TCGA2BED: extracting, extending, integrating, and querying The Cancer Genome Atlas.

PubMed

Cumbo, Fabio; Fiscon, Giulia; Ceri, Stefano; Masseroli, Marco; Weitschek, Emanuel

2017-01-03

Data extraction and integration methods are becoming essential to effectively access and take advantage of the huge amounts of heterogeneous genomics and clinical data increasingly available. In this work, we focus on The Cancer Genome Atlas, a comprehensive archive of tumoral data containing the results of high-throughout experiments, mainly Next Generation Sequencing, for more than 30 cancer types. We propose TCGA2BED a software tool to search and retrieve TCGA data, and convert them in the structured BED format for their seamless use and integration. Additionally, it supports the conversion in CSV, GTF, JSON, and XML standard formats. Furthermore, TCGA2BED extends TCGA data with information extracted from other genomic databases (i.e., NCBI Entrez Gene, HGNC, UCSC, and miRBase). We also provide and maintain an automatically updated data repository with publicly available Copy Number Variation, DNA-methylation, DNA-seq, miRNA-seq, and RNA-seq (V1,V2) experimental data of TCGA converted into the BED format, and their associated clinical and biospecimen meta data in attribute-value text format. The availability of the valuable TCGA data in BED format reduces the time spent in taking advantage of them: it is possible to efficiently and effectively deal with huge amounts of cancer genomic data integratively, and to search, retrieve and extend them with additional information. The BED format facilitates the investigators allowing several knowledge discovery analyses on all tumor types in TCGA with the final aim of understanding pathological mechanisms and aiding cancer treatments.

Regulation of Breast Cancer Stem Cell by Tissue Rigidity

DTIC Science & Technology

2015-06-01

analysis. The TCGA breast cancer gene expression data set (TCGA BRCA G4502A_07_3) was downloaded from the UCSC Cancer Genome Browser (https:// genome ...Public Release; Distribution Unlimited The views, opinions and/or findings contained in this report are those of the author(s) and should not be...construed as an official Department of the Army position, policy or decision unless so designated by other documentation. Report Documentation Page Form

CMS: A Web-Based System for Visualization and Analysis of Genome-Wide Methylation Data of Human Cancers

PubMed Central

Huang, Yi-Wen; Roa, Juan C.; Goodfellow, Paul J.; Kizer, E. Lynette; Huang, Tim H. M.; Chen, Yidong

2013-01-01

Background DNA methylation of promoter CpG islands is associated with gene suppression, and its unique genome-wide profiles have been linked to tumor progression. Coupled with high-throughput sequencing technologies, it can now efficiently determine genome-wide methylation profiles in cancer cells. Also, experimental and computational technologies make it possible to find the functional relationship between cancer-specific methylation patterns and their clinicopathological parameters. Methodology/Principal Findings Cancer methylome system (CMS) is a web-based database application designed for the visualization, comparison and statistical analysis of human cancer-specific DNA methylation. Methylation intensities were obtained from MBDCap-sequencing, pre-processed and stored in the database. 191 patient samples (169 tumor and 22 normal specimen) and 41 breast cancer cell-lines are deposited in the database, comprising about 6.6 billion uniquely mapped sequence reads. This provides comprehensive and genome-wide epigenetic portraits of human breast cancer and endometrial cancer to date. Two views are proposed for users to better understand methylation structure at the genomic level or systemic methylation alteration at the gene level. In addition, a variety of annotation tracks are provided to cover genomic information. CMS includes important analytic functions for interpretation of methylation data, such as the detection of differentially methylated regions, statistical calculation of global methylation intensities, multiple gene sets of biologically significant categories, interactivity with UCSC via custom-track data. We also present examples of discoveries utilizing the framework. Conclusions/Significance CMS provides visualization and analytic functions for cancer methylome datasets. A comprehensive collection of datasets, a variety of embedded analytic functions and extensive applications with biological and translational significance make this system powerful

CMS: a web-based system for visualization and analysis of genome-wide methylation data of human cancers.

PubMed

Gu, Fei; Doderer, Mark S; Huang, Yi-Wen; Roa, Juan C; Goodfellow, Paul J; Kizer, E Lynette; Huang, Tim H M; Chen, Yidong

2013-01-01

DNA methylation of promoter CpG islands is associated with gene suppression, and its unique genome-wide profiles have been linked to tumor progression. Coupled with high-throughput sequencing technologies, it can now efficiently determine genome-wide methylation profiles in cancer cells. Also, experimental and computational technologies make it possible to find the functional relationship between cancer-specific methylation patterns and their clinicopathological parameters. Cancer methylome system (CMS) is a web-based database application designed for the visualization, comparison and statistical analysis of human cancer-specific DNA methylation. Methylation intensities were obtained from MBDCap-sequencing, pre-processed and stored in the database. 191 patient samples (169 tumor and 22 normal specimen) and 41 breast cancer cell-lines are deposited in the database, comprising about 6.6 billion uniquely mapped sequence reads. This provides comprehensive and genome-wide epigenetic portraits of human breast cancer and endometrial cancer to date. Two views are proposed for users to better understand methylation structure at the genomic level or systemic methylation alteration at the gene level. In addition, a variety of annotation tracks are provided to cover genomic information. CMS includes important analytic functions for interpretation of methylation data, such as the detection of differentially methylated regions, statistical calculation of global methylation intensities, multiple gene sets of biologically significant categories, interactivity with UCSC via custom-track data. We also present examples of discoveries utilizing the framework. CMS provides visualization and analytic functions for cancer methylome datasets. A comprehensive collection of datasets, a variety of embedded analytic functions and extensive applications with biological and translational significance make this system powerful and unique in cancer methylation research. CMS is freely accessible

Change@ucsc.edu: Managing a Comprehensive Change Effort.

ERIC Educational Resources Information Center

Coate, L. Edwin

This monograph describes how team- and process-oriented change techniques such as Total Quality Management (TQM) and Business Process Reengineering (BPR), were adapted to an academic environment to effect a comprehensive change program at the University of California Santa Cruz (UCSC). The $3 million program, begun in 1993, produced radical…

Center for Cancer Genomics | Office of Cancer Genomics

Cancer.gov

The Center for Cancer Genomics (CCG) was established to unify the National Cancer Institute's activities in cancer genomics, with the goal of advancing genomics research and translating findings into the clinic to improve the precise diagnosis and treatment of cancers. In addition to promoting genomic sequencing approaches, CCG aims to accelerate structural, functional and computational research to explore cancer mechanisms, discover new cancer targets, and develop new therapeutics.

Home - The Cancer Genome Atlas - Cancer Genome - TCGA

Cancer.gov

The Cancer Genome Atlas (TCGA) is a comprehensive and coordinated effort to accelerate our understanding of the molecular basis of cancer through the application of genome analysis technologies, including large-scale genome sequencing.

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

PubMed

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

2014-11-01

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

Determining Epigenetic Targets: A Beginner's Guide to Identifying Genome Functionality Through Database Analysis.

PubMed

Hay, Elizabeth A; Cowie, Philip; MacKenzie, Alasdair

2017-01-01

There can now be little doubt that the cis-regulatory genome represents the largest information source within the human genome essential for health. In addition to containing up to five times more information than the coding genome, the cis-regulatory genome also acts as a major reservoir of disease-associated polymorphic variation. The cis-regulatory genome, which is comprised of enhancers, silencers, promoters, and insulators, also acts as a major functional target for epigenetic modification including DNA methylation and chromatin modifications. These epigenetic modifications impact the ability of cis-regulatory sequences to maintain tissue-specific and inducible expression of genes that preserve health. There has been limited ability to identify and characterize the functional components of this huge and largely misunderstood part of the human genome that, for decades, was ignored as "Junk" DNA. In an attempt to address this deficit, the current chapter will first describe methods of identifying and characterizing functional elements of the cis-regulatory genome at a genome-wide level using databases such as ENCODE, the UCSC browser, and NCBI. We will then explore the databases on the UCSC genome browser, which provides access to DNA methylation and chromatin modification datasets. Finally, we will describe how we can superimpose the huge volume of study data contained in the NCBI archives onto that contained within the UCSC browser in order to glean relevant in vivo study data for any locus within the genome. An ability to access and utilize these information sources will become essential to informing the future design of experiments and subsequent determination of the role of epigenetics in health and disease and will form a critical step in our development of personalized medicine.

GenomeGems: evaluation of genetic variability from deep sequencing data

PubMed Central

2012-01-01

Background Detection of disease-causing mutations using Deep Sequencing technologies possesses great challenges. In particular, organizing the great amount of sequences generated so that mutations, which might possibly be biologically relevant, are easily identified is a difficult task. Yet, for this assignment only limited automatic accessible tools exist. Findings We developed GenomeGems to gap this need by enabling the user to view and compare Single Nucleotide Polymorphisms (SNPs) from multiple datasets and to load the data onto the UCSC Genome Browser for an expanded and familiar visualization. As such, via automatic, clear and accessible presentation of processed Deep Sequencing data, our tool aims to facilitate ranking of genomic SNP calling. GenomeGems runs on a local Personal Computer (PC) and is freely available at http://www.tau.ac.il/~nshomron/GenomeGems. Conclusions GenomeGems enables researchers to identify potential disease-causing SNPs in an efficient manner. This enables rapid turnover of information and leads to further experimental SNP validation. The tool allows the user to compare and visualize SNPs from multiple experiments and to easily load SNP data onto the UCSC Genome browser for further detailed information. PMID:22748151

Office of Cancer Genomics |

Cancer.gov

The mission of the NCI’s Office of Cancer Genomics (OCG) is to enhance the understanding of the molecular mechanisms of cancer, advance and accelerate genomics science and technology development, and efficiently translate the genomics data to improve cancer research, prevention, early detection, diagnosis and treatment.

Systems biology of cancer biomarker detection.

PubMed

Mitra, Sanga; Das, Smarajit; Chakrabarti, Jayprokas

2013-01-01

Cancer systems-biology is an ever-growing area of research due to explosion of data; how to mine these data and extract useful information is the problem. To have an insight on carcinogenesis one need to systematically mine several resources, such as databases, microarray and next-generation sequences. This review encompasses management and analysis of cancer data, databases construction and data deposition, whole transcriptome and genome comparison, analysing results from high throughput experiments to uncover cellular pathways and molecular interactions, and the design of effective algorithms to identify potential biomarkers. Recent technical advances such as ChIP-on-chip, ChIP-seq and RNA-seq can be applied to get epigenetic information transformed into a high-throughput endeavour to which systems biology and bioinformatics are making significant inroads. The data from ENCODE and GENCODE projects available through UCSC genome browser can be considered as benchmark for comparison and meta-analysis. A pipeline for integrating next generation sequencing data, microarray data, and putting them together with the existing database is discussed. The understanding of cancer genomics is changing the way we approach cancer diagnosis and treatment. To give a better understanding of utilizing available resources' we have chosen oral cancer to show how and what kind of analysis can be done. This review is a computational genomic primer that provides a bird's eye view of computational and bioinformatics' tools currently available to perform integrated genomic and system biology analyses of several carcinoma.

Genomic Data Commons | Office of Cancer Genomics

Cancer.gov

The NCI’s Center for Cancer Genomics launches the Genomic Data Commons (GDC), a unified data sharing platform for the cancer research community. The mission of the GDC is to enable data sharing across the entire cancer research community, to ultimately support precision medicine in oncology.

Exploring cancer genomic data from the cancer genome atlas project.

PubMed

Lee, Ju-Seog

2016-11-01

The Cancer Genome Atlas (TCGA) has compiled genomic, epigenomic, and proteomic data from more than 10,000 samples derived from 33 types of cancer, aiming to improve our understanding of the molecular basis of cancer development. Availability of these genome-wide information provides an unprecedented opportunity for uncovering new key regulators of signaling pathways or new roles of pre-existing members in pathways. To take advantage of the advancement, it will be necessary to learn systematic approaches that can help to uncover novel genes reflecting genetic alterations, prognosis, or response to treatments. This minireview describes the updated status of TCGA project and explains how to use TCGA data. [BMB Reports 2016; 49(11): 607-611].

Dana-Farber Cancer Institute | Office of Cancer Genomics

Cancer.gov

Functional Annotation of Cancer Genomes Principal Investigator: William C. Hahn, M.D., Ph.D. The comprehensive characterization of cancer genomes has and will continue to provide an increasingly complete catalog of genetic alterations in specific cancers. However, most epithelial cancers harbor hundreds of genetic alterations as a consequence of genomic instability. Therefore, the functional consequences of the majority of mutations remain unclear.

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

PubMed Central

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

2015-01-01

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

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

PubMed

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

2015-09-01

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

Cancer Genome Anatomy Project | Office of Cancer Genomics

Cancer.gov

The National Cancer Institute (NCI) Cancer Genome Anatomy Project (CGAP) is an online resource designed to provide the research community access to biological tissue characterization data. Request a free copy of the CGAP Website Virtual Tour CD from ocg@mail.nih.gov.

International network of cancer genome projects

PubMed Central

2010-01-01

The International Cancer Genome Consortium (ICGC) was launched to coordinate large-scale cancer genome studies in tumors from 50 different cancer types and/or subtypes that are of clinical and societal importance across the globe. Systematic studies of over 25,000 cancer genomes at the genomic, epigenomic, and transcriptomic levels will reveal the repertoire of oncogenic mutations, uncover traces of the mutagenic influences, define clinically-relevant subtypes for prognosis and therapeutic management, and enable the development of new cancer therapies. PMID:20393554

HAL: a hierarchical format for storing and analyzing multiple genome alignments.

PubMed

Hickey, Glenn; Paten, Benedict; Earl, Dent; Zerbino, Daniel; Haussler, David

2013-05-15

Large multiple genome alignments and inferred ancestral genomes are ideal resources for comparative studies of molecular evolution, and advances in sequencing and computing technology are making them increasingly obtainable. These structures can provide a rich understanding of the genetic relationships between all subsets of species they contain. Current formats for storing genomic alignments, such as XMFA and MAF, are all indexed or ordered using a single reference genome, however, which limits the information that can be queried with respect to other species and clades. This loss of information grows with the number of species under comparison, as well as their phylogenetic distance. We present HAL, a compressed, graph-based hierarchical alignment format for storing multiple genome alignments and ancestral reconstructions. HAL graphs are indexed on all genomes they contain. Furthermore, they are organized phylogenetically, which allows for modular and parallel access to arbitrary subclades without fragmentation because of rearrangements that have occurred in other lineages. HAL graphs can be created or read with a comprehensive C++ API. A set of tools is also provided to perform basic operations, such as importing and exporting data, identifying mutations and coordinate mapping (liftover). All documentation and source code for the HAL API and tools are freely available at http://github.com/glennhickey/hal. hickey@soe.ucsc.edu or haussler@soe.ucsc.edu Supplementary data are available at Bioinformatics online.

Programs | Office of Cancer Genomics

Cancer.gov

OCG facilitates cancer genomics research through a series of highly-focused programs. These programs generate and disseminate genomic data for use by the cancer research community. OCG programs also promote advances in technology-based infrastructure and create valuable experimental reagents and tools. OCG programs encourage collaboration by interconnecting with other genomics and cancer projects in order to accelerate translation of findings into the clinic. Below are OCG’s current, completed, and initiated programs:

The Cancer Genome Atlas Pan-Cancer Analysis Project

PubMed Central

Weinstein, John N.; Collisson, Eric A.; Mills, Gordon B.; Shaw, Kenna M.; Ozenberger, Brad A.; Ellrott, Kyle; Shmulevich, Ilya; Sander, Chris; Stuart, Joshua M.

2014-01-01

Cancer can take hundreds of different forms depending on the location, cell of origin and spectrum of genomic alterations that promote oncogenesis and affect therapeutic response. Although many genomic events with direct phenotypic impact have been identified, much of the complex molecular landscape remains incompletely charted for most cancer lineages. For that reason, The Cancer Genome Atlas (TCGA) Research Network has profiled and analyzed large numbers of human tumours to discover molecular aberrations at the DNA, RNA, protein, and epigenetic levels. The resulting rich data provide a major opportunity to develop an integrated picture of commonalities, differences, and emergent themes across tumour lineages. The Pan-Cancer initiative compares the first twelve tumour types profiled by TCGA. Analysis of the molecular aberrations and their functional roles across tumour types will teach us how to extend therapies effective in one cancer type to others with a similar genomic profile. PMID:24071849

A brief introduction to web-based genome browsers.

PubMed

Wang, Jun; Kong, Lei; Gao, Ge; Luo, Jingchu

2013-03-01

Genome browser provides a graphical interface for users to browse, search, retrieve and analyze genomic sequence and annotation data. Web-based genome browsers can be classified into general genome browsers with multiple species and species-specific genome browsers. In this review, we attempt to give an overview for the main functions and features of web-based genome browsers, covering data visualization, retrieval, analysis and customization. To give a brief introduction to the multiple-species genome browser, we describe the user interface and main functions of the Ensembl and UCSC genome browsers using the human alpha-globin gene cluster as an example. We further use the MSU and the Rice-Map genome browsers to show some special features of species-specific genome browser, taking a rice transcription factor gene OsSPL14 as an example.

Translational Genomics: Practical Applications of the Genomic Revolution in Breast Cancer.

PubMed

Yates, Lucy R; Desmedt, Christine

2017-06-01

The genomic revolution has fundamentally changed our perception of breast cancer. It is now apparent from DNA-based massively parallel sequencing data that at the genomic level, every breast cancer is unique and shaped by the mutational processes to which it was exposed during its lifetime. More than 90 breast cancer driver genes have been identified as recurrently mutated, and many occur at low frequency across the breast cancer population. Certain cancer genes are associated with traditionally defined histologic subtypes, but genomic intertumoral heterogeneity exists even between cancers that appear the same under the microscope. Most breast cancers contain subclonal populations, many of which harbor driver alterations, and subclonal structure is typically remodeled over time, across metastasis and as a consequence of treatment interventions. Genomics is deepening our understanding of breast cancer biology, contributing to an accelerated phase of targeted drug development and providing insights into resistance mechanisms. Genomics is also providing tools necessary to deliver personalized cancer medicine, but a number of challenges must still be addressed. Clin Cancer Res; 23(11); 2630-9. ©2017 AACR See all articles in this CCR Focus section, "Breast Cancer Research: From Base Pairs to Populations." ©2017 American Association for Cancer Research.

Characterizing genomic alterations in cancer by complementary functional associations | Office of Cancer Genomics

Cancer.gov

Systematic efforts to sequence the cancer genome have identified large numbers of mutations and copy number alterations in human cancers. However, elucidating the functional consequences of these variants, and their interactions to drive or maintain oncogenic states, remains a challenge in cancer research. We developed REVEALER, a computational method that identifies combinations of mutually exclusive genomic alterations correlated with functional phenotypes, such as the activation or gene dependency of oncogenic pathways or sensitivity to a drug treatment.

