measurements and provide both, multivariable regression models for prediction and automated variable selection. However, they might be affected by the typical skewness, mean-variance-dependency or extreme values of RNA-Seq covariates and therefore could benefit from transformations of the latter. In an analytical part, we highlight preferential selection of covariates with large variances, which is problematic due to the mean-variance dependency of RNA-Seq data. In a simulation study, we compare different transformations of RNA-Seq data for potentially improving detection of important genes. Specifically, we consider standardization, the log transformation, a variance-stabilizing transformation, the Box-Cox transformation, and rank-based transformations. In addition, the prediction performance for real data from patients with kidney cancer and acute myeloid leukemia is considered. We show that signature size, identification performance, and prediction performance critically depend on the choice of a suitable transformation. Rank-based transformations perform well in all scenarios and can even outperform complex variance-stabilizing approaches. Generally, the results illustrate that the distribution and potential transformations of RNA-Seq data need to be considered as a critical step when building risk prediction models by penalized regression techniques. PMID:24416353

Gene expression signatures differentiate ovarian/peritoneal serous carcinoma from breast carcinoma in effusions

PubMed Central

Davidson, Ben; Stavnes, Helene Tuft; Holth, Arild; Chen, Xu; Yang, Yanqin; Shih, Ie-Ming; Wang, Tian-Li

2011-01-01

Abstract Ovarian/primary peritoneal carcinoma and breast carcinoma are the gynaecological cancers that most frequently involve the serosal cavities. With the objective of improving on the limited diagnostic panel currently available for the differential diagnosis of these two malignancies, as well as to define tumour-specific biological targets, we compared their global gene expression patterns. Gene expression profiles of 10 serous ovarian/peritoneal and eight ductal breast carcinoma effusions were analysed using the HumanRef-8 BeadChip from Illumina. Differentially expressed candidate genes were validated using quantitative real-time PCR and immunohistochemistry. Unsupervised hierarchical clustering using all 54,675 genes in the array separated ovarian from breast carcinoma samples. We identified 288 unique probes that were significantly differentially expressed in the two cancers by greater than 3.5-fold, of which 81 and 207 were overexpressed in breast and ovarian/peritoneal carcinoma, respectively. SAM analysis identified 1078 differentially expressed probes with false discovery rate less than 0.05. Genes overexpressed in breast carcinoma included TFF1, TFF3, FOXA1, CA12, GATA3, SDC1, PITX1, TH, EHFD1, EFEMP1, TOB1 and KLF2. Genes overexpressed in ovarian/peritoneal carcinoma included SPON1, RBP1, MFGE8, TM4SF12, MMP7, KLK5/6/7, FOLR1/3, PAX8, APOL2 and NRCAM. The differential expression of 14 genes was validated by quantitative real-time PCR, and differences in 5 gene products were confirmed by immunohistochemistry. Expression profiling distinguishes ovarian/peritoneal carcinoma from breast carcinoma and identifies genes that are differentially expressed in these two tumour types. The molecular signatures unique to these cancers may facilitate their differential diagnosis and may provide a molecular basis for therapeutic target discovery. PMID:20132413

Association of a cytarabine chemosensitivity related gene expression signature with survival in cytogenetically normal acute myeloid leukemia.

PubMed

Yan, Han; Wen, Lu; Tan, Dan; Xie, Pan; Pang, Feng-Mei; Zhou, Hong-Hao; Zhang, Wei; Liu, Zhao-Qian; Tang, Jie; Li, Xi; Chen, Xiao-Ping

2017-01-03

The prognosis of cytogenetically normal acute myeloid leukemia (CN-AML) varies greatly among patients. Achievement of complete remission (CR) after chemotherapy is indispensable for a better prognosis. To develop a gene signature predicting overall survival (OS) in CN-AML, we performed data mining procedure based on whole genome expression data of both blood cancer cell lines and AML patients from open access database. A gene expression signature including 42 probes was derived. These probes were significantly associated with both cytarabine half maximal inhibitory concentration values in blood cancer cell lines and OS in CN-AML patients. By using cox regression analysis and linear regression analysis, a chemo-sensitive score calculated algorithm based on mRNA expression levels of the 42 probes was established. The scores were associated with OS in both the training sample (p=5.13 × 10-4, HR=2.040, 95% CI: 1.364-3.051) and the validation sample (p=0.002, HR=2.528, 95% CI: 1.393-4.591) of the GSE12417 dataset from Gene Expression Omnibus. In The Cancer Genome Atlas (TCGA) CN-AML patients, higher scores were found to be associated with both worse OS (p=0.013, HR=2.442, 95% CI: 1.205-4.950) and DFS (p=0.015, HR=2.376, 95% CI: 1.181-4.779). Results of gene ontology (GO) analysis showed that all the significant GO Terms were correlated with cellular component of mitochondrion. In summary, a novel gene set that could predict prognosis of CN-AML was identified presently, which provided a new way to identify genes impacting AML chemo-sensitivity and prognosis.

Association of a cytarabine chemosensitivity related gene expression signature with survival in cytogenetically normal acute myeloid leukemia

PubMed Central

Yan, Han; Wen, Lu; Tan, Dan; Xie, Pan; Pang, Feng-mei; Zhou, Hong-hao; Zhang, Wei; Liu, Zhao-qian; Tang, Jie; Li, Xi; Chen, Xiao-ping

2017-01-01

The prognosis of cytogenetically normal acute myeloid leukemia (CN-AML) varies greatly among patients. Achievement of complete remission (CR) after chemotherapy is indispensable for a better prognosis. To develop a gene signature predicting overall survival (OS) in CN-AML, we performed data mining procedure based on whole genome expression data of both blood cancer cell lines and AML patients from open access database. A gene expression signature including 42 probes was derived. These probes were significantly associated with both cytarabine half maximal inhibitory concentration values in blood cancer cell lines and OS in CN-AML patients. By using cox regression analysis and linear regression analysis, a chemo-sensitive score calculated algorithm based on mRNA expression levels of the 42 probes was established. The scores were associated with OS in both the training sample (p=5.13 × 10−4, HR=2.040, 95% CI: 1.364-3.051) and the validation sample (p=0.002, HR=2.528, 95% CI: 1.393-4.591) of the GSE12417 dataset from Gene Expression Omnibus. In The Cancer Genome Atlas (TCGA) CN-AML patients, higher scores were found to be associated with both worse OS (p=0.013, HR=2.442, 95% CI: 1.205-4.950) and DFS (p=0.015, HR=2.376, 95% CI: 1.181-4.779). Results of gene ontology (GO) analysis showed that all the significant GO Terms were correlated with cellular component of mitochondrion. In summary, a novel gene set that could predict prognosis of CN-AML was identified presently, which provided a new way to identify genes impacting AML chemo-sensitivity and prognosis. PMID:27903973

Glioma IL13Rα2 Is Associated with Mesenchymal Signature Gene Expression and Poor Patient Prognosis

PubMed Central

Starr, Renate; Deng, Xutao; Badie, Behnam; Yuan, Yate-Ching; Forman, Stephen J.; Barish, Michael E.

2013-01-01

A major challenge for successful immunotherapy against glioma is the identification and characterization of validated targets. We have taken a bioinformatics approach towards understanding the biological context of IL-13 receptor α2 (IL13Rα2) expression in brain tumors, and its functional significance for patient survival. Querying multiple gene expression databases, we show that IL13Rα2 expression increases with glioma malignancy grade, and expression for high-grade tumors is bimodal, with approximately 58% of WHO grade IV gliomas over-expressing this receptor. By several measures, IL13Rα2 expression in patient samples and low-passage primary glioma lines most consistently correlates with the expression of signature genes defining mesenchymal subclass tumors and negatively correlates with proneural signature genes as defined by two studies. Positive associations were also noted with proliferative signature genes, whereas no consistent associations were found with either classical or neural signature genes. Probing the potential functional consequences of this mesenchymal association through IPA analysis suggests that IL13Rα2 expression is associated with activation of proinflammatory and immune pathways characteristic of mesenchymal subclass tumors. In addition, survival analyses indicate that IL13Rα2 over-expression is associated with poor patient prognosis, a single gene correlation ranking IL13Rα2 in the top ~1% of total gene expression probes with regard to survival association with WHO IV gliomas. This study better defines the functional consequences of IL13Rα2 expression by demonstrating association with mesenchymal signature gene expression and poor patient prognosis. It thus highlights the utility of IL13Rα2 as a therapeutic target, and helps define patient populations most likely to respond to immunotherapy in present and future clinical trials. PMID:24204956

Glioma IL13Rα2 is associated with mesenchymal signature gene expression and poor patient prognosis.

PubMed

Brown, Christine E; Warden, Charles D; Starr, Renate; Deng, Xutao; Badie, Behnam; Yuan, Yate-Ching; Forman, Stephen J; Barish, Michael E

2013-01-01

A major challenge for successful immunotherapy against glioma is the identification and characterization of validated targets. We have taken a bioinformatics approach towards understanding the biological context of IL-13 receptor α2 (IL13Rα2) expression in brain tumors, and its functional significance for patient survival. Querying multiple gene expression databases, we show that IL13Rα2 expression increases with glioma malignancy grade, and expression for high-grade tumors is bimodal, with approximately 58% of WHO grade IV gliomas over-expressing this receptor. By several measures, IL13Rα2 expression in patient samples and low-passage primary glioma lines most consistently correlates with the expression of signature genes defining mesenchymal subclass tumors and negatively correlates with proneural signature genes as defined by two studies. Positive associations were also noted with proliferative signature genes, whereas no consistent associations were found with either classical or neural signature genes. Probing the potential functional consequences of this mesenchymal association through IPA analysis suggests that IL13Rα2 expression is associated with activation of proinflammatory and immune pathways characteristic of mesenchymal subclass tumors. In addition, survival analyses indicate that IL13Rα2 over-expression is associated with poor patient prognosis, a single gene correlation ranking IL13Rα2 in the top ~1% of total gene expression probes with regard to survival association with WHO IV gliomas. This study better defines the functional consequences of IL13Rα2 expression by demonstrating association with mesenchymal signature gene expression and poor patient prognosis. It thus highlights the utility of IL13Rα2 as a therapeutic target, and helps define patient populations most likely to respond to immunotherapy in present and future clinical trials.

Human melanomas and ovarian cancers overexpressing mechanical barrier molecule genes lack immune signatures and have increased patient mortality risk

PubMed Central

Salerno, Elise P.; Bedognetti, Davide; Mauldin, Ileana S.; Deacon, Donna H.; Shea, Sofia M.; Obeid, Joseph M.; Coukos, George; Gajewski, Thomas F.; Marincola, Francesco M.; Slingluff, Craig L.

2016-01-01

ABSTRACT We have identified eight genes whose expression in human melanoma metastases and ovarian cancers is associated with a lack of Th1 immune signatures. They encode molecules with mechanical barrier function in the skin and other normal tissues and include filaggrin (FLG), tumor-associated calcium signal transducer 2 (TACSTD2), and six desmosomal proteins (DST, DSC3, DSP, PPL, PKP3, and JUP). This association has been validated in an independent series of 114 melanoma metastases. In these, DST expression alone is sufficient to identify melanomas without immune signatures, while FLG and the other six putative barrier molecules are overexpressed in a different subset of melanomas lacking immune signatures. Similar associations have been identified in a set of 186 ovarian cancers. RNA-seq data from 471 melanomas and 307 ovarian cancers in the TCGA database further support these findings and also reveal that overexpression of barrier molecules is strongly associated with early patient mortality for melanoma (p = 0.0002) and for ovarian cancer (p < 0.01). Interestingly, this association persists for FLG for melanoma (p = 0.012) and ovarian cancer (p = 0.006), whereas DST overexpression is negatively associated with CD8+ gene expression, but not with patient survival. Thus, overexpression of FLG or DST identifies two distinct patient populations with low immune cell infiltration in these cancers, but with different prognostic implications for each. These data raise the possibility that molecules with mechanical barrier function in skin and other tissues may be used by cancer cells to protect them from immune cell infiltration and immune-mediated destruction. PMID:28123876

Genetically diverse CC-founder mouse strains replicate the human influenza gene expression signature.

PubMed

Elbahesh, Husni; Schughart, Klaus

2016-05-19

Influenza A viruses (IAV) are zoonotic pathogens that pose a major threat to human and animal health. Influenza virus disease severity is influenced by viral virulence factors as well as individual differences in host response. We analyzed gene expression changes in the blood of infected mice using a previously defined set of signature genes that was derived from changes in the blood transcriptome of IAV-infected human volunteers. We found that the human signature was reproduced well in the founder strains of the Collaborative Cross (CC) mice, thus demonstrating the relevance and importance of mouse experimental model systems for studying human influenza disease.

An independent validation of a gene expression signature to differentiate malignant melanoma from benign melanocytic nevi.

PubMed

Clarke, Loren E; Flake, Darl D; Busam, Klaus; Cockerell, Clay; Helm, Klaus; McNiff, Jennifer; Reed, Jon; Tschen, Jaime; Kim, Jinah; Barnhill, Raymond; Elenitsas, Rosalie; Prieto, Victor G; Nelson, Jonathan; Kimbrell, Hillary; Kolquist, Kathryn A; Brown, Krystal L; Warf, M Bryan; Roa, Benjamin B; Wenstrup, Richard J

2017-02-15

Recently, a 23-gene signature was developed to produce a melanoma diagnostic score capable of differentiating malignant and benign melanocytic lesions. The primary objective of this study was to independently assess the ability of the gene signature to differentiate melanoma from benign nevi in clinically relevant lesions. A set of 1400 melanocytic lesions was selected from samples prospectively submitted for gene expression testing at a clinical laboratory. Each sample was tested and subjected to an independent histopathologic evaluation by 3 experienced dermatopathologists. A primary diagnosis (benign or malignant) was assigned to each sample, and diagnostic concordance among the 3 dermatopathologists was required for inclusion in analyses. The sensitivity and specificity of the score in differentiating benign and malignant melanocytic lesions were calculated to assess the association between the score and the pathologic diagnosis. The gene expression signature differentiated benign nevi from malignant melanoma with a sensitivity of 91.5% and a specificity of 92.5%. These results reflect the performance of the gene signature in a diverse array of samples encountered in routine clinical practice. Cancer 2017;123:617-628. © 2016 American Cancer Society. © 2016 Myriad Genetics, Inc. Cancer published by Wiley Periodicals, Inc. on behalf of American Cancer Society.

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

An extended data mining method for identifying differentially expressed assay-specific signatures in functional genomic studies.

PubMed

Rollins, Derrick K; Teh, Ailing

2010-12-17

Microarray data sets provide relative expression levels for thousands of genes for a small number, in comparison, of different experimental conditions called assays. Data mining techniques are used to extract specific information of genes as they relate to the assays. The multivariate statistical technique of principal component analysis (PCA) has proven useful in providing effective data mining methods. This article extends the PCA approach of Rollins et al. to the development of ranking genes of microarray data sets that express most differently between two biologically different grouping of assays. This method is evaluated on real and simulated data and compared to a current approach on the basis of false discovery rate (FDR) and statistical power (SP) which is the ability to correctly identify important genes. This work developed and evaluated two new test statistics based on PCA and compared them to a popular method that is not PCA based. Both test statistics were found to be effective as evaluated in three case studies: (i) exposing E. coli cells to two different ethanol levels; (ii) application of myostatin to two groups of mice; and (iii) a simulated data study derived from the properties of (ii). The proposed method (PM) effectively identified critical genes in these studies based on comparison with the current method (CM). The simulation study supports higher identification accuracy for PM over CM for both proposed test statistics when the gene variance is constant and for one of the test statistics when the gene variance is non-constant. PM compares quite favorably to CM in terms of lower FDR and much higher SP. Thus, PM can be quite effective in producing accurate signatures from large microarray data sets for differential expression between assays groups identified in a preliminary step of the PCA procedure and is, therefore, recommended for use in these applications.

Age gene expression and coexpression progressive signatures in peripheral blood leukocytes.

PubMed

Irizar, Haritz; Goñi, Joaquín; Alzualde, Ainhoa; Castillo-Triviño, Tamara; Olascoaga, Javier; Lopez de Munain, Adolfo; Otaegui, David

2015-12-01

Both cellular senescence and organismic aging are known to be dynamic processes that start early in life and progress constantly during the whole life of the individual. In this work, with the objective of identifying signatures of age-related progressive change at the transcriptomic level, we have performed a whole-genome gene expression analysis of peripheral blood leukocytes in a group of healthy individuals with ages ranging from 14 to 93 years. A set of genes with progressively changing gene expression (either increase or decrease with age) has been identified and contextualized in a coexpression network. A modularity analysis has been performed on this network and biological-term and pathway enrichment analyses have been used for biological interpretation of each module. In summary, the results of the present work reveal the existence of a transcriptomic component that shows progressive expression changes associated to age in peripheral blood leukocytes, highlighting both the dynamic nature of the process and the need to complement young vs. elder studies with longitudinal studies that include middle aged individuals. From the transcriptional point of view, immunosenescence seems to be occurring from a relatively early age, at least from the late 20s/early 30s, and the 49-56 year old age-range appears to be critical. In general, the genes that, according to our results, show progressive expression changes with aging are involved in pathogenic/cellular processes that have classically been linked to aging in humans: cancer, immune processes and cellular growth vs. maintenance. Copyright © 2015 Elsevier Inc. All rights reserved.

A radiosensitivity gene signature and PD-L1 status predict clinical outcome of patients with invasive breast carcinoma in The Cancer Genome Atlas (TCGA) dataset.

PubMed

Jang, Bum-Sup; Kim, In Ah

2017-09-01

We investigated the link between the radiosensitivity gene signature and programmed cell death ligand 1 (PD-L1) status and clinical outcome in order to identify a group of patients that would possibly receive clinical benefit of radiotherapy (RT) combined with anti-PD1/PD-L1 therapy. We validated the identified gene signature related to radiosensitivity and analyzed the PD-L1 status of invasive breast cancer in The Cancer Genome Atlas (TCGA) dataset. To validate the gene signature, 1045 patients were selected and divided into two clusters using a consensus clustering algorithm based on their radiosensitive (RS) or radioresistant (RR) designation according to their prognosis. Patients were also stratified as PD-L1-high or PD-L1-low based on the median value of CD274 mRNA expression level as surrogates of PD-L1. Patents assigned to the RS group had decreased risk of recurrence-free survival (RFS) rate than patients in the RR group by univariate analysis (HR 0.45, 95% CI 0.25-0.81, p=0.008) only when treated with RT. The RS group was independently associated with the PD-L1-high group, and CD274 mRNA expression was significantly higher in the RS group (p<0.001) than the RR group. In the PD-L1-high group, the RS group was associated with better RFS compared to the RR group (HR 0.37, 95% CI 0.16-0.87, p=0.022) in multivariate analysis. The level of PD-L1 expression may represent the immunogenicity of tumors, and thus, we speculated that the PD-L1-high group had more immunogenic tumors, which could be more sensitive to radiation-induced immunologic cell death. We first evaluated the predictive value of the radiosensitivity gene signature and described a relationship with this radiosensitivity gene signature and PD-L1. The radiosensitivity gene signature and PD-L1 status were important factors for prediction of the clinical outcome of RT in patients with invasive breast cancer and may be used for selecting patients who will benefit from RT combined with anti-PD1/PDL1

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

Sorghum Expressed Sequence Tags Identify Signature Genes for Drought, Pathogenesis, and Skotomorphogenesis from a Milestone Set of 16,801 Unique Transcripts1[w

PubMed Central

Pratt, Lee H.; Liang, Chun; Shah, Manish; Sun, Feng; Wang, Haiming; Reid, St. Patrick; Gingle, Alan R.; Paterson, Andrew H.; Wing, Rod; Dean, Ralph; Klein, Robert; Nguyen, Henry T.; Ma, Hong-mei; Zhao, Xin; Morishige, Daryl T.; Mullet, John E.; Cordonnier-Pratt, Marie-Michèle

2005-01-01

Improved knowledge of the sorghum transcriptome will enhance basic understanding of how plants respond to stresses and serve as a source of genes of value to agriculture. Toward this goal, Sorghum bicolor L. Moench cDNA libraries were prepared from light- and dark-grown seedlings, drought-stressed plants, Colletotrichum-infected seedlings and plants, ovaries, embryos, and immature panicles. Other libraries were prepared with meristems from Sorghum propinquum (Kunth) Hitchc. that had been photoperiodically induced to flower, and with rhizomes from S. propinquum and johnsongrass (Sorghum halepense L. Pers.). A total of 117,682 expressed sequence tags (ESTs) were obtained representing both 3′ and 5′ sequences from about half that number of cDNA clones. A total of 16,801 unique transcripts, representing tentative UniScripts (TUs), were identified from 55,783 3′ ESTs. Of these TUs, 9,032 are represented by two or more ESTs. Collectively, these libraries were predicted to contain a total of approximately 31,000 TUs. Individual libraries, however, were predicted to contain no more than about 6,000 to 9,000, with the exception of light-grown seedlings, which yielded an estimate of close to 13,000. In addition, each library exhibits about the same level of complexity with respect to both the number of TUs preferentially expressed in that library and the frequency with which two or more ESTs is found in only that library. These results indicate that the sorghum genome is expressed in highly selective fashion in the individual organs and in response to the environmental conditions surveyed here. Close to 2,000 differentially expressed TUs were identified among the cDNA libraries examined, of which 775 were differentially expressed at a confidence level of 98%. From these 775 TUs, signature genes were identified defining drought, Colletotrichum infection, skotomorphogenesis (etiolation), ovary, immature panicle, and embryo. PMID:16169961

Delineation of metabolic gene clusters in plant genomes by chromatin signatures

PubMed Central

Yu, Nan; Nützmann, Hans-Wilhelm; MacDonald, James T.; Moore, Ben; Field, Ben; Berriri, Souha; Trick, Martin; Rosser, Susan J.; Kumar, S. Vinod; Freemont, Paul S.; Osbourn, Anne

2016-01-01

Plants are a tremendous source of diverse chemicals, including many natural product-derived drugs. It has recently become apparent that the genes for the biosynthesis of numerous different types of plant natural products are organized as metabolic gene clusters, thereby unveiling a highly unusual form of plant genome architecture and offering novel avenues for discovery and exploitation of plant specialized metabolism. Here we show that these clustered pathways are characterized by distinct chromatin signatures of histone 3 lysine trimethylation (H3K27me3) and histone 2 variant H2A.Z, associated with cluster repression and activation, respectively, and represent discrete windows of co-regulation in the genome. We further demonstrate that knowledge of these chromatin signatures along with chromatin mutants can be used to mine genomes for cluster discovery. The roles of H3K27me3 and H2A.Z in repression and activation of single genes in plants are well known. However, our discovery of highly localized operon-like co-regulated regions of chromatin modification is unprecedented in plants. Our findings raise intriguing parallels with groups of physically linked multi-gene complexes in animals and with clustered pathways for specialized metabolism in filamentous fungi. PMID:26895889

12-Chemokine Gene Signature Identifies Lymph Node-like Structures in Melanoma: Potential for Patient Selection for Immunotherapy?

NASA Astrophysics Data System (ADS)

Messina, Jane L.; Fenstermacher, David A.; Eschrich, Steven; Qu, Xiaotao; Berglund, Anders E.; Lloyd, Mark C.; Schell, Michael J.; Sondak, Vernon K.; Weber, Jeffrey S.; Mulé, James J.

2012-10-01

We have interrogated a 12-chemokine gene expression signature (GES) on genomic arrays of 14,492 distinct solid tumors and show broad distribution across different histologies. We hypothesized that this 12-chemokine GES might accurately predict a unique intratumoral immune reaction in stage IV (non-locoregional) melanoma metastases. The 12-chemokine GES predicted the presence of unique, lymph node-like structures, containing CD20+ B cell follicles with prominent areas of CD3+ T cells (both CD4+ and CD8+ subsets). CD86+, but not FoxP3+, cells were present within these unique structures as well. The direct correlation between the 12-chemokine GES score and the presence of unique, lymph nodal structures was also associated with better overall survival of the subset of melanoma patients. The use of this novel 12-chemokine GES may reveal basic information on in situ mechanisms of the anti-tumor immune response, potentially leading to improvements in the identification and selection of melanoma patients most suitable for immunotherapy.

Testing an aflatoxin B1 gene signature in rat archival tissues.

PubMed

Merrick, B Alex; Auerbach, Scott S; Stockton, Patricia S; Foley, Julie F; Malarkey, David E; Sills, Robert C; Irwin, Richard D; Tice, Raymond R

2012-05-21

Archival tissues from laboratory studies represent a unique opportunity to explore the relationship between genomic changes and agent-induced disease. In this study, we evaluated the applicability of qPCR for detecting genomic changes in formalin-fixed, paraffin-embedded (FFPE) tissues by determining if a subset of 14 genes from a 90-gene signature derived from microarray data and associated with eventual tumor development could be detected in archival liver, kidney, and lung of rats exposed to aflatoxin B1 (AFB1) for 90 days in feed at 1 ppm. These tissues originated from the same rats used in the microarray study. The 14 genes evaluated were Adam8, Cdh13, Ddit4l, Mybl2, Akr7a3, Akr7a2, Fhit, Wwox, Abcb1b, Abcc3, Cxcl1, Gsta5, Grin2c, and the C8orf46 homologue. The qPCR FFPE liver results were compared to the original liver microarray data and to qPCR results using RNA from fresh frozen liver. Archival liver paraffin blocks yielded 30 to 50 μg of degraded RNA that ranged in size from 0.1 to 4 kB. qPCR results from FFPE and fresh frozen liver samples were positively correlated (p ≤ 0.05) by regression analysis and showed good agreement in direction and proportion of change with microarray data for 11 of 14 genes. All 14 transcripts could be amplified from FFPE kidney RNA except the glutamate receptor gene Grin2c; however, only Abcb1b was significantly upregulated from control. Abundant constitutive transcripts, S18 and β-actin, could be amplified from lung FFPE samples, but the narrow RNA size range (25-500 bp length) prevented consistent detection of target transcripts. Overall, a discrete gene signature derived from prior transcript profiling and representing cell cycle progression, DNA damage response, and xenosensor and detoxication pathways was successfully applied to archival liver and kidney by qPCR and indicated that gene expression changes in response to subchronic AFB1 exposure occurred predominantly in the liver, the primary target for AFB1-induced

Transcriptional dissection of melanoma identifies a high-risk subtype underlying TP53 family genes and epigenome deregulation

PubMed Central

Badal, Brateil; Solovyov, Alexander; Di Cecilia, Serena; Chan, Joseph Minhow; Chang, Li-Wei; Iqbal, Ramiz; Aydin, Iraz T.; Rajan, Geena S.; Chen, Chen; Abbate, Franco; Arora, Kshitij S.; Tanne, Antoine; Gruber, Stephen B.; Johnson, Timothy M.; Fullen, Douglas R.; Phelps, Robert; Bhardwaj, Nina; Bernstein, Emily; Ting, David T.; Brunner, Georg; Schadt, Eric E.; Greenbaum, Benjamin D.; Celebi, Julide Tok

2017-01-01

BACKGROUND. Melanoma is a heterogeneous malignancy. We set out to identify the molecular underpinnings of high-risk melanomas, those that are likely to progress rapidly, metastasize, and result in poor outcomes. METHODS. We examined transcriptome changes from benign states to early-, intermediate-, and late-stage tumors using a set of 78 treatment-naive melanocytic tumors consisting of primary melanomas of the skin and benign melanocytic lesions. We utilized a next-generation sequencing platform that enabled a comprehensive analysis of protein-coding and -noncoding RNA transcripts. RESULTS. Gene expression changes unequivocally discriminated between benign and malignant states, and a dual epigenetic and immune signature emerged defining this transition. To our knowledge, we discovered previously unrecognized melanoma subtypes. A high-risk primary melanoma subset was distinguished by a 122-epigenetic gene signature (“epigenetic” cluster) and TP53 family gene deregulation (TP53, TP63, and TP73). This subtype associated with poor overall survival and showed enrichment of cell cycle genes. Noncoding repetitive element transcripts (LINEs, SINEs, and ERVs) that can result in immunostimulatory signals recapitulating a state of “viral mimicry” were significantly repressed. The high-risk subtype and its poor predictive characteristics were validated in several independent cohorts. Additionally, primary melanomas distinguished by specific immune signatures (“immune” clusters) were identified. CONCLUSION. The TP53 family of genes and genes regulating the epigenetic machinery demonstrate strong prognostic and biological relevance during progression of early disease. Gene expression profiling of protein-coding and -noncoding RNA transcripts may be a better predictor for disease course in melanoma. This study outlines the transcriptional interplay of the cancer cell’s epigenome with the immune milieu with potential for future therapeutic targeting. FUNDING

Building gene expression signatures indicative of transcription factor activation to predict AOP modulation

EPA Science Inventory

Building gene expression signatures indicative of transcription factor activation to predict AOP modulation Adverse outcome pathways (AOPs) are a framework for predicting quantitative relationships between molecular initiatin...

Comparison of transcriptomic signature of post-Chernobyl and postradiotherapy thyroid tumors.

PubMed

Ory, Catherine; Ugolin, Nicolas; Hofman, Paul; Schlumberger, Martin; Likhtarev, Illya A; Chevillard, Sylvie

2013-11-01

We previously identified two highly discriminating and predictive radiation-induced transcriptomic signatures by comparing series of sporadic and postradiotherapy thyroid tumors (322-gene signature), and by reanalyzing a previously published data set of sporadic and post-Chernobyl thyroid tumors (106-gene signature). The aim of the present work was (i) to compare the two signatures in terms of gene expression deregulations and molecular features/pathways, and (ii) to test the capacity of the postradiotherapy signature in classifying the post-Chernobyl series of tumors and reciprocally of the post-Chernobyl signature in classifying the postradiotherapy-induced tumors. We now explored if postradiotherapy and post-Chernobyl papillary thyroid carcinomas (PTC) display common molecular features by comparing molecular pathways deregulated in the two tumor series, and tested the potential of gene subsets of the postradiotherapy signature to classify the post-Chernobyl series (14 sporadic and 12 post-Chernobyl PTC), and reciprocally of gene subsets of the post-Chernobyl signature to classify the postradiotherapy series (15 sporadic and 12 postradiotherapy PTC), by using conventional principal component analysis. We found that the five genes common to the two signatures classified the learning/training tumors (used to search these signatures) of both the postradiotherapy (seven PTC) and the post-Chernobyl (six PTC) thyroid tumor series as compared with the sporadic tumors (seven sporadic PTC in each series). Importantly, these five genes were also effective for classifying independent series of postradiotherapy (five PTC) and post-Chernobyl (six PTC) tumors compared to independent series of sporadic tumors (eight PTC and six PTC respectively; testing tumors). Moreover, part of each postradiotherapy (32 genes) and post-Chernobyl signature (16 genes) cross-classified the respective series of thyroid tumors. Finally, several molecular pathways deregulated in post

The Molecular Signatures Database (MSigDB) hallmark gene set collection.

PubMed

Liberzon, Arthur; Birger, Chet; Thorvaldsdóttir, Helga; Ghandi, Mahmoud; Mesirov, Jill P; Tamayo, Pablo

2015-12-23

The Molecular Signatures Database (MSigDB) is one of the most widely used and comprehensive databases of gene sets for performing gene set enrichment analysis. Since its creation, MSigDB has grown beyond its roots in metabolic disease and cancer to include >10,000 gene sets. These better represent a wider range of biological processes and diseases, but the utility of the database is reduced by increased redundancy across, and heterogeneity within, gene sets. To address this challenge, here we use a combination of automated approaches and expert curation to develop a collection of "hallmark" gene sets as part of MSigDB. Each hallmark in this collection consists of a "refined" gene set, derived from multiple "founder" sets, that conveys a specific biological state or process and displays coherent expression. The hallmarks effectively summarize most of the relevant information of the original founder sets and, by reducing both variation and redundancy, provide more refined and concise inputs for gene set enrichment analysis.

Integrating genome-wide association study and expression quantitative trait loci data identifies multiple genes and gene set associated with neuroticism.

PubMed

Fan, Qianrui; Wang, Wenyu; Hao, Jingcan; He, Awen; Wen, Yan; Guo, Xiong; Wu, Cuiyan; Ning, Yujie; Wang, Xi; Wang, Sen; Zhang, Feng

2017-08-01

Neuroticism is a fundamental personality trait with significant genetic determinant. To identify novel susceptibility genes for neuroticism, we conducted an integrative analysis of genomic and transcriptomic data of genome wide association study (GWAS) and expression quantitative trait locus (eQTL) study. GWAS summary data was driven from published studies of neuroticism, totally involving 170,906 subjects. eQTL dataset containing 927,753 eQTLs were obtained from an eQTL meta-analysis of 5311 samples. Integrative analysis of GWAS and eQTL data was conducted by summary data-based Mendelian randomization (SMR) analysis software. To identify neuroticism associated gene sets, the SMR analysis results were further subjected to gene set enrichment analysis (GSEA). The gene set annotation dataset (containing 13,311 annotated gene sets) of GSEA Molecular Signatures Database was used. SMR single gene analysis identified 6 significant genes for neuroticism, including MSRA (p value=2.27×10 -10 ), MGC57346 (p value=6.92×10 -7 ), BLK (p value=1.01×10 -6 ), XKR6 (p value=1.11×10 -6 ), C17ORF69 (p value=1.12×10 -6 ) and KIAA1267 (p value=4.00×10 -6 ). Gene set enrichment analysis observed significant association for Chr8p23 gene set (false discovery rate=0.033). Our results provide novel clues for the genetic mechanism studies of neuroticism. Copyright © 2017. Published by Elsevier Inc.

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

Genetic signatures of natural selection in a model invasive ascidian

NASA Astrophysics Data System (ADS)

Lin, Yaping; Chen, Yiyong; Yi, Changho; Fong, Jonathan J.; Kim, Won; Rius, Marc; Zhan, Aibin

2017-03-01

Invasive species represent promising models to study species’ responses to rapidly changing environments. Although local adaptation frequently occurs during contemporary range expansion, the associated genetic signatures at both population and genomic levels remain largely unknown. Here, we use genome-wide gene-associated microsatellites to investigate genetic signatures of natural selection in a model invasive ascidian, Ciona robusta. Population genetic analyses of 150 individuals sampled in Korea, New Zealand, South Africa and Spain showed significant genetic differentiation among populations. Based on outlier tests, we found high incidence of signatures of directional selection at 19 loci. Hitchhiking mapping analyses identified 12 directional selective sweep regions, and all selective sweep windows on chromosomes were narrow (~8.9 kb). Further analyses indentified 132 candidate genes under selection. When we compared our genetic data and six crucial environmental variables, 16 putatively selected loci showed significant correlation with these environmental variables. This suggests that the local environmental conditions have left significant signatures of selection at both population and genomic levels. Finally, we identified “plastic” genomic regions and genes that are promising regions to investigate evolutionary responses to rapid environmental change in C. robusta.

Genetic signatures of natural selection in a model invasive ascidian

PubMed Central

Lin, Yaping; Chen, Yiyong; Yi, Changho; Fong, Jonathan J.; Kim, Won; Rius, Marc; Zhan, Aibin

2017-01-01

Invasive species represent promising models to study species’ responses to rapidly changing environments. Although local adaptation frequently occurs during contemporary range expansion, the associated genetic signatures at both population and genomic levels remain largely unknown. Here, we use genome-wide gene-associated microsatellites to investigate genetic signatures of natural selection in a model invasive ascidian, Ciona robusta. Population genetic analyses of 150 individuals sampled in Korea, New Zealand, South Africa and Spain showed significant genetic differentiation among populations. Based on outlier tests, we found high incidence of signatures of directional selection at 19 loci. Hitchhiking mapping analyses identified 12 directional selective sweep regions, and all selective sweep windows on chromosomes were narrow (~8.9 kb). Further analyses indentified 132 candidate genes under selection. When we compared our genetic data and six crucial environmental variables, 16 putatively selected loci showed significant correlation with these environmental variables. This suggests that the local environmental conditions have left significant signatures of selection at both population and genomic levels. Finally, we identified “plastic” genomic regions and genes that are promising regions to investigate evolutionary responses to rapid environmental change in C. robusta. PMID:28266616

Pathway-Enriched Gene Signature Associated with 53BP1 Response to PARP Inhibition in Triple-Negative Breast Cancer.

PubMed

Hassan, Saima; Esch, Amanda; Liby, Tiera; Gray, Joe W; Heiser, Laura M

2017-12-01

Effective treatment of patients with triple-negative (ER-negative, PR-negative, HER2-negative) breast cancer remains a challenge. Although PARP inhibitors are being evaluated in clinical trials, biomarkers are needed to identify patients who will most benefit from anti-PARP therapy. We determined the responses of three PARP inhibitors (veliparib, olaparib, and talazoparib) in a panel of eight triple-negative breast cancer cell lines. Therapeutic responses and cellular phenotypes were elucidated using high-content imaging and quantitative immunofluorescence to assess markers of DNA damage (53BP1) and apoptosis (cleaved PARP). We determined the pharmacodynamic changes as percentage of cells positive for 53BP1, mean number of 53BP1 foci per cell, and percentage of cells positive for cleaved PARP. Inspired by traditional dose-response measures of cell viability, an EC 50 value was calculated for each cellular phenotype and each PARP inhibitor. The EC 50 values for both 53BP1 metrics strongly correlated with IC 50 values for each PARP inhibitor. Pathway enrichment analysis identified a set of DNA repair and cell cycle-associated genes that were associated with 53BP1 response following PARP inhibition. The overall accuracy of our 63 gene set in predicting response to olaparib in seven breast cancer patient-derived xenograft tumors was 86%. In triple-negative breast cancer patients who had not received anti-PARP therapy, the predicted response rate of our gene signature was 45%. These results indicate that 53BP1 is a biomarker of response to anti-PARP therapy in the laboratory, and our DNA damage response gene signature may be used to identify patients who are most likely to respond to PARP inhibition. Mol Cancer Ther; 16(12); 2892-901. ©2017 AACR . ©2017 American Association for Cancer Research.

Delineation of metabolic gene clusters in plant genomes by chromatin signatures.

PubMed

Yu, Nan; Nützmann, Hans-Wilhelm; MacDonald, James T; Moore, Ben; Field, Ben; Berriri, Souha; Trick, Martin; Rosser, Susan J; Kumar, S Vinod; Freemont, Paul S; Osbourn, Anne

2016-03-18

Plants are a tremendous source of diverse chemicals, including many natural product-derived drugs. It has recently become apparent that the genes for the biosynthesis of numerous different types of plant natural products are organized as metabolic gene clusters, thereby unveiling a highly unusual form of plant genome architecture and offering novel avenues for discovery and exploitation of plant specialized metabolism. Here we show that these clustered pathways are characterized by distinct chromatin signatures of histone 3 lysine trimethylation (H3K27me3) and histone 2 variant H2A.Z, associated with cluster repression and activation, respectively, and represent discrete windows of co-regulation in the genome. We further demonstrate that knowledge of these chromatin signatures along with chromatin mutants can be used to mine genomes for cluster discovery. The roles of H3K27me3 and H2A.Z in repression and activation of single genes in plants are well known. However, our discovery of highly localized operon-like co-regulated regions of chromatin modification is unprecedented in plants. Our findings raise intriguing parallels with groups of physically linked multi-gene complexes in animals and with clustered pathways for specialized metabolism in filamentous fungi. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Selection signatures in four lignin genes from switchgrass populations divergently selected for in vitro dry matter digestibility

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

Chen, Shiyu; Kaeppler, Shawn M.; Vogel, Kenneth P.

Switchgrass is undergoing development as a dedicated cellulosic bioenergy crop. Fermentation of lignocellulosic biomass to ethanol in a bioenergy system or to volatile fatty acids in a livestock production system is strongly and negatively influenced by lignification of cell walls. This study detects specific loci that exhibit selection signatures across switchgrass breeding populations that differ in in vitro dry matter digestibility (IVDMD), ethanol yield, and lignin concentration. Allele frequency changes in candidate genes were used to detect loci under selection. Out of the 183 polymorphisms identified in the four candidate genes, twenty-five loci in the intron regions and four locimore » in coding regions were found to display a selection signature. All loci in the coding regions are synonymous substitutions. Selection in both directions were observed on polymorphisms that appeared to be under selection. Genetic diversity and linkage disequilibrium within the candidate genes were low. The recurrent divergent selection caused excessive moderate allele frequencies in the cycle 3 reduced lignin population as compared to the base population. As a result, this study provides valuable insight on genetic changes occurring in short-term selection in the polyploid populations, and discovered potential markers for breeding switchgrass with improved biomass quality.« less

Selection signatures in four lignin genes from switchgrass populations divergently selected for in vitro dry matter digestibility

DOE PAGES

Chen, Shiyu; Kaeppler, Shawn M.; Vogel, Kenneth P.; ...

2016-11-28

Switchgrass is undergoing development as a dedicated cellulosic bioenergy crop. Fermentation of lignocellulosic biomass to ethanol in a bioenergy system or to volatile fatty acids in a livestock production system is strongly and negatively influenced by lignification of cell walls. This study detects specific loci that exhibit selection signatures across switchgrass breeding populations that differ in in vitro dry matter digestibility (IVDMD), ethanol yield, and lignin concentration. Allele frequency changes in candidate genes were used to detect loci under selection. Out of the 183 polymorphisms identified in the four candidate genes, twenty-five loci in the intron regions and four locimore » in coding regions were found to display a selection signature. All loci in the coding regions are synonymous substitutions. Selection in both directions were observed on polymorphisms that appeared to be under selection. Genetic diversity and linkage disequilibrium within the candidate genes were low. The recurrent divergent selection caused excessive moderate allele frequencies in the cycle 3 reduced lignin population as compared to the base population. As a result, this study provides valuable insight on genetic changes occurring in short-term selection in the polyploid populations, and discovered potential markers for breeding switchgrass with improved biomass quality.« less

A Patient-Derived, Pan-Cancer EMT Signature Identifies Global Molecular Alterations and Immune Target Enrichment Following Epithelial-to-Mesenchymal Transition.

PubMed

Mak, Milena P; Tong, Pan; Diao, Lixia; Cardnell, Robert J; Gibbons, Don L; William, William N; Skoulidis, Ferdinandos; Parra, Edwin R; Rodriguez-Canales, Jaime; Wistuba, Ignacio I; Heymach, John V; Weinstein, John N; Coombes, Kevin R; Wang, Jing; Byers, Lauren Averett

2016-02-01

We previously demonstrated the association between epithelial-to-mesenchymal transition (EMT) and drug response in lung cancer using an EMT signature derived in cancer cell lines. Given the contribution of tumor microenvironments to EMT, we extended our investigation of EMT to patient tumors from 11 cancer types to develop a pan-cancer EMT signature. Using the pan-cancer EMT signature, we conducted an integrated, global analysis of genomic and proteomic profiles associated with EMT across 1,934 tumors including breast, lung, colon, ovarian, and bladder cancers. Differences in outcome and in vitro drug response corresponding to expression of the pan-cancer EMT signature were also investigated. Compared with the lung cancer EMT signature, the patient-derived, pan-cancer EMT signature encompasses a set of core EMT genes that correlate even more strongly with known EMT markers across diverse tumor types and identifies differences in drug sensitivity and global molecular alterations at the DNA, RNA, and protein levels. Among those changes associated with EMT, pathway analysis revealed a strong correlation between EMT and immune activation. Further supervised analysis demonstrated high expression of immune checkpoints and other druggable immune targets, such as PD1, PD-L1, CTLA4, OX40L, and PD-L2, in tumors with the most mesenchymal EMT scores. Elevated PD-L1 protein expression in mesenchymal tumors was confirmed by IHC in an independent lung cancer cohort. This new signature provides a novel, patient-based, histology-independent tool for the investigation of EMT and offers insights into potential novel therapeutic targets for mesenchymal tumors, independent of cancer type, including immune checkpoints. ©2015 American Association for Cancer Research.

BMI1 induces an invasive signature in melanoma that promotes metastasis and chemoresistance

PubMed Central

Ferretti, Roberta; Bhutkar, Arjun; McNamara, Molly C.; Lees, Jacqueline A.

2016-01-01

Melanoma can switch between proliferative and invasive states, which have identifying gene expression signatures that correlate with good and poor prognosis, respectively. However, the mechanisms controlling these signatures are poorly understood. In this study, we identify BMI1 as a key determinant of melanoma metastasis by which its overexpression enhanced and its deletion impaired dissemination. Remarkably, in this tumor type, BMI1 had no effect on proliferation or primary tumor growth but enhanced every step of the metastatic cascade. Consistent with the broad spectrum of effects, BMI1 activated widespread gene expression changes, which are characteristic of melanoma progression and also chemoresistance. Accordingly, we showed that up-regulation or down-regulation of BMI1 induced resistance or sensitivity to BRAF inhibitor treatment and that induction of noncanonical Wnt by BMI1 is required for this resistance. Finally, we showed that our BMI1-induced gene signature encompasses all of the hallmarks of the previously described melanoma invasive signature. Moreover, our signature is predictive of poor prognosis in human melanoma and is able to identify primary tumors that are likely to become metastatic. These data yield key insights into melanoma biology and establish BMI1 as a compelling drug target whose inhibition would suppress both metastasis and chemoresistance of melanoma. PMID:26679841

Analysis of blood-based gene expression in idiopathic Parkinson disease.

PubMed

Shamir, Ron; Klein, Christine; Amar, David; Vollstedt, Eva-Juliane; Bonin, Michael; Usenovic, Marija; Wong, Yvette C; Maver, Ales; Poths, Sven; Safer, Hershel; Corvol, Jean-Christophe; Lesage, Suzanne; Lavi, Ofer; Deuschl, Günther; Kuhlenbaeumer, Gregor; Pawlack, Heike; Ulitsky, Igor; Kasten, Meike; Riess, Olaf; Brice, Alexis; Peterlin, Borut; Krainc, Dimitri

2017-10-17

To examine whether gene expression analysis of a large-scale Parkinson disease (PD) patient cohort produces a robust blood-based PD gene signature compared to previous studies that have used relatively small cohorts (≤220 samples). Whole-blood gene expression profiles were collected from a total of 523 individuals. After preprocessing, the data contained 486 gene profiles (n = 205 PD, n = 233 controls, n = 48 other neurodegenerative diseases) that were partitioned into training, validation, and independent test cohorts to identify and validate a gene signature. Batch-effect reduction and cross-validation were performed to ensure signature reliability. Finally, functional and pathway enrichment analyses were applied to the signature to identify PD-associated gene networks. A gene signature of 100 probes that mapped to 87 genes, corresponding to 64 upregulated and 23 downregulated genes differentiating between patients with idiopathic PD and controls, was identified with the training cohort and successfully replicated in both an independent validation cohort (area under the curve [AUC] = 0.79, p = 7.13E-6) and a subsequent independent test cohort (AUC = 0.74, p = 4.2E-4). Network analysis of the signature revealed gene enrichment in pathways, including metabolism, oxidation, and ubiquitination/proteasomal activity, and misregulation of mitochondria-localized genes, including downregulation of COX4I1 , ATP5A1 , and VDAC3 . We present a large-scale study of PD gene expression profiling. This work identifies a reliable blood-based PD signature and highlights the importance of large-scale patient cohorts in developing potential PD biomarkers. © 2017 American Academy of Neurology.

Identification of Novel Gene Signatures in Atopic Dermatitis Complicated by Eczema Herpeticum

PubMed Central

Bin, Lianghua; Edwards, Michael G.; Heiser, Ryan; Streib, Joanne; Richers, Brittany; Hall, Cliff; Leung, Donald Y.M.

2014-01-01

Background A subset of patients with atopic dermatitis (AD) is prone to disseminated herpes simplex virus (HSV) infection, i.e. eczema herpeticum (ADEH+). Biomarkers that identify ADEH+ are lacking. Objective To search for novel ADEH+ gene signatures in peripheral blood mononuclear cells (PBMCs). Methods A RNA-sequencing (RNA-seq) approach was applied to evaluate global transcriptional changes using PBMCs from ADEH+ and AD without a history of EH (ADEH−). Candidate genes were confirmed by qPCR or ELISA. RESULTS ADEH+ PBMCs had distinct changes to the transcriptome when compared to ADEH− PBMCs following HSV-1 stimulation: 792 genes were differentially expressed at a false discovery rate (FDR) < 0.05 (ANOVA), and 15 type I and type III interferon (IFN) genes were among the top 20 most down-regulated genes in ADEH+. We further validated that IFN-α and IL-29 mRNA and protein levels were significantly decreased in HSV-1 stimulated PBMCs from ADEH+ compared to ADEH− and normal. Ingenuity pathway analysis (IPA) demonstrated that the up-stream regulators of type I and type III IFNs, IRF3 and IRF7, was significantly inhibited in ADEH+ based on the down-regulation of their target genes. Furthermore, we found that gene expression of IRF3 and IRF7 were significantly decreased in HSV-1 stimulated PBMC from ADEH+ subjects. CONCLUSIONS PBMCs from ADEH+ have a distinct immune response following HSV-1 exposure compared to ADEH−. Inhibition of the IRF3 and IRF7 innate immune pathways in ADEH+ may be important mechanism for increased susceptibility to disseminated viral infection. PMID:25159465

Dynamic transcriptional signatures and network responses for clinical symptoms in influenza-infected human subjects using systems biology approaches.

PubMed

Linel, Patrice; Wu, Shuang; Deng, Nan; Wu, Hulin

2014-10-01

Recent studies demonstrate that human blood transcriptional signatures may be used to support diagnosis and clinical decisions for acute respiratory viral infections such as influenza. In this article, we propose to use a newly developed systems biology approach for time course gene expression data to identify significant dynamically response genes and dynamic gene network responses to viral infection. We illustrate the methodological pipeline by reanalyzing the time course gene expression data from a study with healthy human subjects challenged by live influenza virus. We observed clear differences in the number of significant dynamic response genes (DRGs) between the symptomatic and asymptomatic subjects and also identified DRG signatures for symptomatic subjects with influenza infection. The 505 common DRGs shared by the symptomatic subjects have high consistency with the signature genes for predicting viral infection identified in previous works. The temporal response patterns and network response features were carefully analyzed and investigated.

Gene signature in Alzheimer's disease and environmental factors: the virus chronicle.

PubMed

Licastro, Federico; Carbone, Ilaria; Ianni, Manuela; Porcellini, Elisa

2011-01-01

Genome wide association investigations from large cohorts of patients with Alzheimer's disease (AD) and non demented controls (CTR) showed that a limited set of genes were associated (p > 10-5) with the disease. A very recent study from our group showed that an additional limited group of SNP in selected genes were associated with AD. In this report we argue that the association of these genes with AD is suggestive of a pivotal role of environmental factors in the pathogenesis of the disease and one of these factors is virus infection. In other words, the genetic signature revealed by genome wide association (GWA) studies discloses a network of genes that might influence the ability of the central nervous system to cope with and fight against the invasion by virus of the herpes family. In fact, Nectin-2 (NC-2); apolipoprotein E (APOE); glycoprotein carcinoembryonic antigen related cell adhesion molecule-16 (CEACAM-16); B-cell lymphoma-3 (Bcl-3); translocase of outer mitochondrial membrane 40 homolog (T0MM-40); complement receptor-1 (CR-l); APOJ or clusterin and C-type lectin domain A family-16 member (CLEC-16A); Phosphatidyl inositol- binding clathrin assembly protein gene (PICALM); ATP-bonding cassette, sub family A, member 7 (ABCA7); membrane spanning A4 (MSA4); CD2 associated protein (CD2AP); cluster of differentiation 33 (CD33); and ephrin receptor A1 (EPHA1) result in a genetic signature that might affect individual brain susceptibility to infection by the herpes virus family during aging, leading to neuronal loss, inflammation, and amyloid deposition.

Quantitative multiplex quantum dot in-situ hybridisation based gene expression profiling in tissue microarrays identifies prognostic genes in acute myeloid leukaemia

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

Tholouli, Eleni; MacDermott, Sarah; Hoyland, Judith

2012-08-24

Highlights: Black-Right-Pointing-Pointer Development of a quantitative high throughput in situ expression profiling method. Black-Right-Pointing-Pointer Application to a tissue microarray of 242 AML bone marrow samples. Black-Right-Pointing-Pointer Identification of HOXA4, HOXA9, Meis1 and DNMT3A as prognostic markers in AML. -- Abstract: Measurement and validation of microarray gene signatures in routine clinical samples is problematic and a rate limiting step in translational research. In order to facilitate measurement of microarray identified gene signatures in routine clinical tissue a novel method combining quantum dot based oligonucleotide in situ hybridisation (QD-ISH) and post-hybridisation spectral image analysis was used for multiplex in-situ transcript detection inmore » archival bone marrow trephine samples from patients with acute myeloid leukaemia (AML). Tissue-microarrays were prepared into which white cell pellets were spiked as a standard. Tissue microarrays were made using routinely processed bone marrow trephines from 242 patients with AML. QD-ISH was performed for six candidate prognostic genes using triplex QD-ISH for DNMT1, DNMT3A, DNMT3B, and for HOXA4, HOXA9, Meis1. Scrambled oligonucleotides were used to correct for background staining followed by normalisation of expression against the expression values for the white cell pellet standard. Survival analysis demonstrated that low expression of HOXA4 was associated with poorer overall survival (p = 0.009), whilst high expression of HOXA9 (p < 0.0001), Meis1 (p = 0.005) and DNMT3A (p = 0.04) were associated with early treatment failure. These results demonstrate application of a standardised, quantitative multiplex QD-ISH method for identification of prognostic markers in formalin-fixed paraffin-embedded clinical samples, facilitating measurement of gene expression signatures in routine clinical samples.« less

MARQ: an online tool to mine GEO for experiments with similar or opposite gene expression signatures.

PubMed

Vazquez, Miguel; Nogales-Cadenas, Ruben; Arroyo, Javier; Botías, Pedro; García, Raul; Carazo, Jose M; Tirado, Francisco; Pascual-Montano, Alberto; Carmona-Saez, Pedro

2010-07-01

The enormous amount of data available in public gene expression repositories such as Gene Expression Omnibus (GEO) offers an inestimable resource to explore gene expression programs across several organisms and conditions. This information can be used to discover experiments that induce similar or opposite gene expression patterns to a given query, which in turn may lead to the discovery of new relationships among diseases, drugs or pathways, as well as the generation of new hypotheses. In this work, we present MARQ, a web-based application that allows researchers to compare a query set of genes, e.g. a set of over- and under-expressed genes, against a signature database built from GEO datasets for different organisms and platforms. MARQ offers an easy-to-use and integrated environment to mine GEO, in order to identify conditions that induce similar or opposite gene expression patterns to a given experimental condition. MARQ also includes additional functionalities for the exploration of the results, including a meta-analysis pipeline to find genes that are differentially expressed across different experiments. The application is freely available at http://marq.dacya.ucm.es.

Using Functional Signature Ontology (FUSION) to Identify Mechanisms of Action for Natural Products

PubMed Central

Potts, Malia B.; Kim, Hyun Seok; Fisher, Kurt W.; Hu, Youcai; Carrasco, Yazmin P.; Bulut, Gamze Betul; Ou, Yi-Hung; Herrera-Herrera, Mireya L.; Cubillos, Federico; Mendiratta, Saurabh; Xiao, Guanghua; Hofree, Matan; Ideker, Trey; Xie, Yang; Huang, Lily Jun-shen; Lewis, Robert E.; MacMillan, John B.; White, Michael A.

2014-01-01

A challenge for biomedical research is the development of pharmaceuticals that appropriately target disease mechanisms. Natural products can be a rich source of bioactive chemicals for medicinal applications but can act through unknown mechanisms and can be difficult to produce or obtain. To address these challenges, we developed a new marine-derived, renewable natural products resource and a method for linking bioactive derivatives of this library to the proteins and biological processes that they target in cells. We used cell-based screening and computational analysis to match gene expression signatures produced by natural products to those produced by siRNA and synthetic microRNA libraries. With this strategy, we matched proteins and microRNAs with diverse biological processes and also identified putative protein targets and mechanisms of action for several previously undescribed marine-derived natural products. We confirmed mechanistic relationships for selected short-interfering RNAs, microRNAs, and compounds with functional roles in autophagy, chemotaxis mediated by discoidin domain receptor 2, or activation of the kinase AKT. Thus, this approach may be an effective method for screening new drugs while simultaneously identifying their targets. PMID:24129700

Clustered Mutation Signatures Reveal that Error-Prone DNA Repair Targets Mutations to Active Genes.

PubMed

Supek, Fran; Lehner, Ben

2017-07-27

Many processes can cause the same nucleotide change in a genome, making the identification of the mechanisms causing mutations a difficult challenge. Here, we show that clustered mutations provide a more precise fingerprint of mutagenic processes. Of nine clustered mutation signatures identified from >1,000 tumor genomes, three relate to variable APOBEC activity and three are associated with tobacco smoking. An additional signature matches the spectrum of translesion DNA polymerase eta (POLH). In lymphoid cells, these mutations target promoters, consistent with AID-initiated somatic hypermutation. In solid tumors, however, they are associated with UV exposure and alcohol consumption and target the H3K36me3 chromatin of active genes in a mismatch repair (MMR)-dependent manner. These regions normally have a low mutation rate because error-free MMR also targets H3K36me3 chromatin. Carcinogens and error-prone repair therefore redistribute mutations to the more important regions of the genome, contributing a substantial mutation load in many tumors, including driver mutations. Copyright © 2017 Elsevier Inc. All rights reserved.

Genome-wide strategies identify downstream target genes of chick connective tissue-associated transcription factors.

PubMed

Orgeur, Mickael; Martens, Marvin; Leonte, Georgeta; Nassari, Sonya; Bonnin, Marie-Ange; Börno, Stefan T; Timmermann, Bernd; Hecht, Jochen; Duprez, Delphine; Stricker, Sigmar

2018-03-29

Connective tissues support organs and play crucial roles in development, homeostasis and fibrosis, yet our understanding of their formation is still limited. To gain insight into the molecular mechanisms of connective tissue specification, we selected five zinc-finger transcription factors - OSR1, OSR2, EGR1, KLF2 and KLF4 - based on their expression patterns and/or known involvement in connective tissue subtype differentiation. RNA-seq and ChIP-seq profiling of chick limb micromass cultures revealed a set of common genes regulated by all five transcription factors, which we describe as a connective tissue core expression set. This common core was enriched with genes associated with axon guidance and myofibroblast signature, including fibrosis-related genes. In addition, each transcription factor regulated a specific set of signalling molecules and extracellular matrix components. This suggests a concept whereby local molecular niches can be created by the expression of specific transcription factors impinging on the specification of local microenvironments. The regulatory network established here identifies common and distinct molecular signatures of limb connective tissue subtypes, provides novel insight into the signalling pathways governing connective tissue specification, and serves as a resource for connective tissue development. © 2018. Published by The Company of Biologists Ltd.

Gene signature based on degradome-related genes can predict distal metastasis in cervical cancer patients.

PubMed

Fernandez-Retana, Jorge; Zamudio-Meza, Horacio; Rodriguez-Morales, Miguel; Pedroza-Torres, Abraham; Isla-Ortiz, David; Herrera, Luis; Jacobo-Herrera, Nadia; Peralta-Zaragoza, Oscar; López-Camarillo, César; Morales-Gonzalez, Fermin; Cantu de Leon, David; Pérez-Plasencia, Carlos

2017-06-01

Cervical cancer is one of the leading causes of death in women worldwide, which mainly affects developing countries. The patients who suffer a recurrence and/or progression disease have a higher risk of developing distal metastases. Proteases comprising the degradome given its ability to promote cell growth, migration, and invasion of tissues play an important role during tumor development and progression. In this study, we used high-density microarrays and quantitative reverse transcriptase polymerase chain reaction to evaluate the degradome profile and their inhibitors in 112 samples of patients diagnosed with locally advanced cervical cancer. Clinical follow-up was done during a period of 3 years. Using a correlation analysis between the response to treatment and the development of metastasis, we established a molecular signature comprising eight degradome-related genes (FAM111B, FAM111A, CFB, PSMB8, PSMB9, CASP7, PRSS16, and CD74) with the ability to discriminate patients at risk of distal metastases. In conclusion, present results show that molecular signature obtained from degradome genes can predict the possibility of metastasis in patients with locally advanced cervical cancer.

Comprehensive Gene expression meta-analysis and integrated bioinformatic approaches reveal shared signatures between thrombosis and myeloproliferative disorders

PubMed Central

Jha, Prabhash Kumar; Vijay, Aatira; Sahu, Anita; Ashraf, Mohammad Zahid

2016-01-01

Thrombosis is a leading cause of morbidity and mortality in patients with myeloproliferative disorders (MPDs), particularly polycythemia vera (PV) and essential thrombocythemia (ET). Despite the attempts to establish a link between them, the shared biological mechanisms are yet to be characterized. An integrated gene expression meta-analysis of five independent publicly available microarray data of the three diseases was conducted to identify shared gene expression signatures and overlapping biological processes. Using INMEX bioinformatic tool, based on combined Effect Size (ES) approaches, we identified a total of 1,157 differentially expressed genes (DEGs) (697 overexpressed and 460 underexpressed genes) shared between the three diseases. EnrichR tool’s rich library was used for comprehensive functional enrichment and pathway analysis which revealed “mRNA Splicing” and “SUMO E3 ligases SUMOylate target proteins” among the most enriched terms. Network based meta-analysis identified MYC and FN1 to be the most highly ranked hub genes. Our results reveal that the alterations in biomarkers of the coagulation cascade like F2R, PROS1, SELPLG and ITGB2 were common between the three diseases. Interestingly, the study has generated a novel database of candidate genetic markers, pathways and transcription factors shared between thrombosis and MPDs, which might aid in the development of prognostic therapeutic biomarkers. PMID:27892526

Autophagy-related prognostic signature for breast cancer.

PubMed

Gu, Yunyan; Li, Pengfei; Peng, Fuduan; Zhang, Mengmeng; Zhang, Yuanyuan; Liang, Haihai; Zhao, Wenyuan; Qi, Lishuang; Wang, Hongwei; Wang, Chenguang; Guo, Zheng

2016-03-01

Autophagy is a process that degrades intracellular constituents, such as long-lived or damaged proteins and organelles, to buffer metabolic stress under starvation conditions. Deregulation of autophagy is involved in the progression of cancer. However, the predictive value of autophagy for breast cancer prognosis remains unclear. First, based on gene expression profiling, we found that autophagy genes were implicated in breast cancer. Then, using the Cox proportional hazard regression model, we detected autophagy prognostic signature for breast cancer in a training dataset. We identified a set of eight autophagy genes (BCL2, BIRC5, EIF4EBP1, ERO1L, FOS, GAPDH, ITPR1 and VEGFA) that were significantly associated with overall survival in breast cancer. The eight autophagy genes were assigned as a autophagy-related prognostic signature for breast cancer. Based on the autophagy-related signature, the training dataset GSE21653 could be classified into high-risk and low-risk subgroups with significantly different survival times (HR = 2.72, 95% CI = (1.91, 3.87); P = 1.37 × 10(-5)). Inactivation of autophagy was associated with shortened survival of breast cancer patients. The prognostic value of the autophagy-related signature was confirmed in the testing dataset GSE3494 (HR = 2.12, 95% CI = (1.48, 3.03); P = 1.65 × 10(-3)) and GSE7390 (HR = 1.76, 95% CI = (1.22, 2.54); P = 9.95 × 10(-4)). Further analysis revealed that the prognostic value of the autophagy signature was independent of known clinical prognostic factors, including age, tumor size, grade, estrogen receptor status, progesterone receptor status, ERBB2 status, lymph node status and TP53 mutation status. Finally, we demonstrated that the autophagy signature could also predict distant metastasis-free survival for breast cancer. © 2015 Wiley Periodicals, Inc.

Genetic risk profiling and gene signature modeling to predict risk of complications after IPAA.

PubMed

Sehgal, Rishabh; Berg, Arthur; Polinski, Joseph I; Hegarty, John P; Lin, Zhenwu; McKenna, Kevin J; Stewart, David B; Poritz, Lisa S; Koltun, Walter A

2012-03-01

Severe pouchitis and Crohn's disease-like complications are 2 adverse postoperative complications that confound the success of the IPAA in patients with ulcerative colitis. To date, approximately 83 single nucleotide polymorphisms within 55 genes have been associated with IBD. The aim of this study was to identify single-nucleotide polymorphisms that correlate with complications after IPAA that could be utilized in a gene signature fashion to predict postoperative complications and aid in preoperative surgical decision making. One hundred forty-two IPAA patients were retrospectively classified as "asymptomatic" (n = 104, defined as no Crohn's disease-like complications or severe pouchitis for at least 2 years after IPAA) and compared with a "severe pouchitis" group (n = 12, ≥ 4 episodes pouchitis per year for 2 years including the need for long-term therapy to maintain remission) and a "Crohn's disease-like" group (n = 26, presence of fistulae, pouch inlet stricture, proximal small-bowel disease, or pouch granulomata, occurring at least 6 months after surgery). Genotyping for 83 single-nucleotide polymorphisms previously associated with Crohn's disease and/or ulcerative colitis was performed on a customized Illumina genotyping platform. The top 2 single-nucleotide polymorphisms statistically identified as being independently associated with each of Crohn's disease-like and severe pouchitis were used in a multivariate logistic regression model. These single-nucleotide polymorphisms were then used to create probability equations to predict overall chance of a positive or negative outcome for that complication. The top 2 single-nucleotide polymorphisms for Crohn's disease-like complications were in the 10q21 locus and the gene for PTGER4 (p = 0.006 and 0.007), whereas for severe pouchitis it was NOD2 and TNFSF15 (p = 0.003 and 0.011). Probability equations suggested that the risk of these 2 complications greatly increased with increasing number of risk alleles

sscMap: an extensible Java application for connecting small-molecule drugs using gene-expression signatures.

PubMed

Zhang, Shu-Dong; Gant, Timothy W

2009-07-31

Connectivity mapping is a process to recognize novel pharmacological and toxicological properties in small molecules by comparing their gene expression signatures with others in a database. A simple and robust method for connectivity mapping with increased specificity and sensitivity was recently developed, and its utility demonstrated using experimentally derived gene signatures. This paper introduces sscMap (statistically significant connections' map), a Java application designed to undertake connectivity mapping tasks using the recently published method. The software is bundled with a default collection of reference gene-expression profiles based on the publicly available dataset from the Broad Institute Connectivity Map 02, which includes data from over 7000 Affymetrix microarrays, for over 1000 small-molecule compounds, and 6100 treatment instances in 5 human cell lines. In addition, the application allows users to add their custom collections of reference profiles and is applicable to a wide range of other 'omics technologies. The utility of sscMap is two fold. First, it serves to make statistically significant connections between a user-supplied gene signature and the 6100 core reference profiles based on the Broad Institute expanded dataset. Second, it allows users to apply the same improved method to custom-built reference profiles which can be added to the database for future referencing. The software can be freely downloaded from http://purl.oclc.org/NET/sscMap.

Males are from Mars, females are from Venus: sex-specific fetal brain gene expression signatures in a mouse model of maternal diet-induced obesity

PubMed Central

EDLOW, Andrea G.; GUEDJ, Faycal; PENNINGS, Jeroen L.A.; SVERDLOV, Deanna; NERI, Caterina; BIANCHI, Diana W.

2016-01-01

BACKGROUND Maternal obesity is associated with adverse neurodevelopmental outcomes in children, including autism spectrum disorders, developmental delay, and attention deficit hyperactivity disorder. The underlying mechanisms remain unclear. We previously identified second trimester amniotic fluid and term cord blood gene expression patterns suggesting dysregulated brain development in fetuses of obese compared to lean women. OBJECTIVES We sought to investigate the biological significance of these findings in a mouse model of maternal diet-induced obesity. We evaluated sex-specific differences in fetal growth, brain gene expression signatures and associated pathways. STUDY DESIGN Female C57BL/6J mice were fed a 60% high-fat diet or 10% fat control diet for 12–14 weeks prior to mating. During pregnancy, obese dams continued on the high-fat diet (HFD/HFD), or transitioned to the CD (HFD/CD). Lean dams stayed on the control diet. On embryonic day 17.5, embryos were weighed and fetal brains were snap frozen. RNA was extracted from male and female forebrains (10/diet group/sex) and hybridized to whole genome expression arrays. Significantly differentially expressed genes were identified using Welch’s t-test with the Benjamini-Hochberg correction. Functional analyses were performed using Ingenuity Pathways Analysis and Gene Set Enrichment Analysis. RESULTS Embryos of HFD/HFD dams were significantly smaller than controls, with males more severely affected than females (p=0.01). Maternal obesity and maternal obesity with dietary change in pregnancy resulted in significantly more dysregulated genes in male versus female fetal brains (386 vs 66, p<0.001). Maternal obesity with and without dietary change in pregnancy was associated with unique brain gene expression signatures for each sex, with overlap of only one gene. Changing obese dams to a control diet in pregnancy resulted in more differentially expressed genes in the fetal brain than maternal obesity alone

Four-gene Pan-African Blood Signature Predicts Progression to Tuberculosis.

PubMed

Suliman, Sara; Thompson, Ethan; Sutherland, Jayne; Weiner Rd, January; Ota, Martin O C; Shankar, Smitha; Penn-Nicholson, Adam; Thiel, Bonnie; Erasmus, Mzwandile; Maertzdorf, Jeroen; Duffy, Fergal J; Hill, Philip C; Hughes, E Jane; Stanley, Kim; Downing, Katrina; Fisher, Michelle L; Valvo, Joe; Parida, Shreemanta K; van der Spuy, Gian; Tromp, Gerard; Adetifa, Ifedayo M O; Donkor, Simon; Howe, Rawleigh; Mayanja-Kizza, Harriet; Boom, W Henry; Dockrell, Hazel; Ottenhoff, Tom H M; Hatherill, Mark; Aderem, Alan; Hanekom, Willem A; Scriba, Thomas J; Kaufmann, Stefan He; Zak, Daniel E; Walzl, Gerhard

2018-04-06

Contacts of tuberculosis (TB) patients constitute an important target population for preventative measures as they are at high risk of infection with Mycobacterium tuberculosis and progression to disease. We investigated biosignatures with predictive ability for incident tuberculosis. In a case-control study nested within the Grand Challenges 6-74 longitudinal HIV-negative African cohort of exposed household contacts, we employed RNA sequencing, polymerase chain reaction (PCR) and the Pair Ratio algorithm in a training/test set approach. Overall, 79 progressors, who developed tuberculosis between 3 and 24 months following exposure, and 328 matched non-progressors, who remained healthy during 24 months of follow-up, were investigated. A four-transcript signature (RISK4), derived from samples in a South African and Gambian training set, predicted progression up to two years before onset of disease in blinded test set samples from South Africa, The Gambia and Ethiopia with little population-associated variability and also validated on an external cohort of South African adolescents with latent Mycobacterium tuberculosis infection. By contrast, published diagnostic or prognostic tuberculosis signatures predicted on samples from some but not all 3 countries, indicating site-specific variability. Post-hoc meta-analysis identified a single gene pair, C1QC/TRAV27, that would consistently predict TB progression in household contacts from multiple African sites but not in infected adolescents without known recent exposure events. Collectively, we developed a simple whole blood-based PCR test to predict tuberculosis in household contacts from diverse African populations, with potential for implementation in national TB contact investigation programs.

Stromal-Based Signatures for the Classification of Gastric Cancer.

PubMed

Uhlik, Mark T; Liu, Jiangang; Falcon, Beverly L; Iyer, Seema; Stewart, Julie; Celikkaya, Hilal; O'Mahony, Marguerita; Sevinsky, Christopher; Lowes, Christina; Douglass, Larry; Jeffries, Cynthia; Bodenmiller, Diane; Chintharlapalli, Sudhakar; Fischl, Anthony; Gerald, Damien; Xue, Qi; Lee, Jee-Yun; Santamaria-Pang, Alberto; Al-Kofahi, Yousef; Sui, Yunxia; Desai, Keyur; Doman, Thompson; Aggarwal, Amit; Carter, Julia H; Pytowski, Bronislaw; Jaminet, Shou-Ching; Ginty, Fiona; Nasir, Aejaz; Nagy, Janice A; Dvorak, Harold F; Benjamin, Laura E

2016-05-01

Treatment of metastatic gastric cancer typically involves chemotherapy and monoclonal antibodies targeting HER2 (ERBB2) and VEGFR2 (KDR). However, reliable methods to identify patients who would benefit most from a combination of treatment modalities targeting the tumor stroma, including new immunotherapy approaches, are still lacking. Therefore, we integrated a mouse model of stromal activation and gastric cancer genomic information to identify gene expression signatures that may inform treatment strategies. We generated a mouse model in which VEGF-A is expressed via adenovirus, enabling a stromal response marked by immune infiltration and angiogenesis at the injection site, and identified distinct stromal gene expression signatures. With these data, we designed multiplexed IHC assays that were applied to human primary gastric tumors and classified each tumor to a dominant stromal phenotype representative of the vascular and immune diversity found in gastric cancer. We also refined the stromal gene signatures and explored their relation to the dominant patient phenotypes identified by recent large-scale studies of gastric cancer genomics (The Cancer Genome Atlas and Asian Cancer Research Group), revealing four distinct stromal phenotypes. Collectively, these findings suggest that a genomics-based systems approach focused on the tumor stroma can be used to discover putative predictive biomarkers of treatment response, especially to antiangiogenesis agents and immunotherapy, thus offering an opportunity to improve patient stratification. Cancer Res; 76(9); 2573-86. ©2016 AACR. ©2016 American Association for Cancer Research.