The ISB Cancer Genomics Cloud: A Flexible Cloud-Based Platform for Cancer Genomics Research.

PubMed

Reynolds, Sheila M; Miller, Michael; Lee, Phyliss; Leinonen, Kalle; Paquette, Suzanne M; Rodebaugh, Zack; Hahn, Abigail; Gibbs, David L; Slagel, Joseph; Longabaugh, William J; Dhankani, Varsha; Reyes, Madelyn; Pihl, Todd; Backus, Mark; Bookman, Matthew; Deflaux, Nicole; Bingham, Jonathan; Pot, David; Shmulevich, Ilya

2017-11-01

The ISB Cancer Genomics Cloud (ISB-CGC) is one of three pilot projects funded by the National Cancer Institute to explore new approaches to computing on large cancer datasets in a cloud environment. With a focus on Data as a Service, the ISB-CGC offers multiple avenues for accessing and analyzing The Cancer Genome Atlas, TARGET, and other important references such as GENCODE and COSMIC using the Google Cloud Platform. The open approach allows researchers to choose approaches best suited to the task at hand: from analyzing terabytes of data using complex workflows to developing new analysis methods in common languages such as Python, R, and SQL; to using an interactive web application to create synthetic patient cohorts and to explore the wealth of available genomic data. Links to resources and documentation can be found at www.isb-cgc.org Cancer Res; 77(21); e7-10. ©2017 AACR . ©2017 American Association for Cancer Research.

Contact | Office of Cancer Genomics

Cancer.gov

For more information about the Office of Cancer Genomics, please contact: Office of Cancer Genomics National Cancer Institute 31 Center Drive, 10A07 Bethesda, Maryland 20892-2580 Phone: (240) 781-3280 Fax: (240) 541-4510 Email: ocg@mail.nih.gov *Please note that this site will not function properly in Internet Explorer unless you completely turn off the Compatibility View*

The Pediatric Cancer Genome Project

PubMed Central

Downing, James R; Wilson, Richard K; Zhang, Jinghui; Mardis, Elaine R; Pui, Ching-Hon; Ding, Li; Ley, Timothy J; Evans, William E

2013-01-01

The St. Jude Children’s Research Hospital–Washington University Pediatric Cancer Genome Project (PCGP) is participating in the international effort to identify somatic mutations that drive cancer. These cancer genome sequencing efforts will not only yield an unparalleled view of the altered signaling pathways in cancer but should also identify new targets against which novel therapeutics can be developed. Although these projects are still deep in the phase of generating primary DNA sequence data, important results are emerging and valuable community resources are being generated that should catalyze future cancer research. We describe here the rationale for conducting the PCGP, present some of the early results of this project and discuss the major lessons learned and how these will affect the application of genomic sequencing in the clinic. PMID:22641210

Punctuated Evolution of Prostate Cancer Genomes

PubMed Central

Baca, Sylvan C.; Prandi, Davide; Lawrence, Michael S.; Mosquera, Juan Miguel; Romanel, Alessandro; Drier, Yotam; Park, Kyung; Kitabayashi, Naoki; MacDonald, Theresa Y.; Ghandi, Mahmoud; Van Allen, Eliezer; Kryukov, Gregory V.; Sboner, Andrea; Theurillat, Jean-Philippe; Soong, T. David; Nickerson, Elizabeth; Auclair, Daniel; Tewari, Ashutosh; Beltran, Himisha; Onofrio, Robert C.; Boysen, Gunther; Guiducci, Candace; Barbieri, Christopher E.; Cibulskis, Kristian; Sivachenko, Andrey; Carter, Scott L.; Saksena, Gordon; Voet, Douglas; Ramos, Alex H; Winckler, Wendy; Cipicchio, Michelle; Ardlie, Kristin; Kantoff, Philip W.; Berger, Michael F.; Gabriel, Stacey B.; Golub, Todd R.; Meyerson, Matthew; Lander, Eric S.; Elemento, Olivier; Getz, Gad; Demichelis, Francesca; Rubin, Mark A.; Garraway, Levi A.

2013-01-01

SUMMARY The analysis of exonic DNA from prostate cancers has identified recurrently mutated genes, but the spectrum of genome-wide alterations has not been profiled extensively in this disease. We sequenced the genomes of 57 prostate tumors and matched normal tissues to characterize somatic alterations and to study how they accumulate during oncogenesis and progression. By modeling the genesis of genomic rearrangements, we identified abundant DNA translocations and deletions that arise in a highly interdependent manner. This phenomenon, which we term “chromoplexy”, frequently accounts for the dysregulation of prostate cancer genes and appears to disrupt multiple cancer genes coordinately. Our modeling suggests that chromoplexy may induce considerable genomic derangement over relatively few events in prostate cancer and other neoplasms, supporting a model of punctuated cancer evolution. By characterizing the clonal hierarchy of genomic lesions in prostate tumors, we charted a path of oncogenic events along which chromoplexy may drive prostate carcinogenesis. PMID:23622249

Punctuated evolution of prostate cancer genomes.

PubMed

Baca, Sylvan C; Prandi, Davide; Lawrence, Michael S; Mosquera, Juan Miguel; Romanel, Alessandro; Drier, Yotam; Park, Kyung; Kitabayashi, Naoki; MacDonald, Theresa Y; Ghandi, Mahmoud; Van Allen, Eliezer; Kryukov, Gregory V; Sboner, Andrea; Theurillat, Jean-Philippe; Soong, T David; Nickerson, Elizabeth; Auclair, Daniel; Tewari, Ashutosh; Beltran, Himisha; Onofrio, Robert C; Boysen, Gunther; Guiducci, Candace; Barbieri, Christopher E; Cibulskis, Kristian; Sivachenko, Andrey; Carter, Scott L; Saksena, Gordon; Voet, Douglas; Ramos, Alex H; Winckler, Wendy; Cipicchio, Michelle; Ardlie, Kristin; Kantoff, Philip W; Berger, Michael F; Gabriel, Stacey B; Golub, Todd R; Meyerson, Matthew; Lander, Eric S; Elemento, Olivier; Getz, Gad; Demichelis, Francesca; Rubin, Mark A; Garraway, Levi A

2013-04-25

The analysis of exonic DNA from prostate cancers has identified recurrently mutated genes, but the spectrum of genome-wide alterations has not been profiled extensively in this disease. We sequenced the genomes of 57 prostate tumors and matched normal tissues to characterize somatic alterations and to study how they accumulate during oncogenesis and progression. By modeling the genesis of genomic rearrangements, we identified abundant DNA translocations and deletions that arise in a highly interdependent manner. This phenomenon, which we term "chromoplexy," frequently accounts for the dysregulation of prostate cancer genes and appears to disrupt multiple cancer genes coordinately. Our modeling suggests that chromoplexy may induce considerable genomic derangement over relatively few events in prostate cancer and other neoplasms, supporting a model of punctuated cancer evolution. By characterizing the clonal hierarchy of genomic lesions in prostate tumors, we charted a path of oncogenic events along which chromoplexy may drive prostate carcinogenesis. Copyright © 2013 Elsevier Inc. All rights reserved.

International Cancer Genome Consortium Data Portal--a one-stop shop for cancer genomics data.

PubMed

Zhang, Junjun; Baran, Joachim; Cros, A; Guberman, Jonathan M; Haider, Syed; Hsu, Jack; Liang, Yong; Rivkin, Elena; Wang, Jianxin; Whitty, Brett; Wong-Erasmus, Marie; Yao, Long; Kasprzyk, Arek

2011-01-01

The International Cancer Genome Consortium (ICGC) is a collaborative effort to characterize genomic abnormalities in 50 different cancer types. To make this data available, the ICGC has created the ICGC Data Portal. Powered by the BioMart software, the Data Portal allows each ICGC member institution to manage and maintain its own databases locally, while seamlessly presenting all the data in a single access point for users. The Data Portal currently contains data from 24 cancer projects, including ICGC, The Cancer Genome Atlas (TCGA), Johns Hopkins University, and the Tumor Sequencing Project. It consists of 3478 genomes and 13 cancer types and subtypes. Available open access data types include simple somatic mutations, copy number alterations, structural rearrangements, gene expression, microRNAs, DNA methylation and exon junctions. Additionally, simple germline variations are available as controlled access data. The Data Portal uses a web-based graphical user interface (GUI) to offer researchers multiple ways to quickly and easily search and analyze the available data. The web interface can assist in constructing complicated queries across multiple data sets. Several application programming interfaces are also available for programmatic access. Here we describe the organization, functionality, and capabilities of the ICGC Data Portal.

Breast cancer: The translation of big genomic data to cancer precision medicine.

PubMed

Low, Siew-Kee; Zembutsu, Hitoshi; Nakamura, Yusuke

2018-03-01

Cancer is a complex genetic disease that develops from the accumulation of genomic alterations in which germline variations predispose individuals to cancer and somatic alterations initiate and trigger the progression of cancer. For the past 2 decades, genomic research has advanced remarkably, evolving from single-gene to whole-genome screening by using genome-wide association study and next-generation sequencing that contributes to big genomic data. International collaborative efforts have contributed to curating these data to identify clinically significant alterations that could be used in clinical settings. Focusing on breast cancer, the present review summarizes the identification of genomic alterations with high-throughput screening as well as the use of genomic information in clinical trials that match cancer patients to therapies, which further leads to cancer precision medicine. Furthermore, cancer screening and monitoring were enhanced greatly by the use of liquid biopsies. With the growing data complexity and size, there is much anticipation in exploiting deep machine learning and artificial intelligence to curate integrative "-omics" data to refine the current medical practice to be applied in the near future. © 2017 The Authors. Cancer Science published by John Wiley & Sons Australia, Ltd on behalf of Japanese Cancer Association.

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas. | Office of Cancer Genomics

Cancer.gov

Although the MYC oncogene has been implicated in cancer, a systematic assessment of alterations of MYC, related transcription factors, and co-regulatory proteins, forming the proximal MYC network (PMN), across human cancers is lacking. Using computational approaches, we define genomic and proteomic features associated with MYC and the PMN across the 33 cancers of The Cancer Genome Atlas. Pan-cancer, 28% of all samples had at least one of the MYC paralogs amplified.

Genomic and Epigenomic Alterations in Cancer.

PubMed

Chakravarthi, Balabhadrapatruni V S K; Nepal, Saroj; Varambally, Sooryanarayana

2016-07-01

Multiple genetic and epigenetic events characterize tumor progression and define the identity of the tumors. Advances in high-throughput technologies, like gene expression profiling, next-generation sequencing, proteomics, and metabolomics, have enabled detailed molecular characterization of various tumors. The integration and analyses of these high-throughput data have unraveled many novel molecular aberrations and network alterations in tumors. These molecular alterations include multiple cancer-driving mutations, gene fusions, amplification, deletion, and post-translational modifications, among others. Many of these genomic events are being used in cancer diagnosis, whereas others are therapeutically targeted with small-molecule inhibitors. Multiple genes/enzymes that play a role in DNA and histone modifications are also altered in various cancers, changing the epigenomic landscape during cancer initiation and progression. Apart from protein-coding genes, studies are uncovering the critical regulatory roles played by noncoding RNAs and noncoding regions of the genome during cancer progression. Many of these genomic and epigenetic events function in tandem to drive tumor development and metastasis. Concurrent advances in genome-modulating technologies, like gene silencing and genome editing, are providing ability to understand in detail the process of cancer initiation, progression, and signaling as well as opening up avenues for therapeutic targeting. In this review, we discuss some of the recent advances in cancer genomic and epigenomic research. Copyright © 2016 American Society for Investigative Pathology. Published by Elsevier Inc. All rights reserved.

Genomic Biomarkers for Breast Cancer Risk

PubMed Central

Walsh, Michael F.; Nathanson, Katherine L.; Couch, Fergus J.

2016-01-01

Clinical risk assessment for cancer predisposition includes a three-generation pedigree and physical examination to identify inherited syndromes. Additionally genetic and genomic biomarkers may identify individuals with a constitutional basis for their disease that may not be evident clinically. Genomic biomarker testing may detect molecular variations in single genes, panels of genes, or entire genomes. The strength of evidence for the association of a genomic biomarker with disease risk may be weak or strong. The factors contributing to clinical validity and utility of genomic biomarkers include functional laboratory analyses and genetic epidemiologic evidence. Genomic biomarkers may be further classified as low, moderate or highly penetrant based on the likelihood of disease. Genomic biomarkers for breast cancer are comprised of rare highly penetrant mutations of genes such as BRCA1 or BRCA2, moderately penetrant mutations of genes such as CHEK2, as well as more common genomic variants, including single nucleotide polymorphisms, associated with modest effect sizes. When applied in the context of appropriate counseling and interpretation, identification of genomic biomarkers of inherited risk for breast cancer may decrease morbidity and mortality, allow for definitive prevention through assisted reproduction, and serve as a guide to targeted therapy. PMID:26987529

From cancer genomes to cancer models: bridging the gaps

PubMed Central

Baudot, Anaïs; Real, Francisco X.; Izarzugaza, José M. G.; Valencia, Alfonso

2009-01-01

Cancer genome projects are now being expanded in an attempt to provide complete landscapes of the mutations that exist in tumours. Although the importance of cataloguing genome variations is well recognized, there are obvious difficulties in bridging the gaps between high-throughput resequencing information and the molecular mechanisms of cancer evolution. Here, we describe the current status of the high-throughput genomic technologies, and the current limitations of the associated computational analysis and experimental validation of cancer genetic variants. We emphasize how the current cancer-evolution models will be influenced by the high-throughput approaches, in particular through efforts devoted to monitoring tumour progression, and how, in turn, the integration of data and models will be translated into mechanistic knowledge and clinical applications. PMID:19305388

Genomic instability--an evolving hallmark of cancer.

PubMed

Negrini, Simona; Gorgoulis, Vassilis G; Halazonetis, Thanos D

2010-03-01

Genomic instability is a characteristic of most cancers. In hereditary cancers, genomic instability results from mutations in DNA repair genes and drives cancer development, as predicted by the mutator hypothesis. In sporadic (non-hereditary) cancers the molecular basis of genomic instability remains unclear, but recent high-throughput sequencing studies suggest that mutations in DNA repair genes are infrequent before therapy, arguing against the mutator hypothesis for these cancers. Instead, the mutation patterns of the tumour suppressor TP53 (which encodes p53), ataxia telangiectasia mutated (ATM) and cyclin-dependent kinase inhibitor 2A (CDKN2A; which encodes p16INK4A and p14ARF) support the oncogene-induced DNA replication stress model, which attributes genomic instability and TP53 and ATM mutations to oncogene-induced DNA damage.

The Cancer Genome Atlas Pan-Cancer analysis project.

PubMed

Weinstein, John N; Collisson, Eric A; Mills, Gordon B; Shaw, Kenna R Mills; Ozenberger, Brad A; Ellrott, Kyle; Shmulevich, Ilya; Sander, Chris; Stuart, Joshua M

2013-10-01

The Cancer Genome Atlas (TCGA) Research Network has profiled and analyzed large numbers of human tumors to discover molecular aberrations at the DNA, RNA, protein and epigenetic levels. The resulting rich data provide a major opportunity to develop an integrated picture of commonalities, differences and emergent themes across tumor lineages. The Pan-Cancer initiative compares the first 12 tumor types profiled by TCGA. Analysis of the molecular aberrations and their functional roles across tumor types will teach us how to extend therapies effective in one cancer type to others with a similar genomic profile.

Cell Context Dependent p53 Genome-Wide Binding Patterns and Enrichment at Repeats

DOE PAGES

Botcheva, Krassimira; McCorkle, Sean R.

2014-11-21

The p53 ability to elicit stress specific and cell type specific responses is well recognized, but how that specificity is established remains to be defined. Whether upon activation p53 binds to its genomic targets in a cell type and stress type dependent manner is still an open question. Here we show that the p53 binding to the human genome is selective and cell context-dependent. We mapped the genomic binding sites for the endogenous wild type p53 protein in the human cancer cell line HCT116 and compared them to those we previously determined in the normal cell line IMR90. We reportmore » distinct p53 genome-wide binding landscapes in two different cell lines, analyzed under the same treatment and experimental conditions, using the same ChIP-seq approach. This is evidence for cell context dependent p53 genomic binding. The observed differences affect the p53 binding sites distribution with respect to major genomic and epigenomic elements (promoter regions, CpG islands and repeats). We correlated the high-confidence p53 ChIP-seq peaks positions with the annotated human repeats (UCSC Human Genome Browser) and observed both common and cell line specific trends. In HCT116, the p53 binding was specifically enriched at LINE repeats, compared to IMR90 cells. The p53 genome-wide binding patterns in HCT116 and IMR90 likely reflect the different epigenetic landscapes in these two cell lines, resulting from cancer-associated changes (accumulated in HCT116) superimposed on tissue specific differences (HCT116 has epithelial, while IMR90 has mesenchymal origin). In conclusion, our data support the model for p53 binding to the human genome in a highly selective manner, mobilizing distinct sets of genes, contributing to distinct pathways.« less

Collaborators | Office of Cancer Genomics

Cancer.gov

The TARGET initiative is jointly managed within the National Cancer Institute (NCI) by the Office of Cancer Genomics (OCG)Opens in a New Tab and the Cancer Therapy Evaluation Program (CTEP)Opens in a New Tab.

Dr. Marco Marra: Pioneer and Visionary in Cancer Genomics Research | Office of Cancer Genomics

Cancer.gov

Dr. Marco Marra is a highly distinguished genomics and bioinformatics researcher. He is the Director of Canada’s Michael Smith Genome Sciences Centre at the BC Cancer Agency and holds a faculty position at the University of British Columbia. The Centre is a state-of-the-art sequencing facility in Vancouver, Canada, with a major focus on the study of cancers.  Many of their research projects are undertaken in collaborations with other Canadian and international institutions.

Collaborators | Office of Cancer Genomics

Cancer.gov

The TARGET initiative has been jointly managed within the National Cancer Institute (NCI) by the Office of Cancer Genomics (OCG)Opens in a New Tab and the Cancer Therapy Evaluation Program (CTEP)Opens in a New Tab.

Endometrial and acute myeloid leukemia cancer genomes characterized

Cancer.gov

Two studies from The Cancer Genome Atlas (TCGA) program reveal details about the genomic landscapes of acute myeloid leukemia (AML) and endometrial cancer. Both provide new insights into the molecular underpinnings of these cancers.

Genomic and Functional Approaches to Understanding Cancer Aneuploidy.