Targeted proteomics identifies liquid-biopsy signatures for extracapsular prostate cancer

PubMed Central

Kim, Yunee; Jeon, Jouhyun; Mejia, Salvador; Yao, Cindy Q; Ignatchenko, Vladimir; Nyalwidhe, Julius O; Gramolini, Anthony O; Lance, Raymond S; Troyer, Dean A; Drake, Richard R; Boutros, Paul C; Semmes, O. John; Kislinger, Thomas

2016-01-01

Biomarkers are rapidly gaining importance in personalized medicine. Although numerous molecular signatures have been developed over the past decade, there is a lack of overlap and many biomarkers fail to validate in independent patient cohorts and hence are not useful for clinical application. For these reasons, identification of novel and robust biomarkers remains a formidable challenge. We combine targeted proteomics with computational biology to discover robust proteomic signatures for prostate cancer. Quantitative proteomics conducted in expressed prostatic secretions from men with extraprostatic and organ-confined prostate cancers identified 133 differentially expressed proteins. Using synthetic peptides, we evaluate them by targeted proteomics in a 74-patient cohort of expressed prostatic secretions in urine. We quantify a panel of 34 candidates in an independent 207-patient cohort. We apply machine-learning approaches to develop clinical predictive models for prostate cancer diagnosis and prognosis. Our results demonstrate that computationally guided proteomics can discover highly accurate non-invasive biomarkers. PMID:27350604

S100A9 and EGFR gene signatures predict disease progression in muscle invasive bladder cancer patients after chemotherapy.

PubMed

Kim, W T; Kim, J; Yan, C; Jeong, P; Choi, S Y; Lee, O J; Chae, Y B; Yun, S J; Lee, S C; Kim, W J

2014-05-01

In our previous gene expression profile analysis, IL1B, S100A8, S100A9, and EGFR were shown to be important mediators of muscle invasive bladder cancer (MIBC) progression. The aim of the present study was to investigate the ability of these gene signatures to predict disease progression after chemotherapy in patients with locally recurrent or metastatic MIBC. Patients with locally advanced MIBC who received chemotherapy were enrolled. The expression signatures of four genes were measured and carried out further functional analysis to confirm our findings. Two of the four genes, S100A9 and EGFR, were determined to significantly influence disease progression (P = 0.023, 0.045, respectively). Based on a receiver operating characteristic curve, a cut-off value for disease progression was determined. Patients with the good-prognostic signature group had a significantly longer time to progression and cancer-specific survival time than those with the poor-prognostic signature group (P < 0.001, 0.042, respectively). In the multivariate Cox regression analysis, gene signature was the only factor that significantly influenced disease progression [hazard ratio: 4.726, confidence interval: 1.623-13.763, P = 0.004]. In immunohistochemical analysis, S100A9 and EGFR positivity were associated with disease progression after chemotherapy. Protein expression of S100A9/EGFR showed modest correlation with gene expression of S100A9/EGFR (r = 0.395, P = 0.014 and r = 0.453, P = 0.004). Our functional analysis provided the evidence demonstrating that expression of S100A9 and EGFR closely associated chemoresistance, and that inhibition of S100A9 and EGFR may sensitize bladder tumor cells to the cisplatin-based chemotherapy. The S100A9/EGFR level is a novel prognostic marker to predict the chemoresponsiveness of patients with locally recurrent or metastatic MIBC.

Males are from Mars, and females are from Venus: sex-specific fetal brain gene expression signatures in a mouse model of maternal diet-induced obesity.

PubMed

Edlow, Andrea G; Guedj, Faycal; Pennings, Jeroen L A; Sverdlov, Deanna; Neri, Caterina; Bianchi, Diana W

2016-05-01

Maternal obesity is associated with adverse neurodevelopmental outcomes in children, including autism spectrum disorders, developmental delay, and attention-deficit hyperactivity disorder. The underlying mechanisms remain unclear. We previously identified second-trimester amniotic fluid and term cord blood gene expression patterns suggesting dysregulated brain development in fetuses of obese compared with lean women. We sought to investigate the biological significance of these findings in a mouse model of maternal diet-induced obesity. We evaluated sex-specific differences in fetal growth, brain gene expression signatures, and associated pathways. Female C57BL/6J mice were fed a 60% high-fat diet or 10% fat control diet for 12-14 weeks prior to mating. During pregnancy, obese dams continued on the high-fat diet or transitioned to the control diet. Lean dams stayed on the control diet. On embryonic day 17.5, embryos were weighed and fetal brains were snap frozen. RNA was extracted from male and female forebrains (10 per diet group per sex) and hybridized to whole-genome expression arrays. Significantly differentially expressed genes were identified using a Welch's t test with the Benjamini-Hochberg correction. Functional analyses were performed using ingenuity pathways analysis and gene set enrichment analysis. Embryos of dams on the high-fat diet were significantly smaller than controls, with males more severely affected than females (P = .01). Maternal obesity and maternal obesity with dietary change in pregnancy resulted in significantly more dysregulated genes in male vs female fetal brains (386 vs 66, P < .001). Maternal obesity with and without dietary change in pregnancy was associated with unique brain gene expression signatures for each sex, with an overlap of only 1 gene. Changing obese dams to a control diet in pregnancy resulted in more differentially expressed genes in the fetal brain than maternal obesity alone. Functional analyses identified common

Identifying developmental vascular disruptor compounds using a predictive signature and alternative toxicity models

EPA Science Inventory

Identifying Developmental Vascular Disruptor Compounds Using a Predictive Signature and Alternative Toxicity Models Presenting Author: Tamara Tal Affiliation: U.S. EPA/ORD/ISTD, RTP, NC, USA Chemically induced vascular toxicity during embryonic development can result in a wide...

miRvestigator: web application to identify miRNAs responsible for co-regulated gene expression patterns discovered through transcriptome profiling.

PubMed

Plaisier, Christopher L; Bare, J Christopher; Baliga, Nitin S

2011-07-01

Transcriptome profiling studies have produced staggering numbers of gene co-expression signatures for a variety of biological systems. A significant fraction of these signatures will be partially or fully explained by miRNA-mediated targeted transcript degradation. miRvestigator takes as input lists of co-expressed genes from Caenorhabditis elegans, Drosophila melanogaster, G. gallus, Homo sapiens, Mus musculus or Rattus norvegicus and identifies the specific miRNAs that are likely to bind to 3' un-translated region (UTR) sequences to mediate the observed co-regulation. The novelty of our approach is the miRvestigator hidden Markov model (HMM) algorithm which systematically computes a similarity P-value for each unique miRNA seed sequence from the miRNA database miRBase to an overrepresented sequence motif identified within the 3'-UTR of the query genes. We have made this miRNA discovery tool accessible to the community by integrating our HMM algorithm with a proven algorithm for de novo discovery of miRNA seed sequences and wrapping these algorithms into a user-friendly interface. Additionally, the miRvestigator web server also produces a list of putative miRNA binding sites within 3'-UTRs of the query transcripts to facilitate the design of validation experiments. The miRvestigator is freely available at http://mirvestigator.systemsbiology.net.

Knowledge Driven Variable Selection (KDVS) – a new approach to enrichment analysis of gene signatures obtained from high–throughput data

PubMed Central

2013-01-01

Background High–throughput (HT) technologies provide huge amount of gene expression data that can be used to identify biomarkers useful in the clinical practice. The most frequently used approaches first select a set of genes (i.e. gene signature) able to characterize differences between two or more phenotypical conditions, and then provide a functional assessment of the selected genes with an a posteriori enrichment analysis, based on biological knowledge. However, this approach comes with some drawbacks. First, gene selection procedure often requires tunable parameters that affect the outcome, typically producing many false hits. Second, a posteriori enrichment analysis is based on mapping between biological concepts and gene expression measurements, which is hard to compute because of constant changes in biological knowledge and genome analysis. Third, such mapping is typically used in the assessment of the coverage of gene signature by biological concepts, that is either score–based or requires tunable parameters as well, limiting its power. Results We present Knowledge Driven Variable Selection (KDVS), a framework that uses a priori biological knowledge in HT data analysis. The expression data matrix is transformed, according to prior knowledge, into smaller matrices, easier to analyze and to interpret from both computational and biological viewpoints. Therefore KDVS, unlike most approaches, does not exclude a priori any function or process potentially relevant for the biological question under investigation. Differently from the standard approach where gene selection and functional assessment are applied independently, KDVS embeds these two steps into a unified statistical framework, decreasing the variability derived from the threshold–dependent selection, the mapping to the biological concepts, and the signature coverage. We present three case studies to assess the usefulness of the method. Conclusions We showed that KDVS not only enables the

Common patterns and disease-related signatures in tuberculosis and sarcoidosis.

PubMed

Maertzdorf, Jeroen; Weiner, January; Mollenkopf, Hans-Joachim; Bauer, Torsten; Prasse, Antje; Müller-Quernheim, Joachim; Kaufmann, Stefan H E

2012-05-15

In light of the marked global health impact of tuberculosis (TB), strong focus has been on identifying biosignatures. Gene expression profiles in blood cells identified so far are indicative of a persistent activation of the immune system and chronic inflammatory pathology in active TB. Definition of a biosignature with unique specificity for TB demands that identified profiles can differentiate diseases with similar pathology, like sarcoidosis (SARC). Here, we present a detailed comparison between pulmonary TB and SARC, including whole-blood gene expression profiling, microRNA expression, and multiplex serum analytes. Our analysis reveals that previously disclosed gene expression signatures in TB show highly similar patterns in SARC, with a common up-regulation of proinflammatory pathways and IFN signaling and close similarity to TB-related signatures. microRNA expression also presented a highly similar pattern in both diseases, whereas cytokines in the serum of TB patients revealed a slightly elevated proinflammatory pattern compared with SARC and controls. Our results indicate several differences in expression between the two diseases, with increased metabolic activity and significantly higher antimicrobial defense responses in TB. However, matrix metallopeptidase 14 was identified as the most distinctive marker of SARC. Described communalities as well as unique signatures in blood profiles of two distinct inflammatory pulmonary diseases not only have considerable implications for the design of TB biosignatures and future diagnosis, but they also provide insights into biological processes underlying chronic inflammatory disease entities of different etiology.

Gene Expression Signature in Adipose Tissue of Acromegaly Patients

PubMed Central

Hochberg, Irit; Tran, Quynh T.; Barkan, Ariel L.; Saltiel, Alan R.; Chandler, William F.; Bridges, Dave

2015-01-01

To study the effect of chronic excess growth hormone on adipose tissue, we performed RNA sequencing in adipose tissue biopsies from patients with acromegaly (n = 7) or non-functioning pituitary adenomas (n = 11). The patients underwent clinical and metabolic profiling including assessment of HOMA-IR. Explants of adipose tissue were assayed ex vivo for lipolysis and ceramide levels. Patients with acromegaly had higher glucose, higher insulin levels and higher HOMA-IR score. We observed several previously reported transcriptional changes (IGF1, IGFBP3, CISH, SOCS2) that are known to be induced by GH/IGF-1 in liver but are also induced in adipose tissue. We also identified several novel transcriptional changes, some of which may be important for GH/IGF responses (PTPN3 and PTPN4) and the effects of acromegaly on growth and proliferation. Several differentially expressed transcripts may be important in GH/IGF-1-induced metabolic changes. Specifically, induction of LPL, ABHD5, and NRIP1 can contribute to enhanced lipolysis and may explain the elevated adipose tissue lipolysis in acromegalic patients. Higher expression of TCF7L2 and the fatty acid desaturases FADS1, FADS2 and SCD could contribute to insulin resistance. Ceramides were not different between the two groups. In summary, we have identified the acromegaly gene expression signature in human adipose tissue. The significance of altered expression of specific transcripts will enhance our understanding of the metabolic and proliferative changes associated with acromegaly. PMID:26087292

Epstein-Barr virus latent gene sequences as geographical markers of viral origin: unique EBNA3 gene signatures identify Japanese viruses as distinct members of the Asian virus family.

PubMed

Sawada, Akihisa; Croom-Carter, Deborah; Kondo, Osamu; Yasui, Masahiro; Koyama-Sato, Maho; Inoue, Masami; Kawa, Keisei; Rickinson, Alan B; Tierney, Rosemary J

2011-05-01

Polymorphisms in Epstein-Barr virus (EBV) latent genes can identify virus strains from different human populations and individual strains within a population. An Asian EBV signature has been defined almost exclusively from Chinese viruses, with little information from other Asian countries. Here we sequenced polymorphic regions of the EBNA1, 2, 3A, 3B, 3C and LMP1 genes of 31 Japanese strains from control donors and EBV-associated T/NK-cell lymphoproliferative disease (T/NK-LPD) patients. Though identical to Chinese strains in their dominant EBNA1 and LMP1 alleles, Japanese viruses were subtly different at other loci. Thus, while Chinese viruses mainly fall into two families with strongly linked 'Wu' or 'Li' alleles at EBNA2 and EBNA3A/B/C, Japanese viruses all have the consensus Wu EBNA2 allele but fall into two families at EBNA3A/B/C. One family has variant Li-like sequences at EBNA3A and 3B and the consensus Li sequence at EBNA3C; the other family has variant Wu-like sequences at EBNA3A, variants of a low frequency Chinese allele 'Sp' at EBNA3B and a consensus Sp sequence at EBNA3C. Thus, EBNA3A/B/C allelotypes clearly distinguish Japanese from Chinese strains. Interestingly, most Japanese viruses also lack those immune-escape mutations in the HLA-A11 epitope-encoding region of EBNA3B that are so characteristic of viruses from the highly A11-positive Chinese population. Control donor-derived and T/NK-LPD-derived strains were similarly distributed across allelotypes and, by using allelic polymorphisms to track virus strains in patients pre- and post-haematopoietic stem-cell transplant, we show that a single strain can induce both T/NK-LPD and B-cell-lymphoproliferative disease in the same patient.

Gene expression signature of tolerance and lymphocyte subsets in stable renal transplants: results of a cross-sectional study.

PubMed

Moreso, Francesc; Torres, Irina B; Martínez-Gallo, Monica; Benlloch, Susana; Cantarell, Carme; Perelló, Manel; Jimeno, José; Pujol-Borrell, Ricardo; Seron, Daniel

2014-06-01

In kidney transplants operational tolerance has been associated with up-regulation of B cell differentiation genes and an increased number of total, naive and transitional peripheral B cells. The aim is to evaluate tolerance biomarkers in different cohorts of stable renal transplants under immunosuppression. This is a cross-sectional study conducted in renal transplants. We evaluate genetic tolerance signature and lymphocyte subsets in stable transplants treated with calcineurin inhibitors (CNI) at 1 (n=15), 5 (n=14) and 10 (n=16) years, and azathioprine-treated transplants followed 30 years (n=8). Healthy volunteers (n=10) and patients with chronic rejection (n=15) served as controls. We confirm that peripheral expression of IGKV1D-13 and IGKV4-1 genes by RT-PCR distinguish tolerant (n=10) from stable transplants (n=10) provided by the International Tolerance Network. Tolerance signature was defined as the lowest expression for both genes in tolerant patients. In CNI-treated patients, genetic signature of tolerance and B cells showed a time-dependent increase not observed in azathioprine-treated patients (p<0.01). Genetic tolerance signature was observed in 0% at 1, 7% at 5 and 25% at 10-years while it was not observed in azathioprine-treated and chronic rejection patients. Fifteen out of 16 CNI-treated transplants at 10 years were revaluated 3 months apart. Nine did not show the tolerance signature in any determination, 4 in one and 2 in both determinations. Genetic signature of tolerance was associated with an increase of total, naive and transitional B cells (p<0.05). IGKV1D-13 and IGKV4-1 gene expression and its linked B cell populations increase during follow up in CNI-treated patients. At 10 years, 2 out of 15 CNI treated patients consistently express biomarkers associated with true tolerance. In azathioprine-treated patients these biomarkers were down-regulated. Copyright © 2014 Elsevier B.V. All rights reserved.

Common and specific signatures of gene expression and protein-protein interactions in autoimmune diseases.

PubMed

Tuller, T; Atar, S; Ruppin, E; Gurevich, M; Achiron, A

2013-03-01

different subsignaling pathways. Analyses of the expression levels of dozens of genes and the protein-protein interactions among them demonstrated that CD and UC have relatively similar gene expression signatures, whereas the gene expression signatures of T1D and JRA relatively differ from the signatures of the other autoimmune diseases. These diseases are the only ones activated via the Fcɛ pathway. The relevant genes and pathways reported in this study are discussed at length, and may be helpful in the diagnoses and understanding of autoimmunity and/or specific autoimmune diseases.

Immune signatures of protective spleen memory CD8 T cells.

PubMed

Brinza, Lilia; Djebali, Sophia; Tomkowiak, Martine; Mafille, Julien; Loiseau, Céline; Jouve, Pierre-Emmanuel; de Bernard, Simon; Buffat, Laurent; Lina, Bruno; Ottmann, Michèle; Rosa-Calatrava, Manuel; Schicklin, Stéphane; Bonnefoy, Nathalie; Lauvau, Grégoire; Grau, Morgan; Wencker, Mélanie; Arpin, Christophe; Walzer, Thierry; Leverrier, Yann; Marvel, Jacqueline

2016-11-24

Memory CD8 T lymphocyte populations are remarkably heterogeneous and differ in their ability to protect the host. In order to identify the whole range of qualities uniquely associated with protective memory cells we compared the gene expression signatures of two qualities of memory CD8 T cells sharing the same antigenic-specificity: protective (Influenza-induced, Flu-TM) and non-protective (peptide-induced, TIM) spleen memory CD8 T cells. Although Flu-TM and TIM express classical phenotypic memory markers and are polyfunctional, only Flu-TM protects against a lethal viral challenge. Protective memory CD8 T cells express a unique set of genes involved in migration and survival that correlate with their unique capacity to rapidly migrate within the infected lung parenchyma in response to influenza infection. We also enlighten a new set of poised genes expressed by protective cells that is strongly enriched in cytokines and chemokines such as Ccl1, Ccl9 and Gm-csf. CCL1 and GM-CSF genes are also poised in human memory CD8 T cells. These immune signatures are also induced by two other pathogens (vaccinia virus and Listeria monocytogenes). The immune signatures associated with immune protection were identified on circulating cells, i.e. those that are easily accessible for immuno-monitoring and could help predict vaccines efficacy.

Prevalence of interferon type I signature in CD14 monocytes of patients with Sjögren's syndrome and association with disease activity and BAFF gene expression

PubMed Central

Brkic, Zana; Maria, Naomi I; van Helden-Meeuwsen, Cornelia G; van de Merwe, Joop P; van Daele, Paul L; Dalm, Virgil A; Wildenberg, Manon E; Beumer, Wouter; Drexhage, Hemmo A; Versnel, Marjan A

2013-01-01

Objective To determine the prevalence of upregulation of interferon (IFN) type I inducible genes, the so called ‘IFN type I signature’, in CD14 monocytes in 69 patients with primary Sjögren's syndrome (pSS) and 44 healthy controls (HC) and correlate it with disease manifestations and expression of B cell activating factor (BAFF). Methods Expression of IFI44L, IFI44, IFIT3, LY6E and MX1 was measured using real time quantitative PCR in monocytes. Expression values were used to calculate IFN type I scores for each subject. pSS patients positive for the IFN type I signature (IFN score≥10) and patients negative for the signature (IFN score<10) were then compared for clinical disease manifestations and BAFF expression. A bioassay using a monocytic cell line was performed to study whether BAFF mRNA expression was inducible by IFN type I activity in serum of patients with pSS. Results An IFN type I signature was present in 55% of patients with pSS compared with 4.5% of HC. Patients with the IFN type I signature showed: (a) higher EULAR Sjögren's Syndrome Disease Activity Index scores; higher anti-Ro52, anti-Ro60 and anti-La autoantibodies; higher rheumatoid factor; higher serum IgG; lower C3, lower absolute lymphocyte and neutrophil counts; (b)higher BAFF gene expression in monocytes. In addition, serum of signature-positive patients induced BAFF gene expression in monocytes. Conclusions The monocyte IFN type I signature identifies a subgroup of patients with pSS with a higher clinical disease activity together with higher BAFF mRNA expression. Such patients might benefit from treatment blocking IFN type I production or activity. PMID:22736090

Identification of two poorly prognosed ovarian carcinoma subtypes associated with CHEK2 germ-line mutation and non-CHEK2 somatic mutation gene signatures.

PubMed

Ow, Ghim Siong; Ivshina, Anna V; Fuentes, Gloria; Kuznetsov, Vladimir A

2014-01-01

High-grade serous ovarian cancer (HG-SOC), a major histologic type of epithelial ovarian cancer (EOC), is a poorly-characterized, heterogeneous and lethal disease where somatic mutations of TP53 are common and inherited loss-of-function mutations in BRCA1/2 predispose to cancer in 9.5-13% of EOC patients. However, the overall burden of disease due to either inherited or sporadic mutations is not known. We performed bioinformatics analyses of mutational and clinical data of 334 HG-SOC tumor samples from The Cancer Genome Atlas to identify novel tumor-driving mutations, survival-significant patient subgroups and tumor subtypes potentially driven by either hereditary or sporadic factors. We identified a sub-cluster of high-frequency mutations in 22 patients and 58 genes associated with DNA damage repair, apoptosis and cell cycle. Mutations of CHEK2, observed with the highest intensity, were associated with poor therapy response and overall survival (OS) of these patients (P = 8.00e-05), possibly due to detrimental effect of mutations at the nuclear localization signal. A 21-gene mutational prognostic signature significantly stratifies patients into relatively low or high-risk subgroups with 5-y OS of 37% or 6%, respectively (P = 7.31e-08). Further analysis of these genes and high-risk subgroup revealed 2 distinct classes of tumors characterized by either germline mutations of genes such as CHEK2, RPS6KA2 and MLL4, or somatic mutations of other genes in the signature. Our results could provide improvement in prediction and clinical management of HG-SOC, facilitate our understanding of this complex disease, guide the design of targeted therapeutics and improve screening efforts to identify women at high-risk of hereditary ovarian cancers distinct from those associated with BRCA1/2 mutations.

Identification of two poorly prognosed ovarian carcinoma subtypes associated with CHEK2 germ-line mutation and non-CHEK2 somatic mutation gene signatures

PubMed Central

Ow, Ghim Siong; Ivshina, Anna V; Fuentes, Gloria; Kuznetsov, Vladimir A

2014-01-01

High-grade serous ovarian cancer (HG-SOC), a major histologic type of epithelial ovarian cancer (EOC), is a poorly-characterized, heterogeneous and lethal disease where somatic mutations of TP53 are common and inherited loss-of-function mutations in BRCA1/2 predispose to cancer in 9.5–13% of EOC patients. However, the overall burden of disease due to either inherited or sporadic mutations is not known.     We performed bioinformatics analyses of mutational and clinical data of 334 HG-SOC tumor samples from The Cancer Genome Atlas to identify novel tumor-driving mutations, survival-significant patient subgroups and tumor subtypes potentially driven by either hereditary or sporadic factors. We identified a sub-cluster of high-frequency mutations in 22 patients and 58 genes associated with DNA damage repair, apoptosis and cell cycle. Mutations of CHEK2, observed with the highest intensity, were associated with poor therapy response and overall survival (OS) of these patients (P = 8.00e-05), possibly due to detrimental effect of mutations at the nuclear localization signal. A 21-gene mutational prognostic signature significantly stratifies patients into relatively low or high-risk subgroups with 5-y OS of 37% or 6%, respectively (P = 7.31e-08). Further analysis of these genes and high-risk subgroup revealed 2 distinct classes of tumors characterized by either germline mutations of genes such as CHEK2, RPS6KA2 and MLL4, or somatic mutations of other genes in the signature. Our results could provide improvement in prediction and clinical management of HG-SOC, facilitate our understanding of this complex disease, guide the design of targeted therapeutics and improve screening efforts to identify women at high-risk of hereditary ovarian cancers distinct from those associated with BRCA1/2 mutations. PMID:24879340

Longitudinal Analysis of Whole Blood Transcriptomes to Explore Molecular Signatures Associated With Acute Renal Allograft Rejection

PubMed Central

Shin, Heesun; Günther, Oliver; Hollander, Zsuzsanna; Wilson-McManus, Janet E.; Ng, Raymond T.; Balshaw, Robert; Keown, Paul A.; McMaster, Robert; McManus, Bruce M.; Isbel, Nicole M.; Knoll, Greg; Tebbutt, Scott J.

2014-01-01

In this study, we explored a time course of peripheral whole blood transcriptomes from kidney transplantation patients who either experienced an acute rejection episode or did not in order to better delineate the immunological and biological processes measureable in blood leukocytes that are associated with acute renal allograft rejection. Using microarrays, we generated gene expression data from 24 acute rejectors and 24 nonrejectors. We filtered the data to obtain the most unambiguous and robustly expressing probe sets and selected a subset of patients with the clearest phenotype. We then performed a data-driven exploratory analysis using data reduction and differential gene expression analysis tools in order to reveal gene expression signatures associated with acute allograft rejection. Using a template-matching algorithm, we then expanded our analysis to include time course data, identifying genes whose expression is modulated leading up to acute rejection. We have identified molecular phenotypes associated with acute renal allograft rejection, including a significantly upregulated signature of neutrophil activation and accumulation following transplant surgery that is common to both acute rejectors and nonrejectors. Our analysis shows that this expression signature appears to stabilize over time in nonrejectors but persists in patients who go on to reject the transplanted organ. In addition, we describe an expression signature characteristic of lymphocyte activity and proliferation. This lymphocyte signature is significantly downregulated in both acute rejectors and nonrejectors following surgery; however, patients who go on to reject the organ show a persistent downregulation of this signature relative to the neutrophil signature. PMID:24526836

Co-expression network analysis identified six hub genes in association with metastasis risk and prognosis in hepatocellular carcinoma

PubMed Central

Feng, Juerong; Zhou, Rui; Chang, Ying; Liu, Jing; Zhao, Qiu

2017-01-01

Hepatocellular carcinoma (HCC) has a high incidence and mortality worldwide, and its carcinogenesis and progression are influenced by a complex network of gene interactions. A weighted gene co-expression network was constructed to identify gene modules associated with the clinical traits in HCC (n = 214). Among the 13 modules, high correlation was only found between the red module and metastasis risk (classified by the HCC metastasis gene signature) (R2 = −0.74). Moreover, in the red module, 34 network hub genes for metastasis risk were identified, six of which (ABAT, AGXT, ALDH6A1, CYP4A11, DAO and EHHADH) were also hub nodes in the protein-protein interaction network of the module genes. Thus, a total of six hub genes were identified. In validation, all hub genes showed a negative correlation with the four-stage HCC progression (P for trend < 0.05) in the test set. Furthermore, in the training set, HCC samples with any hub gene lowly expressed demonstrated a higher recurrence rate and poorer survival rate (hazard ratios with 95% confidence intervals > 1). RNA-sequencing data of 142 HCC samples showed consistent results in the prognosis. Gene set enrichment analysis (GSEA) demonstrated that in the samples with any hub gene highly expressed, a total of 24 functional gene sets were enriched, most of which focused on amino acid metabolism and oxidation. In conclusion, co-expression network analysis identified six hub genes in association with HCC metastasis risk and prognosis, which might improve the prognosis by influencing amino acid metabolism and oxidation. PMID:28430663

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.

High-Throughput, Signature-Tagged Mutagenic Approach To Identify Novel Virulence Factors of Yersinia pestis CO92 in a Mouse Model of Infection

PubMed Central

Ponnusamy, Duraisamy; Fitts, Eric C.; Erova, Tatiana E.; Kozlova, Elena V.; Kirtley, Michelle L.; Tiner, Bethany L.; Andersson, Jourdan A.

2015-01-01

The identification of new virulence factors in Yersinia pestis and understanding their molecular mechanisms during an infection process are necessary in designing a better vaccine or to formulate an appropriate therapeutic intervention. By using a high-throughput, signature-tagged mutagenic approach, we created 5,088 mutants of Y. pestis strain CO92 and screened them in a mouse model of pneumonic plague at a dose equivalent to 5 50% lethal doses (LD50) of wild-type (WT) CO92. From this screen, we obtained 118 clones showing impairment in disseminating to the spleen, based on hybridization of input versus output DNA from mutant pools with 53 unique signature tags. In the subsequent screen, 20/118 mutants exhibited attenuation at 8 LD50 when tested in a mouse model of bubonic plague, with infection by 10/20 of the aforementioned mutants resulting in 40% or higher survival rates at an infectious dose of 40 LD50. Upon sequencing, six of the attenuated mutants were found to carry interruptions in genes encoding hypothetical proteins or proteins with putative functions. Mutants with in-frame deletion mutations of two of the genes identified from the screen, namely, rbsA, which codes for a putative sugar transport system ATP-binding protein, and vasK, a component of the type VI secretion system, were also found to exhibit some attenuation at 11 or 12 LD50 in a mouse model of pneumonic plague. Likewise, among the remaining 18 signature-tagged mutants, 9 were also attenuated (40 to 100%) at 12 LD50 in a pneumonic plague mouse model. Previously, we found that deleting genes encoding Braun lipoprotein (Lpp) and acyltransferase (MsbB), the latter of which modifies lipopolysaccharide function, reduced the virulence of Y. pestis CO92 in mouse models of bubonic and pneumonic plague. Deletion of rbsA and vasK genes from either the Δlpp single or the Δlpp ΔmsbB double mutant augmented the attenuation to provide 90 to 100% survivability to mice in a pneumonic plague model at 20

High-throughput, signature-tagged mutagenic approach to identify novel virulence factors of Yersinia pestis CO92 in a mouse model of infection.

PubMed

Ponnusamy, Duraisamy; Fitts, Eric C; Sha, Jian; Erova, Tatiana E; Kozlova, Elena V; Kirtley, Michelle L; Tiner, Bethany L; Andersson, Jourdan A; Chopra, Ashok K

2015-05-01

The identification of new virulence factors in Yersinia pestis and understanding their molecular mechanisms during an infection process are necessary in designing a better vaccine or to formulate an appropriate therapeutic intervention. By using a high-throughput, signature-tagged mutagenic approach, we created 5,088 mutants of Y. pestis strain CO92 and screened them in a mouse model of pneumonic plague at a dose equivalent to 5 50% lethal doses (LD50) of wild-type (WT) CO92. From this screen, we obtained 118 clones showing impairment in disseminating to the spleen, based on hybridization of input versus output DNA from mutant pools with 53 unique signature tags. In the subsequent screen, 20/118 mutants exhibited attenuation at 8 LD50 when tested in a mouse model of bubonic plague, with infection by 10/20 of the aforementioned mutants resulting in 40% or higher survival rates at an infectious dose of 40 LD50. Upon sequencing, six of the attenuated mutants were found to carry interruptions in genes encoding hypothetical proteins or proteins with putative functions. Mutants with in-frame deletion mutations of two of the genes identified from the screen, namely, rbsA, which codes for a putative sugar transport system ATP-binding protein, and vasK, a component of the type VI secretion system, were also found to exhibit some attenuation at 11 or 12 LD50 in a mouse model of pneumonic plague. Likewise, among the remaining 18 signature-tagged mutants, 9 were also attenuated (40 to 100%) at 12 LD50 in a pneumonic plague mouse model. Previously, we found that deleting genes encoding Braun lipoprotein (Lpp) and acyltransferase (MsbB), the latter of which modifies lipopolysaccharide function, reduced the virulence of Y. pestis CO92 in mouse models of bubonic and pneumonic plague. Deletion of rbsA and vasK genes from either the Δlpp single or the Δlpp ΔmsbB double mutant augmented the attenuation to provide 90 to 100% survivability to mice in a pneumonic plague model at 20

Using variable rate models to identify genes under selection in sequence pairs: their validity and limitations for EST sequences.

PubMed

Church, Sheri A; Livingstone, Kevin; Lai, Zhao; Kozik, Alexander; Knapp, Steven J; Michelmore, Richard W; Rieseberg, Loren H

2007-02-01

Using likelihood-based variable selection models, we determined if positive selection was acting on 523 EST sequence pairs from two lineages of sunflower and lettuce. Variable rate models are generally not used for comparisons of sequence pairs due to the limited information and the inaccuracy of estimates of specific substitution rates. However, previous studies have shown that the likelihood ratio test (LRT) is reliable for detecting positive selection, even with low numbers of sequences. These analyses identified 56 genes that show a signature of selection, of which 75% were not identified by simpler models that average selection across codons. Subsequent mapping studies in sunflower show four of five of the positively selected genes identified by these methods mapped to domestication QTLs. We discuss the validity and limitations of using variable rate models for comparisons of sequence pairs, as well as the limitations of using ESTs for identification of positively selected genes.

A New Gene Expression Signature for Triple-Negative Breast Cancer Using Frozen Fresh Tissue before Neoadjuvant Chemotherapy

PubMed Central

Santuario-Facio, Sandra K; Cardona-Huerta, Servando; Perez-Paramo, Yadira X; Trevino, Victor; Hernandez-Cabrera, Francisco; Rojas-Martinez, Augusto; Uscanga-Perales, Grecia; Martinez-Rodriguez, Jorge L; Martinez-Jacobo, Lizeth; Padilla-Rivas, Gerardo; Muñoz-Maldonado, Gerardo; Gonzalez-Guerrero, Juan Francisco; Valero-Gomez, Javier; Vazquez-Guerrero, Ana L; Martinez-Rodriguez, Herminia G; Barboza-Quintana, Alvaro; Barboza-Quintana, Oralia; Garza-Guajardo, Raquel; Ortiz-Lopez, Rocio

2017-01-01

Triple-negative breast cancer (TNBC) is an aggressive subtype of breast cancer tumors. Comparisons between TNBC and non–triple-negative breast cancer (nTNBC) may help to differentiate key components involved in TNBC neoplasms. The purpose of the study was to analyze the expression profile of TNBC versus nTNBC tumors in a homogeneous population from northeastern Mexico. A prospective study of 50 patients (25 TNBC and 25 nTNBC) was conducted. Clinic parameters were equally distributed for TNBC and nTNBC: age at diagnosis (51 versus 47 years, p = 0.1), glucose level (107 mg/dl versus 104 mg/dl, p = 0.64), and body mass index (28 versus 29, p = 0.14). Core biopsies were collected for histopathological diagnosis and gene expression analysis. Total RNA was isolated and expression profiling was performed. Forty genes showed differential expression pattern in TNBC tumors. Among these, nine overexpressed genes (PRKX/PRKY, UGT8, HMGA1, LPIN1, HAPLN3, FAM171A1, BCL141A, FOXC1, and ANKRD11), and one underexpressed gene (ANX9) are involved in general metabolism. Based on this biochemical peculiarity and the overexpression of BCL11A and FOXC1 (involved in tumor growth and metastasis, respectively), we validated by quantitative polymerase chain reaction the expression profiles of seven genes out of the signature. In this report, a new gene signature for TNBC is proposed. To our knowledge, this is the first TNBC signature that describes genes involved in general metabolism. The findings may be pertinent for Mexican patients and require evaluation in other ethnic groups and populations. PMID:28474731

Gene expression profiles reveal key genes for early diagnosis and treatment of adamantinomatous craniopharyngioma.

PubMed

Yang, Jun; Hou, Ziming; Wang, Changjiang; Wang, Hao; Zhang, Hongbing

2018-04-23

Adamantinomatous craniopharyngioma (ACP) is an aggressive brain tumor that occurs predominantly in the pediatric population. Conventional diagnosis method and standard therapy cannot treat ACPs effectively. In this paper, we aimed to identify key genes for ACP early diagnosis and treatment. Datasets GSE94349 and GSE68015 were obtained from Gene Expression Omnibus database. Consensus clustering was applied to discover the gene clusters in the expression data of GSE94349 and functional enrichment analysis was performed on gene set in each cluster. The protein-protein interaction (PPI) network was built by the Search Tool for the Retrieval of Interacting Genes, and hubs were selected. Support vector machine (SVM) model was built based on the signature genes identified from enrichment analysis and PPI network. Dataset GSE94349 was used for training and testing, and GSE68015 was used for validation. Besides, RT-qPCR analysis was performed to analyze the expression of signature genes in ACP samples compared with normal controls. Seven gene clusters were discovered in the differentially expressed genes identified from GSE94349 dataset. Enrichment analysis of each cluster identified 25 pathways that highly associated with ACP. PPI network was built and 46 hubs were determined. Twenty-five pathway-related genes that overlapped with the hubs in PPI network were used as signatures to establish the SVM diagnosis model for ACP. The prediction accuracy of SVM model for training, testing, and validation data were 94, 85, and 74%, respectively. The expression of CDH1, CCL2, ITGA2, COL8A1, COL6A2, and COL6A3 were significantly upregulated in ACP tumor samples, while CAMK2A, RIMS1, NEFL, SYT1, and STX1A were significantly downregulated, which were consistent with the differentially expressed gene analysis. SVM model is a promising classification tool for screening and early diagnosis of ACP. The ACP-related pathways and signature genes will advance our knowledge of ACP pathogenesis

REDD1 induction regulates the skeletal muscle gene expression signature following acute aerobic exercise.