PubMed

Taylor, Alison M; Shih, Juliann; Ha, Gavin; Gao, Galen F; Zhang, Xiaoyang; Berger, Ashton C; Schumacher, Steven E; Wang, Chen; Hu, Hai; Liu, Jianfang; Lazar, Alexander J; Cherniack, Andrew D; Beroukhim, Rameen; Meyerson, Matthew

2018-04-09

Aneuploidy, whole chromosome or chromosome arm imbalance, is a near-universal characteristic of human cancers. In 10,522 cancer genomes from The Cancer Genome Atlas, aneuploidy was correlated with TP53 mutation, somatic mutation rate, and expression of proliferation genes. Aneuploidy was anti-correlated with expression of immune signaling genes, due to decreased leukocyte infiltrates in high-aneuploidy samples. Chromosome arm-level alterations show cancer-specific patterns, including loss of chromosome arm 3p in squamous cancers. We applied genome engineering to delete 3p in lung cells, causing decreased proliferation rescued in part by chromosome 3 duplication. This study defines genomic and phenotypic correlates of cancer aneuploidy and provides an experimental approach to study chromosome arm aneuploidy. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

The Cancer Genome Atlas Clinical Explorer: a web and mobile interface for identifying clinical-genomic driver associations.

PubMed

Lee, HoJoon; Palm, Jennifer; Grimes, Susan M; Ji, Hanlee P

2015-10-27

The Cancer Genome Atlas (TCGA) project has generated genomic data sets covering over 20 malignancies. These data provide valuable insights into the underlying genetic and genomic basis of cancer. However, exploring the relationship among TCGA genomic results and clinical phenotype remains a challenge, particularly for individuals lacking formal bioinformatics training. Overcoming this hurdle is an important step toward the wider clinical translation of cancer genomic/proteomic data and implementation of precision cancer medicine. Several websites such as the cBio portal or University of California Santa Cruz genome browser make TCGA data accessible but lack interactive features for querying clinically relevant phenotypic associations with cancer drivers. To enable exploration of the clinical-genomic driver associations from TCGA data, we developed the Cancer Genome Atlas Clinical Explorer. The Cancer Genome Atlas Clinical Explorer interface provides a straightforward platform to query TCGA data using one of the following methods: (1) searching for clinically relevant genes, micro RNAs, and proteins by name, cancer types, or clinical parameters; (2) searching for genomic/proteomic profile changes by clinical parameters in a cancer type; or (3) testing two-hit hypotheses. SQL queries run in the background and results are displayed on our portal in an easy-to-navigate interface according to user's input. To derive these associations, we relied on elastic-net estimates of optimal multiple linear regularized regression and clinical parameters in the space of multiple genomic/proteomic features provided by TCGA data. Moreover, we identified and ranked gene/micro RNA/protein predictors of each clinical parameter for each cancer. The robustness of the results was estimated by bootstrapping. Overall, we identify associations of potential clinical relevance among genes/micro RNAs/proteins using our statistical analysis from 25 cancer types and 18 clinical parameters that

BigWig and BigBed: enabling browsing of large distributed datasets.

PubMed

Kent, W J; Zweig, A S; Barber, G; Hinrichs, A S; Karolchik, D

2010-09-01

BigWig and BigBed files are compressed binary indexed files containing data at several resolutions that allow the high-performance display of next-generation sequencing experiment results in the UCSC Genome Browser. The visualization is implemented using a multi-layered software approach that takes advantage of specific capabilities of web-based protocols and Linux and UNIX operating systems files, R trees and various indexing and compression tricks. As a result, only the data needed to support the current browser view is transmitted rather than the entire file, enabling fast remote access to large distributed data sets. Binaries for the BigWig and BigBed creation and parsing utilities may be downloaded at http://hgdownload.cse.ucsc.edu/admin/exe/linux.x86_64/. Source code for the creation and visualization software is freely available for non-commercial use at http://hgdownload.cse.ucsc.edu/admin/jksrc.zip, implemented in C and supported on Linux. The UCSC Genome Browser is available at http://genome.ucsc.edu.

The future of clinical cancer genomics.

PubMed

Offit, Kenneth

2016-10-01

The current and future applications of genomics to the practice of preventive oncology are being impacted by a number of challenges. These include rapid advances in genomic science and technology that allow massively parallel sequencing of both tumors and the germline, a diminishing of intellectual property restrictions on diagnostic genetic applications, rapid expansion of access to the internet which includes mobile access to both genomic data and tools to communicate and interpret genetic data in a medical context, the expansion of for-profit diagnostic companies seeking to monetize genetic information, and a simultaneous effort to depict medical professionals as barriers to rather than facilitators of understanding one's genome. Addressing each of these issues will be required to bring "personalized" germline genomics to cancer prevention and care. A profound future challenge will be whether clinical cancer genomics will be "de-medicalized" by commercial interests and their advocates, or whether the future course of this field can be modulated in a responsible way that protects the public health while implementing powerful new medical tools for cancer prevention and early detection. Copyright © 2016. Published by Elsevier Inc.

WhopGenome: high-speed access to whole-genome variation and sequence data in R.

PubMed

Wittelsbürger, Ulrich; Pfeifer, Bastian; Lercher, Martin J

2015-02-01

The statistical programming language R has become a de facto standard for the analysis of many types of biological data, and is well suited for the rapid development of new algorithms. However, variant call data from population-scale resequencing projects are typically too large to be read and processed efficiently with R's built-in I/O capabilities. WhopGenome can efficiently read whole-genome variation data stored in the widely used variant call format (VCF) file format into several R data types. VCF files can be accessed either on local hard drives or on remote servers. WhopGenome can associate variants with annotations such as those available from the UCSC genome browser, and can accelerate the reading process by filtering loci according to user-defined criteria. WhopGenome can also read other Tabix-indexed files and create indices to allow fast selective access to FASTA-formatted sequence files. The WhopGenome R package is available on CRAN at http://cran.r-project.org/web/packages/WhopGenome/. A Bioconductor package has been submitted. lercher@cs.uni-duesseldorf.de. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Genome-wide identification of significant aberrations in cancer genome.

PubMed

Yuan, Xiguo; Yu, Guoqiang; Hou, Xuchu; Shih, Ie-Ming; Clarke, Robert; Zhang, Junying; Hoffman, Eric P; Wang, Roger R; Zhang, Zhen; Wang, Yue

2012-07-27

Somatic Copy Number Alterations (CNAs) in human genomes are present in almost all human cancers. Systematic efforts to characterize such structural variants must effectively distinguish significant consensus events from random background aberrations. Here we introduce Significant Aberration in Cancer (SAIC), a new method for characterizing and assessing the statistical significance of recurrent CNA units. Three main features of SAIC include: (1) exploiting the intrinsic correlation among consecutive probes to assign a score to each CNA unit instead of single probes; (2) performing permutations on CNA units that preserve correlations inherent in the copy number data; and (3) iteratively detecting Significant Copy Number Aberrations (SCAs) and estimating an unbiased null distribution by applying an SCA-exclusive permutation scheme. We test and compare the performance of SAIC against four peer methods (GISTIC, STAC, KC-SMART, CMDS) on a large number of simulation datasets. Experimental results show that SAIC outperforms peer methods in terms of larger area under the Receiver Operating Characteristics curve and increased detection power. We then apply SAIC to analyze structural genomic aberrations acquired in four real cancer genome-wide copy number data sets (ovarian cancer, metastatic prostate cancer, lung adenocarcinoma, glioblastoma). When compared with previously reported results, SAIC successfully identifies most SCAs known to be of biological significance and associated with oncogenes (e.g., KRAS, CCNE1, and MYC) or tumor suppressor genes (e.g., CDKN2A/B). Furthermore, SAIC identifies a number of novel SCAs in these copy number data that encompass tumor related genes and may warrant further studies. Supported by a well-grounded theoretical framework, SAIC has been developed and used to identify SCAs in various cancer copy number data sets, providing useful information to study the landscape of cancer genomes. Open-source and platform-independent SAIC software is

Functional precision cancer medicine-moving beyond pure genomics.

PubMed

Letai, Anthony

2017-09-08

The essential job of precision medicine is to match the right drugs to the right patients. In cancer, precision medicine has been nearly synonymous with genomics. However, sobering recent studies have generally shown that most patients with cancer who receive genomic testing do not benefit from a genomic precision medicine strategy. Although some call the entire project of precision cancer medicine into question, I suggest instead that the tools employed must be broadened. Instead of relying exclusively on big data measurements of initial conditions, we should also acquire highly actionable functional information by perturbing-for example, with cancer therapies-viable primary tumor cells from patients with cancer.

Measuring cancer evolution from the genome.

PubMed

Graham, Trevor A; Sottoriva, Andrea

2017-01-01

The temporal dynamics of cancer evolution remain elusive, because it is impractical to longitudinally observe cancers unperturbed by treatment. Consequently, our knowledge of how cancers grow largely derives from inferences made from a single point in time - the endpoint in the cancer's evolution, when it is removed from the body and studied in the laboratory. Fortuitously however, the cancer genome, by virtue of ongoing mutations that uniquely mark clonal lineages within the tumour, provides a rich, yet surreptitious, record of cancer development. In this review, we describe how a cancer's genome can be analysed to reveal the temporal history of mutation and selection, and discuss why both selective and neutral evolution feature prominently in carcinogenesis. We argue that selection in cancer can only be properly studied once we have some understanding of what the absence of selection looks like. We review the data describing punctuated evolution in cancer, and reason that punctuated phenotype evolution is consistent with both gradual and punctuated genome evolution. We conclude that, to map and predict evolutionary trajectories during carcinogenesis, it is critical to better understand the relationship between genotype change and phenotype change. Copyright © 2016 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd. Copyright © 2016 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Genomic Datasets for Cancer Research

Cancer.gov

A variety of datasets from genome-wide association studies of cancer and other genotype-phenotype studies, including sequencing and molecular diagnostic assays, are available to approved investigators through the Extramural National Cancer Institute Data Access Committee.

Break Breast Cancer Addiction by CRISPR/Cas9 Genome Editing.

PubMed

Yang, Haitao; Jaeger, MariaLynn; Walker, Averi; Wei, Daniel; Leiker, Katie; Weitao, Tao

2018-01-01

Breast cancer is the leading diagnosed cancer for women globally. Evolution of breast cancer in tumorigenesis, metastasis and treatment resistance appears to be driven by the aberrant gene expression and protein degradation encoded by the cancer genomes. The uncontrolled cancer growth relies on these cellular events, thus constituting the cancerous programs and rendering the addiction towards them. These programs are likely the potential anticancer biomarkers for Personalized Medicine of breast cancer. This review intends to delineate the impact of the CRSPR/Cas-mediated genome editing in identification and validation of these anticancer biomarkers. It reviews the progress in three aspects of CRISPR/Cas9-mediated editing of the breast cancer genomes: Somatic genome editing, transcription and protein degradation addictions.

Applications of Support Vector Machine (SVM) Learning in Cancer Genomics

PubMed Central

HUANG, SHUJUN; CAI, NIANGUANG; PACHECO, PEDRO PENZUTI; NARANDES, SHAVIRA; WANG, YANG; XU, WAYNE

2017-01-01

Machine learning with maximization (support) of separating margin (vector), called support vector machine (SVM) learning, is a powerful classification tool that has been used for cancer genomic classification or subtyping. Today, as advancements in high-throughput technologies lead to production of large amounts of genomic and epigenomic data, the classification feature of SVMs is expanding its use in cancer genomics, leading to the discovery of new biomarkers, new drug targets, and a better understanding of cancer driver genes. Herein we reviewed the recent progress of SVMs in cancer genomic studies. We intend to comprehend the strength of the SVM learning and its future perspective in cancer genomic applications. PMID:29275361

Cancer vulnerabilities unveiled by genomic loss

PubMed Central

Nijhawan, Deepak; Zack, Travis I.; Ren, Yin; Strickland, Matthew R.; Lamothe, Rebecca; Schumacher, Steven E.; Tsherniak, Aviad; Besche, Henrike C.; Rosenbluh, Joseph; Shehata, Shyemaa; Cowley, Glenn S.; Weir, Barbara A.; Goldberg, Alfred L.; Mesirov, Jill P.; Root, David E.; Bhatia, Sangeeta N.; Beroukhim, Rameen; Hahn, William C.

2012-01-01

Summary Due to genome instability, most cancers exhibit loss of regions containing tumor suppressor genes and collateral loss of other genes. To identify cancer-specific vulnerabilities that are the result of copy-number losses, we performed integrated analyses of genome-wide copy-number and RNAi profiles and identified 56 genes for which gene suppression specifically inhibited the proliferation of cells harboring partial copy-number loss of that gene. These CYCLOPS (Copy-number alterations Yielding Cancer Liabilities Owing to Partial losS) genes are enriched for spliceosome, proteasome and ribosome components. One CYCLOPS gene, PSMC2, encodes an essential member of the 19S proteasome. Normal cells express excess PSMC2, which resides in a complex with PSMC1, PSMD2, and PSMD5 and acts as a reservoir protecting cells from PSMC2 suppression. Cells harboring partial PSMC2 copy-number loss lack this complex and die after PSMC2 suppression. These observations define a distinct class of cancer-specific liabilities resulting from genome instability. PMID:22901813

Cancer genomics: technology, discovery, and translation.

PubMed

Tran, Ben; Dancey, Janet E; Kamel-Reid, Suzanne; McPherson, John D; Bedard, Philippe L; Brown, Andrew M K; Zhang, Tong; Shaw, Patricia; Onetto, Nicole; Stein, Lincoln; Hudson, Thomas J; Neel, Benjamin G; Siu, Lillian L

2012-02-20

In recent years, the increasing awareness that somatic mutations and other genetic aberrations drive human malignancies has led us within reach of personalized cancer medicine (PCM). The implementation of PCM is based on the following premises: genetic aberrations exist in human malignancies; a subset of these aberrations drive oncogenesis and tumor biology; these aberrations are actionable (defined as having the potential to affect management recommendations based on diagnostic, prognostic, and/or predictive implications); and there are highly specific anticancer agents available that effectively modulate these targets. This article highlights the technology underlying cancer genomics and examines the early results of genome sequencing and the challenges met in the discovery of new genetic aberrations. Finally, drawing from experiences gained in a feasibility study of somatic mutation genotyping and targeted exome sequencing led by Princess Margaret Hospital-University Health Network and the Ontario Institute for Cancer Research, the processes, challenges, and issues involved in the translation of cancer genomics to the clinic are discussed.

Cancer Genomic Resources and Present Needs in the Latin American Region.

PubMed

Torres, Ángela; Oliver, Javier; Frecha, Cecilia; Montealegre, Ana Lorena; Quezada-Urbán, Rosalía; Díaz-Velásquez, Clara Estela; Vaca-Paniagua, Felipe; Perdomo, Sandra

2017-01-01

In Latin America (LA), cancer is the second leading cause of death, and little is known about the capacities and needs for the development of research in the field of cancer genomics. In order to evaluate the current capacity for and development of cancer genomics in LA, we collected the available information on genomics, including the number of next-generation sequencing (NGS) platforms, the number of cancer research institutions and research groups, publications in the last 10 years, educational programs, and related national cancer control policies. Currently, there are 221 NGS platforms and 118 research groups in LA developing cancer genomics projects. A total of 272 articles in the field of cancer genetics/genomics were published by authors affiliated to Latin American institutions. Educational programs in genomics are scarce, almost exclusive of graduate programs, and only few are concerning cancer. Only 14 countries have national cancer control plans, but all of them consider secondary prevention strategies for early diagnosis, opportune treatment, and decreasing mortality, where genomic analyses could be implemented. Despite recent advances in introducing knowledge about cancer genomics and its application to LA, the region lacks development of integrated genomic research projects, improved use of NGS platforms, implementation of associated educational programs, and health policies that could have an impact on cancer care. © 2017 S. Karger AG, Basel.

Childhood Cancer Genomics Gaps and Opportunities - Workshop Summary

Cancer.gov

NCI convened a workshop of representative research teams that have been leaders in defining the genomic landscape of childhood cancers to discuss the influence of genomic discoveries on the future of childhood cancer research.

Characterizing genomic alterations in cancer by complementary functional associations.

PubMed

Kim, Jong Wook; Botvinnik, Olga B; Abudayyeh, Omar; Birger, Chet; Rosenbluh, Joseph; Shrestha, Yashaswi; Abazeed, Mohamed E; Hammerman, Peter S; DiCara, Daniel; Konieczkowski, David J; Johannessen, Cory M; Liberzon, Arthur; Alizad-Rahvar, Amir Reza; Alexe, Gabriela; Aguirre, Andrew; Ghandi, Mahmoud; Greulich, Heidi; Vazquez, Francisca; Weir, Barbara A; Van Allen, Eliezer M; Tsherniak, Aviad; Shao, Diane D; Zack, Travis I; Noble, Michael; Getz, Gad; Beroukhim, Rameen; Garraway, Levi A; Ardakani, Masoud; Romualdi, Chiara; Sales, Gabriele; Barbie, David A; Boehm, Jesse S; Hahn, William C; Mesirov, Jill P; Tamayo, Pablo

2016-05-01

Systematic efforts to sequence the cancer genome have identified large numbers of mutations and copy number alterations in human cancers. However, elucidating the functional consequences of these variants, and their interactions to drive or maintain oncogenic states, remains a challenge in cancer research. We developed REVEALER, a computational method that identifies combinations of mutually exclusive genomic alterations correlated with functional phenotypes, such as the activation or gene dependency of oncogenic pathways or sensitivity to a drug treatment. We used REVEALER to uncover complementary genomic alterations associated with the transcriptional activation of β-catenin and NRF2, MEK-inhibitor sensitivity, and KRAS dependency. REVEALER successfully identified both known and new associations, demonstrating the power of combining functional profiles with extensive characterization of genomic alterations in cancer genomes.

Cancer Genome Anatomy Project (CGAP) | Office of Cancer Genomics

Cancer.gov

CGAP generated a wide range of genomics data on cancerous cells that are accessible through easy-to-use online tools. Researchers, educators, and students can find "in silico" answers to biological questions through the CGAP website. Request a free copy of the CGAP Website Virtual Tour CD from ocg@mail.nih.gov to learn how to navigate the website.

Break Breast Cancer Addiction by CRISPR/Cas9 Genome Editing

PubMed Central

Yang, Haitao; Jaeger, MariaLynn; Walker, Averi; Wei, Daniel; Leiker, Katie; Weitao, Tao

2018-01-01

Breast cancer is the leading diagnosed cancer for women globally. Evolution of breast cancer in tumorigenesis, metastasis and treatment resistance appears to be driven by the aberrant gene expression and protein degradation encoded by the cancer genomes. The uncontrolled cancer growth relies on these cellular events, thus constituting the cancerous programs and rendering the addiction towards them. These programs are likely the potential anticancer biomarkers for Personalized Medicine of breast cancer. This review intends to delineate the impact of the CRSPR/Cas-mediated genome editing in identification and validation of these anticancer biomarkers. It reviews the progress in three aspects of CRISPR/Cas9-mediated editing of the breast cancer genomes: Somatic genome editing, transcription and protein degradation addictions. PMID:29344267

Overview | Office of Cancer Genomics

Cancer.gov

The Human Cancer Model Initiative (HCMI) is an international consortium that is generating novel human tumor-derived culture models with associated genomic and clinical data. The HCMI consortium includes the US-National Cancer Institute, part of the National Institutes of Health, Cancer Research UK, foundation Hubrecht Organoid Technology, and Wellcome Sanger Institute. The goal of HCMI is to create up to one thousand cancer models from patient tumors.