PubMed

Gordon, Bradley S; Steiner, Jennifer L; Rossetti, Michael L; Qiao, Shuxi; Ellisen, Leif W; Govindarajan, Subramaniam S; Eroshkin, Alexey M; Williamson, David L; Coen, Paul M

2017-12-01

The metabolic stress placed on skeletal muscle by aerobic exercise promotes acute and long-term health benefits in part through changes in gene expression. However, the transducers that mediate altered gene expression signatures have not been completely elucidated. Regulated in development and DNA damage 1 (REDD1) is a stress-induced protein whose expression is transiently increased in skeletal muscle following acute aerobic exercise. However, the role of this induction remains unclear. Because REDD1 altered gene expression in other model systems, we sought to determine whether REDD1 induction following acute exercise altered the gene expression signature in muscle. To do this, wild-type and REDD1-null mice were randomized to remain sedentary or undergo a bout of acute treadmill exercise. Exercised mice recovered for 1, 3, or 6 h before euthanization. Acute exercise induced a transient increase in REDD1 protein expression within the plantaris only at 1 h postexercise, and the induction occurred in both cytosolic and nuclear fractions. At this time point, global changes in gene expression were surveyed using microarray. REDD1 induction was required for the exercise-induced change in expression of 24 genes. Validation by RT-PCR confirmed that the exercise-mediated changes in genes related to exercise capacity, muscle protein metabolism, neuromuscular junction remodeling, and Metformin action were negated in REDD1-null mice. Finally, the exercise-mediated induction of REDD1 was partially dependent upon glucocorticoid receptor activation. In all, these data show that REDD1 induction regulates the exercise-mediated change in a distinct set of genes within skeletal muscle. Copyright © 2017 the American Physiological Society.

Transcriptome meta-analysis reveals common differential and global gene expression profiles in cystic fibrosis and other respiratory disorders and identifies CFTR regulators.

PubMed

Clarke, Luka A; Botelho, Hugo M; Sousa, Lisete; Falcao, Andre O; Amaral, Margarida D

2015-11-01

A meta-analysis of 13 independent microarray data sets was performed and gene expression profiles from cystic fibrosis (CF), similar disorders (COPD: chronic obstructive pulmonary disease, IPF: idiopathic pulmonary fibrosis, asthma), environmental conditions (smoking, epithelial injury), related cellular processes (epithelial differentiation/regeneration), and non-respiratory "control" conditions (schizophrenia, dieting), were compared. Similarity among differentially expressed (DE) gene lists was assessed using a permutation test, and a clustergram was constructed, identifying common gene markers. Global gene expression values were standardized using a novel approach, revealing that similarities between independent data sets run deeper than shared DE genes. Correlation of gene expression values identified putative gene regulators of the CF transmembrane conductance regulator (CFTR) gene, of potential therapeutic significance. Our study provides a novel perspective on CF epithelial gene expression in the context of other lung disorders and conditions, and highlights the contribution of differentiation/EMT and injury to gene signatures of respiratory disease. Copyright © 2015 Elsevier Inc. All rights reserved.

Gene expression of Caenorhabditis elegans neurons carries information on their synaptic connectivity.

PubMed

Kaufman, Alon; Dror, Gideon; Meilijson, Isaac; Ruppin, Eytan

2006-12-08

The claim that genetic properties of neurons significantly influence their synaptic network structure is a common notion in neuroscience. The nematode Caenorhabditis elegans provides an exciting opportunity to approach this question in a large-scale quantitative manner. Its synaptic connectivity network has been identified, and, combined with cellular studies, we currently have characteristic connectivity and gene expression signatures for most of its neurons. By using two complementary analysis assays we show that the expression signature of a neuron carries significant information about its synaptic connectivity signature, and identify a list of putative genes predicting neural connectivity. The current study rigorously quantifies the relation between gene expression and synaptic connectivity signatures in the C. elegans nervous system and identifies subsets of neurons where this relation is highly marked. The results presented and the genes identified provide a promising starting point for further, more detailed computational and experimental investigations.

Gene expression-based chemical genomics identifies potential therapeutic drugs in hepatocellular carcinoma.

PubMed

Chen, Ming-Huang; Yang, Wu-Lung R; Lin, Kuan-Ting; Liu, Chia-Hung; Liu, Yu-Wen; Huang, Kai-Wen; Chang, Peter Mu-Hsin; Lai, Jin-Mei; Hsu, Chun-Nan; Chao, Kun-Mao; Kao, Cheng-Yan; Huang, Chi-Ying F

2011-01-01

Hepatocellular carcinoma (HCC) is an aggressive tumor with a poor prognosis. Currently, only sorafenib is approved by the FDA for advanced HCC treatment; therefore, there is an urgent need to discover candidate therapeutic drugs for HCC. We hypothesized that if a drug signature could reverse, at least in part, the gene expression signature of HCC, it might have the potential to inhibit HCC-related pathways and thereby treat HCC. To test this hypothesis, we first built an integrative platform, the "Encyclopedia of Hepatocellular Carcinoma genes Online 2", dubbed EHCO2, to systematically collect, organize and compare the publicly available data from HCC studies. The resulting collection includes a total of 4,020 genes. To systematically query the Connectivity Map (CMap), which includes 6,100 drug-mediated expression profiles, we further designed various gene signature selection and enrichment methods, including a randomization technique, majority vote, and clique analysis. Subsequently, 28 out of 50 prioritized drugs, including tanespimycin, trichostatin A, thioguanosine, and several anti-psychotic drugs with anti-tumor activities, were validated via MTT cell viability assays and clonogenic assays in HCC cell lines. To accelerate their future clinical use, possibly through drug-repurposing, we selected two well-established drugs to test in mice, chlorpromazine and trifluoperazine. Both drugs inhibited orthotopic liver tumor growth. In conclusion, we successfully discovered and validated existing drugs for potential HCC therapeutic use with the pipeline of Connectivity Map analysis and lab verification, thereby suggesting the usefulness of this procedure to accelerate drug repurposing for HCC treatment.

Transcriptome profiling of the whitefly Bemisia tabaci reveals stage-specific gene expression signatures for thiamethoxam resistance

PubMed Central

Yang, N; Xie, W; Jones, CM; Bass, C; Jiao, X; Yang, X; Liu, B; Li, R; Zhang, Y

2013-01-01

Bemisia tabaci has developed high levels of resistance to many insecticides including the neonicotinoids and there is strong evidence that for some compounds resistance is stage-specific. To investigate the molecular basis of B. tabaci resistance to the neonicotinoid thiamethoxam we used a custom whitefly microarray to compare gene expression in the egg, nymph and adult stages of a thiamethoxam-resistant strain (TH-R) with a susceptible strain (TH-S). Gene ontology and bioinformatic analyses revealed that in all life stages many of the differentially expressed transcripts encoded enzymes involved in metabolic processes and/or metabolism of xenobiotics. Several of these are candidate resistance genes and include the cytochrome P450 CYP6CM1, which has been shown to confer resistance to several neonicotinoids previously, a P450 belonging to the Cytochrome P450s 4 family and a glutathione S-transferase (GST) belonging to the sigma class. Finally several ATP-binding cassette transporters of the ABCG subfamily were highly over-expressed in the adult stage of the TH-R strain and may play a role in resistance by active efflux. Here, we evaluated both common and stage-specific gene expression signatures and identified several candidate resistance genes that may underlie B. tabaci resistance to thiamethoxam. PMID:23889345

A BRCA1 deficient-like signature is enriched in breast cancer brain metastases and predicts DNA damage-induced poly (ADP-ribose) polymerase inhibitor sensitivity.

PubMed

McMullin, Ryan P; Wittner, Ben S; Yang, Chuanwei; Denton-Schneider, Benjamin R; Hicks, Daniel; Singavarapu, Raj; Moulis, Sharon; Lee, Jeongeun; Akbari, Mohammad R; Narod, Steven A; Aldape, Kenneth D; Steeg, Patricia S; Ramaswamy, Sridhar; Sgroi, Dennis C

2014-03-14

There is an unmet clinical need for biomarkers to identify breast cancer patients at an increased risk of developing brain metastases. The objective is to identify gene signatures and biological pathways associated with human epidermal growth factor receptor 2-positive (HER2+) brain metastasis. We combined laser capture microdissection and gene expression microarrays to analyze malignant epithelium from HER2+ breast cancer brain metastases with that from HER2+ nonmetastatic primary tumors. Differential gene expression was performed including gene set enrichment analysis (GSEA) using publicly available breast cancer gene expression data sets. In a cohort of HER2+ breast cancer brain metastases, we identified a gene expression signature that anti-correlates with overexpression of BRCA1. Sequence analysis of the HER2+ brain metastases revealed no pathogenic mutations of BRCA1, and therefore the aforementioned signature was designated BRCA1 Deficient-Like (BD-L). Evaluation of an independent cohort of breast cancer metastases demonstrated that BD-L values are significantly higher in brain metastases as compared to other metastatic sites. Although the BD-L signature is present in all subtypes of breast cancer, it is significantly higher in BRCA1 mutant primary tumors as compared with sporadic breast tumors. Additionally, BD-L signature values are significantly higher in HER2-/ER- primary tumors as compared with HER2+/ER + and HER2-/ER + tumors. The BD-L signature correlates with breast cancer cell line pharmacologic response to a combination of poly (ADP-ribose) polymerase (PARP) inhibitor and temozolomide, and the signature outperformed four published gene signatures of BRCA1/2 deficiency. A BD-L signature is enriched in HER2+ breast cancer brain metastases without pathogenic BRCA1 mutations. Unexpectedly, elevated BD-L values are found in a subset of primary tumors across all breast cancer subtypes. Evaluation of pharmacological sensitivity in breast cancer

A BRCA1 deficient-like signature is enriched in breast cancer brain metastases and predicts DNA damage-induced poly (ADP-ribose) polymerase inhibitor sensitivity

PubMed Central

2014-01-01

Introduction There is an unmet clinical need for biomarkers to identify breast cancer patients at an increased risk of developing brain metastases. The objective is to identify gene signatures and biological pathways associated with human epidermal growth factor receptor 2-positive (HER2+) brain metastasis. Methods We combined laser capture microdissection and gene expression microarrays to analyze malignant epithelium from HER2+ breast cancer brain metastases with that from HER2+ nonmetastatic primary tumors. Differential gene expression was performed including gene set enrichment analysis (GSEA) using publicly available breast cancer gene expression data sets. Results In a cohort of HER2+ breast cancer brain metastases, we identified a gene expression signature that anti-correlates with overexpression of BRCA1. Sequence analysis of the HER2+ brain metastases revealed no pathogenic mutations of BRCA1, and therefore the aforementioned signature was designated BRCA1 Deficient-Like (BD-L). Evaluation of an independent cohort of breast cancer metastases demonstrated that BD-L values are significantly higher in brain metastases as compared to other metastatic sites. Although the BD-L signature is present in all subtypes of breast cancer, it is significantly higher in BRCA1 mutant primary tumors as compared with sporadic breast tumors. Additionally, BD-L signature values are significantly higher in HER2-/ER- primary tumors as compared with HER2+/ER + and HER2-/ER + tumors. The BD-L signature correlates with breast cancer cell line pharmacologic response to a combination of poly (ADP-ribose) polymerase (PARP) inhibitor and temozolomide, and the signature outperformed four published gene signatures of BRCA1/2 deficiency. Conclusions A BD-L signature is enriched in HER2+ breast cancer brain metastases without pathogenic BRCA1 mutations. Unexpectedly, elevated BD-L values are found in a subset of primary tumors across all breast cancer subtypes. Evaluation of

Peripheral Blood Gene Expression as a Novel Genomic Biomarker in Complicated Sarcoidosis

PubMed Central

Sweiss, Nadera J.; Chen, Edward S.; Moller, David R.; Knox, Kenneth S.; Ma, Shwu-Fan; Wade, Michael S.; Noth, Imre; Machado, Roberto F.; Garcia, Joe G. N.

2012-01-01

Sarcoidosis, a systemic granulomatous syndrome invariably affecting the lung, typically spontaneously remits but in ∼20% of cases progresses with severe lung dysfunction or cardiac and neurologic involvement (complicated sarcoidosis). Unfortunately, current biomarkers fail to distinguish patients with remitting (uncomplicated) sarcoidosis from other fibrotic lung disorders, and fail to identify individuals at risk for complicated sarcoidosis. We utilized genome-wide peripheral blood gene expression analysis to identify a 20-gene sarcoidosis biomarker signature distinguishing sarcoidosis (n = 39) from healthy controls (n = 35, 86% classification accuracy) and which served as a molecular signature for complicated sarcoidosis (n = 17). As aberrancies in T cell receptor (TCR) signaling, JAK-STAT (JS) signaling, and cytokine-cytokine receptor (CCR) signaling are implicated in sarcoidosis pathogenesis, a 31-gene signature comprised of T cell signaling pathway genes associated with sarcoidosis (TCR/JS/CCR) was compared to the unbiased 20-gene biomarker signature but proved inferior in prediction accuracy in distinguishing complicated from uncomplicated sarcoidosis. Additional validation strategies included significant association of single nucleotide polymorphisms (SNPs) in signature genes with sarcoidosis susceptibility and severity (unbiased signature genes - CX3CR1, FKBP1A, NOG, RBM12B, SENS3, TSHZ2; T cell/JAK-STAT pathway genes such as AKT3, CBLB, DLG1, IFNG, IL2RA, IL7R, ITK, JUN, MALT1, NFATC2, PLCG1, SPRED1). In summary, this validated peripheral blood molecular gene signature appears to be a valuable biomarker in identifying cases with sarcoidoisis and predicting risk for complicated sarcoidosis. PMID:22984568

L1000CDS2: LINCS L1000 characteristic direction signatures search engine.

PubMed

Duan, Qiaonan; Reid, St Patrick; Clark, Neil R; Wang, Zichen; Fernandez, Nicolas F; Rouillard, Andrew D; Readhead, Ben; Tritsch, Sarah R; Hodos, Rachel; Hafner, Marc; Niepel, Mario; Sorger, Peter K; Dudley, Joel T; Bavari, Sina; Panchal, Rekha G; Ma'ayan, Avi

2016-01-01

The library of integrated network-based cellular signatures (LINCS) L1000 data set currently comprises of over a million gene expression profiles of chemically perturbed human cell lines. Through unique several intrinsic and extrinsic benchmarking schemes, we demonstrate that processing the L1000 data with the characteristic direction (CD) method significantly improves signal to noise compared with the MODZ method currently used to compute L1000 signatures. The CD processed L1000 signatures are served through a state-of-the-art web-based search engine application called L1000CDS 2 . The L1000CDS 2 search engine provides prioritization of thousands of small-molecule signatures, and their pairwise combinations, predicted to either mimic or reverse an input gene expression signature using two methods. The L1000CDS 2 search engine also predicts drug targets for all the small molecules profiled by the L1000 assay that we processed. Targets are predicted by computing the cosine similarity between the L1000 small-molecule signatures and a large collection of signatures extracted from the gene expression omnibus (GEO) for single-gene perturbations in mammalian cells. We applied L1000CDS 2 to prioritize small molecules that are predicted to reverse expression in 670 disease signatures also extracted from GEO, and prioritized small molecules that can mimic expression of 22 endogenous ligand signatures profiled by the L1000 assay. As a case study, to further demonstrate the utility of L1000CDS 2 , we collected expression signatures from human cells infected with Ebola virus at 30, 60 and 120 min. Querying these signatures with L1000CDS 2 we identified kenpaullone, a GSK3B/CDK2 inhibitor that we show, in subsequent experiments, has a dose-dependent efficacy in inhibiting Ebola infection in vitro without causing cellular toxicity in human cell lines. In summary, the L1000CDS 2 tool can be applied in many biological and biomedical settings, while improving the extraction of

L1000CDS2: LINCS L1000 characteristic direction signatures search engine

PubMed Central

Duan, Qiaonan; Reid, St Patrick; Clark, Neil R; Wang, Zichen; Fernandez, Nicolas F; Rouillard, Andrew D; Readhead, Ben; Tritsch, Sarah R; Hodos, Rachel; Hafner, Marc; Niepel, Mario; Sorger, Peter K; Dudley, Joel T; Bavari, Sina; Panchal, Rekha G; Ma’ayan, Avi

2016-01-01

The library of integrated network-based cellular signatures (LINCS) L1000 data set currently comprises of over a million gene expression profiles of chemically perturbed human cell lines. Through unique several intrinsic and extrinsic benchmarking schemes, we demonstrate that processing the L1000 data with the characteristic direction (CD) method significantly improves signal to noise compared with the MODZ method currently used to compute L1000 signatures. The CD processed L1000 signatures are served through a state-of-the-art web-based search engine application called L1000CDS2. The L1000CDS2 search engine provides prioritization of thousands of small-molecule signatures, and their pairwise combinations, predicted to either mimic or reverse an input gene expression signature using two methods. The L1000CDS2 search engine also predicts drug targets for all the small molecules profiled by the L1000 assay that we processed. Targets are predicted by computing the cosine similarity between the L1000 small-molecule signatures and a large collection of signatures extracted from the gene expression omnibus (GEO) for single-gene perturbations in mammalian cells. We applied L1000CDS2 to prioritize small molecules that are predicted to reverse expression in 670 disease signatures also extracted from GEO, and prioritized small molecules that can mimic expression of 22 endogenous ligand signatures profiled by the L1000 assay. As a case study, to further demonstrate the utility of L1000CDS2, we collected expression signatures from human cells infected with Ebola virus at 30, 60 and 120 min. Querying these signatures with L1000CDS2 we identified kenpaullone, a GSK3B/CDK2 inhibitor that we show, in subsequent experiments, has a dose-dependent efficacy in inhibiting Ebola infection in vitro without causing cellular toxicity in human cell lines. In summary, the L1000CDS2 tool can be applied in many biological and biomedical settings, while improving the extraction of knowledge

Epigenomic Elements Analyses for Promoters Identify ESRRG as a New Susceptibility Gene for Obesity-related Traits

PubMed Central

Dong, Shan-Shan; Guo, Yan; Zhu, Dong-Li; Chen, Xiao-Feng; Wu, Xiao-Ming; Shen, Hui; Chen, Xiang-Ding; Tan, Li-Jun; Tian, Qing; Deng, Hong-Wen; Yang, Tie-Lin

2016-01-01

OBJECTIVES With ENCODE epigenomic data and results from published genome-wide association studies (GWASs), we aimed to find regulatory signatures of obesity genes and discover novel susceptibility genes. METHODS Obesity genes were obtained from public GWASs databases and their promoters were annotated based on the regulatory elements information. Significantly enriched or depleted epigenomic elements in the promoters of obesity genes were evaluated and all human genes were then prioritized according to the existence of the selected elements to predict new candidate genes. Top ranked genes were subsequently applied to validate their associations with obesity-related traits in three independent in-house GWASs samples. RESULTS We identified RAD21 and EZH2 as over-represented, STAT2 and IRF3 as depleted transcription factors. Histone modification of H3K9me3 and chromatin state segmentation of “poised promoter” and “repressed” were overrepresented. All genes were prioritized and we selected the top five genes for validation at population level. Combined results from the three GWASs samples, rs7522101 in ESRRG remained significantly associated with BMI after multiple testing corrections (P = 7.25 × 10−5). It was also associated with β-cell function (P = 1.99 × 10−3) and fasting glucose level (P < 0.05) in the meta-analyses of glucose and insulin-related traits consortium (MAGIC) dataset. CONCLUSIONS In summary, we identified epigenomic characteristics for obesity genes and suggested ESRRG as a novel obesity susceptibility gene. PMID:27113491

Using Signature Genes as Tools To Assess Environmental Viral Ecology and Diversity

PubMed Central

Adriaenssens, Evelien M.

2014-01-01

Viruses (including bacteriophages) are the most abundant biological entities on the planet. As such, they are thought to have a major impact on all aspects of microbial community structure and function. Despite this critical role in ecosystem processes, the study of virus/phage diversity has lagged far behind parallel studies of the bacterial and eukaryotic kingdoms, largely due to the absence of any universal phylogenetic marker. Here we review the development and use of signature genes to investigate viral diversity, as a viable strategy for data sets of specific virus groups. Genes that have been used include those encoding structural proteins, such as portal protein, major capsid protein, and tail sheath protein, auxiliary metabolism genes, such as psbA, psbB, and phoH, and several polymerase genes. These marker genes have been used in combination with PCR-based fingerprinting and/or sequencing strategies to investigate spatial, temporal, and seasonal variations and diversity in a wide range of habitats. PMID:24837394

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.

Sphingosine-1-Phosphate Signaling and Metabolism Gene Signature in Pediatric Inflammatory Bowel Disease: A Matched-case Control Pilot Study

PubMed Central

Suh, Jung H.; Degagné, Émilie; Gleghorn, Elizabeth E.; Setty, Mala; Rodriguez, Alexis; Park, K. T.; Verstraete, Sofia G.; Heyman, Melvin B.; Patel, Ashish S.; Irek, Melissa; Gildengorin, Ginny L.; Hubbard, Neil E.; Borowsky, Alexander D.; Saba, Julie D.

2018-01-01

Goal The aim of this study was to investigate gene expression levels of proteins involved in sphingosine-1-phosphate (S1P) metabolism and signaling in a pediatric inflammatory bowel disease (IBD) patient population. Background IBD is a debilitating disease affecting 0.4% of the US population. The incidence of IBD in childhood is rising. Identifying effective targeted therapies that can be used safely in young patients and developing tools for selecting specific candidates for targeted therapies are important goals. Clinical IBD trials now underway target S1PR1, a receptor for the pro-inflammatory sphingolipid S1P. However, circulating and tissue sphingolipid levels and S1P-related gene expression have not been characterized in pediatric IBD. Methods Pediatric IBD patients and controls were recruited in a four-site study. Patients received a clinical score using PUCAI or PCDAI evaluation. Colon biopsies were collected during endoscopy. Gene expression was measured by qRT-PCR. Plasma and gut tissue sphingolipids were measured by LC-MS/MS. Results Genes of S1P synthesis (SPHK1, SPHK2), degradation (SGPL1), and signaling (S1PR1, S1PR2, and S1PR4) were significantly upregulated in colon biopsies of IBD patients with moderate/severe symptoms compared with controls or patients in remission. Tissue ceramide, dihydroceramide, and ceramide-1-phosphate (C1P) levels were significantly elevated in IBD patients compared with controls. Conclusions A signature of elevated S1P-related gene expression in colon tissues of pediatric IBD patients correlates with active disease and normalizes in remission. Biopsied gut tissue from symptomatic IBD patients contains high levels of pro-apoptotic and pro-inflammatory sphingolipids. A combined analysis of gut tissue sphingolipid profiles with this S1P-related gene signature may be useful for monitoring response to conventional therapy. PMID:29788359

An interferon signature identified by RNA-sequencing of mammary tissues varies across the estrous cycle and is predictive of metastasis-free survival

DOE PAGES

Snijders, Antoine M.; Langley, Sasha; Mao, Jian-Hua; ...

2014-06-30

The concept that a breast cancer patient's menstrual stage at the time of tumor surgery influences risk of metastases remains controversial. The scarcity of comprehensive molecular studies of menstrual stage-dependent fluctuations in the breast provides little insight. To gain a deeper understanding of the biological changes in mammary tissue and blood during the menstrual cycle and to determine the influence of environmental exposures, such as low-dose ionizing radiation (LDIR), we used the mouse to characterize estrous-cycle variations in mammary gene transcripts by RNA-sequencing, peripheral white blood cell (WBC) counts and plasma cytokine levels. We identified an estrous-variable and hormone-dependent genemore » cluster enriched for Type-1 interferon genes. Cox regression identified a 117-gene signature of interferon-associated genes, which correlated with lower frequencies of metastasis in breast cancer patients. LDIR (10cGy) exposure had no detectable effect on mammary transcripts. However, peripheral WBC counts varied across the estrous cycle and LDIR exposure reduced lymphocyte counts and cytokine levels in tumor-susceptible mice. Our finding of variations in mammary Type-1 interferon and immune functions across the estrous cycle provides a mechanism by which timing of breast tumor surgery during the menstrual cycle may have clinical relevance to a patient's risk for distant metastases.« less

An interferon signature identified by RNA-sequencing of mammary tissues varies across the estrous cycle and is predictive of metastasis-free survival

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

Snijders, Antoine M.; Langley, Sasha; Mao, Jian-Hua

The concept that a breast cancer patient's menstrual stage at the time of tumor surgery influences risk of metastases remains controversial. The scarcity of comprehensive molecular studies of menstrual stage-dependent fluctuations in the breast provides little insight. To gain a deeper understanding of the biological changes in mammary tissue and blood during the menstrual cycle and to determine the influence of environmental exposures, such as low-dose ionizing radiation (LDIR), we used the mouse to characterize estrous-cycle variations in mammary gene transcripts by RNA-sequencing, peripheral white blood cell (WBC) counts and plasma cytokine levels. We identified an estrous-variable and hormone-dependent genemore » cluster enriched for Type-1 interferon genes. Cox regression identified a 117-gene signature of interferon-associated genes, which correlated with lower frequencies of metastasis in breast cancer patients. LDIR (10cGy) exposure had no detectable effect on mammary transcripts. However, peripheral WBC counts varied across the estrous cycle and LDIR exposure reduced lymphocyte counts and cytokine levels in tumor-susceptible mice. Our finding of variations in mammary Type-1 interferon and immune functions across the estrous cycle provides a mechanism by which timing of breast tumor surgery during the menstrual cycle may have clinical relevance to a patient's risk for distant metastases.« less

Histone methylation mediates plasticity of human FOXP3(+) regulatory T cells by modulating signature gene expressions.

PubMed

He, Haiqi; Ni, Bing; Tian, Yi; Tian, Zhiqiang; Chen, Yanke; Liu, Zhengwen; Yang, Xiaomei; Lv, Yi; Zhang, Yong

2014-03-01

CD4(+) FOXP3(+) regulatory T (Treg) cells constitute a heterogeneous and plastic T-cell lineage that plays a pivotal role in maintaining immune homeostasis and immune tolerance. However, the fate of human Treg cells after loss of FOXP3 expression and the epigenetic mechanisms contributing to such a phenotype switch remain to be fully elucidated. In the current study, we demonstrate that human CD4(+) CD25(high) CD127(low/-) Treg cells convert to two subpopulations with distinctive FOXP3(+) and FOXP3(-) phenotypes following in vitro culture with anti-CD3/CD28 and interleukin-2. Digital gene expression analysis showed that upon in vitro expansion, human Treg cells down-regulated Treg cell signature genes, such as FOXP3, CTLA4, ICOS, IKZF2 and LRRC32, but up-regulated a set of T helper lineage-associated genes, especially T helper type 2 (Th2)-associated, such as GATA3, GFI1 and IL13. Subsequent chromatin immunoprecipitation-sequencing of these subpopulations yielded genome-wide maps of their H3K4me3 and H3K27me3 profiles. Surprisingly, reprogramming of Treg cells was associated with differential histone modifications, as evidenced by decreased abundance of permissive H3K4me3 within the down-regulated Treg cell signature genes, such as FOXP3, CTLA4 and LRRC32 loci, and increased abundance of H3K4me3 within the Th2-associated genes, such as IL4 and IL5; however, the H3K27me3 modification profile was not significantly different between the two subpopulations. In conclusion, this study revealed that loss of FOXP3 expression from human Treg cells during in vitro expansion can induce reprogramming to a T helper cell phenotype with a gene expression signature dominated by Th2 lineage-associated genes, and that this cell type conversion may be mediated by histone methylation events. © 2013 John Wiley & Sons Ltd.

Histone methylation mediates plasticity of human FOXP3+ regulatory T cells by modulating signature gene expressions

PubMed Central

He, Haiqi; Ni, Bing; Tian, Yi; Tian, Zhiqiang; Chen, Yanke; Liu, Zhengwen; Yang, Xiaomei; Lv, Yi; Zhang, Yong

2014-01-01

CD4+ FOXP3+ regulatory T (Treg) cells constitute a heterogeneous and plastic T-cell lineage that plays a pivotal role in maintaining immune homeostasis and immune tolerance. However, the fate of human Treg cells after loss of FOXP3 expression and the epigenetic mechanisms contributing to such a phenotype switch remain to be fully elucidated. In the current study, we demonstrate that human CD4+ CD25high CD127low/− Treg cells convert to two subpopulations with distinctive FOXP3+ and FOXP3− phenotypes following in vitro culture with anti-CD3/CD28 and interleukin-2. Digital gene expression analysis showed that upon in vitro expansion, human Treg cells down-regulated Treg cell signature genes, such as FOXP3, CTLA4, ICOS, IKZF2 and LRRC32, but up-regulated a set of T helper lineage-associated genes, especially T helper type 2 (Th2)-associated, such as GATA3, GFI1 and IL13. Subsequent chromatin immunoprecipitation-sequencing of these subpopulations yielded genome-wide maps of their H3K4me3 and H3K27me3 profiles. Surprisingly, reprogramming of Treg cells was associated with differential histone modifications, as evidenced by decreased abundance of permissive H3K4me3 within the down-regulated Treg cell signature genes, such as FOXP3, CTLA4 and LRRC32 loci, and increased abundance of H3K4me3 within the Th2-associated genes, such as IL4 and IL5; however, the H3K27me3 modification profile was not significantly different between the two subpopulations. In conclusion, this study revealed that loss of FOXP3 expression from human Treg cells during in vitro expansion can induce reprogramming to a T helper cell phenotype with a gene expression signature dominated by Th2 lineage-associated genes, and that this cell type conversion may be mediated by histone methylation events. PMID:24152290

High expression of ID family and IGJ genes signature as predictor of low induction treatment response and worst survival in adult Hispanic patients with B-acute lymphoblastic leukemia.

PubMed

Cruz-Rodriguez, Nataly; Combita, Alba L; Enciso, Leonardo J; Quijano, Sandra M; Pinzon, Paula L; Lozano, Olga C; Castillo, Juan S; Li, Li; Bareño, Jose; Cardozo, Claudia; Solano, Julio; Herrera, Maria V; Cudris, Jennifer; Zabaleta, Jovanny

2016-04-05

B-Acute lymphoblastic leukemia (B-ALL) represents a hematologic malignancy with poor clinical outcome and low survival rates in adult patients. Remission rates in Hispanic population are almost 30% lower and Overall Survival (OS) nearly two years inferior than those reported in other ethnic groups. Only 61% of Colombian adult patients with ALL achieve complete remission (CR), median overall survival is 11.3 months and event-free survival (EFS) is 7.34 months. Identification of prognostic factors is crucial for the application of proper treatment strategies and subsequently for successful outcome. Our goal was to identify a gene expression signature that might correlate with response to therapy and evaluate the utility of these as prognostic tool in hispanic patients. We included 43 adult patients newly diagnosed with B-ALL. We used microarray analysis in order to identify genes that distinguish poor from good response to treatment using differential gene expression analysis. The expression profile was validated by real-time PCR (RT-PCT). We identified 442 differentially expressed genes between responders and non-responders to induction treatment. Hierarchical analysis according to the expression of a 7-gene signature revealed 2 subsets of patients that differed in their clinical characteristics and outcome. Our study suggests that response to induction treatment and clinical outcome of Hispanic patients can be predicted from the onset of the disease and that gene expression profiles can be used to stratify patient risk adequately and accurately. The present study represents the first that shows the gene expression profiling of B-ALL Colombian adults and its relevance for stratification in the early course of disease.

Connecting genes, coexpression modules, and molecular signatures to environmental stress phenotypes in plants

PubMed Central

Weston, David J; Gunter, Lee E; Rogers, Alistair; Wullschleger, Stan D

2008-01-01

Background One of the eminent opportunities afforded by modern genomic technologies is the potential to provide a mechanistic understanding of the processes by which genetic change translates to phenotypic variation and the resultant appearance of distinct physiological traits. Indeed much progress has been made in this area, particularly in biomedicine where functional genomic information can be used to determine the physiological state (e.g., diagnosis) and predict phenotypic outcome (e.g., patient survival). Ecology currently lacks an analogous approach where genomic information can be used to diagnose the presence of a given physiological state (e.g., stress response) and then predict likely phenotypic outcomes (e.g., stress duration and tolerance, fitness). Results Here, we demonstrate that a compendium of genomic signatures can be used to classify the plant abiotic stress phenotype in Arabidopsis according to the architecture of the transcriptome, and then be linked with gene coexpression network analysis to determine the underlying genes governing the phenotypic response. Using this approach, we confirm the existence of known stress responsive pathways and marker genes, report a common abiotic stress responsive transcriptome and relate phenotypic classification to stress duration. Conclusion Linking genomic signatures to gene coexpression analysis provides a unique method of relating an observed plant phenotype to changes in gene expression that underlie that phenotype. Such information is critical to current and future investigations in plant biology and, in particular, to evolutionary ecology, where a mechanistic understanding of adaptive physiological responses to abiotic stress can provide researchers with a tool of great predictive value in understanding species and population level adaptation to climate change. PMID:18248680

Four-miRNA signature as a prognostic tool for lung adenocarcinoma.

PubMed

Lin, Yan; Lv, Yufeng; Liang, Rong; Yuan, Chunling; Zhang, Jinyan; He, Dan; Zheng, Xiaowen; Zhang, Jianfeng

2018-01-01

The aim of this study was to generate a novel miRNA expression signature to accurately predict prognosis for patients with lung adenocarcinoma (LUAD). Using expression profiles downloaded from The Cancer Genome Atlas database, we identified multiple miRNAs with differential expression between LUAD and paired healthy tissues. We then evaluated the prognostic values of the differentially expressed miRNAs using univariate/multivariate Cox regression analysis. This analysis was ultimately used to construct a four-miRNA signature that effectively predicted patient survival. Finally, we analyzed potential functional roles of the target genes for these four miRNAs using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses. Based on our cutoff criteria ( P <0.05 and |log2FC| >1.0), we identified a total of 187 differentially expressed miRNAs, including 148 that were upregulated in LUAD tissues and 39 that were downregulated. Four miRNAs (miR-148a-5p, miR-31-5p, miR-548v, and miR-550a-5p) were independently associated with survival based on Kaplan-Meier analysis. We generated a signature index based on the expression of these four miRNAs and stratified patients into low- and high-risk groups. Patients in the high-risk group had significantly shorter survival times than those in the low-risk group ( P =0.002). A functional enrichment analysis suggested that the target genes of these four miRNAs were involved in protein phosphorylation and the Hippo and sphingolipid signaling pathways. Taken together, our results suggest that our four-miRNA signature can be used as a prognostic tool for patients with LUAD.

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- ...

A Type I Interferon Transcriptional Signature Precedes Autoimmunity in Children Genetically at Risk for Type 1 Diabetes

PubMed Central

Ferreira, Ricardo C.; Guo, Hui; Coulson, Richard M.R.; Smyth, Deborah J.; Pekalski, Marcin L.; Burren, Oliver S.; Cutler, Antony J.; Doecke, James D.; Flint, Shaun; McKinney, Eoin F.; Lyons, Paul A.; Smith, Kenneth G.C.; Achenbach, Peter; Beyerlein, Andreas; Dunger, David B.; Clayton, David G.; Wicker, Linda S.; Bonifacio, Ezio

2014-01-01

Diagnosis of the autoimmune disease type 1 diabetes (T1D) is preceded by the appearance of circulating autoantibodies to pancreatic islets. However, almost nothing is known about events leading to this islet autoimmunity. Previous epidemiological and genetic data have associated viral infections and antiviral type I interferon (IFN) immune response genes with T1D. Here, we first used DNA microarray analysis to identify IFN-β–inducible genes in vitro and then used this set of genes to define an IFN-inducible transcriptional signature in peripheral blood mononuclear cells from a group of active systemic lupus erythematosus patients (n = 25). Using this predefined set of 225 IFN signature genes, we investigated the expression of the signature in cohorts of healthy controls (n = 87), patients with T1D (n = 64), and a large longitudinal birth cohort of children genetically predisposed to T1D (n = 109; 454 microarrayed samples). Expression of the IFN signature was increased in genetically predisposed children before the development of autoantibodies (P = 0.0012) but not in patients with established T1D. Upregulation of IFN-inducible genes was transient, temporally associated with a recent history of upper respiratory tract infections (P = 0.0064), and marked by increased expression of SIGLEC-1 (CD169), a lectin-like receptor expressed on CD14+ monocytes. DNA variation in IFN-inducible genes altered T1D risk (P = 0.007), as exemplified by IFIH1, one of the genes in our IFN signature for which increased expression is a known risk factor for disease. These findings identify transient increased expression of type I IFN genes in preclinical diabetes as a risk factor for autoimmunity in children with a genetic predisposition to T1D. PMID:24561305

Classification of a large microarray data set: Algorithm comparison and analysis of drug signatures

PubMed Central

Natsoulis, Georges; El Ghaoui, Laurent; Lanckriet, Gert R.G.; Tolley, Alexander M.; Leroy, Fabrice; Dunlea, Shane; Eynon, Barrett P.; Pearson, Cecelia I.; Tugendreich, Stuart; Jarnagin, Kurt

2005-01-01

A large gene expression database has been produced that characterizes the gene expression and physiological effects of hundreds of approved and withdrawn drugs, toxicants, and biochemical standards in various organs of live rats. In order to derive useful biological knowledge from this large database, a variety of supervised classification algorithms were compared using a 597-microarray subset of the data. Our studies show that several types of linear classifiers based on Support Vector Machines (SVMs) and Logistic Regression can be used to derive readily interpretable drug signatures with high classification performance. Both methods can be tuned to produce classifiers of drug treatments in the form of short, weighted gene lists which upon analysis reveal that some of the signature genes have a positive contribution (act as “rewards” for the class-of-interest) while others have a negative contribution (act as “penalties”) to the classification decision. The combination of reward and penalty genes enhances performance by keeping the number of false positive treatments low. The results of these algorithms are combined with feature selection techniques that further reduce the length of the drug signatures, an important step towards the development of useful diagnostic biomarkers and low-cost assays. Multiple signatures with no genes in common can be generated for the same classification end-point. Comparison of these gene lists identifies biological processes characteristic of a given class. PMID:15867433

Circulating neutrophil transcriptome may reveal intracranial aneurysm signature

PubMed Central

Tutino, Vincent M.; Poppenberg, Kerry E.; Jiang, Kaiyu; Jarvis, James N.; Sun, Yijun; Sonig, Ashish; Siddiqui, Adnan H.; Snyder, Kenneth V.; Levy, Elad I.; Kolega, John

2018-01-01

Background Unruptured intracranial aneurysms (IAs) are typically asymptomatic and undetected except for incidental discovery on imaging. Blood-based diagnostic biomarkers could lead to improvements in IA management. This exploratory study examined circulating neutrophils to determine whether they carry RNA expression signatures of IAs. Methods Blood samples were collected from patients receiving cerebral angiography. Eleven samples were collected from patients with IAs and 11 from patients without IAs as controls. Samples from the two groups were paired based on demographics and comorbidities. RNA was extracted from isolated neutrophils and subjected to next-generation RNA sequencing to obtain differential expressions for identification of an IA-associated signature. Bioinformatics analyses, including gene set enrichment analysis and Ingenuity Pathway Analysis, were used to investigate the biological function of all differentially expressed transcripts. Results Transcriptome profiling identified 258 differentially expressed transcripts in patients with and without IAs. Expression differences were consistent with peripheral neutrophil activation. An IA-associated RNA expression signature was identified in 82 transcripts (p<0.05, fold-change ≥2). This signature was able to separate patients with and without IAs on hierarchical clustering. Furthermore, in an independent, unpaired, replication cohort of patients with IAs (n = 5) and controls (n = 5), the 82 transcripts separated 9 of 10 patients into their respective groups. Conclusion Preliminary findings show that RNA expression from circulating neutrophils carries an IA-associated signature. These findings highlight a potential to use predictive biomarkers from peripheral blood samples to identify patients with IAs. PMID:29342213

Epigenomic elements analyses for promoters identify ESRRG as a new susceptibility gene for obesity-related traits.