Applications of Support Vector Machine (SVM) Learning in Cancer Genomics.

PubMed

Huang, Shujun; Cai, Nianguang; Pacheco, Pedro Penzuti; Narrandes, Shavira; Wang, Yang; Xu, Wayne

2018-01-01

Machine learning with maximization (support) of separating margin (vector), called support vector machine (SVM) learning, is a powerful classification tool that has been used for cancer genomic classification or subtyping. Today, as advancements in high-throughput technologies lead to production of large amounts of genomic and epigenomic data, the classification feature of SVMs is expanding its use in cancer genomics, leading to the discovery of new biomarkers, new drug targets, and a better understanding of cancer driver genes. Herein we reviewed the recent progress of SVMs in cancer genomic studies. We intend to comprehend the strength of the SVM learning and its future perspective in cancer genomic applications. Copyright© 2018, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.

TCGA study identifies genomic features of cervical cancer

Cancer.gov

Investigators with The Cancer Genome Atlas (TCGA) Research Network have identified novel genomic and molecular characteristics of cervical cancer that will aid in subclassification of the disease and may help target therapies that are most appropriate for each patient.

Human Cancer Models Initiative | Office of Cancer Genomics

Cancer.gov

The Human Cancer Models Initiative (HCMI) is an international consortium that is generating novel human tumor-derived culture models, which are annotated with genomic and clinical data. In an effort to advance cancer research and more fully understand how in vitro findings are related to clinical biology, HCMI-developed models and related data will be available as a community resource for cancer and other research.

Human Cancer Models Initiative | Office of Cancer Genomics

Cancer.gov

The Human Cancer Models Initiative (HCMI) is an international consortium that is generating novel human tumor-derived culture models, which are annotated with genomic and clinical data. In an effort to advance cancer research and more fully understand how in vitro findings are related to clinical biology, HCMI-developed models and related data will be available as a community resource for cancer research.

Cancer 2015: a longitudinal whole-of-system study of genomic cancer medicine.

PubMed

Thomas, David M; Fox, Stephen; Lorgelly, Paula K; Ashley, David; Richardson, Gary; Lipton, Lara; Parisot, John P; Lucas, Mark; McNeil, John; Wright, Michael

2015-12-01

Genomic cancer medicine promises revolutionary change in oncology. The impacts of 'personalized medicine', based upon a molecular classification of cancer and linked to targeted therapies, will extend from individual patient outcomes to the health economy at large. To address the 'whole-of-system' impact of genomic cancer medicine, we have established a prospective cohort of patients with newly diagnosed cancer in the state of Victoria, Australia, about whom we have collected a broad range of clinical, demographic, molecular, and patient-reported data, as well as data on health resource utilization. Our goal is to create a model for investigating public investment in genomic medicine that maximizes the cost:benefit ratio for the Australian community at large. Copyright © 2015 Elsevier Ltd. All rights reserved.

GENCODE: the reference human genome annotation for The ENCODE Project.

PubMed

Harrow, Jennifer; Frankish, Adam; Gonzalez, Jose M; Tapanari, Electra; Diekhans, Mark; Kokocinski, Felix; Aken, Bronwen L; Barrell, Daniel; Zadissa, Amonida; Searle, Stephen; Barnes, If; Bignell, Alexandra; Boychenko, Veronika; Hunt, Toby; Kay, Mike; Mukherjee, Gaurab; Rajan, Jeena; Despacio-Reyes, Gloria; Saunders, Gary; Steward, Charles; Harte, Rachel; Lin, Michael; Howald, Cédric; Tanzer, Andrea; Derrien, Thomas; Chrast, Jacqueline; Walters, Nathalie; Balasubramanian, Suganthi; Pei, Baikang; Tress, Michael; Rodriguez, Jose Manuel; Ezkurdia, Iakes; van Baren, Jeltje; Brent, Michael; Haussler, David; Kellis, Manolis; Valencia, Alfonso; Reymond, Alexandre; Gerstein, Mark; Guigó, Roderic; Hubbard, Tim J

2012-09-01

The GENCODE Consortium aims to identify all gene features in the human genome using a combination of computational analysis, manual annotation, and experimental validation. Since the first public release of this annotation data set, few new protein-coding loci have been added, yet the number of alternative splicing transcripts annotated has steadily increased. The GENCODE 7 release contains 20,687 protein-coding and 9640 long noncoding RNA loci and has 33,977 coding transcripts not represented in UCSC genes and RefSeq. It also has the most comprehensive annotation of long noncoding RNA (lncRNA) loci publicly available with the predominant transcript form consisting of two exons. We have examined the completeness of the transcript annotation and found that 35% of transcriptional start sites are supported by CAGE clusters and 62% of protein-coding genes have annotated polyA sites. Over one-third of GENCODE protein-coding genes are supported by peptide hits derived from mass spectrometry spectra submitted to Peptide Atlas. New models derived from the Illumina Body Map 2.0 RNA-seq data identify 3689 new loci not currently in GENCODE, of which 3127 consist of two exon models indicating that they are possibly unannotated long noncoding loci. GENCODE 7 is publicly available from gencodegenes.org and via the Ensembl and UCSC Genome Browsers.

Identification of coding and non-coding mutational hotspots in cancer genomes.

PubMed

Piraino, Scott W; Furney, Simon J

2017-01-05

The identification of mutations that play a causal role in tumour development, so called "driver" mutations, is of critical importance for understanding how cancers form and how they might be treated. Several large cancer sequencing projects have identified genes that are recurrently mutated in cancer patients, suggesting a role in tumourigenesis. While the landscape of coding drivers has been extensively studied and many of the most prominent driver genes are well characterised, comparatively less is known about the role of mutations in the non-coding regions of the genome in cancer development. The continuing fall in genome sequencing costs has resulted in a concomitant increase in the number of cancer whole genome sequences being produced, facilitating systematic interrogation of both the coding and non-coding regions of cancer genomes. To examine the mutational landscapes of tumour genomes we have developed a novel method to identify mutational hotspots in tumour genomes using both mutational data and information on evolutionary conservation. We have applied our methodology to over 1300 whole cancer genomes and show that it identifies prominent coding and non-coding regions that are known or highly suspected to play a role in cancer. Importantly, we applied our method to the entire genome, rather than relying on predefined annotations (e.g. promoter regions) and we highlight recurrently mutated regions that may have resulted from increased exposure to mutational processes rather than selection, some of which have been identified previously as targets of selection. Finally, we implicate several pan-cancer and cancer-specific candidate non-coding regions, which could be involved in tumourigenesis. We have developed a framework to identify mutational hotspots in cancer genomes, which is applicable to the entire genome. This framework identifies known and novel coding and non-coding mutional hotspots and can be used to differentiate candidate driver regions from

Pattern Analysis and Decision Support for Cancer through Clinico-Genomic Profiles

NASA Astrophysics Data System (ADS)

Exarchos, Themis P.; Giannakeas, Nikolaos; Goletsis, Yorgos; Papaloukas, Costas; Fotiadis, Dimitrios I.

Advances in genome technology are playing a growing role in medicine and healthcare. With the development of new technologies and opportunities for large-scale analysis of the genome, genomic data have a clear impact on medicine. Cancer prognostics and therapeutics are among the first major test cases for genomic medicine, given that all types of cancer are related with genomic instability. In this paper we present a novel system for pattern analysis and decision support in cancer. The system integrates clinical data from electronic health records and genomic data. Pattern analysis and data mining methods are applied to these integrated data and the discovered knowledge is used for cancer decision support. Through this integration, conclusions can be drawn for early diagnosis, staging and cancer treatment.

Cancer Genomics: Diversity and Disparity Across Ethnicity and Geography.

PubMed

Tan, Daniel S W; Mok, Tony S K; Rebbeck, Timothy R

2016-01-01

Ethnic and geographic differences in cancer incidence, prognosis, and treatment outcomes can be attributed to diversity in the inherited (germline) and somatic genome. Although international large-scale sequencing efforts are beginning to unravel the genomic underpinnings of cancer traits, much remains to be known about the underlying mechanisms and determinants of genomic diversity. Carcinogenesis is a dynamic, complex phenomenon representing the interplay between genetic and environmental factors that results in divergent phenotypes across ethnicities and geography. For example, compared with whites, there is a higher incidence of prostate cancer among Africans and African Americans, and the disease is generally more aggressive and fatal. Genome-wide association studies have identified germline susceptibility loci that may account for differences between the African and non-African patients, but the lack of availability of appropriate cohorts for replication studies and the incomplete understanding of genomic architecture across populations pose major limitations. We further discuss the transformative potential of routine diagnostic evaluation for actionable somatic alterations, using lung cancer as an example, highlighting implications of population disparities, current hurdles in implementation, and the far-reaching potential of clinical genomics in enhancing cancer prevention, diagnosis, and treatment. As we enter the era of precision cancer medicine, a concerted multinational effort is key to addressing population and genomic diversity as well as overcoming barriers and geographical disparities in research and health care delivery. © 2015 by American Society of Clinical Oncology.

Nervous system regulation of the cancer genome

PubMed Central

Cole, Steven W.

2012-01-01

Genomics-based analyses have provided deep insight into the basic biology of cancer and are now clarifying the molecular pathways by which psychological and social factors can regulate tumor cell gene expression and genome evolution. This review summarizes basic and clinical research on neural and endocrine regulation of the cancer genome and its interactions with the surrounding tumor microenvironment, including the specific types of genes subject to neural and endocrine regulation, the signal transduction pathways that mediate such effects, and therapeutic approaches that might be deployed to mitigate their impact. Beta-adrenergic signaling from the sympathetic nervous system has been found to up-regulated a diverse array of genes that contribute to tumor progression and metastasis, whereas glucocorticoid-regulated genes can inhibit DNA repair and promote cancer cell survival and resistance to chemotherapy. Relationships between socio-environmental risk factors, neural and endocrine signaling to the tumor microenvironment, and transcriptional responses by cancer cells and surrounding stromal cells are providing new mechanistic insights into the social epidemiology of cancer, new therapeutic approaches for protecting the health of cancer patients, and new molecular biomarkers for assessing the impact of behavioral and pharmacologic interventions. PMID:23207104

Contributions to Cancer Research: Finding a Niche in Communication | Office of Cancer Genomics

Cancer.gov

This past July, I started a journey into the fields of communications and cancer research when I joined the Office of Cancer Genomics (OCG) as a fellow in the National Cancer Institute (NCI) Health Communications Internship Program (HCIP). Cancer genomics and working in an office were new and uncharted territory for me: before I came to OCG, I was finishing a Ph.D. in cell biology at Vanderbilt University in Dr. Matthew Tyska’s laboratory.

The Genomic Landscape and Clinical Relevance of A-to-I RNA Editing in Human Cancers | Office of Cancer Genomics

Cancer.gov

Adenosine-to-inosine (A-to-I) RNA editing is a widespread post-transcriptional mechanism, but its genomic landscape and clinical relevance in cancer have not been investigated systematically. We characterized the global A-to-I RNA editing profiles of 6,236 patient samples of 17 cancer types from The Cancer Genome Atlas and revealed a striking diversity of altered RNA-editing patterns in tumors relative to normal tissues. We identified an appreciable number of clinically relevant editing events, many of which are in noncoding regions.

Toward a Comprehensive Genomic Analysis of Cancer - TCGA

Cancer.gov

The National Cancer Institute (NCI) and National Human Genome Research Institute (NHGRI) convened a "Toward a Comprehensive Genomic Analysis of Cancer" workshop in Washington, D.C. This workshop brought together physicians, basic scientists and other members of the U.S. and international cancer communities to assist in outlining the most effective strategies for the development of a successful project. Information about this workshop is reported in the Executive Summary.

Genome-wide Association Studies from the Cancer Genetic Markers of Susceptibility (CGEMS) Initiative | Office of Cancer Genomics

Cancer.gov

CGEMS identifies common inherited genetic variations associated with a number of cancers, including breast and prostate. Data from these genome-wide association studies (GWAS) are available through the Division of Cancer Epidemiology & Genetics website.

The Cancer Genome Atlas (TCGA): The next stage - TCGA

Cancer.gov

The Cancer Genome Atlas (TCGA), the NIH research program that has helped set the standards for characterizing the genomic underpinnings of dozens of cancers on a large scale, is moving to its next phase.

SPOP mutation leads to genomic instability in prostate cancer

PubMed Central

Boysen, Gunther; Barbieri, Christopher E; Prandi, Davide; Blattner, Mirjam; Chae, Sung-Suk; Dahija, Arun; Nataraj, Srilakshmi; Huang, Dennis; Marotz, Clarisse; Xu, Limei; Huang, Julie; Lecca, Paola; Chhangawala, Sagar; Liu, Deli; Zhou, Pengbo; Sboner, Andrea; de Bono, Johann S

2015-01-01

Genomic instability is a fundamental feature of human cancer often resulting from impaired genome maintenance. In prostate cancer, structural genomic rearrangements are a common mechanism driving tumorigenesis. However, somatic alterations predisposing to chromosomal rearrangements in prostate cancer remain largely undefined. Here, we show that SPOP, the most commonly mutated gene in primary prostate cancer modulates DNA double strand break (DSB) repair, and that SPOP mutation is associated with genomic instability. In vivo, SPOP mutation results in a transcriptional response consistent with BRCA1 inactivation resulting in impaired homology-directed repair (HDR) of DSB. Furthermore, we found that SPOP mutation sensitizes to DNA damaging therapeutic agents such as PARP inhibitors. These results implicate SPOP as a novel participant in DSB repair, suggest that SPOP mutation drives prostate tumorigenesis in part through genomic instability, and indicate that mutant SPOP may increase response to DNA-damaging therapeutics. DOI: http://dx.doi.org/10.7554/eLife.09207.001 PMID:26374986

The TTSMI database: a catalog of triplex target DNA sites associated with genes and regulatory elements in the human genome.

PubMed

Jenjaroenpun, Piroon; Chew, Chee Siang; Yong, Tai Pang; Choowongkomon, Kiattawee; Thammasorn, Wimada; Kuznetsov, Vladimir A

2015-01-01

A triplex target DNA site (TTS), a stretch of DNA that is composed of polypurines, is able to form a triple-helix (triplex) structure with triplex-forming oligonucleotides (TFOs) and is able to influence the site-specific modulation of gene expression and/or the modification of genomic DNA. The co-localization of a genomic TTS with gene regulatory signals and functional genome structures suggests that TFOs could potentially be exploited in antigene strategies for the therapy of cancers and other genetic diseases. Here, we present the TTS Mapping and Integration (TTSMI; http://ttsmi.bii.a-star.edu.sg) database, which provides a catalog of unique TTS locations in the human genome and tools for analyzing the co-localization of TTSs with genomic regulatory sequences and signals that were identified using next-generation sequencing techniques and/or predicted by computational models. TTSMI was designed as a user-friendly tool that facilitates (i) fast searching/filtering of TTSs using several search terms and criteria associated with sequence stability and specificity, (ii) interactive filtering of TTSs that co-localize with gene regulatory signals and non-B DNA structures, (iii) exploration of dynamic combinations of the biological signals of specific TTSs and (iv) visualization of a TTS simultaneously with diverse annotation tracks via the UCSC genome browser. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

Genomic tests for ovarian cancer detection and management.

PubMed

Myers, Evan R; Havrilesky, Laura J; Kulasingam, Shalini L; Sanders, Gillian D; Cline, Kathryn E; Gray, Rebecca N; Berchuck, Andrew; McCrory, Douglas C

2006-10-01

To assess the evidence that the use of genomic tests for ovarian cancer screening, diagnosis, and treatment leads to improved outcomes. PubMed and reference lists of recent reviews. We evaluated tests for: (a) single gene products; (b) genetic variations affecting risk of ovarian cancer; (c) gene expression; and (d) proteomics. For tests covered in recent evidence reports (cancer antigen 125 [CA-125] and breast cancer genes 1 and 2 [BRCA1/2]), we added studies published subsequent to the reports. We sought evidence on: (a) the analytic performance of tests in clinical laboratories; (b) the sensitivity and specificity of tests in different patient populations; (c) the clinical impact of testing in asymptomatic women, women with suspected ovarian cancer, and women with diagnosed ovarian cancer; (d) the harms of genomic testing; and (e) the impact of direct-to-consumer and direct-to-physician advertising on appropriate use of tests. We also constructed a computer simulation model to test the impact of different assumptions about ovarian cancer natural history on the relative effectiveness of different strategies. There are reasonable data on the clinical laboratory performance of most radioimmunoassays, but the majority of the data on other genomic tests comes from research laboratories. Genomic test sensitivity/specificity estimates are limited by small sample sizes, spectrum bias, and unrealistically large prevalences of ovarian cancer; in particular, estimates of positive predictive values derived from most of the studies are substantially higher than would be expected in most screening or diagnostic settings. We found no evidence relevant to the question of the impact of genomic tests on health outcomes in asymptomatic women. Although there is a relatively large literature on the association of test results and various clinical outcomes, the clinical utility of changing management based on these results has not been evaluated. We found no evidence that genomic

David Haussler, Ph.D., Lectures on Cancer Genomics - TCGA

Cancer.gov

In this lecture, Dr. David Haussler provides a historical overview of the field of genomics leading up to TCGA, including the Cancer Genomics Hub at the University of California, Santa Cruz, and the TCGA Pan-Cancer initiative.

Chapter 27 -- Breast Cancer Genomics, Section VI, Pathology and Biological Markers of Invasive Breast Cancer

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

Spellman, Paul T.; Heiser, Laura; Gray, Joe W.

2009-06-18

Breast cancer is predominantly a disease of the genome with cancers arising and progressing through accumulation of aberrations that alter the genome - by changing DNA sequence, copy number, and structure in ways that that contribute to diverse aspects of cancer pathophysiology. Classic examples of genomic events that contribute to breast cancer pathophysiology include inherited mutations in BRCA1, BRCA2, TP53, and CHK2 that contribute to the initiation of breast cancer, amplification of ERBB2 (formerly HER2) and mutations of elements of the PI3-kinase pathway that activate aspects of epidermal growth factor receptor (EGFR) signaling and deletion of CDKN2A/B that contributes tomore » cell cycle deregulation and genome instability. It is now apparent that accumulation of these aberrations is a time-dependent process that accelerates with age. Although American women living to an age of 85 have a 1 in 8 chance of developing breast cancer, the incidence of cancer in women younger than 30 years is uncommon. This is consistent with a multistep cancer progression model whereby mutation and selection drive the tumor's development, analogous to traditional Darwinian evolution. In the case of cancer, the driving events are changes in sequence, copy number, and structure of DNA and alterations in chromatin structure or other epigenetic marks. Our understanding of the genetic, genomic, and epigenomic events that influence the development and progression of breast cancer is increasing at a remarkable rate through application of powerful analysis tools that enable genome-wide analysis of DNA sequence and structure, copy number, allelic loss, and epigenomic modification. Application of these techniques to elucidation of the nature and timing of these events is enriching our understanding of mechanisms that increase breast cancer susceptibility, enable tumor initiation and progression to metastatic disease, and determine therapeutic response or resistance. These studies also

A Genome-Wide Breast Cancer Scan in African Americans

DTIC Science & Technology

2011-06-01

cancer in women of African ancestry. 13 References 1. Easton DF, P.K., Dunning AM, Pharoah PDP, Thompson D, Ballinger DG, et al . Genome...M, Hankinson, SE, et al . A genome-wide association study identifies alleles in FGFR2 associated with risk of sporadic postmenopausal breast cancer...Millikan, R.C. Race, breast cancer subtypes, and survival in the Carolina Breast Cancer Study. Jama 295, 2492-502 ( 2006 ). 16 17. Huo, D., Ikpatt

The topography of mutational processes in breast cancer genomes

DOE PAGES

Morganella, Sandro; Alexandrov, Ludmil B.; Glodzik, Dominik; ...

2016-01-01

Somatic mutations in human cancers show unevenness in genomic distribution that correlate with aspects of genome structure and function. These mutations are, however, generated by multiple mutational processes operating through the cellular lineage between the fertilized egg and the cancer cell, each composed of specific DNA damage and repair components and leaving its own characteristic mutational signature on the genome. Using somatic mutation catalogues from 560 breast cancer whole-genome sequences, here we show that each of 12 base substitution, 2 insertion/deletion (indel) and 6 rearrangement mutational signatures present in breast tissue, exhibit distinct relationships with genomic features relating to transcription,more » DNA replication and chromatin organization. This signature-based approach permits visualization of the genomic distribution of mutational processes associated with APOBEC enzymes, mismatch repair deficiency and homologous recombinational repair deficiency, as well as mutational processes of unknown aetiology. Lastly, it highlights mechanistic insights including a putative replication-dependent mechanism of APOBEC-related mutagenesis.« less

The topography of mutational processes in breast cancer genomes.

PubMed

Morganella, Sandro; Alexandrov, Ludmil B; Glodzik, Dominik; Zou, Xueqing; Davies, Helen; Staaf, Johan; Sieuwerts, Anieta M; Brinkman, Arie B; Martin, Sancha; Ramakrishna, Manasa; Butler, Adam; Kim, Hyung-Yong; Borg, Åke; Sotiriou, Christos; Futreal, P Andrew; Campbell, Peter J; Span, Paul N; Van Laere, Steven; Lakhani, Sunil R; Eyfjord, Jorunn E; Thompson, Alastair M; Stunnenberg, Hendrik G; van de Vijver, Marc J; Martens, John W M; Børresen-Dale, Anne-Lise; Richardson, Andrea L; Kong, Gu; Thomas, Gilles; Sale, Julian; Rada, Cristina; Stratton, Michael R; Birney, Ewan; Nik-Zainal, Serena

2016-05-02

Somatic mutations in human cancers show unevenness in genomic distribution that correlate with aspects of genome structure and function. These mutations are, however, generated by multiple mutational processes operating through the cellular lineage between the fertilized egg and the cancer cell, each composed of specific DNA damage and repair components and leaving its own characteristic mutational signature on the genome. Using somatic mutation catalogues from 560 breast cancer whole-genome sequences, here we show that each of 12 base substitution, 2 insertion/deletion (indel) and 6 rearrangement mutational signatures present in breast tissue, exhibit distinct relationships with genomic features relating to transcription, DNA replication and chromatin organization. This signature-based approach permits visualization of the genomic distribution of mutational processes associated with APOBEC enzymes, mismatch repair deficiency and homologous recombinational repair deficiency, as well as mutational processes of unknown aetiology. Furthermore, it highlights mechanistic insights including a putative replication-dependent mechanism of APOBEC-related mutagenesis.

Genome Stability Pathways in Head and Neck Cancers

PubMed Central

O'Byrne, Kenneth J.; Panizza, Benedict; Richard, Derek J.

2013-01-01

Genomic instability underlies the transformation of host cells toward malignancy, promotes development of invasion and metastasis and shapes the response of established cancer to treatment. In this review, we discuss recent advances in our understanding of genomic stability in squamous cell carcinoma of the head and neck (HNSCC), with an emphasis on DNA repair pathways. HNSCC is characterized by distinct profiles in genome stability between similarly staged cancers that are reflected in risk, treatment response and outcomes. Defective DNA repair generates chromosomal derangement that can cause subsequent alterations in gene expression, and is a hallmark of progression toward carcinoma. Variable functionality of an increasing spectrum of repair gene polymorphisms is associated with increased cancer risk, while aetiological factors such as human papillomavirus, tobacco and alcohol induce significantly different behaviour in induced malignancy, underpinned by differences in genomic stability. Targeted inhibition of signalling receptors has proven to be a clinically-validated therapy, and protein expression of other DNA repair and signalling molecules associated with cancer behaviour could potentially provide a more refined clinical model for prognosis and treatment prediction. Development and expansion of current genomic stability models is furthering our understanding of HNSCC pathophysiology and uncovering new, promising treatment strategies. PMID:24364026

Childhood Cancer Genomics (PDQ®)—Health Professional Version

Cancer.gov

Genomic findings have been useful in the identification of subsets of patients that have distinct biological features and clinical characteristics (such as prognosis) for some pediatric cancers. Learn about the genomic alterations associated with central nervous system, leukemia, lymphoma, liver, sarcoma, neuroblastoma, retinoblastoma, melanoma, kidney, and thyroid cancers in children in this comprehensive summary for clinicians.

Pathways to Genome-targeted Therapies in Serous Ovarian Cancer.

PubMed

Axelrod, Joshua; Delaney, Joe

2017-07-01

Genome sequencing technologies and corresponding oncology publications have generated enormous publicly available datasets for many cancer types. While this has enabled new treatments, and in some limited cases lifetime management of the disease, the treatment options for serous ovarian cancer remain dismal. This review summarizes recent advances in our understanding of ovarian cancer, with a focus on heterogeneity, functional genomics, and actionable data.

A Platform for Designing Genome-Based Personalized Immunotherapy or Vaccine against Cancer

PubMed Central

Gupta, Sudheer; Chaudhary, Kumardeep; Dhanda, Sandeep Kumar; Kumar, Rahul; Kumar, Shailesh; Sehgal, Manika; Nagpal, Gandharva

2016-01-01

Due to advancement in sequencing technology, genomes of thousands of cancer tissues or cell-lines have been sequenced. Identification of cancer-specific epitopes or neoepitopes from cancer genomes is one of the major challenges in the field of immunotherapy or vaccine development. This paper describes a platform Cancertope, developed for designing genome-based immunotherapy or vaccine against a cancer cell. Broadly, the integrated resources on this platform are apportioned into three precise sections. First section explains a cancer-specific database of neoepitopes generated from genome of 905 cancer cell lines. This database harbors wide range of epitopes (e.g., B-cell, CD8+ T-cell, HLA class I, HLA class II) against 60 cancer-specific vaccine antigens. Second section describes a partially personalized module developed for predicting potential neoepitopes against a user-specific cancer genome. Finally, we describe a fully personalized module developed for identification of neoepitopes from genomes of cancerous and healthy cells of a cancer-patient. In order to assist the scientific community, wide range of tools are incorporated in this platform that includes screening of epitopes against human reference proteome (http://www.imtech.res.in/raghava/cancertope/). PMID:27832200

Genomic Approaches to Zebrafish Cancer

PubMed Central

2017-01-01

The zebrafish has emerged as an important model for studying cancer biology. Identification of DNA, RNA and chromatin abnormalities can give profound insight into the mechanisms of tumorigenesis and the there are many techniques for analyzing the genomes of these tumors. Here, I present an overview of the available technologies for analyzing tumor genomes in the zebrafish, including array based methods as well as next-generation sequencing technologies. I also discuss the ways in which zebrafish tumor genomes can be compared to human genomes using cross-species oncogenomics, which act to filter genomic noise and ultimately uncover central drivers of malignancy. Finally, I discuss downstream analytic tools, including network analysis, that can help to organize the alterations into coherent biological frameworks that can then be investigated further. PMID:27165352

Genomic Resources for Cancer Epidemiology

Cancer.gov

This page provides links to research resources, complied by the Epidemiology and Genomics Research Program, that may be of interest to genetic epidemiologists conducting cancer research, but is not exhaustive.

Genomic Data Sharing Administrator | Center for Cancer Research

Cancer.gov

Be part of our mission to support research against cancer. We are looking for an organized, detail oriented, dependable person with strong interpersonal skills to serve as a key member of the genomic data sharing administration team at the National Cancer Institute (NCI) on the campus of NIH. Work supports the implementation of the NIH Genomic Data Sharing Policy (GDS) in the

Computational approaches to identify functional genetic variants in cancer genomes

PubMed Central

Gonzalez-Perez, Abel; Mustonen, Ville; Reva, Boris; Ritchie, Graham R.S.; Creixell, Pau; Karchin, Rachel; Vazquez, Miguel; Fink, J. Lynn; Kassahn, Karin S.; Pearson, John V.; Bader, Gary; Boutros, Paul C.; Muthuswamy, Lakshmi; Ouellette, B.F. Francis; Reimand, Jüri; Linding, Rune; Shibata, Tatsuhiro; Valencia, Alfonso; Butler, Adam; Dronov, Serge; Flicek, Paul; Shannon, Nick B.; Carter, Hannah; Ding, Li; Sander, Chris; Stuart, Josh M.; Stein, Lincoln D.; Lopez-Bigas, Nuria

2014-01-01

The International Cancer Genome Consortium (ICGC) aims to catalog genomic abnormalities in tumors from 50 different cancer types. Genome sequencing reveals hundreds to thousands of somatic mutations in each tumor, but only a minority drive tumor progression. We present the result of discussions within the ICGC on how to address the challenge of identifying mutations that contribute to oncogenesis, tumor maintenance or response to therapy, and recommend computational techniques to annotate somatic variants and predict their impact on cancer phenotype. PMID:23900255

Pathway and network analysis of cancer genomes.

PubMed

Creixell, Pau; Reimand, Jüri; Haider, Syed; Wu, Guanming; Shibata, Tatsuhiro; Vazquez, Miguel; Mustonen, Ville; Gonzalez-Perez, Abel; Pearson, John; Sander, Chris; Raphael, Benjamin J; Marks, Debora S; Ouellette, B F Francis; Valencia, Alfonso; Bader, Gary D; Boutros, Paul C; Stuart, Joshua M; Linding, Rune; Lopez-Bigas, Nuria; Stein, Lincoln D

2015-07-01

Genomic information on tumors from 50 cancer types cataloged by the International Cancer Genome Consortium (ICGC) shows that only a few well-studied driver genes are frequently mutated, in contrast to many infrequently mutated genes that may also contribute to tumor biology. Hence there has been large interest in developing pathway and network analysis methods that group genes and illuminate the processes involved. We provide an overview of these analysis techniques and show where they guide mechanistic and translational investigations.

Next-generation sequencing of cancer genomes: back to the future

PubMed Central

Walter, Matthew J; Graubert, Timothy A; DiPersio, John F; Mardis, Elaine R; Wilson, Richard K; Ley, Timothy J

2010-01-01

The systematic karyotyping of bone marrow cells was the first genomic approach used to personalize therapy for patients with leukemia. The paradigm established by cytogenetic studies in leukemia (from gene discovery to therapeutic intervention) now has the potential to be rapidly extended with the use of whole-genome sequencing approaches for cancer, which are now possible. We are now entering a period of exponential growth in cancer gene discovery that will provide many novel therapeutic targets for a large number of cancer types. Establishing the pathogenetic relevance of individual mutations is a major challenge that must be solved. However, after thousands of cancer genomes have been sequenced, the genetic rules of cancer will become known and new approaches for diagnosis, risk stratification and individualized treatment of cancer patients will surely follow. PMID:20161678

Predictive genomics: a cancer hallmark network framework for predicting tumor clinical phenotypes using genome sequencing data.

PubMed

Wang, Edwin; Zaman, Naif; Mcgee, Shauna; Milanese, Jean-Sébastien; Masoudi-Nejad, Ali; O'Connor-McCourt, Maureen

2015-02-01

Tumor genome sequencing leads to documenting thousands of DNA mutations and other genomic alterations. At present, these data cannot be analyzed adequately to aid in the understanding of tumorigenesis and its evolution. Moreover, we have little insight into how to use these data to predict clinical phenotypes and tumor progression to better design patient treatment. To meet these challenges, we discuss a cancer hallmark network framework for modeling genome sequencing data to predict cancer clonal evolution and associated clinical phenotypes. The framework includes: (1) cancer hallmarks that can be represented by a few molecular/signaling networks. 'Network operational signatures' which represent gene regulatory logics/strengths enable to quantify state transitions and measures of hallmark traits. Thus, sets of genomic alterations which are associated with network operational signatures could be linked to the state/measure of hallmark traits. The network operational signature transforms genotypic data (i.e., genomic alterations) to regulatory phenotypic profiles (i.e., regulatory logics/strengths), to cellular phenotypic profiles (i.e., hallmark traits) which lead to clinical phenotypic profiles (i.e., a collection of hallmark traits). Furthermore, the framework considers regulatory logics of the hallmark networks under tumor evolutionary dynamics and therefore also includes: (2) a self-promoting positive feedback loop that is dominated by a genomic instability network and a cell survival/proliferation network is the main driver of tumor clonal evolution. Surrounding tumor stroma and its host immune systems shape the evolutionary paths; (3) cell motility initiating metastasis is a byproduct of the above self-promoting loop activity during tumorigenesis; (4) an emerging hallmark network which triggers genome duplication dominates a feed-forward loop which in turn could act as a rate-limiting step for tumor formation; (5) mutations and other genomic alterations have

Sensitivity to sequencing depth in single-cell cancer genomics.

PubMed

Alves, João M; Posada, David

2018-04-16

Querying cancer genomes at single-cell resolution is expected to provide a powerful framework to understand in detail the dynamics of cancer evolution. However, given the high costs currently associated with single-cell sequencing, together with the inevitable technical noise arising from single-cell genome amplification, cost-effective strategies that maximize the quality of single-cell data are critically needed. Taking advantage of previously published single-cell whole-genome and whole-exome cancer datasets, we studied the impact of sequencing depth and sampling effort towards single-cell variant detection. Five single-cell whole-genome and whole-exome cancer datasets were independently downscaled to 25, 10, 5, and 1× sequencing depth. For each depth level, ten technical replicates were generated, resulting in a total of 6280 single-cell BAM files. The sensitivity of variant detection, including structural and driver mutations, genotyping, clonal inference, and phylogenetic reconstruction to sequencing depth was evaluated using recent tools specifically designed for single-cell data. Altogether, our results suggest that for relatively large sample sizes (25 or more cells) sequencing single tumor cells at depths > 5× does not drastically improve somatic variant discovery, characterization of clonal genotypes, or estimation of single-cell phylogenies. We suggest that sequencing multiple individual tumor cells at a modest depth represents an effective alternative to explore the mutational landscape and clonal evolutionary patterns of cancer genomes.

A Genome-Wide Breast Cancer Scan in African Americans

DTIC Science & Technology

2010-06-01

SNPs from the African American breast cancer scan to COGs , a European collaborative study which is has designed a SNP array with that will be genotyped...Award Number: W81XWH-08-1-0383 TITLE: A Genome-wide Breast Cancer Scan in African Americans PRINCIPAL INVESTIGATOR: Christopher A...SUBTITLE A Genome-wide Breast Cancer Scan in African Americans 5a. CONTRACT NUMBER 5b. GRANT NUMBER W81XWH-08-1-0383 5c. PROGRAM

Multi-OMICs and Genome Editing Perspectives on Liver Cancer Signaling Networks.

PubMed

Lin, Shengda; Yin, Yi A; Jiang, Xiaoqian; Sahni, Nidhi; Yi, Song

2016-01-01

The advent of the human genome sequence and the resulting ~20,000 genes provide a crucial framework for a transition from traditional biology to an integrative "OMICs" arena (Lander et al., 2001; Venter et al., 2001; Kitano, 2002). This brings in a revolution for cancer research, which now enters a big data era. In the past decade, with the facilitation by next-generation sequencing, there have been a huge number of large-scale sequencing efforts, such as The Cancer Genome Atlas (TCGA), the HapMap, and the 1000 genomes project. As a result, a deluge of genomic information becomes available from patients stricken by a variety of cancer types. The list of cancer-associated genes is ever expanding. New discoveries are made on how frequent and highly penetrant mutations, such as those in the telomerase reverse transcriptase (TERT) and TP53, function in cancer initiation, progression, and metastasis. Most genes with relatively frequent but weakly penetrant cancer mutations still remain to be characterized. In addition, genes that harbor rare but highly penetrant cancer-associated mutations continue to emerge. Here, we review recent advances related to cancer genomics, proteomics, and systems biology and suggest new perspectives in targeted therapy and precision medicine.

Collaborative Research to Advance Precision Medicine in the Post-Genomic World | Office of Cancer Genomics

Cancer.gov

My name is Subhashini Jagu, and I am the Scientific Program Manager for the Cancer Target Discovery and Development (CTD2) Network at the Office of Cancer Genomics (OCG). In my new role, I help CTD2 work toward its mission, which is to develop new scientific approaches to accelerate the translation of genomic discoveries into new treatments. Collaborative efforts that bring together a variety of expertise and infrastructure are needed to understand and successfully treat cancer, a highly complex disease.