PubMed

Dong, S-S; Guo, Y; Zhu, D-L; Chen, X-F; Wu, X-M; Shen, H; Chen, X-D; Tan, L-J; Tian, Q; Deng, H-W; Yang, T-L

2016-07-01

With ENCODE epigenomic data and results from published genome-wide association studies (GWASs), we aimed to find regulatory signatures of obesity genes and discover novel susceptibility genes. Obesity genes were obtained from public GWAS databases and their promoters were annotated based on the regulatory element information. Significantly enriched or depleted epigenomic elements in the promoters of obesity genes were evaluated and all human genes were then prioritized according to the existence of the selected elements to predict new candidate genes. Top-ranked genes were subsequently applied to validate their associations with obesity-related traits in three independent in-house GWAS samples. We identified RAD21 and EZH2 as over-represented, and STAT2 (signal transducer and activator of transcription 2) and IRF3 (interferon regulatory transcription factor 3) as depleted transcription factors. Histone modification of H3K9me3 and chromatin state segmentation of 'poised promoter' and 'repressed' were over-represented. All genes were prioritized and we selected the top five genes for validation at the population level. Combining results from the three GWAS samples, rs7522101 in ESRRG (estrogen-related receptor-γ) remained significantly associated with body mass index after multiple testing corrections (P=7.25 × 10(-5)). It was also associated with β-cell function (P=1.99 × 10(-3)) and fasting glucose level (P<0.05) in the meta-analyses of glucose and insulin-related traits consortium (MAGIC) data set.Cnoclusions:In summary, we identified epigenomic characteristics for obesity genes and suggested ESRRG as a novel obesity-susceptibility gene.

Dissecting the Gene Network of Dietary Restriction to Identify Evolutionarily Conserved Pathways and New Functional Genes

PubMed Central

Wuttke, Daniel; Connor, Richard; Vora, Chintan; Craig, Thomas; Li, Yang; Wood, Shona; Vasieva, Olga; Shmookler Reis, Robert; Tang, Fusheng; de Magalhães, João Pedro

2012-01-01

Dietary restriction (DR), limiting nutrient intake from diet without causing malnutrition, delays the aging process and extends lifespan in multiple organisms. The conserved life-extending effect of DR suggests the involvement of fundamental mechanisms, although these remain a subject of debate. To help decipher the life-extending mechanisms of DR, we first compiled a list of genes that if genetically altered disrupt or prevent the life-extending effects of DR. We called these DR–essential genes and identified more than 100 in model organisms such as yeast, worms, flies, and mice. In order for other researchers to benefit from this first curated list of genes essential for DR, we established an online database called GenDR (http://genomics.senescence.info/diet/). To dissect the interactions of DR–essential genes and discover the underlying lifespan-extending mechanisms, we then used a variety of network and systems biology approaches to analyze the gene network of DR. We show that DR–essential genes are more conserved at the molecular level and have more molecular interactions than expected by chance. Furthermore, we employed a guilt-by-association method to predict novel DR–essential genes. In budding yeast, we predicted nine genes related to vacuolar functions; we show experimentally that mutations deleting eight of those genes prevent the life-extending effects of DR. Three of these mutants (OPT2, FRE6, and RCR2) had extended lifespan under ad libitum, indicating that the lack of further longevity under DR is not caused by a general compromise of fitness. These results demonstrate how network analyses of DR using GenDR can be used to make phenotypically relevant predictions. Moreover, gene-regulatory circuits reveal that the DR–induced transcriptional signature in yeast involves nutrient-sensing, stress responses and meiotic transcription factors. Finally, comparing the influence of gene expression changes during DR on the interactomes of multiple

Mining Gene Expression Signature for the Detection of Pre-Malignant Melanocytes and Early Melanomas with Risk for Metastasis

PubMed Central

de Souza, Camila Ferreira; Xander, Patrícia; Monteiro, Ana Carolina; Silva, Amanda Gonçalves dos Santos; da Silva, Débora Castanheira Pereira; Mai, Sabine; Bernardo, Viviane; Lopes, José Daniel; Jasiulionis, Miriam Galvonas

2012-01-01

progression model to identify molecular markers commonly perturbed in metastasis. Additionally, the novel gene expression signature identified here may be useful in the future into a model more closely related to translational research. PMID:22984562

LINCS Canvas Browser: interactive web app to query, browse and interrogate LINCS L1000 gene expression signatures.

PubMed

Duan, Qiaonan; Flynn, Corey; Niepel, Mario; Hafner, Marc; Muhlich, Jeremy L; Fernandez, Nicolas F; Rouillard, Andrew D; Tan, Christopher M; Chen, Edward Y; Golub, Todd R; Sorger, Peter K; Subramanian, Aravind; Ma'ayan, Avi

2014-07-01

For the Library of Integrated Network-based Cellular Signatures (LINCS) project many gene expression signatures using the L1000 technology have been produced. The L1000 technology is a cost-effective method to profile gene expression in large scale. LINCS Canvas Browser (LCB) is an interactive HTML5 web-based software application that facilitates querying, browsing and interrogating many of the currently available LINCS L1000 data. LCB implements two compacted layered canvases, one to visualize clustered L1000 expression data, and the other to display enrichment analysis results using 30 different gene set libraries. Clicking on an experimental condition highlights gene-sets enriched for the differentially expressed genes from the selected experiment. A search interface allows users to input gene lists and query them against over 100 000 conditions to find the top matching experiments. The tool integrates many resources for an unprecedented potential for new discoveries in systems biology and systems pharmacology. The LCB application is available at http://www.maayanlab.net/LINCS/LCB. Customized versions will be made part of the http://lincscloud.org and http://lincs.hms.harvard.edu websites. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

A peripheral blood transcriptomic signature predicts autoantibody development in infants at risk of type 1 diabetes.

PubMed

Mehdi, Ahmed M; Hamilton-Williams, Emma E; Cristino, Alexandre; Ziegler, Anette; Bonifacio, Ezio; Le Cao, Kim-Anh; Harris, Mark; Thomas, Ranjeny

2018-03-08

Autoimmune-mediated destruction of pancreatic islet β cells results in type 1 diabetes (T1D). Serum islet autoantibodies usually develop in genetically susceptible individuals in early childhood before T1D onset, with multiple islet autoantibodies predicting diabetes development. However, most at-risk children remain islet-antibody negative, and no test currently identifies those likely to seroconvert. We sought a genomic signature predicting seroconversion risk by integrating longitudinal peripheral blood gene expression profiles collected in high-risk children included in the BABYDIET and DIPP cohorts, of whom 50 seroconverted. Subjects were followed for 10 years to determine time of seroconversion. Any cohort effect and the time of seroconversion were corrected to uncover genes differentially expressed (DE) in seroconverting children. Gene expression signatures associated with seroconversion were evident during the first year of life, with 67 DE genes identified in seroconverting children relative to those remaining antibody negative. These genes contribute to T cell-, DC-, and B cell-related immune responses. Near-birth expression of ADCY9, PTCH1, MEX3B, IL15RA, ZNF714, TENM1, and PLEKHA5, along with HLA risk score predicted seroconversion (AUC 0.85). The ubiquitin-proteasome pathway linked DE genes and T1D susceptibility genes. Therefore, a gene expression signature in infancy predicts risk of seroconversion. Ubiquitination may play a mechanistic role in diabetes progression.

A peripheral blood transcriptomic signature predicts autoantibody development in infants at risk of type 1 diabetes

PubMed Central

Mehdi, Ahmed M.; Hamilton-Williams, Emma E.; Cristino, Alexandre; Ziegler, Anette; Harris, Mark

2018-01-01

Autoimmune-mediated destruction of pancreatic islet β cells results in type 1 diabetes (T1D). Serum islet autoantibodies usually develop in genetically susceptible individuals in early childhood before T1D onset, with multiple islet autoantibodies predicting diabetes development. However, most at-risk children remain islet-antibody negative, and no test currently identifies those likely to seroconvert. We sought a genomic signature predicting seroconversion risk by integrating longitudinal peripheral blood gene expression profiles collected in high-risk children included in the BABYDIET and DIPP cohorts, of whom 50 seroconverted. Subjects were followed for 10 years to determine time of seroconversion. Any cohort effect and the time of seroconversion were corrected to uncover genes differentially expressed (DE) in seroconverting children. Gene expression signatures associated with seroconversion were evident during the first year of life, with 67 DE genes identified in seroconverting children relative to those remaining antibody negative. These genes contribute to T cell–, DC-, and B cell–related immune responses. Near-birth expression of ADCY9, PTCH1, MEX3B, IL15RA, ZNF714, TENM1, and PLEKHA5, along with HLA risk score predicted seroconversion (AUC 0.85). The ubiquitin-proteasome pathway linked DE genes and T1D susceptibility genes. Therefore, a gene expression signature in infancy predicts risk of seroconversion. Ubiquitination may play a mechanistic role in diabetes progression. PMID:29515040

A gene expression signature of confinement in peripheral blood of red wolves (Canis rufus).

PubMed

Kennerly, Erin; Ballmann, Anne; Martin, Stanton; Wolfinger, Russ; Gregory, Simon; Stoskopf, Michael; Gibson, Greg

2008-06-01

The stresses that animals experience as a result of modification of their ecological circumstances induce physiological changes that leave a signature in profiles of gene expression. We illustrate this concept in a comparison of free range and confined North American red wolves (Canis rufus). Transcription profiling of peripheral blood samples from 13 red wolf individuals in the Alligator River region of North Carolina revealed a strong signal of differentiation. Four hundred eighty-two out of 2980 transcripts detected on Illumina HumanRef8 oligonucleotide bead arrays were found to differentiate free range and confined wolves at a false discovery rate of 12.8% and P < 0.05. Over-representation of genes in focal adhesion, insulin signalling, proteasomal, and tryptophan metabolism pathways suggests the activation of pro-inflammatory and stress responses in confined animals. Consequently, characterization of differential transcript abundance in an accessible tissue such as peripheral blood identifies biomarkers that could be useful in animal management practices and for evaluating the impact of habitat changes on population health, particularly as attention turns to the impact of climate change on physiology and in turn species distributions.

Peripheral Blood Signatures of Lead Exposure

PubMed Central

LaBreche, Heather G.; Meadows, Sarah K.; Nevins, Joseph R.; Chute, John P.

2011-01-01

Background Current evidence indicates that even low-level lead (Pb) exposure can have detrimental effects, especially in children. We tested the hypothesis that Pb exposure alters gene expression patterns in peripheral blood cells and that these changes reflect dose-specific alterations in the activity of particular pathways. Methodology/Principal Finding Using Affymetrix Mouse Genome 430 2.0 arrays, we examined gene expression changes in the peripheral blood of female Balb/c mice following exposure to per os lead acetate trihydrate or plain drinking water for two weeks and after a two-week recovery period. Data sets were RMA-normalized and dose-specific signatures were generated using established methods of supervised classification and binary regression. Pathway activity was analyzed using the ScoreSignatures module from GenePattern. Conclusions/Significance The low-level Pb signature was 93% sensitive and 100% specific in classifying samples a leave-one-out crossvalidation. The high-level Pb signature demonstrated 100% sensitivity and specificity in the leave-one-out crossvalidation. These two signatures exhibited dose-specificity in their ability to predict Pb exposure and had little overlap in terms of constituent genes. The signatures also seemed to reflect current levels of Pb exposure rather than past exposure. Finally, the two doses showed differential activation of cellular pathways. Low-level Pb exposure increased activity of the interferon-gamma pathway, whereas high-level Pb exposure increased activity of the E2F1 pathway. PMID:21829687

Can specific transcriptional regulators assemble a universal cancer signature?

NASA Astrophysics Data System (ADS)

Roy, Janine; Isik, Zerrin; Pilarsky, Christian; Schroeder, Michael

2013-10-01

Recently, there is a lot of interest in using biomarker signatures derived from gene expression data to predict cancer progression. We assembled signatures of 25 published datasets covering 13 types of cancers. How do these signatures compare with each other? On one hand signatures answering the same biological question should overlap, whereas signatures predicting different cancer types should differ. On the other hand, there could also be a Universal Cancer Signature that is predictive independently of the cancer type. Initially, we generate signatures for all datasets using classical approaches such as t-test and fold change and then, we explore signatures resulting from a network-based method, that applies the random surfer model of Google's PageRank algorithm. We show that the signatures as published by the authors and the signatures generated with classical methods do not overlap - not even for the same cancer type - whereas the network-based signatures strongly overlap. Selecting 10 out of 37 universal cancer genes gives the optimal prediction for all cancers thus taking a first step towards a Universal Cancer Signature. We furthermore analyze and discuss the involved genes in terms of the Hallmarks of cancer and in particular single out SP1, JUN/FOS and NFKB1 and examine their specific role in cancer progression.

Robust transcriptional tumor signatures applicable to both formalin-fixed paraffin-embedded and fresh-frozen samples

PubMed Central

Cheng, Jun; He, Jun; Liu, Huaping; Cai, Hao; Hong, Guini; Zhang, Jiahui; Li, Na; Ao, Lu; Guo, Zheng

2017-01-01

Formalin-fixed paraffin-embedded (FFPE) samples represent a valuable resource for clinical researches. However, FFPE samples are usually considered an unreliable source for gene expression analysis due to the partial RNA degradation. In this study, through comparing gene expression profiles between FFPE samples and paired fresh-frozen (FF) samples for three cancer types, we firstly showed that expression measurements of thousands of genes had at least two-fold change in FFPE samples compared with paired FF samples. Therefore, for a transcriptional signature based on risk scores summarized from the expression levels of the signature genes, the risk score thresholds trained from FFPE (or FF) samples could not be applied to FF (or FFPE) samples. On the other hand, we found that more than 90% of the relative expression orderings (REOs) of gene pairs in the FF samples were maintained in their paired FFPE samples and largely unaffected by the storage time. The result suggested that the REOs of gene pairs were highly robust against partial RNA degradation in FFPE samples. Finally, as a case study, we developed a REOs-based signature to distinguish liver cirrhosis from hepatocellular carcinoma (HCC) using FFPE samples. The signature was validated in four datasets of FFPE samples and eight datasets of FF samples. In conclusion, the valuable FFPE samples can be fully exploited to identify REOs-based diagnostic and prognostic signatures which could be robustly applicable to both FF samples and FFPE samples with degraded RNA. PMID:28036264

Signatures of positive selection in the cis-regulatory sequences of the human oxytocin receptor (OXTR) and arginine vasopressin receptor 1a (AVPR1A) genes.

PubMed

Schaschl, Helmut; Huber, Susanne; Schaefer, Katrin; Windhager, Sonja; Wallner, Bernard; Fieder, Martin

2015-05-13

The evolutionary highly conserved neurohypophyseal hormones oxytocin and arginine vasopressin play key roles in regulating social cognition and behaviours. The effects of these two peptides are meditated by their specific receptors, which are encoded by the oxytocin receptor (OXTR) and arginine vasopressin receptor 1a genes (AVPR1A), respectively. In several species, polymorphisms in these genes have been linked to various behavioural traits. Little, however, is known about whether positive selection acts on sequence variants in genes influencing variation in human behaviours. We identified, in both neuroreceptor genes, signatures of balancing selection in the cis-regulative acting sequences such as transcription factor binding and enhancer sequences, as well as in a transcriptional repressor sequence motif. Additionally, in the intron 3 of the OXTR gene, the SNP rs59190448 appears to be under positive directional selection. For rs59190448, only one phenotypical association is known so far, but it is in high LD' (>0.8) with loci of known association; i.e., variants associated with key pro-social behaviours and mental disorders in humans. Only for one SNP on the OXTR gene (rs59190448) was a sign of positive directional selection detected with all three methods of selection detection. For rs59190448, however, only one phenotypical association is known, but rs59190448 is in high LD' (>0.8), with variants associated with important pro-social behaviours and mental disorders in humans. We also detected various signatures of balancing selection on both neuroreceptor genes.

Digital transcriptome profiling of normal and glioblastoma-derived neural stem cells identifies genes associated with patient survival

PubMed Central

2012-01-01

Background Glioblastoma multiforme, the most common type of primary brain tumor in adults, is driven by cells with neural stem (NS) cell characteristics. Using derivation methods developed for NS cells, it is possible to expand tumorigenic stem cells continuously in vitro. Although these glioblastoma-derived neural stem (GNS) cells are highly similar to normal NS cells, they harbor mutations typical of gliomas and initiate authentic tumors following orthotopic xenotransplantation. Here, we analyzed GNS and NS cell transcriptomes to identify gene expression alterations underlying the disease phenotype. Methods Sensitive measurements of gene expression were obtained by high-throughput sequencing of transcript tags (Tag-seq) on adherent GNS cell lines from three glioblastoma cases and two normal NS cell lines. Validation by quantitative real-time PCR was performed on 82 differentially expressed genes across a panel of 16 GNS and 6 NS cell lines. The molecular basis and prognostic relevance of expression differences were investigated by genetic characterization of GNS cells and comparison with public data for 867 glioma biopsies. Results Transcriptome analysis revealed major differences correlated with glioma histological grade, and identified misregulated genes of known significance in glioblastoma as well as novel candidates, including genes associated with other malignancies or glioma-related pathways. This analysis further detected several long non-coding RNAs with expression profiles similar to neighboring genes implicated in cancer. Quantitative PCR validation showed excellent agreement with Tag-seq data (median Pearson r = 0.91) and discerned a gene set robustly distinguishing GNS from NS cells across the 22 lines. These expression alterations include oncogene and tumor suppressor changes not detected by microarray profiling of tumor tissue samples, and facilitated the identification of a GNS expression signature strongly associated with patient survival (P = 1e

Phenotypic signatures arising from unbalanced bacterial growth.

PubMed

Tan, Cheemeng; Smith, Robert Phillip; Tsai, Ming-Chi; Schwartz, Russell; You, Lingchong

2014-08-01

Fluctuations in the growth rate of a bacterial culture during unbalanced growth are generally considered undesirable in quantitative studies of bacterial physiology. Under well-controlled experimental conditions, however, these fluctuations are not random but instead reflect the interplay between intra-cellular networks underlying bacterial growth and the growth environment. Therefore, these fluctuations could be considered quantitative phenotypes of the bacteria under a specific growth condition. Here, we present a method to identify "phenotypic signatures" by time-frequency analysis of unbalanced growth curves measured with high temporal resolution. The signatures are then applied to differentiate amongst different bacterial strains or the same strain under different growth conditions, and to identify the essential architecture of the gene network underlying the observed growth dynamics. Our method has implications for both basic understanding of bacterial physiology and for the classification of bacterial strains.

Genome-Wide Transcriptome Analysis of Cotton (Gossypium hirsutum L.) Identifies Candidate Gene Signatures in Response to Aflatoxin Producing Fungus Aspergillus flavus.

PubMed

Bedre, Renesh; Rajasekaran, Kanniah; Mangu, Venkata Ramanarao; Sanchez Timm, Luis Eduardo; Bhatnagar, Deepak; Baisakh, Niranjan

2015-01-01

Aflatoxins are toxic and potent carcinogenic metabolites produced from the fungi Aspergillus flavus and A. parasiticus. Aflatoxins can contaminate cottonseed under conducive preharvest and postharvest conditions. United States federal regulations restrict the use of aflatoxin contaminated cottonseed at >20 ppb for animal feed. Several strategies have been proposed for controlling aflatoxin contamination, and much success has been achieved by the application of an atoxigenic strain of A. flavus in cotton, peanut and maize fields. Development of cultivars resistant to aflatoxin through overexpression of resistance associated genes and/or knocking down aflatoxin biosynthesis of A. flavus will be an effective strategy for controlling aflatoxin contamination in cotton. In this study, genome-wide transcriptome profiling was performed to identify differentially expressed genes in response to infection with both toxigenic and atoxigenic strains of A. flavus on cotton (Gossypium hirsutum L.) pericarp and seed. The genes involved in antifungal response, oxidative burst, transcription factors, defense signaling pathways and stress response were highly differentially expressed in pericarp and seed tissues in response to A. flavus infection. The cell-wall modifying genes and genes involved in the production of antimicrobial substances were more active in pericarp as compared to seed. The genes involved in auxin and cytokinin signaling were also induced. Most of the genes involved in defense response in cotton were highly induced in pericarp than in seed. The global gene expression analysis in response to fungal invasion in cotton will serve as a source for identifying biomarkers for breeding, potential candidate genes for transgenic manipulation, and will help in understanding complex plant-fungal interaction for future downstream research.

Visualization and analysis for multidimensional gene expressions signature of cigarette smoking

NASA Astrophysics Data System (ADS)

Wang, Changbo; Xiao, Zhao; Zhang, Tianlun; Cui, Jin; Pang, Chenming

2011-11-01

Biologists often use gene chip to get massive experimental data in the field of bioscience and chemical sciences. Facing a large amount of experimental data, researchers often need to find out a few interesting data or simple regulations. This paper presents a set of methods to visualize and analyze the data for gene expression signatures of people who smoke. We use the latest research data from National Center for Biotechnology Information. Totally, there are more than 400 thousand expressions data. Using these data, we can use parallel coordinates method to visualize the different gene expressions between smokers and nonsmokers and we can distinguish non-smokers, former smokers and current smokers by using the different colors. It can be easy to find out which gene is more important during the lung cancer angiogenesis in the smoking people. In another way, we can use a hierarchical model to visualize the inner relation of different genes. The location of the nodes shows different expression moment and the distance to the root shows the sequence of the expression. We can use the ring layout to represent all the nodes, and connect the different nodes which are related with color lines. Combined with the parallel coordinates method, the visualization result show the important genes and some inner relation obviously, which is useful for examination and prevention of lung cancer.

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.

Population genomic scan for candidate signatures of balancing selection to guide antigen characterization in malaria parasites.

PubMed

Amambua-Ngwa, Alfred; Tetteh, Kevin K A; Manske, Magnus; Gomez-Escobar, Natalia; Stewart, Lindsay B; Deerhake, M Elizabeth; Cheeseman, Ian H; Newbold, Christopher I; Holder, Anthony A; Knuepfer, Ellen; Janha, Omar; Jallow, Muminatou; Campino, Susana; Macinnis, Bronwyn; Kwiatkowski, Dominic P; Conway, David J

2012-01-01

Acquired immunity in vertebrates maintains polymorphisms in endemic pathogens, leading to identifiable signatures of balancing selection. To comprehensively survey for genes under such selection in the human malaria parasite Plasmodium falciparum, we generated paired-end short-read sequences of parasites in clinical isolates from an endemic Gambian population, which were mapped to the 3D7 strain reference genome to yield high-quality genome-wide coding sequence data for 65 isolates. A minority of genes did not map reliably, including the hypervariable var, rifin, and stevor families, but 5,056 genes (90.9% of all in the genome) had >70% sequence coverage with minimum read depth of 5 for at least 50 isolates, of which 2,853 genes contained 3 or more single nucleotide polymorphisms (SNPs) for analysis of polymorphic site frequency spectra. Against an overall background of negatively skewed frequencies, as expected from historical population expansion combined with purifying selection, the outlying minority of genes with signatures indicating exceptionally intermediate frequencies were identified. Comparing genes with different stage-specificity, such signatures were most common in those with peak expression at the merozoite stage that invades erythrocytes. Members of clag, PfMC-2TM, surfin, and msp3-like gene families were highly represented, the strongest signature being in the msp3-like gene PF10_0355. Analysis of msp3-like transcripts in 45 clinical and 11 laboratory adapted isolates grown to merozoite-containing schizont stages revealed surprisingly low expression of PF10_0355. In diverse clonal parasite lines the protein product was expressed in a minority of mature schizonts (<1% in most lines and ∼10% in clone HB3), and eight sub-clones of HB3 cultured separately had an intermediate spectrum of positive frequencies (0.9 to 7.5%), indicating phase variable expression of this polymorphic antigen. This and other identified targets of balancing selection are now

Meta-Analysis of Placental Transcriptome Data Identifies a Novel Molecular Pathway Related to Preeclampsia.

PubMed

van Uitert, Miranda; Moerland, Perry D; Enquobahrie, Daniel A; Laivuori, Hannele; van der Post, Joris A M; Ris-Stalpers, Carrie; Afink, Gijs B

2015-01-01

Studies using the placental transcriptome to identify key molecules relevant for preeclampsia are hampered by a relatively small sample size. In addition, they use a variety of bioinformatics and statistical methods, making comparison of findings challenging. To generate a more robust preeclampsia gene expression signature, we performed a meta-analysis on the original data of 11 placenta RNA microarray experiments, representing 139 normotensive and 116 preeclamptic pregnancies. Microarray data were pre-processed and analyzed using standardized bioinformatics and statistical procedures and the effect sizes were combined using an inverse-variance random-effects model. Interactions between genes in the resulting gene expression signature were identified by pathway analysis (Ingenuity Pathway Analysis, Gene Set Enrichment Analysis, Graphite) and protein-protein associations (STRING). This approach has resulted in a comprehensive list of differentially expressed genes that led to a 388-gene meta-signature of preeclamptic placenta. Pathway analysis highlights the involvement of the previously identified hypoxia/HIF1A pathway in the establishment of the preeclamptic gene expression profile, while analysis of protein interaction networks indicates CREBBP/EP300 as a novel element central to the preeclamptic placental transcriptome. In addition, there is an apparent high incidence of preeclampsia in women carrying a child with a mutation in CREBBP/EP300 (Rubinstein-Taybi Syndrome). The 388-gene preeclampsia meta-signature offers a vital starting point for further studies into the relevance of these genes (in particular CREBBP/EP300) and their concomitant pathways as biomarkers or functional molecules in preeclampsia. This will result in a better understanding of the molecular basis of this disease and opens up the opportunity to develop rational therapies targeting the placental dysfunction causal to preeclampsia.

MicroRNA signature of the human developing pancreas.

PubMed

Rosero, Samuel; Bravo-Egana, Valia; Jiang, Zhijie; Khuri, Sawsan; Tsinoremas, Nicholas; Klein, Dagmar; Sabates, Eduardo; Correa-Medina, Mayrin; Ricordi, Camillo; Domínguez-Bendala, Juan; Diez, Juan; Pastori, Ricardo L

2010-09-22

MicroRNAs are non-coding RNAs that regulate gene expression including differentiation and development by either inhibiting translation or inducing target degradation. The aim of this study is to determine the microRNA expression signature during human pancreatic development and to identify potential microRNA gene targets calculating correlations between the signature microRNAs and their corresponding mRNA targets, predicted by bioinformatics, in genome-wide RNA microarray study. The microRNA signature of human fetal pancreatic samples 10-22 weeks of gestational age (wga), was obtained by PCR-based high throughput screening with Taqman Low Density Arrays. This method led to identification of 212 microRNAs. The microRNAs were classified in 3 groups: Group number I contains 4 microRNAs with the increasing profile; II, 35 microRNAs with decreasing profile and III with 173 microRNAs, which remain unchanged. We calculated Pearson correlations between the expression profile of microRNAs and target mRNAs, predicted by TargetScan 5.1 and miRBase algorithms, using genome-wide mRNA expression data. Group I correlated with the decreasing expression of 142 target mRNAs and Group II with the increasing expression of 876 target mRNAs. Most microRNAs correlate with multiple targets, just as mRNAs are targeted by multiple microRNAs. Among the identified targets are the genes and transcription factors known to play an essential role in pancreatic development. We have determined specific groups of microRNAs in human fetal pancreas that change the degree of their expression throughout the development. A negative correlative analysis suggests an intertwined network of microRNAs and mRNAs collaborating with each other. This study provides information leading to potential two-way level of combinatorial control regulating gene expression through microRNAs targeting multiple mRNAs and, conversely, target mRNAs regulated in parallel by other microRNAs as well. This study may further the

MicroRNA signature of the human developing pancreas

PubMed Central

2010-01-01

Background MicroRNAs are non-coding RNAs that regulate gene expression including differentiation and development by either inhibiting translation or inducing target degradation. The aim of this study is to determine the microRNA expression signature during human pancreatic development and to identify potential microRNA gene targets calculating correlations between the signature microRNAs and their corresponding mRNA targets, predicted by bioinformatics, in genome-wide RNA microarray study. Results The microRNA signature of human fetal pancreatic samples 10-22 weeks of gestational age (wga), was obtained by PCR-based high throughput screening with Taqman Low Density Arrays. This method led to identification of 212 microRNAs. The microRNAs were classified in 3 groups: Group number I contains 4 microRNAs with the increasing profile; II, 35 microRNAs with decreasing profile and III with 173 microRNAs, which remain unchanged. We calculated Pearson correlations between the expression profile of microRNAs and target mRNAs, predicted by TargetScan 5.1 and miRBase altgorithms, using genome-wide mRNA expression data. Group I correlated with the decreasing expression of 142 target mRNAs and Group II with the increasing expression of 876 target mRNAs. Most microRNAs correlate with multiple targets, just as mRNAs are targeted by multiple microRNAs. Among the identified targets are the genes and transcription factors known to play an essential role in pancreatic development. Conclusions We have determined specific groups of microRNAs in human fetal pancreas that change the degree of their expression throughout the development. A negative correlative analysis suggests an intertwined network of microRNAs and mRNAs collaborating with each other. This study provides information leading to potential two-way level of combinatorial control regulating gene expression through microRNAs targeting multiple mRNAs and, conversely, target mRNAs regulated in parallel by other microRNAs as well

Longitudinal Transcriptome Analysis Reveals a Sustained Differential Gene Expression Signature in Patients Treated for Acute Lyme Disease.

PubMed

Bouquet, Jerome; Soloski, Mark J; Swei, Andrea; Cheadle, Chris; Federman, Scot; Billaud, Jean-Noel; Rebman, Alison W; Kabre, Beniwende; Halpert, Richard; Boorgula, Meher; Aucott, John N; Chiu, Charles Y

2016-02-12

Lyme disease is a tick-borne illness caused by the bacterium Borrelia burgdorferi, and approximately 10 to 20% of patients report persistent symptoms lasting months to years despite appropriate treatment with antibiotics. To gain insights into the molecular basis of acute Lyme disease and the ensuing development of post-treatment symptoms, we conducted a longitudinal transcriptome study of 29 Lyme disease patients (and 13 matched controls) enrolled at the time of diagnosis and followed for up to 6 months. The differential gene expression signature of Lyme disease following the acute phase of infection persisted for at least 3 weeks and had fewer than 44% differentially expressed genes (DEGs) in common with other infectious or noninfectious syndromes. Early Lyme disease prior to antibiotic therapy was characterized by marked upregulation of Toll-like receptor signaling but lack of activation of the inflammatory T-cell apoptotic and B-cell developmental pathways seen in other acute infectious syndromes. Six months after completion of therapy, Lyme disease patients were found to have 31 to 60% of their pathways in common with three different immune-mediated chronic diseases. No differential gene expression signature was observed between Lyme disease patients with resolved illness to those with persistent symptoms at 6 months post-treatment. The identification of a sustained differential gene expression signature in Lyme disease suggests that a panel of selected human host-based biomarkers may address the need for sensitive clinical diagnostics during the "window period" of infection prior to the appearance of a detectable antibody response and may also inform the development of new therapeutic targets. Lyme disease is the most common tick-borne infection in the United States, and some patients report lingering symptoms lasting months to years despite antibiotic treatment. To better understand the role of the human host response in acute Lyme disease and the

Association of a murine leukaemia stem cell gene signature based on nucleostemin promoter activity with prognosis of acute myeloid leukaemia in patients.

PubMed

Ali, Mohamed A E; Naka, Kazuhito; Yoshida, Akiyo; Fuse, Kyoko; Kasada, Atsuo; Hoshii, Takayuki; Tadokoro, Yuko; Ueno, Masaya; Ohta, Kumiko; Kobayashi, Masahiko; Takahashi, Chiaki; Hirao, Atsushi

2014-07-18

Acute myeloid leukaemia (AML) is a heterogeneous neoplastic disorder in which a subset of cells function as leukaemia-initiating cells (LICs). In this study, we prospectively evaluated the leukaemia-initiating capacity of AML cells fractionated according to the expression of a nucleolar GTP binding protein, nucleostemin (NS). To monitor NS expression in living AML cells, we generated a mouse AML model in which green fluorescent protein (GFP) is expressed under the control of a region of the NS promoter (NS-GFP). In AML cells, NS-GFP levels were correlated with endogenous NS mRNA. AML cells with the highest expression of NS-GFP were very immature blast-like cells, efficiently formed leukaemia colonies in vitro, and exhibited the highest leukaemia-initiating capacity in vivo. Gene expression profiling analysis revealed that cell cycle regulators and nucleotide metabolism-related genes were highly enriched in a gene set associated with leukaemia-initiating capacity that we termed the 'leukaemia stem cell gene signature'. This gene signature stratified human AML patients into distinct clusters that reflected prognosis, demonstrating that the mouse leukaemia stem cell gene signature is significantly associated with the malignant properties of human AML. Further analyses of gene regulation in leukaemia stem cells could provide novel insights into diagnostic and therapeutic approaches to AML. Copyright © 2014 Elsevier Inc. All rights reserved.

Genome-wide scan for selection signatures in six cattle breeds in South Africa.

PubMed

Makina, Sithembile O; Muchadeyi, Farai C; van Marle-Köster, Este; Taylor, Jerry F; Makgahlela, Mahlako L; Maiwashe, Azwihangwisi

2015-11-26

The detection of selection signatures in breeds of livestock species can contribute to the identification of regions of the genome that are, or have been, functionally important and, as a consequence, have been targeted by selection. This study used two approaches to detect signatures of selection within and between six cattle breeds in South Africa, including Afrikaner (n = 44), Nguni (n = 54), Drakensberger (n = 47), Bonsmara (n = 44), Angus (n = 31) and Holstein (n = 29). The first approach was based on the detection of genomic regions in which haplotypes have been driven towards complete fixation within breeds. The second approach identified regions of the genome that had very different allele frequencies between populations (F ST). Forty-seven candidate genomic regions were identified as harbouring putative signatures of selection using both methods. Twelve of these candidate selected regions were shared among the breeds and ten were validated by previous studies. Thirty-three of these regions were successfully annotated and candidate genes were identified. Among these genes the keratin genes (KRT222, KRT24, KRT25, KRT26, and KRT27) and one heat shock protein gene (HSPB9) on chromosome 19 between 42,896,570 and 42,897,840 bp were detected for the Nguni breed. These genes were previously associated with adaptation to tropical environments in Zebu cattle. In addition, a number of candidate genes associated with the nervous system (WNT5B, FMOD, PRELP, and ATP2B), immune response (CYM, CDC6, and CDK10), production (MTPN, IGFBP4, TGFB1, and AJAP1) and reproductive performance (ADIPOR2, OVOS2, and RBBP8) were also detected as being under selection. The results presented here provide a foundation for detecting mutations that underlie genetic variation of traits that have economic importance for cattle breeds in South Africa.