Integrative prescreening in analysis of multiple cancer genomic studies

PubMed Central

2012-01-01

Background In high throughput cancer genomic studies, results from the analysis of single datasets often suffer from a lack of reproducibility because of small sample sizes. Integrative analysis can effectively pool and analyze multiple datasets and provides a cost effective way to improve reproducibility. In integrative analysis, simultaneously analyzing all genes profiled may incur high computational cost. A computationally affordable remedy is prescreening, which fits marginal models, can be conducted in a parallel manner, and has low computational cost. Results An integrative prescreening approach is developed for the analysis of multiple cancer genomic datasets. Simulation shows that the proposed integrative prescreening has better performance than alternatives, particularly including prescreening with individual datasets, an intensity approach and meta-analysis. We also analyze multiple microarray gene profiling studies on liver and pancreatic cancers using the proposed approach. Conclusions The proposed integrative prescreening provides an effective way to reduce the dimensionality in cancer genomic studies. It can be coupled with existing analysis methods to identify cancer markers. PMID:22799431

TUMOR HAPLOTYPE ASSEMBLY ALGORITHMS FOR CANCER GENOMICS

PubMed Central

AGUIAR, DEREK; WONG, WENDY S.W.; ISTRAIL, SORIN

2014-01-01

The growing availability of inexpensive high-throughput sequence data is enabling researchers to sequence tumor populations within a single individual at high coverage. But, cancer genome sequence evolution and mutational phenomena like driver mutations and gene fusions are difficult to investigate without first reconstructing tumor haplotype sequences. Haplotype assembly of single individual tumor populations is an exceedingly difficult task complicated by tumor haplotype heterogeneity, tumor or normal cell sequence contamination, polyploidy, and complex patterns of variation. While computational and experimental haplotype phasing of diploid genomes has seen much progress in recent years, haplotype assembly in cancer genomes remains uncharted territory. In this work, we describe HapCompass-Tumor a computational modeling and algorithmic framework for haplotype assembly of copy number variable cancer genomes containing haplotypes at different frequencies and complex variation. We extend our polyploid haplotype assembly model and present novel algorithms for (1) complex variations, including copy number changes, as varying numbers of disjoint paths in an associated graph, (2) variable haplotype frequencies and contamination, and (3) computation of tumor haplotypes using simple cycles of the compass graph which constrain the space of haplotype assembly solutions. The model and algorithm are implemented in the software package HapCompass-Tumor which is available for download from http://www.brown.edu/Research/Istrail_Lab/. PMID:24297529

Databases and Web Tools for Cancer Genomics Study

PubMed Central

Yang, Yadong; Dong, Xunong; Xie, Bingbing; Ding, Nan; Chen, Juan; Li, Yongjun; Zhang, Qian; Qu, Hongzhu; Fang, Xiangdong

2015-01-01

Publicly-accessible resources have promoted the advance of scientific discovery. The era of genomics and big data has brought the need for collaboration and data sharing in order to make effective use of this new knowledge. Here, we describe the web resources for cancer genomics research and rate them on the basis of the diversity of cancer types, sample size, omics data comprehensiveness, and user experience. The resources reviewed include data repository and analysis tools; and we hope such introduction will promote the awareness and facilitate the usage of these resources in the cancer research community. PMID:25707591

Cancer Genomics: Integrative and Scalable Solutions in R / Bioconductor | Informatics Technology for Cancer Research (ITCR)

Cancer.gov

This proposal develops scalable R / Bioconductor software infrastructure and data resources to integrate complex, heterogeneous, and large cancer genomic experiments. The falling cost of genomic assays facilitates collection of multiple data types (e.g., gene and transcript expression, structural variation, copy number, methylation, and microRNA data) from a set of clinical specimens. Furthermore, substantial resources are now available from large consortium activities like The Cancer Genome Atlas (TCGA).

KRAS Genomic Status Predicts the Sensitivity of Ovarian Cancer Cells to Decitabine | Office of Cancer Genomics

Cancer.gov

Decitabine, a cancer therapeutic that inhibits DNA methylation, produces variable antitumor response rates in patients with solid tumors that might be leveraged clinically with identification of a predictive biomarker. In this study, we profiled the response of human ovarian, melanoma, and breast cancer cells treated with decitabine, finding that RAS/MEK/ERK pathway activation and DNMT1 expression correlated with cytotoxic activity. Further, we showed that KRAS genomic status predicted decitabine sensitivity in low-grade and high-grade serous ovarian cancer cells.

Genomic analysis and selected molecular pathways in rare cancers

NASA Astrophysics Data System (ADS)

Liu, Stephen V.; Lenkiewicz, Elizabeth; Evers, Lisa; Holley, Tara; Kiefer, Jeffrey; Ruiz, Christian; Glatz, Katharina; Bubendorf, Lukas; Demeure, Michael J.; Eng, Cathy; Ramanathan, Ramesh K.; Von Hoff, Daniel D.; Barrett, Michael T.

2012-12-01

It is widely accepted that many cancers arise as a result of an acquired genomic instability and the subsequent evolution of tumor cells with variable patterns of selected and background aberrations. The presence and behaviors of distinct neoplastic cell populations within a patient's tumor may underlie multiple clinical phenotypes in cancers. A goal of many current cancer genome studies is the identification of recurring selected driver events that can be advanced for the development of personalized therapies. Unfortunately, in the majority of rare tumors, this type of analysis can be particularly challenging. Large series of specimens for analysis are simply not available, allowing recurring patterns to remain hidden. In this paper, we highlight the use of DNA content-based flow sorting to identify and isolate DNA-diploid and DNA-aneuploid populations from tumor biopsies as a strategy to comprehensively study the genomic composition and behaviors of individual cancers in a series of rare solid tumors: intrahepatic cholangiocarcinoma, anal carcinoma, adrenal leiomyosarcoma, and pancreatic neuroendocrine tumors. We propose that the identification of highly selected genomic events in distinct tumor populations within each tumor can identify candidate driver events that can facilitate the development of novel, personalized treatment strategies for patients with cancer.

Genomic analysis and selected molecular pathways in rare cancers.

PubMed

Liu, Stephen V; Lenkiewicz, Elizabeth; Evers, Lisa; Holley, Tara; Kiefer, Jeffrey; Ruiz, Christian; Glatz, Katharina; Bubendorf, Lukas; Demeure, Michael J; Eng, Cathy; Ramanathan, Ramesh K; Von Hoff, Daniel D; Barrett, Michael T

2012-12-01

It is widely accepted that many cancers arise as a result of an acquired genomic instability and the subsequent evolution of tumor cells with variable patterns of selected and background aberrations. The presence and behaviors of distinct neoplastic cell populations within a patient's tumor may underlie multiple clinical phenotypes in cancers. A goal of many current cancer genome studies is the identification of recurring selected driver events that can be advanced for the development of personalized therapies. Unfortunately, in the majority of rare tumors, this type of analysis can be particularly challenging. Large series of specimens for analysis are simply not available, allowing recurring patterns to remain hidden. In this paper, we highlight the use of DNA content-based flow sorting to identify and isolate DNA-diploid and DNA-aneuploid populations from tumor biopsies as a strategy to comprehensively study the genomic composition and behaviors of individual cancers in a series of rare solid tumors: intrahepatic cholangiocarcinoma, anal carcinoma, adrenal leiomyosarcoma, and pancreatic neuroendocrine tumors. We propose that the identification of highly selected genomic events in distinct tumor populations within each tumor can identify candidate driver events that can facilitate the development of novel, personalized treatment strategies for patients with cancer.

An expanding universe of the non-coding genome in cancer biology.

PubMed

Xue, Bin; He, Lin

2014-06-01

Neoplastic transformation is caused by accumulation of genetic and epigenetic alterations that ultimately convert normal cells into tumor cells with uncontrolled proliferation and survival, unlimited replicative potential and invasive growth [Hanahan,D. et al. (2011) Hallmarks of cancer: the next generation. Cell, 144, 646-674]. Although the majority of the cancer studies have focused on the functions of protein-coding genes, emerging evidence has started to reveal the importance of the vast non-coding genome, which constitutes more than 98% of the human genome. A number of non-coding RNAs (ncRNAs) derived from the 'dark matter' of the human genome exhibit cancer-specific differential expression and/or genomic alterations, and it is increasingly clear that ncRNAs, including small ncRNAs and long ncRNAs (lncRNAs), play an important role in cancer development by regulating protein-coding gene expression through diverse mechanisms. In addition to ncRNAs, nearly half of the mammalian genomes consist of transposable elements, particularly retrotransposons. Once depicted as selfish genomic parasites that propagate at the expense of host fitness, retrotransposon elements could also confer regulatory complexity to the host genomes during development and disease. Reactivation of retrotransposons in cancer, while capable of causing insertional mutagenesis and genome rearrangements to promote oncogenesis, could also alter host gene expression networks to favor tumor development. Taken together, the functional significance of non-coding genome in tumorigenesis has been previously underestimated, and diverse transcripts derived from the non-coding genome could act as integral functional components of the oncogene and tumor suppressor network. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Genome Science and Personalized Cancer Treatment

ScienceCinema

Gray, Joe

2017-12-09

August 4, 2009 Berkeley Lab lecture: Results from the Human Genome Project are enabling scientists to understand how individual cancers form and progress. This information, when combined with newly developed drugs, can optimize the treatment of individual cancers. Joe Gray, director of Berkeley Labs Life Sciences Division and Associate Laboratory Director for Life and Environmental Sciences, will focus on this approach, its promise, and its current roadblocks — particularly with regard to breast cancer.

Genomic instability in cancer: Teetering on the limit of tolerance

PubMed Central

Andor, Noemi; Maley, Carlo C.; Ji, Hanlee P.

2017-01-01

Cancer genomic instability contributes to the phenomenon of intratumoral genetic heterogeneity, provides the genetic diversity required for natural selection and enables the extensive phenotypic diversity that is frequently observed among patients. Genomic instability has previously been associated with poor prognosis. However, we have evidence that for solid tumors of epithelial origin, extreme levels of genomic instability, where more than 75% of the genome is subject to somatic copy number alterations, are associated with a potentially better prognosis compared to intermediate levels under this threshold. This has been observed in clonal subpopulations of larger size, especially when genomic instability is shared among a limited number of clones. We hypothesize that cancers with extreme levels of genomic instability may be teetering on the brink of a threshold where so much of their genome is adversely altered that cells rarely replicate successfully. Another possibility is that tumors with high levels of genomic instability are more immunogenic than other cancers with a less extensive burden of genetic aberrations. Regardless of the exact mechanism, but hinging on our ability to quantify how a tumor’s burden of genetic aberrations is distributed among coexisting clones – genomic instability has important therapeutic implications. Herein, we explore the possibility that a high genomic instability could be the basis for a tumor’s sensitivity to DNA damaging therapies. We primarily focus on studies of epithelial-derived solid tumors. PMID:28432052

Predicting human genetic interactions from cancer genome evolution.

PubMed

Lu, Xiaowen; Megchelenbrink, Wout; Notebaart, Richard A; Huynen, Martijn A

2015-01-01

Synthetic Lethal (SL) genetic interactions play a key role in various types of biological research, ranging from understanding genotype-phenotype relationships to identifying drug-targets against cancer. Despite recent advances in empirical measuring SL interactions in human cells, the human genetic interaction map is far from complete. Here, we present a novel approach to predict this map by exploiting patterns in cancer genome evolution. First, we show that empirically determined SL interactions are reflected in various gene presence, absence, and duplication patterns in hundreds of cancer genomes. The most evident pattern that we discovered is that when one member of an SL interaction gene pair is lost, the other gene tends not to be lost, i.e. the absence of co-loss. This observation is in line with expectation, because the loss of an SL interacting pair will be lethal to the cancer cell. SL interactions are also reflected in gene expression profiles, such as an under representation of cases where the genes in an SL pair are both under expressed, and an over representation of cases where one gene of an SL pair is under expressed, while the other one is over expressed. We integrated the various previously unknown cancer genome patterns and the gene expression patterns into a computational model to identify SL pairs. This simple, genome-wide model achieves a high prediction power (AUC = 0.75) for known genetic interactions. It allows us to present for the first time a comprehensive genome-wide list of SL interactions with a high estimated prediction precision, covering up to 591,000 gene pairs. This unique list can potentially be used in various application areas ranging from biotechnology to medical genetics.

Integrating cancer genomic data into electronic health records.

PubMed

Warner, Jeremy L; Jain, Sandeep K; Levy, Mia A

2016-10-26

The rise of genomically targeted therapies and immunotherapy has revolutionized the practice of oncology in the last 10-15 years. At the same time, new technologies and the electronic health record (EHR) in particular have permeated the oncology clinic. Initially designed as billing and clinical documentation systems, EHR systems have not anticipated the complexity and variety of genomic information that needs to be reviewed, interpreted, and acted upon on a daily basis. Improved integration of cancer genomic data with EHR systems will help guide clinician decision making, support secondary uses, and ultimately improve patient care within oncology clinics. Some of the key factors relating to the challenge of integrating cancer genomic data into EHRs include: the bioinformatics pipelines that translate raw genomic data into meaningful, actionable results; the role of human curation in the interpretation of variant calls; and the need for consistent standards with regard to genomic and clinical data. Several emerging paradigms for integration are discussed in this review, including: non-standardized efforts between individual institutions and genomic testing laboratories; "middleware" products that portray genomic information, albeit outside of the clinical workflow; and application programming interfaces that have the potential to work within clinical workflow. The critical need for clinical-genomic knowledge bases, which can be independent or integrated into the aforementioned solutions, is also discussed.

Mutation of Breast Cancer Cell Genomic DNA by APOBEC3B

DTIC Science & Technology

2012-09-01

down Yes, A3B expression increases the steady-state level of genomic uracil Fig. 2a-2c 2) Can A3B mutate a target gene to escape drug...somatic mutation in human cancer genomes. Nature 446, 153-158 (2007). 10 2 Jones, S. et al. Frequent mutations of chromatin remodeling gene ARID1A in...processes molding the genomes of 21 breast cancers. Cell 149, 979-993 (2012). 9 Stephens, P. J. et al. The landscape of cancer genes and mutational

Emergence of the Noncoding Cancer Genome: A Target of Genetic and Epigenetic Alterations.

PubMed

Zhou, Stanley; Treloar, Aislinn E; Lupien, Mathieu

2016-11-01

The emergence of whole-genome annotation approaches is paving the way for the comprehensive annotation of the human genome across diverse cell and tissue types exposed to various environmental conditions. This has already unmasked the positions of thousands of functional cis-regulatory elements integral to transcriptional regulation, such as enhancers, promoters, and anchors of chromatin interactions that populate the noncoding genome. Recent studies have shown that cis-regulatory elements are commonly the targets of genetic and epigenetic alterations associated with aberrant gene expression in cancer. Here, we review these findings to showcase the contribution of the noncoding genome and its alteration in the development and progression of cancer. We also highlight the opportunities to translate the biological characterization of genetic and epigenetic alterations in the noncoding cancer genome into novel approaches to treat or monitor disease. The majority of genetic and epigenetic alterations accumulate in the noncoding genome throughout oncogenesis. Discriminating driver from passenger events is a challenge that holds great promise to improve our understanding of the etiology of different cancer types. Advancing our understanding of the noncoding cancer genome may thus identify new therapeutic opportunities and accelerate our capacity to find improved biomarkers to monitor various stages of cancer development. Cancer Discov; 6(11); 1215-29. ©2016 AACR. ©2016 American Association for Cancer Research.

Interest in genomic SNP testing for prostate cancer risk: a pilot survey.

PubMed

Hall, Michael J; Ruth, Karen J; Chen, David Yt; Gross, Laura M; Giri, Veda N

2015-01-01

Advancements in genomic testing have led to the identification of single nucleotide polymorphisms (SNPs) associated with prostate cancer. The clinical utility of SNP tests to evaluate prostate cancer risk is unclear. Studies have not examined predictors of interest in novel genomic SNP tests for prostate cancer risk in a diverse population. Consecutive participants in the Fox Chase Prostate Cancer Risk Assessment Program (PRAP) (n = 40) and unselected men from surgical urology clinics (n = 40) completed a one-time survey. Items examined interest in genomic SNP testing for prostate cancer risk, knowledge, impact of unsolicited findings, and psychosocial factors including health literacy. Knowledge of genomic SNP tests was low in both groups, but interest was higher among PRAP men (p < 0.001). The prospect of receiving unsolicited results about ancestral genomic markers increased interest in testing in both groups. Multivariable modeling identified several predictors of higher interest in a genomic SNP test including higher perceived risk (p = 0.025), indicating zero reasons for not wanting testing (vs ≥1 reason) (p = 0.013), and higher health literacy (p = 0.016). Knowledge of genomic SNP testing was low in this sample, but higher among high-risk men. High-risk status may increase interest in novel genomic tests, while low literacy may lessen interest.

A Review of the Accomplishments of the CTD² Network | Office of Cancer Genomics

Cancer.gov

The Office of Cancer Genomics (OCG) Cancer Target Discovery and Development or CTD2 initiative was established by the National Cancer Institute (NCI) to accelerate the “translation” of high-throughput, high-content genomic data to the bedside through functional genomics. The CTD2 initiative is a collaborative network of 13 different research teams, or Centers.

Pancreatic Cancer Genomics 2.0: Profiling Metastases.

PubMed

Collisson, Eric A; Maitra, Anirban

2017-03-13

Pancreatic ductal adenocarcinoma, even when diagnosed early, nearly always metastasizes. Recurrent mutations and genomic instability are early events in the disease. Two recent papers advance our understanding of how the cancer genome evolves as the primary tumor migrates from its origin in the pancreas to colonize distant metastatic sites. Copyright © 2017 Elsevier Inc. All rights reserved.

Perspective on Oncogenic Processes at the End of the Beginning of Cancer Genomics.

PubMed

Ding, Li; Bailey, Matthew H; Porta-Pardo, Eduard; Thorsson, Vesteinn; Colaprico, Antonio; Bertrand, Denis; Gibbs, David L; Weerasinghe, Amila; Huang, Kuan-Lin; Tokheim, Collin; Cortés-Ciriano, Isidro; Jayasinghe, Reyka; Chen, Feng; Yu, Lihua; Sun, Sam; Olsen, Catharina; Kim, Jaegil; Taylor, Alison M; Cherniack, Andrew D; Akbani, Rehan; Suphavilai, Chayaporn; Nagarajan, Niranjan; Stuart, Joshua M; Mills, Gordon B; Wyczalkowski, Matthew A; Vincent, Benjamin G; Hutter, Carolyn M; Zenklusen, Jean Claude; Hoadley, Katherine A; Wendl, Michael C; Shmulevich, Llya; Lazar, Alexander J; Wheeler, David A; Getz, Gad

2018-04-05

The Cancer Genome Atlas (TCGA) has catalyzed systematic characterization of diverse genomic alterations underlying human cancers. At this historic junction marking the completion of genomic characterization of over 11,000 tumors from 33 cancer types, we present our current understanding of the molecular processes governing oncogenesis. We illustrate our insights into cancer through synthesis of the findings of the TCGA PanCancer Atlas project on three facets of oncogenesis: (1) somatic driver mutations, germline pathogenic variants, and their interactions in the tumor; (2) the influence of the tumor genome and epigenome on transcriptome and proteome; and (3) the relationship between tumor and the microenvironment, including implications for drugs targeting driver events and immunotherapies. These results will anchor future characterization of rare and common tumor types, primary and relapsed tumors, and cancers across ancestry groups and will guide the deployment of clinical genomic sequencing. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

GWIPS-viz: development of a ribo-seq genome browser

PubMed Central

Michel, Audrey M.; Fox, Gearoid; M. Kiran, Anmol; De Bo, Christof; O’Connor, Patrick B. F.; Heaphy, Stephen M.; Mullan, James P. A.; Donohue, Claire A.; Higgins, Desmond G.; Baranov, Pavel V.

2014-01-01

We describe the development of GWIPS-viz (http://gwips.ucc.ie), an online genome browser for viewing ribosome profiling data. Ribosome profiling (ribo-seq) is a recently developed technique that provides genome-wide information on protein synthesis (GWIPS) in vivo. It is based on the deep sequencing of ribosome-protected messenger RNA (mRNA) fragments, which allows the ribosome density along all mRNA transcripts present in the cell to be quantified. Since its inception, ribo-seq has been carried out in a number of eukaryotic and prokaryotic organisms. Owing to the increasing interest in ribo-seq, there is a pertinent demand for a dedicated ribo-seq genome browser. GWIPS-viz is based on The University of California Santa Cruz (UCSC) Genome Browser. Ribo-seq tracks, coupled with mRNA-seq tracks, are currently available for several genomes: human, mouse, zebrafish, nematode, yeast, bacteria (Escherichia coli K12, Bacillus subtilis), human cytomegalovirus and bacteriophage lambda. Our objective is to continue incorporating published ribo-seq data sets so that the wider community can readily view ribosome profiling information from multiple studies without the need to carry out computational processing. PMID:24185699

Defining a Cancer Dependency Map | Office of Cancer Genomics

Cancer.gov

Most human epithelial tumors harbor numerous alterations, making it difficult to predict which genes are required for tumor survival. To systematically identify cancer dependencies, we analyzed 501 genome-scale loss-of-function screens performed in diverse human cancer cell lines. We developed DEMETER, an analytical framework that segregates on- from off-target effects of RNAi. 769 genes were differentially required in subsets of these cell lines at a threshold of six SDs from the mean.

[The application of CRISPR/Cas9 genome editing technology in cancer research].

PubMed

Wang, Da-yong; Ma, Ning; Hui, Yang; Gao, Xu

2016-01-01

The CRISPR/Cas9 (clustered regularly interspaced short palindromic repeats/CRISPR-associated protein-9 nuclease) genome editing technology has become more and more popular in gene editing because of its simple design and easy operation. Using the CRISPR/Cas9 system, researchers can perform site-directed genome modification at the base level. Moreover, it has been widely used in genome editing in multiple species and related cancer research. In this review, we summarize the application of the CRISPR/Cas9 system in cancer research based on the latest research progresses as well as our understanding of cancer research and genome editing techniques.

Genome-wide network analysis of Wnt signaling in three pediatric cancers

NASA Astrophysics Data System (ADS)

Bao, Ju; Lee, Ho-Jin; Zheng, Jie J.

2013-10-01

Genomic structural alteration is common in pediatric cancers, and analysis of data generated by the Pediatric Cancer Genome Project reveals such tumor-related alterations in many Wnt signaling-associated genes. Most pediatric cancers are thought to arise within developing tissues that undergo substantial expansion during early organ formation, growth and maturation, and Wnt signaling plays an important role in this development. We examined three pediatric tumors--medullobastoma, early T-cell precursor acute lymphoblastic leukemia, and retinoblastoma--that show multiple genomic structural variations within Wnt signaling pathways. We mathematically modeled this pathway to investigate the effects of cancer-related structural variations on Wnt signaling. Surprisingly, we found that an outcome measure of canonical Wnt signaling was consistently similar in matched cancer cells and normal cells, even in the context of different cancers, different mutations, and different Wnt-related genes. Our results suggest that the cancer cells maintain a normal level of Wnt signaling by developing multiple mutations.

Using large-scale genome variation cohorts to decipher the molecular mechanism of cancer.

PubMed

Habermann, Nina; Mardin, Balca R; Yakneen, Sergei; Korbel, Jan O

2016-01-01

Characterizing genomic structural variations (SVs) in the human genome remains challenging, and there is a growing interest to understand somatic SVs occurring in cancer, a disease of the genome. A havoc-causing SV process known as chromothripsis scars the genome when localized chromosome shattering and repair occur in a one-off catastrophe. Recent efforts led to the development of a set of conceptual criteria for the inference of chromothripsis events in cancer genomes and to the development of experimental model systems for studying this striking DNA alteration process in vitro. We discuss these approaches, and additionally touch upon current "Big Data" efforts that employ hybrid cloud computing to enable studies of numerous cancer genomes in an effort to search for commonalities and differences in molecular DNA alteration processes in cancer. Copyright © 2016. Published by Elsevier SAS.

Knowledge-driven genomic interactions: an application in ovarian cancer.

PubMed

Kim, Dokyoon; Li, Ruowang; Dudek, Scott M; Frase, Alex T; Pendergrass, Sarah A; Ritchie, Marylyn D

2014-01-01

Effective cancer clinical outcome prediction for understanding of the mechanism of various types of cancer has been pursued using molecular-based data such as gene expression profiles, an approach that has promise for providing better diagnostics and supporting further therapies. However, clinical outcome prediction based on gene expression profiles varies between independent data sets. Further, single-gene expression outcome prediction is limited for cancer evaluation since genes do not act in isolation, but rather interact with other genes in complex signaling or regulatory networks. In addition, since pathways are more likely to co-operate together, it would be desirable to incorporate expert knowledge to combine pathways in a useful and informative manner. Thus, we propose a novel approach for identifying knowledge-driven genomic interactions and applying it to discover models associated with cancer clinical phenotypes using grammatical evolution neural networks (GENN). In order to demonstrate the utility of the proposed approach, an ovarian cancer data from the Cancer Genome Atlas (TCGA) was used for predicting clinical stage as a pilot project. We identified knowledge-driven genomic interactions associated with cancer stage from single knowledge bases such as sources of pathway-pathway interaction, but also knowledge-driven genomic interactions across different sets of knowledge bases such as pathway-protein family interactions by integrating different types of information. Notably, an integration model from different sources of biological knowledge achieved 78.82% balanced accuracy and outperformed the top models with gene expression or single knowledge-based data types alone. Furthermore, the results from the models are more interpretable because they are framed in the context of specific biological pathways or other expert knowledge. The success of the pilot study we have presented herein will allow us to pursue further identification of models predictive

TCGA's Pan-Cancer Efforts and Expansion to Include Whole Genome Sequence - TCGA

Cancer.gov

Carolyn Hutter, Ph.D., Program Director of NHGRI's Division of Genomic Medicine, discusses the expansion of TCGA's Pan-Cancer efforts to include the Pan-Cancer Analysis of Whole Genomes (PAWG) project.

The Impact of the Cancer Genome Atlas on Lung Cancer

PubMed Central

Chang, Jeremy Tzu-Huai; Lee, Yee-Ming; Huang, R. Stephanie

2015-01-01

The Cancer Genome Atlas (TCGA) has profiled over 10,000 samples derived from 33 types of cancer to date, with the goal of improving our understanding of the molecular basis of cancer and advancing our ability to diagnose, treat, and prevent cancer. This review focuses on lung cancer as it is the leading cause of cancer-related mortality worldwide in both men and women. Particularly, non-small cell lung cancers (including lung adenocarcinoma and lung squamous cell carcinoma) were evaluated. Our goal is to demonstrate the impact of TCGA on lung cancer research under four themes: namely, diagnostic markers, disease progression markers, novel therapeutic targets, and novel tools. Examples were given related to DNA mutation, copy number variation, mRNA, and microRNA expression along with methylation profiling. PMID:26318634

Comprehensive genomic profiles of small cell lung cancer

PubMed Central

George, Julie; Lim, Jing Shan; Jang, Se Jin; Cun, Yupeng; Ozretić, Luka; Kong, Gu; Leenders, Frauke; Lu, Xin; Fernández-Cuesta, Lynnette; Bosco, Graziella; Müller, Christian; Dahmen, Ilona; Jahchan, Nadine S.; Park, Kwon-Sik; Yang, Dian; Karnezis, Anthony N.; Vaka, Dedeepya; Torres, Angela; Wang, Maia Segura; Korbel, Jan O.; Menon, Roopika; Chun, Sung-Min; Kim, Deokhoon; Wilkerson, Matt; Hayes, Neil; Engelmann, David; Pützer, Brigitte; Bos, Marc; Michels, Sebastian; Vlasic, Ignacija; Seidel, Danila; Pinther, Berit; Schaub, Philipp; Becker, Christian; Altmüller, Janine; Yokota, Jun; Kohno, Takashi; Iwakawa, Reika; Tsuta, Koji; Noguchi, Masayuki; Muley, Thomas; Hoffmann, Hans; Schnabel, Philipp A.; Petersen, Iver; Chen, Yuan; Soltermann, Alex; Tischler, Verena; Choi, Chang-min; Kim, Yong-Hee; Massion, Pierre P.; Zou, Yong; Jovanovic, Dragana; Kontic, Milica; Wright, Gavin M.; Russell, Prudence A.; Solomon, Benjamin; Koch, Ina; Lindner, Michael; Muscarella, Lucia A.; la Torre, Annamaria; Field, John K.; Jakopovic, Marko; Knezevic, Jelena; Castaños-Vélez, Esmeralda; Roz, Luca; Pastorino, Ugo; Brustugun, Odd-Terje; Lund-Iversen, Marius; Thunnissen, Erik; Köhler, Jens; Schuler, Martin; Botling, Johan; Sandelin, Martin; Sanchez-Cespedes, Montserrat; Salvesen, Helga B.; Achter, Viktor; Lang, Ulrich; Bogus, Magdalena; Schneider, Peter M.; Zander, Thomas; Ansén, Sascha; Hallek, Michael; Wolf, Jürgen; Vingron, Martin; Yatabe, Yasushi; Travis, William D.; Nürnberg, Peter; Reinhardt, Christian; Perner, Sven; Heukamp, Lukas; Büttner, Reinhard; Haas, Stefan A.; Brambilla, Elisabeth; Peifer, Martin; Sage, Julien; Thomas, Roman K.

2016-01-01

We have sequenced the genomes of 110 small cell lung cancers (SCLC), one of the deadliest human cancers. In nearly all the tumours analysed we found bi-allelic inactivation of TP53 and RB1, sometimes by complex genomic rearrangements. Two tumours with wild-type RB1 had evidence of chromothripsis leading to overexpression of cyclin D1 (encoded by the CCND1 gene), revealing an alternative mechanism of Rb1 deregulation. Thus, loss of the tumour suppressors TP53 and RB1 is obligatory in SCLC. We discovered somatic genomic rearrangements of TP73 that create an oncogenic version of this gene, TP73Δex2/3. In rare cases, SCLC tumours exhibited kinase gene mutations, providing a possible therapeutic opportunity for individual patients. Finally, we observed inactivating mutations in NOTCH family genes in 25% of human SCLC. Accordingly, activation of Notch signalling in a pre-clinical SCLC mouse model strikingly reduced the number of tumours and extended the survival of the mutant mice. Furthermore, neuroendocrine gene expression was abrogated by Notch activity in SCLC cells. This first comprehensive study of somatic genome alterations in SCLC uncovers several key biological processes and identifies candidate therapeutic targets in this highly lethal form of cancer. PMID:26168399

Genome Sequencing and Analysis of the Tasmanian Devil and Its Transmissible Cancer

PubMed Central

Murchison, Elizabeth P.; Schulz-Trieglaff, Ole B.; Ning, Zemin; Alexandrov, Ludmil B.; Bauer, Markus J.; Fu, Beiyuan; Hims, Matthew; Ding, Zhihao; Ivakhno, Sergii; Stewart, Caitlin; Ng, Bee Ling; Wong, Wendy; Aken, Bronwen; White, Simon; Alsop, Amber; Becq, Jennifer; Bignell, Graham R.; Cheetham, R. Keira; Cheng, William; Connor, Thomas R.; Cox, Anthony J.; Feng, Zhi-Ping; Gu, Yong; Grocock, Russell J.; Harris, Simon R.; Khrebtukova, Irina; Kingsbury, Zoya; Kowarsky, Mark; Kreiss, Alexandre; Luo, Shujun; Marshall, John; McBride, David J.; Murray, Lisa; Pearse, Anne-Maree; Raine, Keiran; Rasolonjatovo, Isabelle; Shaw, Richard; Tedder, Philip; Tregidgo, Carolyn; Vilella, Albert J.; Wedge, David C.; Woods, Gregory M.; Gormley, Niall; Humphray, Sean; Schroth, Gary; Smith, Geoffrey; Hall, Kevin; Searle, Stephen M.J.; Carter, Nigel P.; Papenfuss, Anthony T.; Futreal, P. Andrew; Campbell, Peter J.; Yang, Fengtang; Bentley, David R.; Evers, Dirk J.; Stratton, Michael R.

2012-01-01

Summary The Tasmanian devil (Sarcophilus harrisii), the largest marsupial carnivore, is endangered due to a transmissible facial cancer spread by direct transfer of living cancer cells through biting. Here we describe the sequencing, assembly, and annotation of the Tasmanian devil genome and whole-genome sequences for two geographically distant subclones of the cancer. Genomic analysis suggests that the cancer first arose from a female Tasmanian devil and that the clone has subsequently genetically diverged during its spread across Tasmania. The devil cancer genome contains more than 17,000 somatic base substitution mutations and bears the imprint of a distinct mutational process. Genotyping of somatic mutations in 104 geographically and temporally distributed Tasmanian devil tumors reveals the pattern of evolution and spread of this parasitic clonal lineage, with evidence of a selective sweep in one geographical area and persistence of parallel lineages in other populations. PaperClip PMID:22341448

Prediction of individualized therapeutic vulnerabilities in cancer from genomic profiles

PubMed Central

Aksoy, Bülent Arman; Demir, Emek; Babur, Özgün; Wang, Weiqing; Jing, Xiaohong; Schultz, Nikolaus; Sander, Chris

2014-01-01

Motivation: Somatic homozygous deletions of chromosomal regions in cancer, while not necessarily oncogenic, may lead to therapeutic vulnerabilities specific to cancer cells compared with normal cells. A recently reported example is the loss of one of the two isoenzymes in glioblastoma cancer cells such that the use of a specific inhibitor selectively inhibited growth of the cancer cells, which had become fully dependent on the second isoenzyme. We have now made use of the unprecedented conjunction of large-scale cancer genomics profiling of tumor samples in The Cancer Genome Atlas (TCGA) and of tumor-derived cell lines in the Cancer Cell Line Encyclopedia, as well as the availability of integrated pathway information systems, such as Pathway Commons, to systematically search for a comprehensive set of such epistatic vulnerabilities. Results: Based on homozygous deletions affecting metabolic enzymes in 16 TCGA cancer studies and 972 cancer cell lines, we identified 4104 candidate metabolic vulnerabilities present in 1019 tumor samples and 482 cell lines. Up to 44% of these vulnerabilities can be targeted with at least one Food and Drug Administration-approved drug. We suggest focused experiments to test these vulnerabilities and clinical trials based on personalized genomic profiles of those that pass preclinical filters. We conclude that genomic profiling will in the future provide a promising basis for network pharmacology of epistatic vulnerabilities as a promising therapeutic strategy. Availability and implementation: A web-based tool for exploring all vulnerabilities and their details is available at http://cbio.mskcc.org/cancergenomics/statius/ along with supplemental data files. Contact: statius@cbio.mskcc.org Supplementary information: Supplementary data are available at Bioinformatics online. PMID:24665131

CTD² Publication Guidelines | Office of Cancer Genomics

Cancer.gov

The Cancer Target Discovery and Development (CTD2) Network is a “community resource project” supported by the National Cancer Institute’s Office of Cancer Genomics. Members of the Network release data to the broader research community by depositing data into NCI-supported or public databases. Data deposition is NOT equivalent to publishing in a peer-reviewed journal. Unless there is a manuscript associated with a dataset, the Network considers data to be formally unpublished.

Focusing on function to mine cancer genome data | Center for Cancer Research

Cancer.gov

CCR scientists have devised a strategy to sift through the tens of thousands of mutations in cancer genome data to find mutations that actually drive the disease. They have used the method to discover that the JNK signaling pathway, which in different contexts can either spur cancerous growth or rein it in, acts as a tumor suppressor in gastric cancers. 

Functional genomic Landscape of Human Breast Cancer drivers, vulnerabilities, and resistance

PubMed Central

Marcotte, Richard; Sayad, Azin; Brown, Kevin R.; Sanchez-Garcia, Felix; Reimand, Jüri; Haider, Maliha; Virtanen, Carl; Bradner, James E.; Bader, Gary D.; Mills, Gordon B.; Pe’er, Dana; Moffat, Jason; Neel, Benjamin G.

2016-01-01

Summary Large-scale genomic studies have identified multiple somatic aberrations in breast cancer, including copy number alterations, and point mutations. Still, identifying causal variants and emergent vulnerabilities that arise as a consequence of genetic alterations remain major challenges. We performed whole genome shRNA “dropout screens” on 77 breast cancer cell lines. Using a hierarchical linear regression algorithm to score our screen results and integrate them with accompanying detailed genetic and proteomic information, we identify vulnerabilities in breast cancer, including candidate “drivers,” and reveal general functional genomic properties of cancer cells. Comparisons of gene essentiality with drug sensitivity data suggest potential resistance mechanisms, effects of existing anti-cancer drugs, and opportunities for combination therapy. Finally, we demonstrate the utility of this large dataset by identifying BRD4 as a potential target in luminal breast cancer, and PIK3CA mutations as a resistance determinant for BET-inhibitors. PMID:26771497

Functional Genomic Landscape of Human Breast Cancer Drivers, Vulnerabilities, and Resistance.

PubMed

Marcotte, Richard; Sayad, Azin; Brown, Kevin R; Sanchez-Garcia, Felix; Reimand, Jüri; Haider, Maliha; Virtanen, Carl; Bradner, James E; Bader, Gary D; Mills, Gordon B; Pe'er, Dana; Moffat, Jason; Neel, Benjamin G

2016-01-14

Large-scale genomic studies have identified multiple somatic aberrations in breast cancer, including copy number alterations and point mutations. Still, identifying causal variants and emergent vulnerabilities that arise as a consequence of genetic alterations remain major challenges. We performed whole-genome small hairpin RNA (shRNA) "dropout screens" on 77 breast cancer cell lines. Using a hierarchical linear regression algorithm to score our screen results and integrate them with accompanying detailed genetic and proteomic information, we identify vulnerabilities in breast cancer, including candidate "drivers," and reveal general functional genomic properties of cancer cells. Comparisons of gene essentiality with drug sensitivity data suggest potential resistance mechanisms, effects of existing anti-cancer drugs, and opportunities for combination therapy. Finally, we demonstrate the utility of this large dataset by identifying BRD4 as a potential target in luminal breast cancer and PIK3CA mutations as a resistance determinant for BET-inhibitors. Copyright © 2016 Elsevier Inc. All rights reserved.

GEMINI: Integrative Exploration of Genetic Variation and Genome Annotations

PubMed Central

Paila, Umadevi; Chapman, Brad A.; Kirchner, Rory; Quinlan, Aaron R.