PAGER 2.0: an update to the pathway, annotated-list and gene-signature electronic repository for Human Network Biology

PubMed Central

Yue, Zongliang; Zheng, Qi; Neylon, Michael T; Yoo, Minjae; Shin, Jimin; Zhao, Zhiying; Tan, Aik Choon

2018-01-01

Abstract Integrative Gene-set, Network and Pathway Analysis (GNPA) is a powerful data analysis approach developed to help interpret high-throughput omics data. In PAGER 1.0, we demonstrated that researchers can gain unbiased and reproducible biological insights with the introduction of PAGs (Pathways, Annotated-lists and Gene-signatures) as the basic data representation elements. In PAGER 2.0, we improve the utility of integrative GNPA by significantly expanding the coverage of PAGs and PAG-to-PAG relationships in the database, defining a new metric to quantify PAG data qualities, and developing new software features to simplify online integrative GNPA. Specifically, we included 84 282 PAGs spanning 24 different data sources that cover human diseases, published gene-expression signatures, drug–gene, miRNA–gene interactions, pathways and tissue-specific gene expressions. We introduced a new normalized Cohesion Coefficient (nCoCo) score to assess the biological relevance of genes inside a PAG, and RP-score to rank genes and assign gene-specific weights inside a PAG. The companion web interface contains numerous features to help users query and navigate the database content. The database content can be freely downloaded and is compatible with third-party Gene Set Enrichment Analysis tools. We expect PAGER 2.0 to become a major resource in integrative GNPA. PAGER 2.0 is available at http://discovery.informatics.uab.edu/PAGER/. PMID:29126216

Longitudinal Transcriptome Analysis Reveals a Sustained Differential Gene Expression Signature in Patients Treated for Acute Lyme Disease

PubMed Central

Bouquet, Jerome; Soloski, Mark J.; Swei, Andrea; Cheadle, Chris; Federman, Scot; Billaud, Jean-Noel; Rebman, Alison W.; Kabre, Beniwende; Halpert, Richard; Boorgula, Meher

2016-01-01

ABSTRACT Lyme disease is a tick-borne illness caused by the bacterium Borrelia burgdorferi, and approximately 10 to 20% of patients report persistent symptoms lasting months to years despite appropriate treatment with antibiotics. To gain insights into the molecular basis of acute Lyme disease and the ensuing development of post-treatment symptoms, we conducted a longitudinal transcriptome study of 29 Lyme disease patients (and 13 matched controls) enrolled at the time of diagnosis and followed for up to 6 months. The differential gene expression signature of Lyme disease following the acute phase of infection persisted for at least 3 weeks and had fewer than 44% differentially expressed genes (DEGs) in common with other infectious or noninfectious syndromes. Early Lyme disease prior to antibiotic therapy was characterized by marked upregulation of Toll-like receptor signaling but lack of activation of the inflammatory T-cell apoptotic and B-cell developmental pathways seen in other acute infectious syndromes. Six months after completion of therapy, Lyme disease patients were found to have 31 to 60% of their pathways in common with three different immune-mediated chronic diseases. No differential gene expression signature was observed between Lyme disease patients with resolved illness to those with persistent symptoms at 6 months post-treatment. The identification of a sustained differential gene expression signature in Lyme disease suggests that a panel of selected human host-based biomarkers may address the need for sensitive clinical diagnostics during the “window period” of infection prior to the appearance of a detectable antibody response and may also inform the development of new therapeutic targets. PMID:26873097

A genome-wide scan for signatures of differential artificial selection in ten cattle breeds.

PubMed

Rothammer, Sophie; Seichter, Doris; Förster, Martin; Medugorac, Ivica

2013-12-21

Since the times of domestication, cattle have been continually shaped by the influence of humans. Relatively recent history, including breed formation and the still enduring enormous improvement of economically important traits, is expected to have left distinctive footprints of selection within the genome. The purpose of this study was to map genome-wide selection signatures in ten cattle breeds and thus improve the understanding of the genome response to strong artificial selection and support the identification of the underlying genetic variants of favoured phenotypes. We analysed 47,651 single nucleotide polymorphisms (SNP) using Cross Population Extended Haplotype Homozygosity (XP-EHH). We set the significance thresholds using the maximum XP-EHH values of two essentially artificially unselected breeds and found up to 229 selection signatures per breed. Through a confirmation process we verified selection for three distinct phenotypes typical for one breed (polledness in Galloway, double muscling in Blanc-Bleu Belge and red coat colour in Red Holstein cattle). Moreover, we detected six genes strongly associated with known QTL for beef or dairy traits (TG, ABCG2, DGAT1, GH1, GHR and the Casein Cluster) within selection signatures of at least one breed. A literature search for genes lying in outstanding signatures revealed further promising candidate genes. However, in concordance with previous genome-wide studies, we also detected a substantial number of signatures without any yet known gene content. These results show the power of XP-EHH analyses in cattle to discover promising candidate genes and raise the hope of identifying phenotypically important variants in the near future. The finding of plausible functional candidates in some short signatures supports this hope. For instance, MAP2K6 is the only annotated gene of two signatures detected in Galloway and Gelbvieh cattle and is already known to be associated with carcass weight, back fat thickness and

Genomic Signature of Kin Selection in an Ant with Obligately Sterile Workers

PubMed Central

Warner, Michael R.; Mikheyev, Alexander S.

2017-01-01

Abstract Kin selection is thought to drive the evolution of cooperation and conflict, but the specific genes and genome-wide patterns shaped by kin selection are unknown. We identified thousands of genes associated with the sterile ant worker caste, the archetype of an altruistic phenotype shaped by kin selection, and then used population and comparative genomic approaches to study patterns of molecular evolution at these genes. Consistent with population genetic theoretical predictions, worker-upregulated genes experienced reduced selection compared with genes upregulated in reproductive castes. Worker-upregulated genes included more taxonomically restricted genes, indicating that the worker caste has recruited more novel genes, yet these genes also experienced reduced selection. Our study identifies a putative genomic signature of kin selection and helps to integrate emerging sociogenomic data with longstanding social evolution theory. PMID:28419349

A common molecular signature of intestinal-type gastric carcinoma indicates processes related to gastric carcinogenesis.

PubMed

Binato, Renata; Santos, Everton Cruz; Boroni, Mariana; Demachki, Samia; Assumpção, Paulo; Abdelhay, Eliana

2018-01-26

Gastric carcinoma (GC) is one of the most aggressive cancers and the second leading cause of cancer death in the world. According to the Lauren classification, this adenocarcinoma is divided into two subtypes, intestinal and diffuse, which differ in their clinical, epidemiological and molecular features. Several studies have attempted to delineate the molecular signature of gastric cancer to develop new and non-invasive screening tests that improve diagnosis and lead to new treatment strategies. However, a consensus signature has not yet been identified for each condition. Thus, this work aimed to analyze the gene expression profile of Brazilian intestinal-type GC tissues using microarrays and compare the results to those of non-tumor tissue samples. Moreover, we compared our intestinal-type gastric carcinoma profile with those obtained from populations worldwide to assess their similarity. The results identified a molecular signature for intestinal-type GC and revealed that 38 genes differentially expressed in Brazilian intestinal-type gastric carcinoma samples can successfully distinguish gastric tumors from non-tumor tissue in the global population. These differentially expressed genes participate in biological processes important to cell homeostasis. Furthermore, Kaplan-Meier analysis suggested that 7 of these genes could individually be able to predict overall survival in intestinal-type gastric cancer patients.

Expression profiling feline peripheral blood monocytes identifies a transcriptional signature associated with type two diabetes mellitus.

PubMed

O'Leary, Caroline A; Sedhom, Mamdouh; Reeve-Johnson, Mia; Mallyon, John; Irvine, Katharine M

2017-04-01

Diabetes mellitus is a common disease of cats and is similar to type 2 diabetes (T2D) in humans, especially with respect to the role of obesity-induced insulin resistance, glucose toxicity, decreased number of pancreatic β-cells and pancreatic amyloid deposition. Cats have thus been proposed as a valuable translational model of T2D. In humans, inflammation associated with adipose tissue is believed to be central to T2D development, and peripheral blood monocytes (PBM) are important in the inflammatory cascade which leads to insulin resistance and β-cell failure. PBM may thus provide a useful window to study the pathogenesis of diabetes mellitus in cats, however feline monocytes are poorly characterised. In this study, we used the Affymetrix Feline 1.0ST array to profile peripheral blood monocytes from 3 domestic cats with T2D and 3 cats with normal glucose tolerance. Feline monocytes were enriched for genes expressed in human monocytes, and, despite heterogeneous gene expression, we identified a T2D-associated expression signature associated with cell cycle perturbations, DNA repair and the unfolded protein response, oxidative phosphorylation and inflammatory responses. Our data provide novel insights into the feline monocyte transcriptome, and support the hypothesis that inflammatory monocytes contribute to T2D pathogenesis in cats as well as in humans. Copyright © 2017 Elsevier B.V. All rights reserved.

Molecular signatures of selection on reproductive character displacement of flower color in Phlox drummondii.

PubMed

Hopkins, Robin; Levin, Donald A; Rausher, Mark D

2012-02-01

Character displacement, which arises when species diverge in sympatry to decrease competition for resources or reproductive interference, has been observed in a wide variety of plants and animals. A classic example of reproductive character displacement, presumed to be caused by reinforcing selection, is flower-color variation in the native Texas wildflower Phlox drummondii. Here, we use population genetic analyses to investigate molecular signatures of selection on flower-color variation in this species. First, we quantify patterns of neutral genetic variation across the range of P. drummondii to demonstrate that restricted gene flow and genetic drift cannot explain the pattern of flower-color divergence in this species. There is evidence of extensive gene flow across populations with different flower colors, suggesting selection caused flower-color divergence. Second, analysis of sequence variation in the genes underlying this divergence reveals a signature of a selective sweep in one of the two genes, further indicating selection is responsible for divergence in sympatry. The lack of a signature of selection at the second locus does not necessarily indicate a lack of selection on this locus but instead brings attention to the uncertainty in depending on molecular signatures to identify selection. © 2011 The Author(s). Evolution© 2011 The Society for the Study of Evolution.

Integrating Radiosensitivity and Immune Gene Signatures for Predicting Benefit of Radiotherapy in Breast Cancer.

PubMed

Cui, Yi; Li, Bailiang; Pollom, Erqi Liu; Horst, Kathleen; Li, Ruijiang

2018-06-19

Breast cancer is a heterogeneous disease and not all patients respond equally to adjuvant radiotherapy. Predictive biomarkers are needed to select patients who will benefit from the treatment and spare others the toxicity and burden of radiation. We first trained and tested an intrinsic radiosensitivity gene signature to predict local recurrence after radiotherapy in three cohorts of 948 patients. Next, we developed an antigen processing and presentation-based immune signature by maximizing the treatment interaction effect in 129 patients. To test their predictive value, we matched patients treated with or without radiotherapy in an independent validation cohort for clinicopathologic factors including age, ER status, HER2 status, stage, hormone-therapy, chemotherapy, and surgery. Disease specific survival (DSS) was the primary endpoint. Our validation cohort consisted of 1,439 patients. After matching and stratification by the radiosensitivity signature, patients who received radiotherapy had better DSS than patients who did not in the radiation-sensitive group (hazard ratio [HR]=0.68, P=0.059, n=322), while a reverse trend was observed in the radiation-resistant group (HR=1.53, P=0.059, n=202). Similarly, patients treated with radiotherapy had significantly better DSS in the immuneeffective group (HR=0.46, P=0.0076, n=180), with no difference in DSS in the immunedefective group (HR=1.27, P=0.16, n=348). Both signatures were predictive of radiotherapy benefit (P interaction =0.007 and 0.005). Integration of radiosensitivity and immune signatures further stratified patients into three groups with differential outcomes for those treated with or without radiotherapy (P interaction =0.003). The proposed signatures have the potential to select patients who are most likely to benefit from radiotherapy. Copyright ©2018, American Association for Cancer Research.

Transcriptome-Level Signatures in Gene Expression and Gene Expression Variability during Bacterial Adaptive Evolution.

PubMed

Erickson, Keesha E; Otoupal, Peter B; Chatterjee, Anushree

2017-01-01

Antibiotic-resistant bacteria are an increasingly serious public health concern, as strains emerge that demonstrate resistance to almost all available treatments. One factor that contributes to the crisis is the adaptive ability of bacteria, which exhibit remarkable phenotypic and gene expression heterogeneity in order to gain a survival advantage in damaging environments. This high degree of variability in gene expression across biological populations makes it a challenging task to identify key regulators of bacterial adaptation. Here, we research the regulation of adaptive resistance by investigating transcriptome profiles of Escherichia coli upon adaptation to disparate toxins, including antibiotics and biofuels. We locate potential target genes via conventional gene expression analysis as well as using a new analysis technique examining differential gene expression variability. By investigating trends across the diverse adaptation conditions, we identify a focused set of genes with conserved behavior, including those involved in cell motility, metabolism, membrane structure, and transport, and several genes of unknown function. To validate the biological relevance of the observed changes, we synthetically perturb gene expression using clustered regularly interspaced short palindromic repeat (CRISPR)-dCas9. Manipulation of select genes in combination with antibiotic treatment promotes adaptive resistance as demonstrated by an increased degree of antibiotic tolerance and heterogeneity in MICs. We study the mechanisms by which identified genes influence adaptation and find that select differentially variable genes have the potential to impact metabolic rates, mutation rates, and motility. Overall, this work provides evidence for a complex nongenetic response, encompassing shifts in gene expression and gene expression variability, which underlies adaptive resistance. IMPORTANCE Even initially sensitive bacteria can rapidly thwart antibiotic treatment through stress

Single-cell transcriptomes identify human islet cell signatures and reveal cell-type–specific expression changes in type 2 diabetes

PubMed Central

Bolisetty, Mohan; Kursawe, Romy; Sun, Lili; Sivakamasundari, V.; Kycia, Ina

2017-01-01

Blood glucose levels are tightly controlled by the coordinated action of at least four cell types constituting pancreatic islets. Changes in the proportion and/or function of these cells are associated with genetic and molecular pathophysiology of monogenic, type 1, and type 2 (T2D) diabetes. Cellular heterogeneity impedes precise understanding of the molecular components of each islet cell type that govern islet (dys)function, particularly the less abundant delta and gamma/pancreatic polypeptide (PP) cells. Here, we report single-cell transcriptomes for 638 cells from nondiabetic (ND) and T2D human islet samples. Analyses of ND single-cell transcriptomes identified distinct alpha, beta, delta, and PP/gamma cell-type signatures. Genes linked to rare and common forms of islet dysfunction and diabetes were expressed in the delta and PP/gamma cell types. Moreover, this study revealed that delta cells specifically express receptors that receive and coordinate systemic cues from the leptin, ghrelin, and dopamine signaling pathways implicating them as integrators of central and peripheral metabolic signals into the pancreatic islet. Finally, single-cell transcriptome profiling revealed genes differentially regulated between T2D and ND alpha, beta, and delta cells that were undetectable in paired whole islet analyses. This study thus identifies fundamental cell-type–specific features of pancreatic islet (dys)function and provides a critical resource for comprehensive understanding of islet biology and diabetes pathogenesis. PMID:27864352

CoGAPS matrix factorization algorithm identifies transcriptional changes in AP-2alpha target genes in feedback from therapeutic inhibition of the EGFR network

PubMed Central

Thakar, Manjusha; Howard, Jason D.; Kagohara, Luciane T.; Krigsfeld, Gabriel; Ranaweera, Ruchira S.; Hughes, Robert M.; Perez, Jimena; Jones, Siân; Favorov, Alexander V.; Carey, Jacob; Stein-O'Brien, Genevieve; Gaykalova, Daria A.; Ochs, Michael F.; Chung, Christine H.

2016-01-01

Patients with oncogene driven tumors are treated with targeted therapeutics including EGFR inhibitors. Genomic data from The Cancer Genome Atlas (TCGA) demonstrates molecular alterations to EGFR, MAPK, and PI3K pathways in previously untreated tumors. Therefore, this study uses bioinformatics algorithms to delineate interactions resulting from EGFR inhibitor use in cancer cells with these genetic alterations. We modify the HaCaT keratinocyte cell line model to simulate cancer cells with constitutive activation of EGFR, HRAS, and PI3K in a controlled genetic background. We then measure gene expression after treating modified HaCaT cells with gefitinib, afatinib, and cetuximab. The CoGAPS algorithm distinguishes a gene expression signature associated with the anticipated silencing of the EGFR network. It also infers a feedback signature with EGFR gene expression itself increasing in cells that are responsive to EGFR inhibitors. This feedback signature has increased expression of several growth factor receptors regulated by the AP-2 family of transcription factors. The gene expression signatures for AP-2alpha are further correlated with sensitivity to cetuximab treatment in HNSCC cell lines and changes in EGFR expression in HNSCC tumors with low CDKN2A gene expression. In addition, the AP-2alpha gene expression signatures are also associated with inhibition of MEK, PI3K, and mTOR pathways in the Library of Integrated Network-Based Cellular Signatures (LINCS) data. These results suggest that AP-2 transcription factors are activated as feedback from EGFR network inhibition and may mediate EGFR inhibitor resistance. PMID:27650546

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.

Use of mRNA expression signatures to discover small molecule inhibitors of skeletal muscle atrophy

PubMed Central

Adams, Christopher M.; Ebert, Scott M.; Dyle, Michael C.

2017-01-01

Purpose of review Here, we discuss a recently developed experimental strategy for discovering small molecules with potential to prevent and treat skeletal muscle atrophy. Recent findings Muscle atrophy involves and requires widespread changes in skeletal muscle gene expression, which generate complex but measurable patterns of positive and negative changes in skeletal muscle mRNA levels (a.k.a. mRNA expression signatures of muscle atrophy). Many bioactive small molecules generate their own characteristic mRNA expression signatures, and by identifying small molecules whose signatures approximate mirror images of muscle atrophy signatures, one may identify small molecules with potential to prevent and/or reverse muscle atrophy. Unlike a conventional drug discovery approach, this strategy does not rely on a predefined molecular target but rather exploits the complexity of muscle atrophy to identify small molecules that counter the entire spectrum of pathological changes in atrophic muscle. We discuss how this strategy has been used to identify two natural compounds, ursolic acid and tomatidine, that reduce muscle atrophy and improve skeletal muscle function. Summary Discovery strategies based on mRNA expression signatures can elucidate new approaches for preserving and restoring muscle mass and function. PMID:25807353

Use of mRNA expression signatures to discover small molecule inhibitors of skeletal muscle atrophy.

PubMed

Adams, Christopher M; Ebert, Scott M; Dyle, Michael C

2015-05-01

Here, we discuss a recently developed experimental strategy for discovering small molecules with potential to prevent and treat skeletal muscle atrophy. Muscle atrophy involves and requires widespread changes in skeletal muscle gene expression, which generate complex but measurable patterns of positive and negative changes in skeletal muscle mRNA levels (a.k.a. mRNA expression signatures of muscle atrophy). Many bioactive small molecules generate their own characteristic mRNA expression signatures, and by identifying small molecules whose signatures approximate mirror images of muscle atrophy signatures, one may identify small molecules with potential to prevent and/or reverse muscle atrophy. Unlike a conventional drug discovery approach, this strategy does not rely on a predefined molecular target but rather exploits the complexity of muscle atrophy to identify small molecules that counter the entire spectrum of pathological changes in atrophic muscle. We discuss how this strategy has been used to identify two natural compounds, ursolic acid and tomatidine, that reduce muscle atrophy and improve skeletal muscle function. Discovery strategies based on mRNA expression signatures can elucidate new approaches for preserving and restoring muscle mass and function.

Phylogenomic analysis of UDP glycosyltransferase 1 multigene family in Linum usitatissimum identified genes with varied expression patterns.

PubMed

Barvkar, Vitthal T; Pardeshi, Varsha C; Kale, Sandip M; Kadoo, Narendra Y; Gupta, Vidya S

2012-05-08

The glycosylation process, catalyzed by ubiquitous glycosyltransferase (GT) family enzymes, is a prevalent modification of plant secondary metabolites that regulates various functions such as hormone homeostasis, detoxification of xenobiotics and biosynthesis and storage of secondary metabolites. Flax (Linum usitatissimum L.) is a commercially grown oilseed crop, important because of its essential fatty acids and health promoting lignans. Identification and characterization of UDP glycosyltransferase (UGT) genes from flax could provide valuable basic information about this important gene family and help to explain the seed specific glycosylated metabolite accumulation and other processes in plants. Plant genome sequencing projects are useful to discover complexity within this gene family and also pave way for the development of functional genomics approaches. Taking advantage of the newly assembled draft genome sequence of flax, we identified 137 UDP glycosyltransferase (UGT) genes from flax using a conserved signature motif. Phylogenetic analysis of these protein sequences clustered them into 14 major groups (A-N). Expression patterns of these genes were investigated using publicly available expressed sequence tag (EST), microarray data and reverse transcription quantitative real time PCR (RT-qPCR). Seventy-three per cent of these genes (100 out of 137) showed expression evidence in 15 tissues examined and indicated varied expression profiles. The RT-qPCR results of 10 selected genes were also coherent with the digital expression analysis. Interestingly, five duplicated UGT genes were identified, which showed differential expression in various tissues. Of the seven intron loss/gain positions detected, two intron positions were conserved among most of the UGTs, although a clear relationship about the evolution of these genes could not be established. Comparison of the flax UGTs with orthologs from four other sequenced dicot genomes indicated that seven UGTs were

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

Identification of a transcriptional signature for the wound healing continuum

PubMed Central

Peake, Matthew A; Caley, Mathew; Giles, Peter J; Wall, Ivan; Enoch, Stuart; Davies, Lindsay C; Kipling, David; Thomas, David W; Stephens, Phil

2014-01-01

There is a spectrum/continuum of adult human wound healing outcomes ranging from the enhanced (nearly scarless) healing observed in oral mucosa to scarring within skin and the nonhealing of chronic skin wounds. Central to these outcomes is the role of the fibroblast. Global gene expression profiling utilizing microarrays is starting to give insight into the role of such cells during the healing process, but no studies to date have produced a gene signature for this wound healing continuum. Microarray analysis of adult oral mucosal fibroblast (OMF), normal skin fibroblast (NF), and chronic wound fibroblast (CWF) at 0 and 6 hours post-serum stimulation was performed. Genes whose expression increases following serum exposure in the order OMF < NF < CWF are candidates for a negative/impaired healing phenotype (the dysfunctional healing group), whereas genes with the converse pattern are potentially associated with a positive/preferential healing phenotype (the enhanced healing group). Sixty-six genes in the enhanced healing group and 38 genes in the dysfunctional healing group were identified. Overrepresentation analysis revealed pathways directly and indirectly associated with wound healing and aging and additional categories associated with differentiation, development, and morphogenesis. Knowledge of this wound healing continuum gene signature may in turn assist in the therapeutic assessment/treatment of a patient's wounds. PMID:24844339

Development and Validation of a Novel Platform-Independent Metastasis Signature in Human Breast Cancer

PubMed Central

Speers, Corey; Liu, Meilan; Wilder-Romans, Kari; Lawrence, Theodore S.; Pierce, Lori J.; Feng, Felix Y.

2015-01-01

Purpose The molecular drivers of metastasis in breast cancer are not well understood. Therefore, we sought to identify the biological processes underlying distant progression and define a prognostic signature for metastatic potential in breast cancer. Experimental design In vivo screening for metastases was performed using Chick Chorioallantoic Membrane assays in 21 preclinical breast cancer models. Expressed genes associated with metastatic potential were identified using high-throughput analysis. Correlations with biological function were determined using the Database for Annotation, Visualization and Integrated Discovery. Results We identified a broad range of metastatic potential that was independent of intrinsic breast cancer subtypes. 146 genes were significantly associated with metastasis progression and were linked to cancer-related biological functions, including cell migration/adhesion, Jak-STAT, TGF-beta, and Wnt signaling. These genes were used to develop a platform-independent gene expression signature (M-Sig), which was trained and subsequently validated on 5 independent cohorts totaling nearly 1800 breast cancer patients with all p-values < 0.005 and hazard ratios ranging from approximately 2.5 to 3. On multivariate analysis accounting for standard clinicopathologic prognostic variables, M-Sig remained the strongest prognostic factor for metastatic progression, with p-values < 0.001 and hazard ratios > 2 in three different cohorts. Conclusion M-Sig is strongly prognostic for metastatic progression, and may provide clinical utility in combination with treatment prediction tools to better guide patient care. In addition, the platform-independent nature of the signature makes it an excellent research tool as it can be directly applied onto existing, and future, datasets. PMID:25974184

Strain-Dependent Transcriptome Signatures for Robustness in Lactococcus lactis

PubMed Central

Dijkstra, Annereinou R.; Alkema, Wynand; Starrenburg, Marjo J. C.; van Hijum, Sacha A. F. T.; Bron, Peter A.

2016-01-01

Recently, we demonstrated that fermentation conditions have a strong impact on subsequent survival of Lactococcus lactis strain MG1363 during heat and oxidative stress, two important parameters during spray drying. Moreover, employment of a transcriptome-phenotype matching approach revealed groups of genes associated with robustness towards heat and/or oxidative stress. To investigate if other strains have similar or distinct transcriptome signatures for robustness, we applied an identical transcriptome-robustness phenotype matching approach on the L. lactis strains IL1403, KF147 and SK11, which have previously been demonstrated to display highly diverse robustness phenotypes. These strains were subjected to an identical fermentation regime as was performed earlier for strain MG1363 and consisted of twelve conditions, varying in the level of salt and/or oxygen, as well as fermentation temperature and pH. In the exponential phase of growth, cells were harvested for transcriptome analysis and assessment of heat and oxidative stress survival phenotypes. The variation in fermentation conditions resulted in differences in heat and oxidative stress survival of up to five 10-log units. Effects of the fermentation conditions on stress survival of the L. lactis strains were typically strain-dependent, although the fermentation conditions had mainly similar effects on the growth characteristics of the different strains. By association of the transcriptomes and robustness phenotypes highly strain-specific transcriptome signatures for robustness towards heat and oxidative stress were identified, indicating that multiple mechanisms exist to increase robustness and, as a consequence, robustness of each strain requires individual optimization. However, a relatively small overlap in the transcriptome responses of the strains was also identified and this generic transcriptome signature included genes previously associated with stress (ctsR and lplL) and novel genes, including nan

Integrated Proteomic and Transcriptomic-Based Approaches to Identifying Signature Biomarkers and Pathways for Elucidation of Daoy and UW228 Subtypes.

PubMed

Higdon, Roger; Kala, Jessie; Wilkins, Devan; Yan, Julia Fangfei; Sethi, Manveen K; Lin, Liang; Liu, Siqi; Montague, Elizabeth; Janko, Imre; Choiniere, John; Kolker, Natali; Hancock, William S; Kolker, Eugene; Fanayan, Susan

2017-02-03

Medulloblastoma (MB) is the most common malignant pediatric brain tumor. Patient survival has remained largely the same for the past 20 years, with therapies causing significant health, cognitive, behavioral and developmental complications for those who survive the tumor. In this study, we profiled the total transcriptome and proteome of two established MB cell lines, Daoy and UW228, using high-throughput RNA sequencing (RNA-Seq) and label-free nano-LC-MS/MS-based quantitative proteomics, coupled with advanced pathway analysis. While Daoy has been suggested to belong to the sonic hedgehog (SHH) subtype, the exact UW228 subtype is not yet clearly established. Thus, a goal of this study was to identify protein markers and pathways that would help elucidate their subtype classification. A number of differentially expressed genes and proteins, including a number of adhesion, cytoskeletal and signaling molecules, were observed between the two cell lines. While several cancer-associated genes/proteins exhibited similar expression across the two cell lines, upregulation of a number of signature proteins and enrichment of key components of SHH and WNT signaling pathways were uniquely observed in Daoy and UW228, respectively. The novel information on differentially expressed genes/proteins and enriched pathways provide insights into the biology of MB, which could help elucidate their subtype classification.

Signatures of selection in tilapia revealed by whole genome resequencing

PubMed Central

Hong Xia, Jun; Bai, Zhiyi; Meng, Zining; Zhang, Yong; Wang, Le; Liu, Feng; Jing, Wu; Yi Wan, Zi; Li, Jiale; Lin, Haoran; Hua Yue, Gen

2015-01-01

Natural selection and selective breeding for genetic improvement have left detectable signatures within the genome of a species. Identification of selection signatures is important in evolutionary biology and for detecting genes that facilitate to accelerate genetic improvement. However, selection signatures, including artificial selection and natural selection, have only been identified at the whole genome level in several genetically improved fish species. Tilapia is one of the most important genetically improved fish species in the world. Using next-generation sequencing, we sequenced the genomes of 47 tilapia individuals. We identified a total of 1.43 million high-quality SNPs and found that the LD block sizes ranged from 10–100 kb in tilapia. We detected over a hundred putative selective sweep regions in each line of tilapia. Most selection signatures were located in non-coding regions of the tilapia genome. The Wnt signaling, gonadotropin-releasing hormone receptor and integrin signaling pathways were under positive selection in all improved tilapia lines. Our study provides a genome-wide map of genetic variation and selection footprints in tilapia, which could be important for genetic studies and accelerating genetic improvement of tilapia. PMID:26373374

Signatures of selection in tilapia revealed by whole genome resequencing.

PubMed

Xia, Jun Hong; Bai, Zhiyi; Meng, Zining; Zhang, Yong; Wang, Le; Liu, Feng; Jing, Wu; Wan, Zi Yi; Li, Jiale; Lin, Haoran; Yue, Gen Hua

2015-09-16

Natural selection and selective breeding for genetic improvement have left detectable signatures within the genome of a species. Identification of selection signatures is important in evolutionary biology and for detecting genes that facilitate to accelerate genetic improvement. However, selection signatures, including artificial selection and natural selection, have only been identified at the whole genome level in several genetically improved fish species. Tilapia is one of the most important genetically improved fish species in the world. Using next-generation sequencing, we sequenced the genomes of 47 tilapia individuals. We identified a total of 1.43 million high-quality SNPs and found that the LD block sizes ranged from 10-100 kb in tilapia. We detected over a hundred putative selective sweep regions in each line of tilapia. Most selection signatures were located in non-coding regions of the tilapia genome. The Wnt signaling, gonadotropin-releasing hormone receptor and integrin signaling pathways were under positive selection in all improved tilapia lines. Our study provides a genome-wide map of genetic variation and selection footprints in tilapia, which could be important for genetic studies and accelerating genetic improvement of tilapia.

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

DNA methylation analysis of paediatric low-grade astrocytomas identifies a tumour-specific hypomethylation signature in pilocytic astrocytomas.

PubMed

Jeyapalan, Jennie N; Doctor, Gabriel T; Jones, Tania A; Alberman, Samuel N; Tep, Alexander; Haria, Chirag M; Schwalbe, Edward C; Morley, Isabel C F; Hill, Alfred A; LeCain, Magdalena; Ottaviani, Diego; Clifford, Steven C; Qaddoumi, Ibrahim; Tatevossian, Ruth G; Ellison, David W; Sheer, Denise

2016-05-27

Low-grade gliomas (LGGs) account for about a third of all brain tumours in children. We conducted a detailed study of DNA methylation and gene expression to improve our understanding of the biology of pilocytic and diffuse astrocytomas. Pilocytic astrocytomas were found to have a distinctive signature at 315 CpG sites, of which 312 were hypomethylated and 3 were hypermethylated. Genomic analysis revealed that 182 of these sites are within annotated enhancers. The signature was not present in diffuse astrocytomas, or in published profiles of other brain tumours and normal brain tissue. The AP-1 transcription factor was predicted to bind within 200 bp of a subset of the 315 differentially methylated CpG sites; the AP-1 factors, FOS and FOSL1 were found to be up-regulated in pilocytic astrocytomas. We also analysed splice variants of the AP-1 target gene, CCND1, which encodes cell cycle regulator cyclin D1. CCND1a was found to be highly expressed in both pilocytic and diffuse astrocytomas, but diffuse astrocytomas have far higher expression of the oncogenic variant, CCND1b. These findings highlight novel genetic and epigenetic differences between pilocytic and diffuse astrocytoma, in addition to well-described alterations involving BRAF, MYB and FGFR1.

A dehydration-inducible gene in the truffle Tuber borchii identifies a novel group of dehydrins

PubMed Central

Abba', Simona; Ghignone, Stefano; Bonfante, Paola

2006-01-01

Background The expressed sequence tag M6G10 was originally isolated from a screening for differentially expressed transcripts during the reproductive stage of the white truffle Tuber borchii. mRNA levels for M6G10 increased dramatically during fruiting body maturation compared to the vegetative mycelial stage. Results Bioinformatics tools, phylogenetic analysis and expression studies were used to support the hypothesis that this sequence, named TbDHN1, is the first dehydrin (DHN)-like coding gene isolated in fungi. Homologs of this gene, all defined as "coding for hypothetical proteins" in public databases, were exclusively found in ascomycetous fungi and in plants. Although complete (or almost complete) fungal genomes and EST collections of some Basidiomycota and Glomeromycota are already available, DHN-like proteins appear to be represented only in Ascomycota. A new and previously uncharacterized conserved signature pattern was identified and proposed to Uniprot database as the main distinguishing feature of this new group of DHNs. Expression studies provide experimental evidence of a transcript induction of TbDHN1 during cellular dehydration. Conclusion Expression pattern and sequence similarities to known plant DHNs indicate that TbDHN1 is the first characterized DHN-like protein in fungi. The high similarity of TbDHN1 with homolog coding sequences implies the existence of a novel fungal/plant group of LEA Class II proteins characterized by a previously undescribed signature pattern. PMID:16512918

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

Novel insights into systemic autoimmune rheumatic diseases using shared molecular signatures and an integrative analysis.

PubMed

Hudson, Marie; Bernatsky, Sasha; Colmegna, Ines; Lora, Maximilien; Pastinen, Tomi; Klein Oros, Kathleen; Greenwood, Celia M T

2017-06-03

We undertook this study to identify DNA methylation signatures of three systemic autoimmune rheumatic diseases (SARDs), namely rheumatoid arthritis, systemic lupus erythematosus, and systemic sclerosis, compared to healthy controls. Using a careful design to minimize confounding, we restricted our study to subjects with incident disease and performed our analyses on purified CD4 + T cells, key effector cells in SARD. We identified differentially methylated (using the Illumina Infinium HumanMethylation450 BeadChip array) and expressed (using the Illumina TruSeq stranded RNA-seq protocol) sites between cases and controls, and investigated the biological significance of this SARD signature using gene annotation databases. We recruited 13 seropositive rheumatoid arthritis, 19 systemic sclerosis, 12 systemic lupus erythematosus subjects, and 8 healthy controls. We identified 33 genes that were both differentially methylated and expressed (26 over- and 7 under-expressed) in SARD cases versus controls. The most highly overexpressed gene was CD1C (log fold change in expression = 1.85, adjusted P value = 0.009). In functional analysis (Ingenuity Pathway Analysis), the top network identified was lipid metabolism, molecular transport, small molecule biochemistry. The top canonical pathways included the mitochondrial L-carnitine shuttle pathway (P = 5E-03) and PTEN signaling (P = 8E-03). The top upstream regulator was HNF4A (P = 3E-05). This novel SARD signature contributes to ongoing work to further our understanding of the molecular mechanisms underlying SARD and provides novel targets of interest.

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

Identification and Construction of Combinatory Cancer Hallmark-Based Gene Signature Sets to Predict Recurrence and Chemotherapy Benefit in Stage II Colorectal Cancer.

PubMed

Gao, Shanwu; Tibiche, Chabane; Zou, Jinfeng; Zaman, Naif; Trifiro, Mark; O'Connor-McCourt, Maureen; Wang, Edwin

2016-01-01

Decisions regarding adjuvant therapy in patients with stage II colorectal cancer (CRC) have been among the most challenging and controversial in oncology over the past 20 years. To develop robust combinatory cancer hallmark-based gene signature sets (CSS sets) that more accurately predict prognosis and identify a subset of patients with stage II CRC who could gain survival benefits from adjuvant chemotherapy. Thirteen retrospective studies of patients with stage II CRC who had clinical follow-up and adjuvant chemotherapy were analyzed. Respective totals of 162 and 843 patients from 2 and 11 independent cohorts were used as the discovery and validation cohorts, respectively. A total of 1005 patients with stage II CRC were included in the 13 cohorts. Among them, 84 of 416 patients in 3 independent cohorts received fluorouracil-based adjuvant chemotherapy. Identification of CSS sets to predict relapse-free survival and identify a subset of patients with stage II CRC who could gain substantial survival benefits from fluorouracil-based adjuvant chemotherapy. Eight cancer hallmark-based gene signatures (30 genes each) were identified and used to construct CSS sets for determining prognosis. The CSS sets were validated in 11 independent cohorts of 767 patients with stage II CRC who did not receive adjuvant chemotherapy. The CSS sets accurately stratified patients into low-, intermediate-, and high-risk groups. Five-year relapse-free survival rates were 94%, 78%, and 45%, respectively, representing 60%, 28%, and 12% of patients with stage II disease. The 416 patients with CSS set-defined high-risk stage II CRC who received fluorouracil-based adjuvant chemotherapy showed a substantial gain in survival benefits from the treatment (ie, recurrence reduced by 30%-40% in 5 years). The CSS sets substantially outperformed other prognostic predictors of stage 2 CRC. They are more accurate and robust for prognostic predictions and facilitate the identification of patients with stage

A Gene Expression Signature Associated with Overall Survival in Patients with Hepatocellular Carcinoma Suggests a New Treatment Strategy.

PubMed

Gillet, Jean-Pierre; Andersen, Jesper B; Madigan, James P; Varma, Sudhir; Bagni, Rachel K; Powell, Katie; Burgan, William E; Wu, Chung-Pu; Calcagno, Anna Maria; Ambudkar, Suresh V; Thorgeirsson, Snorri S; Gottesman, Michael M

2016-02-01

Despite improvements in the management of liver cancer, the survival rate for patients with hepatocellular carcinoma (HCC) remains dismal. The survival benefit of systemic chemotherapy for the treatment of liver cancer is only marginal. Although the reasons for treatment failure are multifactorial, intrinsic resistance to chemotherapy plays a primary role. Here, we analyzed the expression of 377 multidrug resistance (MDR)-associated genes in two independent cohorts of patients with advanced HCC, with the aim of finding ways to improve survival in this poor-prognosis cancer. Taqman-based quantitative polymerase chain reaction revealed a 45-gene signature that predicts overall survival (OS) in patients with HCC. Using the Connectivity Map Tool, we were able to identify drugs that converted the gene expression profiles of HCC cell lines from ones matching patients with poor OS to profiles associated with good OS. We found three compounds that convert the gene expression profiles of three HCC cell lines to gene expression profiles associated with good OS. These compounds increase histone acetylation, which correlates with the synergistic sensitization of those MDR tumor cells to conventional chemotherapeutic agents, including cisplatin, sorafenib, and 5-fluorouracil. Our results indicate that it is possible to modulate gene expression profiles in HCC cell lines to those associated with better outcome. This approach also increases sensitization of HCC cells toward conventional chemotherapeutic agents. This work suggests new treatment strategies for a disease for which few therapeutic options exist. U.S. Government work not protected by U.S. copyright.

Signature and Mechanism of the Epithelial-to-Mesenchymal Transition

DTIC Science & Technology

2009-05-01

metastasis of epithelial cancers such as breast cancer . This study seeks to identify genes commonly regulated in the EMT, and identify key regulators...circuit, or portions of it, to cancer metastasis, particularly in breast cancer models, will be investigated. An EMT core gene signature of...Conclusion…………………………………………………………………………… 6 References……………………………………………………………………………. 6 4 Introduction Breast cancer is one of

Phenotypic Robustness and the Assortativity Signature of Human Transcription Factor Networks

PubMed Central

Pechenick, Dov A.; Payne, Joshua L.; Moore, Jason H.

2014-01-01

Many developmental, physiological, and behavioral processes depend on the precise expression of genes in space and time. Such spatiotemporal gene expression phenotypes arise from the binding of sequence-specific transcription factors (TFs) to DNA, and from the regulation of nearby genes that such binding causes. These nearby genes may themselves encode TFs, giving rise to a transcription factor network (TFN), wherein nodes represent TFs and directed edges denote regulatory interactions between TFs. Computational studies have linked several topological properties of TFNs — such as their degree distribution — with the robustness of a TFN's gene expression phenotype to genetic and environmental perturbation. Another important topological property is assortativity, which measures the tendency of nodes with similar numbers of edges to connect. In directed networks, assortativity comprises four distinct components that collectively form an assortativity signature. We know very little about how a TFN's assortativity signature affects the robustness of its gene expression phenotype to perturbation. While recent theoretical results suggest that increasing one specific component of a TFN's assortativity signature leads to increased phenotypic robustness, the biological context of this finding is currently limited because the assortativity signatures of real-world TFNs have not been characterized. It is therefore unclear whether these earlier theoretical findings are biologically relevant. Moreover, it is not known how the other three components of the assortativity signature contribute to the phenotypic robustness of TFNs. Here, we use publicly available DNaseI-seq data to measure the assortativity signatures of genome-wide TFNs in 41 distinct human cell and tissue types. We find that all TFNs share a common assortativity signature and that this signature confers phenotypic robustness to model TFNs. Lastly, we determine the extent to which each of the four components of

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

Regulatory versus coding signatures of natural selection in a candidate gene involved in the adaptive divergence of whitefish species pairs (Coregonus spp.)

PubMed Central

Jeukens, Julie; Bernatchez, Louis

2012-01-01

While gene expression divergence is known to be involved in adaptive phenotypic divergence and speciation, the relative importance of regulatory and structural evolution of genes is poorly understood. A recent next-generation sequencing experiment allowed identifying candidate genes potentially involved in the ongoing speciation of sympatric dwarf and normal lake whitefish (Coregonus clupeaformis), such as cytosolic malate dehydrogenase (MDH1), which showed both significant expression and sequence divergence. The main goal of this study was to investigate into more details the signatures of natural selection in the regulatory and coding sequences of MDH1 in lake whitefish and test for parallelism of these signatures with other coregonine species. Sequencing of the two regions in 118 fish from four sympatric pairs of whitefish and two cisco species revealed a total of 35 single nucleotide polymorphisms (SNPs), with more genetic diversity in European compared to North American coregonine species. While the coding region was found to be under purifying selection, an SNP in the proximal promoter exhibited significant allele frequency divergence in a parallel manner among independent sympatric pairs of North American lake whitefish and European whitefish (C. lavaretus). According to transcription factor binding simulation for 22 regulatory haplotypes of MDH1, putative binding profiles were fairly conserved among species, except for the region around this SNP. Moreover, we found evidence for the role of this SNP in the regulation of MDH1 expression level. Overall, these results provide further evidence for the role of natural selection in gene regulation evolution among whitefish species pairs and suggest its possible link with patterns of phenotypic diversity observed in coregonine species. PMID:22408741

Regulatory versus coding signatures of natural selection in a candidate gene involved in the adaptive divergence of whitefish species pairs (Coregonus spp.).

PubMed

Jeukens, Julie; Bernatchez, Louis

2012-01-01

While gene expression divergence is known to be involved in adaptive phenotypic divergence and speciation, the relative importance of regulatory and structural evolution of genes is poorly understood. A recent next-generation sequencing experiment allowed identifying candidate genes potentially involved in the ongoing speciation of sympatric dwarf and normal lake whitefish (Coregonus clupeaformis), such as cytosolic malate dehydrogenase (MDH1), which showed both significant expression and sequence divergence. The main goal of this study was to investigate into more details the signatures of natural selection in the regulatory and coding sequences of MDH1 in lake whitefish and test for parallelism of these signatures with other coregonine species. Sequencing of the two regions in 118 fish from four sympatric pairs of whitefish and two cisco species revealed a total of 35 single nucleotide polymorphisms (SNPs), with more genetic diversity in European compared to North American coregonine species. While the coding region was found to be under purifying selection, an SNP in the proximal promoter exhibited significant allele frequency divergence in a parallel manner among independent sympatric pairs of North American lake whitefish and European whitefish (C. lavaretus). According to transcription factor binding simulation for 22 regulatory haplotypes of MDH1, putative binding profiles were fairly conserved among species, except for the region around this SNP. Moreover, we found evidence for the role of this SNP in the regulation of MDH1 expression level. Overall, these results provide further evidence for the role of natural selection in gene regulation evolution among whitefish species pairs and suggest its possible link with patterns of phenotypic diversity observed in coregonine species.

Integration of machine learning and meta-analysis identifies the transcriptomic bio-signature of mastitis disease in cattle.

PubMed

Sharifi, Somayeh; Pakdel, Abbas; Ebrahimi, Mansour; Reecy, James M; Fazeli Farsani, Samaneh; Ebrahimie, Esmaeil

2018-01-01

Gram-negative bacteria such as Escherichia coli (E. coli) are assumed to be among the main agents that cause severe mastitis disease with clinical signs in dairy cattle. Rapid detection of this disease is so important in order to prevent transmission to other cows and helps to reduce inappropriate use of antibiotics. With the rapid progress in high-throughput technologies, and accumulation of various kinds of '-omics' data in public repositories, there is an opportunity to retrieve, integrate, and reanalyze these resources to improve the diagnosis and treatment of different diseases and to provide mechanistic insights into host resistance in an efficient way. Meta-analysis is a relatively inexpensive option with good potential to increase the statistical power and generalizability of single-study analysis. In the current meta-analysis research, six microarray-based studies that investigate the transcriptome profile of mammary gland tissue after induced mastitis by E. coli infection were used. This meta-analysis not only reinforced the findings in individual studies, but also several novel terms including responses to hypoxia, response to drug, anti-apoptosis and positive regulation of transcription from RNA polymerase II promoter enriched by up-regulated genes. Finally, in order to identify the small sets of genes that are sufficiently informative in E. coli mastitis, the differentially expressed gene introduced by meta-analysis were prioritized by using ten different attribute weighting algorithms. Twelve meta-genes were detected by the majority of attribute weighting algorithms (with weight above 0.7) as most informative genes including CXCL8 (IL8), NFKBIZ, HP, ZC3H12A, PDE4B, CASP4, CXCL2, CCL20, GRO1(CXCL1), CFB, S100A9, and S100A8. Interestingly, the results have been demonstrated that all of these genes are the key genes in the immune response, inflammation or mastitis. The Decision tree models efficiently discovered the best combination of the meta-genes as

Integration of machine learning and meta-analysis identifies the transcriptomic bio-signature of mastitis disease in cattle

PubMed Central

Sharifi, Somayeh; Ebrahimi, Mansour; Reecy, James M.; Fazeli Farsani, Samaneh; Ebrahimie, Esmaeil

2018-01-01

Gram-negative bacteria such as Escherichia coli (E. coli) are assumed to be among the main agents that cause severe mastitis disease with clinical signs in dairy cattle. Rapid detection of this disease is so important in order to prevent transmission to other cows and helps to reduce inappropriate use of antibiotics. With the rapid progress in high-throughput technologies, and accumulation of various kinds of ‘-omics’ data in public repositories, there is an opportunity to retrieve, integrate, and reanalyze these resources to improve the diagnosis and treatment of different diseases and to provide mechanistic insights into host resistance in an efficient way. Meta-analysis is a relatively inexpensive option with good potential to increase the statistical power and generalizability of single-study analysis. In the current meta-analysis research, six microarray-based studies that investigate the transcriptome profile of mammary gland tissue after induced mastitis by E. coli infection were used. This meta-analysis not only reinforced the findings in individual studies, but also several novel terms including responses to hypoxia, response to drug, anti-apoptosis and positive regulation of transcription from RNA polymerase II promoter enriched by up-regulated genes. Finally, in order to identify the small sets of genes that are sufficiently informative in E. coli mastitis, the differentially expressed gene introduced by meta-analysis were prioritized by using ten different attribute weighting algorithms. Twelve meta-genes were detected by the majority of attribute weighting algorithms (with weight above 0.7) as most informative genes including CXCL8 (IL8), NFKBIZ, HP, ZC3H12A, PDE4B, CASP4, CXCL2, CCL20, GRO1(CXCL1), CFB, S100A9, and S100A8. Interestingly, the results have been demonstrated that all of these genes are the key genes in the immune response, inflammation or mastitis. The Decision tree models efficiently discovered the best combination of the meta-genes

Comprehensive evaluation of gene expression signatures in response to electroacupuncture stimulation at Zusanli (ST36) acupoint by transcriptomic analysis.

PubMed

Wu, Jing-Shan; Lo, Hsin-Yi; Li, Chia-Cheng; Chen, Feng-Yuan; Hsiang, Chien-Yun; Ho, Tin-Yun

2017-08-15

Electroacupuncture (EA) has been applied to treat and prevent diseases for years. However, molecular events happened in both the acupunctured site and the internal organs after EA stimulation have not been clarified. Here we applied transcriptomic analysis to explore the gene expression signatures after EA stimulation. Mice were applied EA stimulation at ST36 for 15 min and nine tissues were collected three hours later for microarray analysis. We found that EA affected the expression of genes not only in the acupunctured site but also in the internal organs. EA commonly affected biological networks involved in cytoskeleton and cell adhesion, and also regulated unique process networks in specific organs, such as γ-aminobutyric acid-ergic neurotransmission in brain and inflammation process in lung. In addition, EA affected the expression of genes related to various diseases, such as neurodegenerative diseases in brain and obstructive pulmonary diseases in lung. This report applied, for the first time, a global comprehensive genome-wide approach to analyze the gene expression profiling of acupunctured site and internal organs after EA stimulation. The connection between gene expression signatures, biological processes, and diseases might provide a basis for prediction and explanation on the therapeutic potentials of acupuncture in organs.

Selection Signature Analysis Implicates the PC1/PCSK1 Region for Chicken Abdominal Fat Content

PubMed Central

Wang, Zhipeng; Zhang, Yuandan; Wang, Shouzhi; Wang, Ning; Ma, Li; Leng, Li; Wang, Shengwen; Wang, Qigui; Wang, Yuxiang; Tang, Zhiquan; Li, Ning; Da, Yang; Li, Hui

2012-01-01

We conducted a selection signature analysis using the chicken 60k SNP chip in two chicken lines that had been divergently selected for abdominal fat content (AFC) for 11 generations. The selection signature analysis used multiple signals of selection, including long-range allele frequency differences between the lean and fat lines, long-range heterozygosity changes, linkage disequilibrium, haplotype frequencies, and extended haplotype homozygosity. Multiple signals of selection identified ten signatures on chromosomes 1, 2, 4, 5, 11, 15, 20, 26 and Z. The 0.73 Mb PC1/PCSK1 region of the Z chromosome at 55.43-56.16 Mb was the most heavily selected region. This region had 26 SNP markers and seven genes, Mar-03, SLC12A2, FBN2, ERAP1, CAST, PC1/PCSK1 and ELL2, where PC1/PCSK1 are the chicken/human names for the same gene. The lean and fat lines had two main haplotypes with completely opposite SNP alleles for the 26 SNP markers and were virtually line-specific, and had a recombinant haplotype with nearly equal frequency (0.193 and 0.196) in both lines. Other haplotypes in this region had negligible frequencies. Nine other regions with selection signatures were PAH-IGF1, TRPC4, GJD4-CCNY, NDST4, NOVA1, GALNT9, the ESRP2-GALR1 region with five genes, the SYCP2-CADH4 with six genes, and the TULP1-KIF21B with 14 genes. Genome-wide association analysis showed that nearly all regions with evidence of selection signature had SNP effects with genome-wide significance (P<10–6) on abdominal fat weight and percentage. The results of this study provide specific gene targets for the control of chicken AFC and a potential model of AFC in human obesity. PMID:22792402

Selection signature analysis implicates the PC1/PCSK1 region for chicken abdominal fat content.

PubMed

Zhang, Hui; Hu, Xiaoxiang; Wang, Zhipeng; Zhang, Yuandan; Wang, Shouzhi; Wang, Ning; Ma, Li; Leng, Li; Wang, Shengwen; Wang, Qigui; Wang, Yuxiang; Tang, Zhiquan; Li, Ning; Da, Yang; Li, Hui

2012-01-01

We conducted a selection signature analysis using the chicken 60k SNP chip in two chicken lines that had been divergently selected for abdominal fat content (AFC) for 11 generations. The selection signature analysis used multiple signals of selection, including long-range allele frequency differences between the lean and fat lines, long-range heterozygosity changes, linkage disequilibrium, haplotype frequencies, and extended haplotype homozygosity. Multiple signals of selection identified ten signatures on chromosomes 1, 2, 4, 5, 11, 15, 20, 26 and Z. The 0.73 Mb PC1/PCSK1 region of the Z chromosome at 55.43-56.16 Mb was the most heavily selected region. This region had 26 SNP markers and seven genes, Mar-03, SLC12A2, FBN2, ERAP1, CAST, PC1/PCSK1 and ELL2, where PC1/PCSK1 are the chicken/human names for the same gene. The lean and fat lines had two main haplotypes with completely opposite SNP alleles for the 26 SNP markers and were virtually line-specific, and had a recombinant haplotype with nearly equal frequency (0.193 and 0.196) in both lines. Other haplotypes in this region had negligible frequencies. Nine other regions with selection signatures were PAH-IGF1, TRPC4, GJD4-CCNY, NDST4, NOVA1, GALNT9, the ESRP2-GALR1 region with five genes, the SYCP2-CADH4 with six genes, and the TULP1-KIF21B with 14 genes. Genome-wide association analysis showed that nearly all regions with evidence of selection signature had SNP effects with genome-wide significance (P<10(-6)) on abdominal fat weight and percentage. The results of this study provide specific gene targets for the control of chicken AFC and a potential model of AFC in human obesity.

Fruit and Juice Epigenetic Signatures Are Associated with Independent Immunoregulatory Pathways.

PubMed

Nicodemus-Johnson, Jessie; Sinnott, Robert A

2017-07-14

Epidemiological evidence strongly suggests that fruit consumption promotes many health benefits. Despite the general consensus that fruit and juice are nutritionally similar, epidemiological results for juice consumption are conflicting. Our objective was to use DNA methylation marks to characterize fruit and juice epigenetic signatures within PBMCs and identify shared and independent signatures associated with these groups. Genome-wide DNA methylation marks (Illumina Human Methylation 450k chip) for 2,148 individuals that participated in the Framingham Offspring exam 8 were analyzed for correlations between fruit or juice consumption using standard linear regression. CpG sites with low P -values ( P < 0.01) were characterized using Gene Set Enrichment Analysis (GSEA), Ingenuity Pathway Analysis (IPA), and epigenetic Functional element Overlap analysis of the Results of Genome Wide Association Study Experiments (eFORGE). Fruit and juice-specific low P -value epigenetic signatures were largely independent. Genes near the fruit-specific epigenetic signature were enriched among pathways associated with antigen presentation and chromosome or telomere maintenance, while the juice-specific epigenetic signature was enriched for proinflammatory pathways. IPA and eFORGE analyses implicate fruit and juice-specific epigenetic signatures in the modulation of macrophage (fruit) and B or T cell (juice) activities. These data suggest a role for epigenetic regulation in fruit and juice-specific health benefits and demonstrate independent associations with distinct immune functions and cell types, suggesting that these groups may not confer the same health benefits. Identification of such differences between foods is the first step toward personalized nutrition and ultimately the improvement of human health and longevity.

Fruit and Juice Epigenetic Signatures Are Associated with Independent Immunoregulatory Pathways

PubMed Central

Nicodemus-Johnson, Jessie; Sinnott, Robert A.

2017-01-01

Epidemiological evidence strongly suggests that fruit consumption promotes many health benefits. Despite the general consensus that fruit and juice are nutritionally similar, epidemiological results for juice consumption are conflicting. Our objective was to use DNA methylation marks to characterize fruit and juice epigenetic signatures within PBMCs and identify shared and independent signatures associated with these groups. Genome-wide DNA methylation marks (Illumina Human Methylation 450k chip) for 2,148 individuals that participated in the Framingham Offspring exam 8 were analyzed for correlations between fruit or juice consumption using standard linear regression. CpG sites with low P-values (P < 0.01) were characterized using Gene Set Enrichment Analysis (GSEA), Ingenuity Pathway Analysis (IPA), and epigenetic Functional element Overlap analysis of the Results of Genome Wide Association Study Experiments (eFORGE). Fruit and juice-specific low P-value epigenetic signatures were largely independent. Genes near the fruit-specific epigenetic signature were enriched among pathways associated with antigen presentation and chromosome or telomere maintenance, while the juice-specific epigenetic signature was enriched for proinflammatory pathways. IPA and eFORGE analyses implicate fruit and juice-specific epigenetic signatures in the modulation of macrophage (fruit) and B or T cell (juice) activities. These data suggest a role for epigenetic regulation in fruit and juice-specific health benefits and demonstrate independent associations with distinct immune functions and cell types, suggesting that these groups may not confer the same health benefits. Identification of such differences between foods is the first step toward personalized nutrition and ultimately the improvement of human health and longevity. PMID:28708104

Multigene signature for predicting prognosis of patients with 1p19q co-deletion diffuse glioma.

PubMed

Hu, Xin; Martinez-Ledesma, Emmanuel; Zheng, Siyuan; Kim, Hoon; Barthel, Floris; Jiang, Tao; Hess, Kenneth R; Verhaak, Roel G W

2017-06-01

Co-deletion of 1p and 19q marks a diffuse glioma subtype associated with relatively favorable overall survival; however, heterogeneous clinical outcomes are observed within this category. We assembled gene expression profiles and sample annotation of 374 glioma patients carrying the 1p/19q co-deletion. We predicted 1p/19q status using gene expression when annotation was missing. A first cohort was randomly split into training (n = 170) and a validation dataset (n = 163). A second validation set consisted of 41 expression profiles. An elastic-net penalized Cox proportional hazards model was applied to build a classifier model through cross-validation within the training dataset. The selected 35-gene signature was used to identify high-risk and low-risk groups in the validation set, which showed significantly different overall survival (P = .00058, log-rank test). For time-to-death events, the high-risk group predicted by the gene signature yielded a hazard ratio of 1.78 (95% confidence interval, 1.02-3.11). The signature was also significantly associated with clinical outcome in the The Cancer Genome Atlas (CGA) IDH-mutant 1p/19q wild-type and IDH-wild-type glioma cohorts. Pathway analysis suggested that high risk was associated with increased acetylation activity and inflammatory response. Tumor purity was found to be significantly decreased in high-risk IDH-mutant with 1p/19q co-deletion gliomas and IDH-wild-type glioblastomas but not in IDH-wild-type lower grade or IDH-mutant, non-co-deleted gliomas. We identified a 35-gene signature that identifies high-risk and low-risk categories of 1p/19q positive glioma patients. We have demonstrated heterogeneity amongst a relatively new glioma subtype and provided a stepping stone towards risk stratification. © The Author(s) 2017. Published by Oxford University Press on behalf of the Society for Neuro-Oncology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Comparing Patterns of Natural Selection across Species Using Selective Signatures

PubMed Central

Shapiro, B. Jesse; Alm, Eric J

2008-01-01

Comparing gene expression profiles over many different conditions has led to insights that were not obvious from single experiments. In the same way, comparing patterns of natural selection across a set of ecologically distinct species may extend what can be learned from individual genome-wide surveys. Toward this end, we show how variation in protein evolutionary rates, after correcting for genome-wide effects such as mutation rate and demographic factors, can be used to estimate the level and types of natural selection acting on genes across different species. We identify unusually rapidly and slowly evolving genes, relative to empirically derived genome-wide and gene family-specific background rates for 744 core protein families in 30 γ-proteobacterial species. We describe the pattern of fast or slow evolution across species as the “selective signature” of a gene. Selective signatures represent a profile of selection across species that is predictive of gene function: pairs of genes with correlated selective signatures are more likely to share the same cellular function, and genes in the same pathway can evolve in concert. For example, glycolysis and phenylalanine metabolism genes evolve rapidly in Idiomarina loihiensis, mirroring an ecological shift in carbon source from sugars to amino acids. In a broader context, our results suggest that the genomic landscape is organized into functional modules even at the level of natural selection, and thus it may be easier than expected to understand the complex evolutionary pressures on a cell. PMID:18266472

Pediatric Crohn disease patients exhibit specific ileal transcriptome and microbiome signature.

PubMed

Haberman, Yael; Tickle, Timothy L; Dexheimer, Phillip J; Kim, Mi-Ok; Tang, Dora; Karns, Rebekah; Baldassano, Robert N; Noe, Joshua D; Rosh, Joel; Markowitz, James; Heyman, Melvin B; Griffiths, Anne M; Crandall, Wallace V; Mack, David R; Baker, Susan S; Huttenhower, Curtis; Keljo, David J; Hyams, Jeffrey S; Kugathasan, Subra; Walters, Thomas D; Aronow, Bruce; Xavier, Ramnik J; Gevers, Dirk; Denson, Lee A

2014-08-01

Interactions between the host and gut microbial community likely contribute to Crohn disease (CD) pathogenesis; however, direct evidence for these interactions at the onset of disease is lacking. Here, we characterized the global pattern of ileal gene expression and the ileal microbial community in 359 treatment-naive pediatric patients with CD, patients with ulcerative colitis (UC), and control individuals. We identified core gene expression profiles and microbial communities in the affected CD ilea that are preserved in the unaffected ilea of patients with colon-only CD but not present in those with UC or control individuals; therefore, this signature is specific to CD and independent of clinical inflammation. An abnormal increase of antimicrobial dual oxidase (DUOX2) expression was detected in association with an expansion of Proteobacteria in both UC and CD, while expression of lipoprotein APOA1 gene was downregulated and associated with CD-specific alterations in Firmicutes. The increased DUOX2 and decreased APOA1 gene expression signature favored oxidative stress and Th1 polarization and was maximally altered in patients with more severe mucosal injury. A regression model that included APOA1 gene expression and microbial abundance more accurately predicted month 6 steroid-free remission than a model using clinical factors alone. These CD-specific host and microbe profiles identify the ileum as the primary inductive site for all forms of CD and may direct prognostic and therapeutic approaches.

Assessing signatures of selection through variation in linkage disequilibrium between taurine and indicine cattle

PubMed Central

2014-01-01

Background Signatures of selection are regions in the genome that have been preferentially increased in frequency and fixed in a population because of their functional importance in specific processes. These regions can be detected because of their lower genetic variability and specific regional linkage disequilibrium (LD) patterns. Methods By comparing the differences in regional LD variation between dairy and beef cattle types, and between indicine and taurine subspecies, we aim at finding signatures of selection for production and adaptation in cattle breeds. The VarLD method was applied to compare the LD variation in the autosomal genome between breeds, including Angus and Brown Swiss, representing taurine breeds, and Nelore and Gir, representing indicine breeds. Genomic regions containing the top 0.01 and 0.1 percentile of signals were characterized using the UMD3.1 Bos taurus genome assembly to identify genes in those regions and compared with previously reported selection signatures and regions with copy number variation. Results For all comparisons, the top 0.01 and 0.1 percentile included 26 and 165 signals and 17 and 125 genes, respectively, including TECRL, BT.23182 or FPPS, CAST, MYOM1, UVRAG and DNAJA1. Conclusions The VarLD method is a powerful tool to identify differences in linkage disequilibrium between cattle populations and putative signatures of selection with potential adaptive and productive importance. PMID:24592996

TransCONFIRM: Identification of a Genetic Signature of Response to Fulvestrant in Advanced Hormone Receptor-Positive Breast Cancer.

PubMed

Jeselsohn, Rinath; Barry, William T; Migliaccio, Ilenia; Biagioni, Chiara; Zhao, Jin; De Tribolet-Hardy, Jonas; Guarducci, Cristina; Bonechi, Martina; Laing, Naomi; Winer, Eric P; Brown, Myles; Leo, Angelo Di; Malorni, Luca

2016-12-01

Fulvestrant is an estrogen receptor (ER) antagonist and an approved treatment for metastatic estrogen receptor-positive (ER + ) breast cancer. With the exception of ER levels, there are no established predictive biomarkers of response to single-agent fulvestrant. We attempted to identify a gene signature of response to fulvestrant in advanced breast cancer. Primary tumor samples from 134 patients enrolled in the phase III CONFIRM study of patients with metastatic ER + breast cancer comparing treatment with either 250 mg or 500 mg fulvestrant were collected for genome-wide transcriptomic analysis. Gene expression profiling was performed using Affymetrix microarrays. An exploratory analysis was performed to identify biologic pathways and new signatures associated with response to fulvestrant. Pathway analysis demonstrated that increased EGF pathway and FOXA1 transcriptional signaling is associated with decreased response to fulvestrant. Using a multivariate Cox model, we identified a novel set of 37 genes with an expression that is independently associated with progression-free survival (PFS). TFAP2C, a known regulator of ER activity, was ranked second in this gene set, and high expression was associated with a decreased response to fulvestrant. The negative predictive value of TFAP2C expression at the protein level was confirmed by IHC. We identified biologic pathways and a novel gene signature in primary ER + breast cancers that predicts for response to treatment in the CONFIRM study. These results suggest potential new therapeutic targets and warrant further validation as predictive biomarkers of fulvestrant treatment in metastatic breast cancer. Clin Cancer Res; 22(23); 5755-64. ©2016 AACR. ©2016 American Association for Cancer Research.

Phylogenomic analysis of UDP glycosyltransferase 1 multigene family in Linum usitatissimum identified genes with varied expression patterns

PubMed Central

2012-01-01

Background The glycosylation process, catalyzed by ubiquitous glycosyltransferase (GT) family enzymes, is a prevalent modification of plant secondary metabolites that regulates various functions such as hormone homeostasis, detoxification of xenobiotics and biosynthesis and storage of secondary metabolites. Flax (Linum usitatissimum L.) is a commercially grown oilseed crop, important because of its essential fatty acids and health promoting lignans. Identification and characterization of UDP glycosyltransferase (UGT) genes from flax could provide valuable basic information about this important gene family and help to explain the seed specific glycosylated metabolite accumulation and other processes in plants. Plant genome sequencing projects are useful to discover complexity within this gene family and also pave way for the development of functional genomics approaches. Results Taking advantage of the newly assembled draft genome sequence of flax, we identified 137 UDP glycosyltransferase (UGT) genes from flax using a conserved signature motif. Phylogenetic analysis of these protein sequences clustered them into 14 major groups (A-N). Expression patterns of these genes were investigated using publicly available expressed sequence tag (EST), microarray data and reverse transcription quantitative real time PCR (RT-qPCR). Seventy-three per cent of these genes (100 out of 137) showed expression evidence in 15 tissues examined and indicated varied expression profiles. The RT-qPCR results of 10 selected genes were also coherent with the digital expression analysis. Interestingly, five duplicated UGT genes were identified, which showed differential expression in various tissues. Of the seven intron loss/gain positions detected, two intron positions were conserved among most of the UGTs, although a clear relationship about the evolution of these genes could not be established. Comparison of the flax UGTs with orthologs from four other sequenced dicot genomes indicated that

Analysis of genomic aberrations and gene expression profiling identifies novel lesions and pathways in myeloproliferative neoplasms

PubMed Central

Rice, K L; Lin, X; Wolniak, K; Ebert, B L; Berkofsky-Fessler, W; Buzzai, M; Sun, Y; Xi, C; Elkin, P; Levine, R; Golub, T; Gilliland, D G; Crispino, J D; Licht, J D; Zhang, W

2011-01-01

Polycythemia vera (PV), essential thrombocythemia and primary myelofibrosis, are myeloproliferative neoplasms (MPNs) with distinct clinical features and are associated with the JAK2V617F mutation. To identify genomic anomalies involved in the pathogenesis of these disorders, we profiled 87 MPN patients using Affymetrix 250K single-nucleotide polymorphism (SNP) arrays. Aberrations affecting chr9 were the most frequently observed and included 9pLOH (n=16), trisomy 9 (n=6) and amplifications of 9p13.3–23.3 (n=1), 9q33.1–34.13 (n=1) and 9q34.13 (n=6). Patients with trisomy 9 were associated with elevated JAK2V617F mutant allele burden, suggesting that gain of chr9 represents an alternative mechanism for increasing JAK2V617F dosage. Gene expression profiling of patients with and without chr9 abnormalities (+9, 9pLOH), identified genes potentially involved in disease pathogenesis including JAK2, STAT5B and MAPK14. We also observed recurrent gains of 1p36.31–36.33 (n=6), 17q21.2–q21.31 (n=5) and 17q25.1–25.3 (n=5) and deletions affecting 18p11.31–11.32 (n=8). Combined SNP and gene expression analysis identified aberrations affecting components of a non-canonical PRC2 complex (EZH1, SUZ12 and JARID2) and genes comprising a ‘HSC signature' (MLLT3, SMARCA2 and PBX1). We show that NFIB, which is amplified in 7/87 MPN patients and upregulated in PV CD34+ cells, protects cells from apoptosis induced by cytokine withdrawal. PMID:22829077

Canonical Genetic Signatures of the Adult Human Brain

PubMed Central

Hawrylycz, Michael; Miller, Jeremy A.; Menon, Vilas; Feng, David; Dolbeare, Tim; Guillozet-Bongaarts, Angela L.; Jegga, Anil G.; Aronow, Bruce J.; Lee, Chang-Kyu; Bernard, Amy; Glasser, Matthew F.; Dierker, Donna L.; Menche, Jörge; Szafer, Aaron; Collman, Forrest; Grange, Pascal; Berman, Kenneth A.; Mihalas, Stefan; Yao, Zizhen; Stewart, Lance; Barabási, Albert-László; Schulkin, Jay; Phillips, John; Ng, Lydia; Dang, Chinh; Haynor, David R.; Jones, Allan; Van Essen, David C.; Koch, Christof; Lein, Ed

2015-01-01

The structure and function of the human brain are highly stereotyped, implying a conserved molecular program responsible for its development, cellular structure, and function. We applied a correlation-based metric of “differential stability” (DS) to assess reproducibility of gene expression patterning across 132 structures in six individual brains, revealing meso-scale genetic organization. The highest DS genes are highly biologically relevant, with enrichment for brain-related biological annotations, disease associations, drug targets, and literature citations. Using high DS genes we identified 32 anatomically diverse and reproducible gene expression signatures, which represent distinct cell types, intracellular components, and/or associations with neurodevelopmental and neurodegenerative disorders. Genes in neuron-associated compared to non-neuronal networks showed higher preservation between human and mouse; however, many diversely-patterned genes displayed dramatic shifts in regulation between species. Finally, highly consistent transcriptional architecture in neocortex is correlated with resting state functional connectivity, suggesting a link between conserved gene expression and functionally relevant circuitry. PMID:26571460

Attenuated Signature-Tagged Mutagenesis Mutants of Brucella melitensis Identified during the Acute Phase of Infection in Mice

PubMed Central

Lestrate, P.; Dricot, A.; Delrue, R.-M.; Lambert, C.; Martinelli, V.; De Bolle, X.; Letesson, J.-J.; Tibor, A.

2003-01-01

For this study, we screened 1,152 signature-tagged mutagenesis mutants of Brucella melitensis 16M in a mouse model of infection and found 36 of them to be attenuated in vivo. Molecular characterization of transposon insertion sites showed that for four mutants, the affected genes were only present in Rhizobiaceae. Another mutant contained a disruption in a gene homologous to mosA, which is involved in rhizopine biosynthesis in some strains of Rhizobium, suggesting that this sugar may be involved in Brucella pathogenicity. A mutant was disrupted in a gene homologous to fliF, a gene potentially coding for the MS ring, a basal component of the flagellar system. Surprisingly, a mutant was affected in the rpoA gene, coding for the essential α-subunit of the RNA polymerase. This disruption leaves a partially functional protein, impaired for the activation of virB transcription, as demonstrated by the absence of induction of the virB promoter in the Tn5::rpoA background. The results presented here highlight the fact that the ability of Brucella to induce pathogenesis shares similarities with the molecular mechanisms used by both Rhizobium and Agrobacterium to colonize their hosts. PMID:14638795

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

Transcriptional profiling of pure fibrolamellar hepatocellular carcinoma reveals an endocrine signature.

PubMed

Malouf, Gabriel G; Job, Sylvie; Paradis, Valérie; Fabre, Monique; Brugières, Laurence; Saintigny, Pierre; Vescovo, Laure; Belghiti, Jacques; Branchereau, Sophie; Faivre, Sandrine; de Reyniès, Aurélien; Raymond, Eric

2014-06-01

Fibrolamellar hepatocellular carcinoma (FLC) is a rare subtype of liver cancer occurring mostly in children and young adults. We have shown that FLC comprises two separate entities: pure (p-FLC) and mixed-FLC (m-FLC), differing in clinical presentation and course. We show that p-FLCs have a distinct gene expression signature different from that of m-FLCs, which have a signature similar to that of classical hepatocellular carcinomas. We found p-FLC profiles to be unique among 263 profiles related to diverse tumoral and nontumoral liver samples. We identified two distinct molecular subgroups of p-FLCs with different outcomes. Pathway analysis of p-FLCs revealed ERBB2 overexpression and an up-regulation of glycolysis, possibly leading to compensatory mitochondrial hyperplasia and oncocytic differentiation. Four of the sixteen genes most significantly overexpressed in p-FLCs were neuroendocrine genes: prohormone convertase 1 (PCSK1); neurotensin; delta/notch-like EGF repeat containing; and calcitonin. PCSK1 overexpression was validated by immunohistochemistry, yielding specific, diffuse staining of the protein throughout the cytoplasm, possibly corresponding to a functional form of this convertase. p-FLCs have a unique transcriptomic signature characterized by the strong expression of specific neuroendocrine genes, suggesting that these tumors may have a cellular origin different from that of HCC. Our data have implications for the use of genomic profiling for diagnosis and selection of targeted therapies in patients with p-FLC. © 2014 by the American Association for the Study of Liver Diseases.

Sample entropy analysis of cervical neoplasia gene-expression signatures

PubMed Central

Botting, Shaleen K; Trzeciakowski, Jerome P; Benoit, Michelle F; Salama, Salama A; Diaz-Arrastia, Concepcion R

2009-01-01

Background We introduce Approximate Entropy as a mathematical method of analysis for microarray data. Approximate entropy is applied here as a method to classify the complex gene expression patterns resultant of a clinical sample set. Since Entropy is a measure of disorder in a system, we believe that by choosing genes which display minimum entropy in normal controls and maximum entropy in the cancerous sample set we will be able to distinguish those genes which display the greatest variability in the cancerous set. Here we describe a method of utilizing Approximate Sample Entropy (ApSE) analysis to identify genes of interest with the highest probability of producing an accurate, predictive, classification model from our data set. Results In the development of a diagnostic gene-expression profile for cervical intraepithelial neoplasia (CIN) and squamous cell carcinoma of the cervix, we identified 208 genes which are unchanging in all normal tissue samples, yet exhibit a random pattern indicative of the genetic instability and heterogeneity of malignant cells. This may be measured in terms of the ApSE when compared to normal tissue. We have validated 10 of these genes on 10 Normal and 20 cancer and CIN3 samples. We report that the predictive value of the sample entropy calculation for these 10 genes of interest is promising (75% sensitivity, 80% specificity for prediction of cervical cancer over CIN3). Conclusion The success of the Approximate Sample Entropy approach in discerning alterations in complexity from biological system with such relatively small sample set, and extracting biologically relevant genes of interest hold great promise. PMID:19232110

Properties of different selection signature statistics and a new strategy for combining them.

PubMed

Ma, Y; Ding, X; Qanbari, S; Weigend, S; Zhang, Q; Simianer, H

2015-11-01

Identifying signatures of recent or ongoing selection is of high relevance in livestock population genomics. From a statistical perspective, determining a proper testing procedure and combining various test statistics is challenging. On the basis of extensive simulations in this study, we discuss the statistical properties of eight different established selection signature statistics. In the considered scenario, we show that a reasonable power to detect selection signatures is achieved with high marker density (>1 SNP/kb) as obtained from sequencing, while rather small sample sizes (~15 diploid individuals) appear to be sufficient. Most selection signature statistics such as composite likelihood ratio and cross population extended haplotype homozogysity have the highest power when fixation of the selected allele is reached, while integrated haplotype score has the highest power when selection is ongoing. We suggest a novel strategy, called de-correlated composite of multiple signals (DCMS) to combine different statistics for detecting selection signatures while accounting for the correlation between the different selection signature statistics. When examined with simulated data, DCMS consistently has a higher power than most of the single statistics and shows a reliable positional resolution. We illustrate the new statistic to the established selective sweep around the lactase gene in human HapMap data providing further evidence of the reliability of this new statistic. Then, we apply it to scan selection signatures in two chicken samples with diverse skin color. Our analysis suggests that a set of well-known genes such as BCO2, MC1R, ASIP and TYR were involved in the divergent selection for this trait.

Identifying sources of nitrogen to Hanalei Bay, Kauai, utilizing the nitrogen isotope signature of macroalgae

USGS Publications Warehouse

Derse, E.; Knee, K.L.; Wankel, Scott D.; Kendall, C.; Berg, C.J.; Paytan, A.

2007-01-01

Sewage effluent, storm runoff, discharge from polluted rivers, and inputs of groundwater have all been suggested as potential sources of land derived nutrients into Hanalei Bay, Kauai. We determined the nitrogen isotopic signatures (??15N) of different nitrate sources to Hanalei Bay along with the isotopic signature recorded by 11 species of macroalgal collected in the Bay. The macroalgae integrate the isotopic signatures of the nitrate sources over time, thus these data along with the nitrate to dissolved inorganic phosphate molar ratios (N:P) of the macroalgae were used to determine the major nitrate source to the bay ecosystem and which of the macro-nutrients is limiting algae growth, respectively. Relatively low ??15N values (average -0.5???) were observed in all algae collected throughout the Bay; implicating fertilizer, rather than domestic sewage, as an important external source of nitrogen to the coastal water around Hanalei. The N:P ratio in the algae compared to the ratio in the Bay waters imply that the Hanalei Bay coastal ecosystem is nitrogen limited and thus, increased nitrogen input may potentially impactthis coastal ecosystem and specifically the coral reefs in the Bay. Identifying the major source of nutrient loading to the Bay is important for risk assessment and potential remediation plans. ?? 2007 American Chemical Society.

Genomic signatures of parasite-driven natural selection in north European Atlantic salmon (Salmo salar).

PubMed

Zueva, Ksenia J; Lumme, Jaakko; Veselov, Alexey E; Kent, Matthew P; Primmer, Craig R

2018-06-01

Understanding the genomic basis of host-parasite adaptation is important for predicting the long-term viability of species and developing successful management practices. However, in wild populations, identifying specific signatures of parasite-driven selection often presents a challenge, as it is difficult to unravel the molecular signatures of selection driven by different, but correlated, environmental factors. Furthermore, separating parasite-mediated selection from similar signatures due to genetic drift and population history can also be difficult. Populations of Atlantic salmon (Salmo salar L.) from northern Europe have pronounced differences in their reactions to the parasitic flatworm Gyrodactylus salaris Malmberg 1957 and are therefore a good model to search for specific genomic regions underlying inter-population differences in pathogen response. We used a dense Atlantic salmon SNP array, along with extensive sampling of 43 salmon populations representing the two G. salaris response extremes (extreme susceptibility vs resistant), to screen the salmon genome for signatures of directional selection while attempting to separate the parasite effect from other factors. After combining the results from two independent genome scan analyses, 57 candidate genes potentially under positive selection were identified, out of which 50 were functionally annotated. This candidate gene set was shown to be functionally enriched for lymph node development, focal adhesion genes and anti-viral response, which suggests that the regulation of both innate and acquired immunity might be an important mechanism for salmon response to G. salaris. Overall, our results offer insights into the apparently complex genetic basis of pathogen susceptibility in salmon and highlight methodological challenges for separating the effects of various environmental factors. Copyright © 2018 Elsevier B.V. All rights reserved.

Molecular Signature for Lymphatic Invasion Associated with Survival of Epithelial Ovarian Cancer.

PubMed

Paik, E Sun; Choi, Hyun Jin; Kim, Tae-Joong; Lee, Jeong-Won; Kim, Byoung-Gie; Bae, Duk-Soo; Choi, Chel Hun

2018-04-01

We aimed to develop molecular classifier that can predict lymphatic invasion and their clinical significance in epithelial ovarian cancer (EOC) patients. We analyzed gene expression (mRNA, methylated DNA) in data from The Cancer Genome Atlas. To identify molecular signatures for lymphatic invasion, we found differentially expressed genes. The performance of classifier was validated by receiver operating characteristics analysis, logistic regression, linear discriminant analysis (LDA), and support vector machine (SVM). We assessed prognostic role of classifier using random survival forest (RSF) model and pathway deregulation score (PDS). For external validation,we analyzed microarray data from 26 EOC samples of Samsung Medical Center and curatedOvarianData database. We identified 21 mRNAs, and seven methylated DNAs from primary EOC tissues that predicted lymphatic invasion and created prognostic models. The classifier predicted lymphatic invasion well, which was validated by logistic regression, LDA, and SVM algorithm (C-index of 0.90, 0.71, and 0.74 for mRNA and C-index of 0.64, 0.68, and 0.69 for DNA methylation). Using RSF model, incorporating molecular data with clinical variables improved prediction of progression-free survival compared with using only clinical variables (p < 0.001 and p=0.008). Similarly, PDS enabled us to classify patients into high-risk and low-risk group, which resulted in survival difference in mRNA profiles (log-rank p-value=0.011). In external validation, gene signature was well correlated with prediction of lymphatic invasion and patients' survival. Molecular signature model predicting lymphatic invasion was well performed and also associated with survival of EOC patients.

mRNA Expression Signatures of Human Skeletal Muscle Atrophy Identify a Natural Compound that Increases Muscle Mass

PubMed Central

Kunkel, Steven D.; Suneja, Manish; Ebert, Scott M.; Bongers, Kale S.; Fox, Daniel K.; Malmberg, Sharon E.; Alipour, Fariborz; Shields, Richard K.; Adams, Christopher M.

2011-01-01

SUMMARY Skeletal muscle atrophy is a common and debilitating condition that lacks a pharmacologic therapy. To develop a potential therapy, we identified 63 mRNAs that were regulated by fasting in both human and mouse muscle, and 29 mRNAs that were regulated by both fasting and spinal cord injury in human muscle. We used these two unbiased mRNA expression signatures of muscle atrophy to query the Connectivity Map, which singled out ursolic acid as a compound whose signature was opposite to those of atrophy-inducing stresses. A natural compound enriched in apples, ursolic acid reduced muscle atrophy and stimulated muscle hypertrophy in mice. It did so by enhancing skeletal muscle insulin/IGF-I signaling, and inhibiting atrophy-associated skeletal muscle mRNA expression. Importantly, ursolic acid’s effects on muscle were accompanied by reductions in adiposity, fasting blood glucose and plasma cholesterol and triglycerides. These findings identify a potential therapy for muscle atrophy and perhaps other metabolic diseases. PMID:21641545

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/

A prospective blood RNA signature for tuberculosis disease risk

PubMed Central

Zak, Daniel E.; Penn-Nicholson, Adam; Scriba, Thomas J.; Thompson, Ethan; Suliman, Sara; Amon, Lynn M.; Mahomed, Hassan; Erasmus, Mzwandile; Whatney, Wendy; Hussey, Gregory D.; Abrahams, Deborah; Kafaar, Fazlin; Hawkridge, Tony; Verver, Suzanne; Hughes, E. Jane; Ota, Martin; Sutherland, Jayne; Howe, Rawleigh; Dockrell, Hazel M.; Boom, W. Henry; Thiel, Bonnie; Ottenhoff, Tom H.M.; Mayanja-Kizza, Harriet; Crampin, Amelia C; Downing, Katrina; Hatherill, Mark; Valvo, Joe; Shankar, Smitha; Parida, Shreemanta K; Kaufmann, Stefan H.E.; Walzl, Gerhard; Aderem, Alan; Hanekom, Willem A.

2016-01-01

Background Identification of blood biomarkers that prospectively predict progression of Mycobacterium tuberculosis infection to tuberculosis disease may lead to interventions that impact the epidemic. Methods Healthy, M. tuberculosis infected South African adolescents were followed for 2 years; blood was collected every 6 months. A prospective signature of risk was derived from whole blood RNA-Sequencing data by comparing participants who ultimately developed active tuberculosis disease (progressors) with those who remained healthy (matched controls). After adaptation to multiplex qRT-PCR, the signature was used to predict tuberculosis disease in untouched adolescent samples and in samples from independent cohorts of South African and Gambian adult progressors and controls. The latter participants were household contacts of adults with active pulmonary tuberculosis disease. Findings Of 6,363 adolescents screened, 46 progressors and 107 matched controls were identified. A 16 gene signature of risk was identified. The signature predicted tuberculosis progression with a sensitivity of 66·1% (95% confidence interval, 63·2–68·9) and a specificity of 80·6% (79·2–82·0) in the 12 months preceding tuberculosis diagnosis. The risk signature was validated in an untouched group of adolescents (p=0·018 for RNA-Seq and p=0·0095 for qRT-PCR) and in the independent South African and Gambian cohorts (p values <0·0001 by qRT-PCR) with a sensitivity of 53·7% (42·6–64·3) and a specificity of 82·8% (76·7–86) in 12 months preceding tuberculosis. Interpretation The whole blood tuberculosis risk signature prospectively identified persons at risk of developing active tuberculosis, opening the possibility for targeted intervention to prevent the disease. Funding Bill and Melinda Gates Foundation, the National Institutes of Health, Aeras, the European Union and the South African Medical Research Council (detail at end of text). PMID:27017310

Gene signatures and expression of miRNAs associated with efficacy of panitumumab in a head and neck cancer phase II trial.

PubMed

Siano, Marco; Espeli, Vittoria; Mach, Nicolas; Bossi, Paolo; Licitra, Lisa; Ghielmini, Michele; Frattini, Milo; Canevari, Silvana; De Cecco, Loris

2018-07-01

Platinum-based chemotherapy plus the anti-EGFR monoclonal antibody (mAb) cetuximab is used to treat recurrent/metastatic (RM) head-neck squamous cell carcinoma (HNSCC). Recently, we defined Cluster3 gene-expression signature as a potential predictor of favorable progression-free survival (PFS) in cetuximab-treated RM-HNSCC patients and predictor of partial metabolic FDG-PET response in an afatinib window-of-opportunity trial. Another anti-EGFR-mAb (panitumumab) was used as the treatment agent in RM-HNSCC patients in the phase II PANI01trial. PANI01 tumor samples were analyzed using functional genomics to explore response predictors to anti-EGFR therapy. Whole-gene expression and real-time PCR analyses were applied to pre-treatment samples from 25 PANI01 patients. Three gene signatures (Cluster3 score, RAS onco-signature, microenvironment score) and seven selected miRNAs were separately analyzed for association with panitumumab efficacy. Cluster3 expression levels had a profile with a significant bimodal separation of samples (P =  3.08 E-13). Higher RAS activation, microenvironment score, and miRNA expression were associated with low-Cluster3 patients. The same biomarkers were separately associated with PFS. Patients with high-Cluster3 had significantly longer PFS than patients with low-Cluster3 (median PFS: 174 versus 51 days; log-rank P = 0.0021). ROC analysis demonstrated accuracy in predicting PFS (AUC = 0.877). Despite differences in clinical settings and anti-EGFR inhibitors used for treatment, response prediction by the Cluster3 signature and selected miRNAs was essentially the same. Translation into a useful clinical assay requires validation in a broader setting. Copyright © 2018 Elsevier Ltd. All rights reserved.

Signatures of Diversifying Selection in European Pig Breeds

PubMed Central

Wilkinson, Samantha; Lu, Zen H.; Megens, Hendrik-Jan; Archibald, Alan L.; Haley, Chris; Jackson, Ian J.; Groenen, Martien A. M.; Crooijmans, Richard P. M. A.; Ogden, Rob; Wiener, Pamela

2013-01-01

Following domestication, livestock breeds have experienced intense selection pressures for the development of desirable traits. This has resulted in a large diversity of breeds that display variation in many phenotypic traits, such as coat colour, muscle composition, early maturity, growth rate, body size, reproduction, and behaviour. To better understand the relationship between genomic composition and phenotypic diversity arising from breed development, the genomes of 13 traditional and commercial European pig breeds were scanned for signatures of diversifying selection using the Porcine60K SNP chip, applying a between-population (differentiation) approach. Signatures of diversifying selection between breeds were found in genomic regions associated with traits related to breed standard criteria, such as coat colour and ear morphology. Amino acid differences in the EDNRB gene appear to be associated with one of these signatures, and variation in the KITLG gene may be associated with another. Other selection signals were found in genomic regions including QTLs and genes associated with production traits such as reproduction, growth, and fat deposition. Some selection signatures were associated with regions showing evidence of introgression from Asian breeds. When the European breeds were compared with wild boar, genomic regions with high levels of differentiation harboured genes related to bone formation, growth, and fat deposition. PMID:23637623

Independent replication of a melanoma subtype gene signature and evaluation of its prognostic value and biological correlates in a population cohort.

PubMed

Nsengimana, Jérémie; Laye, Jon; Filia, Anastasia; Walker, Christy; Jewell, Rosalyn; Van den Oord, Joost J; Wolter, Pascal; Patel, Poulam; Sucker, Antje; Schadendorf, Dirk; Jönsson, Göran B; Bishop, D Timothy; Newton-Bishop, Julia

2015-05-10

Development and validation of robust molecular biomarkers has so far been limited in melanoma research. In this paper we used a large population-based cohort to replicate two published gene signatures for melanoma classification. We assessed the signatures prognostic value and explored their biological significance by correlating them with factors known to be associated with survival (vitamin D) or etiological routes (nevi, sun sensitivity and telomere length). Genomewide microarray gene expressions were profiled in 300 archived tumors (224 primaries, 76 secondaries). The two gene signatures classified up to 96% of our samples and showed strong correlation with melanoma specific survival (P=3 x 10(-4)), Breslow thickness (P=5 x 10(-10)), ulceration (P=9.x10-8) and mitotic rate (P=3 x 10(-7)), adding prognostic value over AJCC stage (adjusted hazard ratio 1.79, 95%CI 1.13-2.83), as previously reported. Furthermore, molecular subtypes were associated with season-adjusted serum vitamin D at diagnosis (P=0.04) and genetically predicted telomere length (P=0.03). Specifically, molecular high-grade tumors were more frequent in patients with lower vitamin D levels whereas high immune tumors came from patients with predicted shorter telomeres. Our data confirm the utility of molecular biomarkers in melanoma prognostic estimation using tiny archived specimens and shed light on biological mechanisms likely to impact on cancer initiation and progression.

KRAS driven expression signature has prognostic power superior to mutation status in non-small cell lung cancer.

PubMed

Nagy, Ádám; Pongor, Lőrinc Sándor; Szabó, András; Santarpia, Mariacarmela; Győrffy, Balázs

2017-02-15

KRAS is the most frequently mutated oncogene in non-small cell lung cancer (NSCLC). However, the prognostic role of KRAS mutation status in NSCLC still remains controversial. We hypothesize that the expression changes of genes affected by KRAS mutation status will have the most prominent effect and could be used as a prognostic signature in lung cancer. We divided NSCLC patients with mutation and RNA-seq data into KRAS mutated and wild type groups. Mann-Whitney test was used to identify genes showing altered expression between these cohorts. Mean expression of the top five genes was designated as a "transcriptomic fingerprint" of the mutation. We evaluated the effect of this signature on clinical outcome in 2,437 NSCLC patients using univariate and multivariate Cox regression analysis. Mutation of KRAS was most common in adenocarcinoma. Mutation status and KRAS expression were not correlated to prognosis. The transcriptomic fingerprint of KRAS include FOXRED2, KRAS, TOP1, PEX3 and ABL2. The KRAS signature had a high prognostic power. Similar results were achieved when using the second and third set of strongest genes. Moreover, all cutoff values delivered significant prognostic power (p < 0.01). The KRAS signature also remained significant (p < 0.01) in a multivariate analysis including age, gender, smoking history and tumor stage. We generated a "surrogate signature" of KRAS mutation status in NSCLC patients by computationally linking genotype and gene expression. We show that secondary effects of a mutation can have a higher prognostic relevance than the primary genetic alteration itself. © 2016 The Authors International Journal of Cancer published by John Wiley & Sons Ltd on behalf of UICC.

Single Molecule Cluster Analysis Identifies Signature Dynamic Conformations along the Splicing Pathway

PubMed Central

Blanco, Mario R.; Martin, Joshua S.; Kahlscheuer, Matthew L.; Krishnan, Ramya; Abelson, John; Laederach, Alain; Walter, Nils G.

2016-01-01

The spliceosome is the dynamic RNA-protein machine responsible for faithfully splicing introns from precursor messenger RNAs (pre-mRNAs). Many of the dynamic processes required for the proper assembly, catalytic activation, and disassembly of the spliceosome as it acts on its pre-mRNA substrate remain poorly understood, a challenge that persists for many biomolecular machines. Here, we developed a fluorescence-based Single Molecule Cluster Analysis (SiMCAn) tool to dissect the manifold conformational dynamics of a pre-mRNA through the splicing cycle. By clustering common dynamic behaviors derived from selectively blocked splicing reactions, SiMCAn was able to identify signature conformations and dynamic behaviors of multiple ATP-dependent intermediates. In addition, it identified a conformation adopted late in splicing by a 3′ splice site mutant, invoking a mechanism for substrate proofreading. SiMCAn presents a novel framework for interpreting complex single molecule behaviors that should prove widely useful for the comprehensive analysis of a plethora of dynamic cellular machines. PMID:26414013

A gene expression signature of RAS pathway dependence predicts response to PI3K and RAS pathway inhibitors and expands the population of RAS pathway activated tumors.

PubMed

Loboda, Andrey; Nebozhyn, Michael; Klinghoffer, Rich; Frazier, Jason; Chastain, Michael; Arthur, William; Roberts, Brian; Zhang, Theresa; Chenard, Melissa; Haines, Brian; Andersen, Jannik; Nagashima, Kumiko; Paweletz, Cloud; Lynch, Bethany; Feldman, Igor; Dai, Hongyue; Huang, Pearl; Watters, James

2010-06-30

Hyperactivation of the Ras signaling pathway is a driver of many cancers, and RAS pathway activation can predict response to targeted therapies. Therefore, optimal methods for measuring Ras pathway activation are critical. The main focus of our work was to develop a gene expression signature that is predictive of RAS pathway dependence. We used the coherent expression of RAS pathway-related genes across multiple datasets to derive a RAS pathway gene expression signature and generate RAS pathway activation scores in pre-clinical cancer models and human tumors. We then related this signature to KRAS mutation status and drug response data in pre-clinical and clinical datasets. The RAS signature score is predictive of KRAS mutation status in lung tumors and cell lines with high (> 90%) sensitivity but relatively low (50%) specificity due to samples that have apparent RAS pathway activation in the absence of a KRAS mutation. In lung and breast cancer cell line panels, the RAS pathway signature score correlates with pMEK and pERK expression, and predicts resistance to AKT inhibition and sensitivity to MEK inhibition within both KRAS mutant and KRAS wild-type groups. The RAS pathway signature is upregulated in breast cancer cell lines that have acquired resistance to AKT inhibition, and is downregulated by inhibition of MEK. In lung cancer cell lines knockdown of KRAS using siRNA demonstrates that the RAS pathway signature is a better measure of dependence on RAS compared to KRAS mutation status. In human tumors, the RAS pathway signature is elevated in ER negative breast tumors and lung adenocarcinomas, and predicts resistance to cetuximab in metastatic colorectal cancer. These data demonstrate that the RAS pathway signature is superior to KRAS mutation status for the prediction of dependence on RAS signaling, can predict response to PI3K and RAS pathway inhibitors, and is likely to have the most clinical utility in lung and breast tumors.

A gene expression signature of RAS pathway dependence predicts response to PI3K and RAS pathway inhibitors and expands the population of RAS pathway activated tumors

PubMed Central

2010-01-01

Background Hyperactivation of the Ras signaling pathway is a driver of many cancers, and RAS pathway activation can predict response to targeted therapies. Therefore, optimal methods for measuring Ras pathway activation are critical. The main focus of our work was to develop a gene expression signature that is predictive of RAS pathway dependence. Methods We used the coherent expression of RAS pathway-related genes across multiple datasets to derive a RAS pathway gene expression signature and generate RAS pathway activation scores in pre-clinical cancer models and human tumors. We then related this signature to KRAS mutation status and drug response data in pre-clinical and clinical datasets. Results The RAS signature score is predictive of KRAS mutation status in lung tumors and cell lines with high (> 90%) sensitivity but relatively low (50%) specificity due to samples that have apparent RAS pathway activation in the absence of a KRAS mutation. In lung and breast cancer cell line panels, the RAS pathway signature score correlates with pMEK and pERK expression, and predicts resistance to AKT inhibition and sensitivity to MEK inhibition within both KRAS mutant and KRAS wild-type groups. The RAS pathway signature is upregulated in breast cancer cell lines that have acquired resistance to AKT inhibition, and is downregulated by inhibition of MEK. In lung cancer cell lines knockdown of KRAS using siRNA demonstrates that the RAS pathway signature is a better measure of dependence on RAS compared to KRAS mutation status. In human tumors, the RAS pathway signature is elevated in ER negative breast tumors and lung adenocarcinomas, and predicts resistance to cetuximab in metastatic colorectal cancer. Conclusions These data demonstrate that the RAS pathway signature is superior to KRAS mutation status for the prediction of dependence on RAS signaling, can predict response to PI3K and RAS pathway inhibitors, and is likely to have the most clinical utility in lung and breast

The thermo-sensitive gene expression signatures of spermatogenesis.

PubMed

Yadav, Santosh K; Pandey, Aastha; Kumar, Lokesh; Devi, Archana; Kushwaha, Bhavana; Vishvkarma, Rahul; Maikhuri, Jagdamba P; Rajender, Singh; Gupta, Gopal

2018-06-02

Spermatogenesis in most mammals (including human and rat) occurs at ~ 3 °C lower than body temperature in a scrotum and fails rapidly at 37 °C inside the abdomen. The present study investigates the heat-sensitive transcriptome and miRNAs in the most vulnerable germ cells (spermatocytes and round spermatids) that are primarily targeted at elevated temperature in a bid to identify novel targets for contraception and/or infertility treatment. Testes of adult male rats subjected to surgical cryptorchidism were obtained at 0, 24, 72 and 120 h post-surgery, followed by isolation of primary spermatocytes and round spermatids and purification to > 90% purity using a combination of trypsin digestion, centrifugal elutriation and density gradient centrifugation techniques. RNA isolated from these cells was sequenced by massive parallel sequencing technique to identify the most-heat sensitive mRNAs and miRNAs. Heat stress altered the expression of a large number of genes by ≥2.0 fold, out of which 594 genes (286↑; 308↓) showed alterations in spermatocytes and 154 genes (105↑; 49↓) showed alterations in spermatids throughout the duration of experiment. 62 heat-sensitive genes were common to both cell types. Similarly, 66 and 60 heat-sensitive miRNAs in spermatocytes and spermatids, respectively, were affected by ≥1.5 fold, out of which 6 were common to both the cell types. The study has identified Acly, selV, SLC16A7(MCT-2), Txnrd1 and Prkar2B as potential heat sensitive targets in germ cells, which may be tightly regulated by heat sensitive miRNAs rno-miR-22-3P, rno-miR-22-5P, rno-miR-129-5P, rno-miR-3560, rno-miR-3560 and rno-miR-466c-5P.

Distinguishing between biochemical and cellular function: Are there peptide signatures for cellular function of proteins?

PubMed

Jain, Shruti; Bhattacharyya, Kausik; Bakshi, Rachit; Narang, Ankita; Brahmachari, Vani

2017-04-01

The genome annotation and identification of gene function depends on conserved biochemical activity. However, in the cell, proteins with the same biochemical function can participate in different cellular pathways and cannot complement one another. Similarly, two proteins of very different biochemical functions are put in the same class of cellular function; for example, the classification of a gene as an oncogene or a tumour suppressor gene is not related to its biochemical function, but is related to its cellular function. We have taken an approach to identify peptide signatures for cellular function in proteins with known biochemical function. ATPases as a test case, we classified ATPases (2360 proteins) and kinases (517 proteins) from the human genome into different cellular function categories such as transcriptional, replicative, and chromatin remodelling proteins. Using publicly available tool, MEME, we identify peptide signatures shared among the members of a given category but not between cellular functional categories; for example, no motif sharing is seen between chromatin remodelling and transporter ATPases, similarly between receptor Serine/Threonine Kinase and Receptor Tyrosine Kinase. There are motifs shared within each category with significant E value and high occurrence. This concept of signature for cellular function was applied to developmental regulators, the polycomb and trithorax proteins which led to the prediction of the role of INO80, a chromatin remodelling protein, in development. This has been experimentally validated earlier for its role in homeotic gene regulation and its interaction with regulatory complexes like the Polycomb and Trithorax complex. Proteins 2017; 85:682-693. © 2016 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

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.

Gene expression profiling in the early phases of DMD: a constant molecular signature characterizes DMD muscle from early postnatal life throughout disease progression.

PubMed

Pescatori, Mario; Broccolini, Aldobrando; Minetti, Carlo; Bertini, Enrico; Bruno, Claudio; D'amico, Adele; Bernardini, Camilla; Mirabella, Massimiliano; Silvestri, Gabriella; Giglio, Vincenzo; Modoni, Anna; Pedemonte, Marina; Tasca, Giorgio; Galluzzi, Giuliana; Mercuri, Eugenio; Tonali, Pietro A; Ricci, Enzo

2007-04-01

Genome-wide gene expression profiling of skeletal muscle from Duchenne muscular dystrophy (DMD) patients has been used to describe muscle tissue alterations in DMD children older than 5 years. By studying the expression profile of 19 patients younger than 2 years, we describe with high resolution the gene expression signature that characterizes DMD muscle during the initial or "presymptomatic" phase of the disease. We show that in the first 2 years of the disease, DMD muscle is already set to express a distinctive gene expression pattern considerably different from the one expressed by normal, age-matched muscle. This "dystrophic" molecular signature is characterized by a coordinate induction of genes involved in the inflammatory response, extracellular matrix (ECM) remodeling and muscle regeneration, and the reduced transcription of those involved in energy metabolism. Despite the lower degree of muscle dysfunction experienced, our younger patients showed abnormal expression of most of the genes reported as differentially expressed in more advanced stages of the disease. By analyzing our patients as a time series, we provide evidence that some genes, including members of three pathways involved in morphogenetic signaling-Wnt, Notch, and BMP-are progressively induced or repressed in the natural history of DMD.

A migration signature and plasma biomarker panel for pancreatic adenocarcinoma.

PubMed

Balasenthil, Seetharaman; Chen, Nanyue; Lott, Steven T; Chen, Jinyun; Carter, Jennifer; Grizzle, William E; Frazier, Marsha L; Sen, Subrata; Killary, Ann McNeill

2011-01-01

Pancreatic ductal adenocarcinoma is a disease of extremely poor prognosis for which there are no reliable markers of asymptomatic disease. To identify pancreatic cancer biomarkers, we focused on a genomic interval proximal to the most common fragile site in the human genome, chromosome 3p12, which undergoes smoking-related breakage, loss of heterozygosity, and homozygous deletion as an early event in many epithelial tumors, including pancreatic cancers. Using a functional genomic approach, we identified a seven-gene panel (TNC, TFPI, TGFBI, SEL-1L, L1CAM, WWTR1, and CDC42BPA) that was differentially expressed across three different expression platforms, including pancreatic tumor/normal samples. In addition, Ingenuity Pathways Analysis (IPA) and literature searches indicated that this seven-gene panel functions in one network associated with cellular movement/morphology/development, indicative of a "migration signature" of the 3p pathway. We tested whether two secreted proteins from this panel, tenascin C (TNC) and tissue factor pathway inhibitor (TFPI), could serve as plasma biomarkers. Plasma ELISA assays for TFPI/TNC resulted in a combined area under the curve (AUC) of 0.88 and, with addition of CA19-9, a combined AUC for the three-gene panel (TNC/TFPI/CA19-9), of 0.99 with 100% specificity at 90% sensitivity and 97.22% sensitivity at 90% specificity. Validation studies using TFPI only in a blinded sample set increased the performance of CA19-9 from an AUC of 0.84 to 0.94 with the two-gene panel. Results identify a novel 3p pathway-associated migration signature and plasma biomarker panel that has utility for discrimination of pancreatic cancer from normal controls and promise for clinical application. ©2010 AACR.

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.

PAM50 gene signatures and breast cancer prognosis with adjuvant anthracycline- and taxane-based chemotherapy: correlative analysis of C9741 (Alliance)

PubMed Central

Liu, Minetta C; Pitcher, Brandelyn N; Mardis, Elaine R; Davies, Sherri R; Friedman, Paula N; Snider, Jacqueline E; Vickery, Tammi L; Reed, Jerry P; DeSchryver, Katherine; Singh, Baljit; Gradishar, William J; Perez, Edith A; Martino, Silvana; Citron, Marc L; Norton, Larry; Winer, Eric P; Hudis, Clifford A; Carey, Lisa A; Bernard, Philip S; Nielsen, Torsten O; Perou, Charles M; Ellis, Matthew J; Barry, William T

2016-01-01

PAM50 intrinsic breast cancer subtypes are prognostic independent of standard clinicopathologic factors. CALGB 9741 demonstrated improved recurrence-free (RFS) and overall survival (OS) with 2-weekly dose-dense (DD) versus 3-weekly therapy. A significant interaction between intrinsic subtypes and DD-therapy benefit was hypothesized. Suitable tumor samples were available from 1,471 (73%) of 2,005 subjects. Multiplexed gene-expression profiling generated the PAM50 subtype call, proliferation score, and risk of recurrence score (ROR-PT) for the evaluable subset of 1,311 treated patients. The interaction between DD-therapy benefit and intrinsic subtype was tested in a Cox proportional hazards model using two-sided alpha=0.05. Additional multivariable Cox models evaluated the proliferation and ROR-PT scores as continuous measures with selected clinical covariates. Improved outcomes for DD therapy in the evaluable subset mirrored results from the complete data set (RFS; hazard ratio=1.20; 95% confidence interval=0.99–1.44) with 12.3-year median follow-up. Intrinsic subtypes were prognostic of RFS (P<0.0001) irrespective of treatment assignment. No subtype-specific treatment effect on RFS was identified (interaction P=0.44). Proliferation and ROR-PT scores were prognostic for RFS (both P<0.0001), but no association with treatment benefit was seen (P=0.14 and 0.59, respectively). Results were similar for OS. The prognostic value of PAM50 intrinsic subtype was greater than estrogen receptor/HER2 immunohistochemistry classification. PAM50 gene signatures were highly prognostic but did not predict for improved outcomes with DD anthracycline- and taxane-based therapy. Clinical validation studies will assess the ability of PAM50 and other gene signatures to stratify patients and individualize treatment based on expected risks of distant recurrence. PMID:28691057

Population effect model identifies gene expression predictors of survival outcomes in lung adenocarcinoma for both Caucasian and Asian patients

PubMed Central

Cai, Guoshuai; Xiao, Feifei; Cheng, Chao; Li, Yafang; Amos, Christopher I.; Whitfield, Michael L.

2017-01-01

Background We analyzed and integrated transcriptome data from two large studies of lung adenocarcinomas on distinct populations. Our goal was to investigate the variable gene expression alterations between paired tumor-normal tissues and prospectively identify those alterations that can reliably predict lung disease related outcomes across populations. Methods We developed a mixed model that combined the paired tumor-normal RNA-seq from two populations. Alterations in gene expression common to both populations were detected and validated in two independent DNA microarray datasets. A 10-gene prognosis signature was developed through a l1 penalized regression approach and its prognostic value was evaluated in a third independent microarray cohort. Results Deregulation of apoptosis pathways and increased expression of cell cycle pathways were identified in tumors of both Caucasian and Asian lung adenocarcinoma patients. We demonstrate that a 10-gene biomarker panel can predict prognosis of lung adenocarcinoma in both Caucasians and Asians. Compared to low risk groups, high risk groups showed significantly shorter overall survival time (Caucasian patients data: HR = 3.63, p-value = 0.007; Asian patients data: HR = 3.25, p-value = 0.001). Conclusions This study uses a statistical framework to detect DEGs between paired tumor and normal tissues that considers variances among patients and ethnicities, which will aid in understanding the common genes and signalling pathways with the largest effect sizes in ethnically diverse cohorts. We propose multifunctional markers for distinguishing tumor from normal tissue and prognosis for both populations studied. PMID:28426704

DiRE: identifying distant regulatory elements of co-expressed genes

PubMed Central

Gotea, Valer; Ovcharenko, Ivan

2008-01-01

Regulation of gene expression in eukaryotic genomes is established through a complex cooperative activity of proximal promoters and distant regulatory elements (REs) such as enhancers, repressors and silencers. We have developed a web server named DiRE, based on the Enhancer Identification (EI) method, for predicting distant regulatory elements in higher eukaryotic genomes, namely for determining their chromosomal location and functional characteristics. The server uses gene co-expression data, comparative genomics and profiles of transcription factor binding sites (TFBSs) to determine TFBS-association signatures that can be used for discriminating specific regulatory functions. DiRE's unique feature is its ability to detect REs outside of proximal promoter regions, as it takes advantage of the full gene locus to conduct the search. DiRE can predict common REs for any set of input genes for which the user has prior knowledge of co-expression, co-function or other biologically meaningful grouping. The server predicts function-specific REs consisting of clusters of specifically-associated TFBSs and it also scores the association of individual transcription factors (TFs) with the biological function shared by the group of input genes. Its integration with the Array2BIO server allows users to start their analysis with raw microarray expression data. The DiRE web server is freely available at http://dire.dcode.org. PMID:18487623

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.

Population genomics of the honey bee reveals strong signatures of positive selection on worker traits.

PubMed

Harpur, Brock A; Kent, Clement F; Molodtsova, Daria; Lebon, Jonathan M D; Alqarni, Abdulaziz S; Owayss, Ayman A; Zayed, Amro

2014-02-18

Most theories used to explain the evolution of eusociality rest upon two key assumptions: mutations affecting the phenotype of sterile workers evolve by positive selection if the resulting traits benefit fertile kin, and that worker traits provide the primary mechanism allowing social insects to adapt to their environment. Despite the common view that positive selection drives phenotypic evolution of workers, we know very little about the prevalence of positive selection acting on the genomes of eusocial insects. We mapped the footprints of positive selection in Apis mellifera through analysis of 40 individual genomes, allowing us to identify thousands of genes and regulatory sequences with signatures of adaptive evolution over multiple timescales. We found Apoidea- and Apis-specific genes to be enriched for signatures of positive selection, indicating that novel genes play a disproportionately large role in adaptive evolution of eusocial insects. Worker-biased proteins have higher signatures of adaptive evolution relative to queen-biased proteins, supporting the view that worker traits are key to adaptation. We also found genes regulating worker division of labor to be enriched for signs of positive selection. Finally, genes associated with worker behavior based on analysis of brain gene expression were highly enriched for adaptive protein and cis-regulatory evolution. Our study highlights the significant contribution of worker phenotypes to adaptive evolution in social insects, and provides a wealth of knowledge on the loci that influence fitness in honey bees.