2013-01-01

Modern DNA sequencing technologies enable geneticists to rapidly identify genetic variation among many human genomes. However, isolating the minority of variants underlying disease remains an important, yet formidable challenge for medical genetics. We have developed GEMINI (GEnome MINIng), a flexible software package for exploring all forms of human genetic variation. Unlike existing tools, GEMINI integrates genetic variation with a diverse and adaptable set of genome annotations (e.g., dbSNP, ENCODE, UCSC, ClinVar, KEGG) into a unified database to facilitate interpretation and data exploration. Whereas other methods provide an inflexible set of variant filters or prioritization methods, GEMINI allows researchers to compose complex queries based on sample genotypes, inheritance patterns, and both pre-installed and custom genome annotations. GEMINI also provides methods for ad hoc queries and data exploration, a simple programming interface for custom analyses that leverage the underlying database, and both command line and graphical tools for common analyses. We demonstrate GEMINI's utility for exploring variation in personal genomes and family based genetic studies, and illustrate its ability to scale to studies involving thousands of human samples. GEMINI is designed for reproducibility and flexibility and our goal is to provide researchers with a standard framework for medical genomics. PMID:23874191

A Decision Support Framework for Genomically Informed Investigational Cancer Therapy

PubMed Central

Johnson, Amber; Holla, Vijaykumar; Bailey, Ann Marie; Brusco, Lauren; Chen, Ken; Routbort, Mark; Patel, Keyur P.; Zeng, Jia; Kopetz, Scott; Davies, Michael A.; Piha-Paul, Sarina A.; Hong, David S.; Eterovic, Agda Karina; Tsimberidou, Apostolia M.; Broaddus, Russell; Bernstam, Elmer V.; Shaw, Kenna R.; Mendelsohn, John; Mills, Gordon B.

2015-01-01

Rapidly improving understanding of molecular oncology, emerging novel therapeutics, and increasingly available and affordable next-generation sequencing have created an opportunity for delivering genomically informed personalized cancer therapy. However, to implement genomically informed therapy requires that a clinician interpret the patient’s molecular profile, including molecular characterization of the tumor and the patient’s germline DNA. In this Commentary, we review existing data and tools for precision oncology and present a framework for reviewing the available biomedical literature on therapeutic implications of genomic alterations. Genomic alterations, including mutations, insertions/deletions, fusions, and copy number changes, need to be curated in terms of the likelihood that they alter the function of a “cancer gene” at the level of a specific variant in order to discriminate so-called “drivers” from “passengers.” Alterations that are targetable either directly or indirectly with approved or investigational therapies are potentially “actionable.” At this time, evidence linking predictive biomarkers to therapies is strong for only a few genomic markers in the context of specific cancer types. For these genomic alterations in other diseases and for other genomic alterations, the clinical data are either absent or insufficient to support routine clinical implementation of biomarker-based therapy. However, there is great interest in optimally matching patients to early-phase clinical trials. Thus, we need accessible, comprehensive, and frequently updated knowledge bases that describe genomic changes and their clinical implications, as well as continued education of clinicians and patients. PMID:25863335

Targeted or whole genome sequencing of formalin fixed tissue samples: potential applications in cancer genomics.

PubMed

Munchel, Sarah; Hoang, Yen; Zhao, Yue; Cottrell, Joseph; Klotzle, Brandy; Godwin, Andrew K; Koestler, Devin; Beyerlein, Peter; Fan, Jian-Bing; Bibikova, Marina; Chien, Jeremy

2015-09-22

Current genomic studies are limited by the poor availability of fresh-frozen tissue samples. Although formalin-fixed diagnostic samples are in abundance, they are seldom used in current genomic studies because of the concern of formalin-fixation artifacts. Better characterization of these artifacts will allow the use of archived clinical specimens in translational and clinical research studies. To provide a systematic analysis of formalin-fixation artifacts on Illumina sequencing, we generated 26 DNA sequencing data sets from 13 pairs of matched formalin-fixed paraffin-embedded (FFPE) and fresh-frozen (FF) tissue samples. The results indicate high rate of concordant calls between matched FF/FFPE pairs at reference and variant positions in three commonly used sequencing approaches (whole genome, whole exome, and targeted exon sequencing). Global mismatch rates and C · G > T · A substitutions were comparable between matched FF/FFPE samples, and discordant rates were low (<0.26%) in all samples. Finally, low-pass whole genome sequencing produces similar pattern of copy number alterations between FF/FFPE pairs. The results from our studies suggest the potential use of diagnostic FFPE samples for cancer genomic studies to characterize and catalog variations in cancer genomes.

Approaches to integrating germline and tumor genomic data in cancer research

PubMed Central

Feigelson, Heather Spencer; Goddard, Katrina A.B.; Hollombe, Celine; Tingle, Sharna R.; Gillanders, Elizabeth M.; Mechanic, Leah E.; Nelson, Stefanie A.

2014-01-01

Cancer is characterized by a diversity of genetic and epigenetic alterations occurring in both the germline and somatic (tumor) genomes. Hundreds of germline variants associated with cancer risk have been identified, and large amounts of data identifying mutations in the tumor genome that participate in tumorigenesis have been generated. Increasingly, these two genomes are being explored jointly to better understand how cancer risk alleles contribute to carcinogenesis and whether they influence development of specific tumor types or mutation profiles. To understand how data from germline risk studies and tumor genome profiling is being integrated, we reviewed 160 articles describing research that incorporated data from both genomes, published between January 2009 and December 2012, and summarized the current state of the field. We identified three principle types of research questions being addressed using these data: (i) use of tumor data to determine the putative function of germline risk variants; (ii) identification and analysis of relationships between host genetic background and particular tumor mutations or types; and (iii) use of tumor molecular profiling data to reduce genetic heterogeneity or refine phenotypes for germline association studies. We also found descriptive studies that compared germline and tumor genomic variation in a gene or gene family, and papers describing research methods, data sources, or analytical tools. We identified a large set of tools and data resources that can be used to analyze and integrate data from both genomes. Finally, we discuss opportunities and challenges for cancer research that integrates germline and tumor genomics data. PMID:25115441

CRISPR/Cas9: From Genome Engineering to Cancer Drug Discovery

PubMed Central

Luo, Ji

2016-01-01

Advances in translational research are often driven by new technologies. The advent of microarrays, next-generation sequencing, proteomics and RNA interference (RNAi) have led to breakthroughs in our understanding of the mechanisms of cancer and the discovery of new cancer drug targets. The discovery of the bacterial clustered regularly interspaced palindromic repeat (CRISPR) system and its subsequent adaptation as a tool for mammalian genome engineering has opened up new avenues for functional genomics studies. This review will focus on the utility of CRISPR in the context of cancer drug target discovery. PMID:28603775

Intratumoral and Intertumoral Genomic Heterogeneity of Multifocal Localized Prostate Cancer Impacts Molecular Classifications and Genomic Prognosticators

PubMed Central

Wei, Lei; Wang, Jianmin; Lampert, Erika; Schlanger, Simon; DePriest, Adam D.; Hu, Qiang; Gomez, Eduardo Cortes; Murakam, Mitsuko; Glenn, Sean T.; Conroy, Jeffrey; Morrison, Carl; Azabdaftari, Gissou; Mohler, James L.; Liu, Song; Heemers, Hannelore V.

2018-01-01

Background Next-generation sequencing is revealing genomic heterogeneity in localized prostate cancer (CaP). Incomplete sampling of CaP multiclonality has limited the implications for molecular subtyping, stratification, and systemic treatment. Objective To determine the impact of genomic and transcriptomic diversity within and among intraprostatic CaP foci on CaP molecular taxonomy, predictors of progression, and actionable therapeutic targets. Design, setting, and participants Four consecutive patients with clinically localized National Comprehensive Cancer Network intermediate- or high-risk CaP who did not receive neoadjuvant therapy underwent radical prostatectomy at Roswell Park Cancer Institute in June–July 2014. Presurgical information on CaP content and a customized tissue procurement procedure were used to isolate nonmicroscopic and noncontiguous CaP foci in radical prostatectomy specimens. Three cores were obtained from the index lesion and one core from smaller lesions. RNA and DNA were extracted simultaneously from 26 cores with ≥90% CaP content and analyzed using whole-exome sequencing, single-nucleotide polymorphism arrays, and RNA sequencing. Outcome measurements and statistical analysis Somatic mutations, copy number alternations, gene expression, gene fusions, and phylogeny were defined. The impact of genomic alterations on CaP molecular classification, gene sets measured in Oncotype DX, Prolaris, and Decipher assays, and androgen receptor activity among CaP cores was determined. Results and limitations There was considerable variability in genomic alterations among CaP cores, and between RNA- and DNA-based platforms. Heterogeneity was found in molecular grouping of individual CaP foci and the activity of gene sets underlying the assays for risk stratification and androgen receptor activity, and was validated in independent genomic data sets. Determination of the implications for clinical decision-making requires follow-up studies. Conclusions

The mediator complex in genomic and non-genomic signaling in cancer.

PubMed

Weber, Hannah; Garabedian, Michael J

2018-05-01

Mediator is a conserved, multi-subunit macromolecular machine divided structurally into head, middle, and tail modules, along with a transiently associating kinase module. Mediator functions as an integrator of transcriptional regulatory activity by interacting with DNA-bound transcription factors and with RNA polymerase II (Pol II) to both activate and repress gene expression. Mediator has been shown to affect multiple steps in transcription, including chromatin looping between enhancers and promoters, pre-initiation complex formation, transcriptional elongation, and mRNA splicing. Individual Mediator subunits participate in regulation of gene expression by the estrogen and androgen receptors and are altered in a number of endocrine cancers, including breast and prostate cancer. In addition to its role in genomic signaling, MED12 has been implicated in non-genomic signaling by interacting with and activating TGF-beta receptor 2 in the cytoplasm. Recent structural studies have revealed extensive inter-domain interactions and complex architecture of the Mediator-Pol II complex, suggesting that Mediator is capable of reorganizing its conformation and composition to fit cellular needs. We propose that alterations in Mediator subunit expression that occur in various cancers could impact the organization and function of Mediator, resulting in changes in gene expression that promote malignancy. A better understanding of the role of Mediator in cancer could reveal new approaches to the diagnosis and treatment of Mediator-dependent endocrine cancers, especially in settings of therapy resistance. Copyright © 2017 Elsevier Inc. All rights reserved.

Genomic Evolution of Breast Cancer Metastasis and Relapse

DOE PAGES

Yates, Lucy R.; Knappskog, Stian; Wedge, David; ...

2017-08-14

Patterns of genomic evolution between primary and metastatic breast cancer have not been studied in large numbers, despite patients with metastatic breast cancer having dismal survival. We sequenced whole genomes or a panel of 365 genes on 299 samples from 170 patients with locally relapsed or metastatic breast cancer. Several lines of analysis indicate that clones seeding metastasis or relapse disseminate late from primary tumors, but continue to acquire mutations, mostly accessing the same mutational processes active in the primary tumor. Most distant metastases acquired driver mutations not seen in the primary tumor, drawing from a wider repertoire of cancermore » genes than early drivers. Lastly, these include a number of clinically actionable alterations and mutations inactivating SWI-SNF and JAK2-STAT3 pathways.« less

Genomic Evolution of Breast Cancer Metastasis and Relapse

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

Yates, Lucy R.; Knappskog, Stian; Wedge, David

Patterns of genomic evolution between primary and metastatic breast cancer have not been studied in large numbers, despite patients with metastatic breast cancer having dismal survival. We sequenced whole genomes or a panel of 365 genes on 299 samples from 170 patients with locally relapsed or metastatic breast cancer. Several lines of analysis indicate that clones seeding metastasis or relapse disseminate late from primary tumors, but continue to acquire mutations, mostly accessing the same mutational processes active in the primary tumor. Most distant metastases acquired driver mutations not seen in the primary tumor, drawing from a wider repertoire of cancermore » genes than early drivers. Lastly, these include a number of clinically actionable alterations and mutations inactivating SWI-SNF and JAK2-STAT3 pathways.« less

The genomic complexity of primary human prostate cancer

PubMed Central

Berger, Michael F.; Lawrence, Michael S.; Demichelis, Francesca; Drier, Yotam; Cibulskis, Kristian; Sivachenko, Andrey Y.; Sboner, Andrea; Esgueva, Raquel; Pflueger, Dorothee; Sougnez, Carrie; Onofrio, Robert; Carter, Scott L.; Park, Kyung; Habegger, Lukas; Ambrogio, Lauren; Fennell, Timothy; Parkin, Melissa; Saksena, Gordon; Voet, Douglas; Ramos, Alex H.; Pugh, Trevor J.; Wilkinson, Jane; Fisher, Sheila; Winckler, Wendy; Mahan, Scott; Ardlie, Kristin; Baldwin, Jennifer; Simons, Jonathan W.; Kitabayashi, Naoki; MacDonald, Theresa Y.; Kantoff, Philip W.; Chin, Lynda; Gabriel, Stacey B.; Gerstein, Mark B.; Golub, Todd R.; Meyerson, Matthew; Tewari, Ashutosh; Lander, Eric S.; Getz, Gad; Rubin, Mark A.; Garraway, Levi A.

2010-01-01

Prostate cancer is the second most common cause of male cancer deaths in the United States. Here we present the complete sequence of seven primary prostate cancers and their paired normal counterparts. Several tumors contained complex chains of balanced rearrangements that occurred within or adjacent to known cancer genes. Rearrangement breakpoints were enriched near open chromatin, androgen receptor and ERG DNA binding sites in the setting of the ETS gene fusion TMPRSS2-ERG, but inversely correlated with these regions in tumors lacking ETS fusions. This observation suggests a link between chromatin or transcriptional regulation and the genesis of genomic aberrations. Three tumors contained rearrangements that disrupted CADM2, and four harbored events disrupting either PTEN (unbalanced events), a prostate tumor suppressor, or MAGI2 (balanced events), a PTEN interacting protein not previously implicated in prostate tumorigenesis. Thus, genomic rearrangements may arise from transcriptional or chromatin aberrancies to engage prostate tumorigenic mechanisms. PMID:21307934

CRISPR-Cas9: from Genome Editing to Cancer Research

PubMed Central

Chen, Si; Sun, Heng; Miao, Kai; Deng, Chu-Xia

2016-01-01

Cancer development is a multistep process triggered by innate and acquired mutations, which cause the functional abnormality and determine the initiation and progression of tumorigenesis. Gene editing is a widely used engineering tool for generating mutations that enhance tumorigenesis. The recent developed clustered regularly interspaced short palindromic repeats-CRISPR-associated 9 (CRISPR-Cas9) system renews the genome editing approach into a more convenient and efficient way. By rapidly introducing genetic modifications in cell lines, organs and animals, CRISPR-Cas9 system extends the gene editing into whole genome screening, both in loss-of-function and gain-of-function manners. Meanwhile, the system accelerates the establishment of animal cancer models, promoting in vivo studies for cancer research. Furthermore, CRISPR-Cas9 system is modified into diverse innovative tools for observing the dynamic bioprocesses in cancer studies, such as image tracing for targeted DNA, regulation of transcription activation or repression. Here, we view recent technical advances in the application of CRISPR-Cas9 system in cancer genetics, large-scale cancer driver gene hunting, animal cancer modeling and functional studies. PMID:27994508

Carcinogen susceptibility is regulated by genome architecture and predicts cancer mutagenesis.

PubMed

García-Nieto, Pablo E; Schwartz, Erin K; King, Devin A; Paulsen, Jonas; Collas, Philippe; Herrera, Rafael E; Morrison, Ashby J

2017-10-02

The development of many sporadic cancers is directly initiated by carcinogen exposure. Carcinogens induce malignancies by creating DNA lesions (i.e., adducts) that can result in mutations if left unrepaired. Despite this knowledge, there has been remarkably little investigation into the regulation of susceptibility to acquire DNA lesions. In this study, we present the first quantitative human genome-wide map of DNA lesions induced by ultraviolet (UV) radiation, the ubiquitous carcinogen in sunlight that causes skin cancer. Remarkably, the pattern of carcinogen susceptibility across the genome of primary cells significantly reflects mutation frequency in malignant melanoma. Surprisingly, DNase-accessible euchromatin is protected from UV, while lamina-associated heterochromatin at the nuclear periphery is vulnerable. Many cancer driver genes have an intrinsic increase in carcinogen susceptibility, including the BRAF oncogene that has the highest mutation frequency in melanoma. These findings provide a genome-wide snapshot of DNA injuries at the earliest stage of carcinogenesis. Furthermore, they identify carcinogen susceptibility as an origin of genome instability that is regulated by nuclear architecture and mirrors mutagenesis in cancer. © 2017 The Authors.

A Genome-Wide Investigation of Autozygosity and Breast Cancer Risk

DTIC Science & Technology

2011-07-01

cases than in controls, using logistic regression methods. Using genome-wide SNP data (525,000 SNPs) on 1,647 non-Hispanic white, early-onset...premenopausal breast cancer cases and 1,556 matched controls we identified over 65,000 individual RoHs and 423 genomic regions harbor RoHs for at least 10...we hypothesize that germline autozygosity is more common in breast cancer cases than in controls. More specifically, we hypothesize that there are

Integrative Clinical Genomics of Metastatic Cancer

PubMed Central

Robinson, Dan R.; Wu, Yi-Mi; Lonigro, Robert J.; Vats, Pankaj; Cobain, Erin; Everett, Jessica; Cao, Xuhong; Rabban, Erica; Kumar-Sinha, Chandan; Raymond, Victoria; Schuetze, Scott; Alva, Ajjai; Siddiqui, Javed; Chugh, Rashmi; Worden, Francis; Zalupski, Mark M.; Innis, Jeffrey; Mody, Rajen J.; Tomlins, Scott A.; Lucas, David; Baker, Laurence H.; Ramnath, Nithya; Schott, Ann F.; Hayes, Daniel F.; Vijai, Joseph; Offit, Kenneth; Stoffel, Elena M.; Roberts, J. Scott; Smith, David C.; Kunju, Lakshmi P.; Talpaz, Moshe; Cieslik, Marcin; Chinnaiyan, Arul M.

2017-01-01

SUMMARY Metastasis is the primary cause of cancer-related deaths. While The Cancer Genome Atlas (TCGA) has sequenced primary tumor types obtained from surgical resections, much less comprehensive molecular analysis is available from clinically acquired metastatic cancers. Here, we perform whole exome and transcriptome sequencing of 500 adult patients with metastatic solid tumors of diverse lineage and biopsy site. The most prevalent genes somatically altered in metastatic cancer included TP53, CDKN2A, PTEN, PIK3CA, and RB1. Putative pathogenic germline variants were present in 12.2% of cases of which 75% were related to defects in DNA repair. RNA sequencing complemented DNA sequencing for the identification of gene fusions, pathway activation, and immune profiling. Integrative sequence analysis provides a clinically relevant, multi-dimensional view of the complex molecular landscape and microenvironment of metastatic cancers. PMID:28783718

Genomic copy number variations in three Southeast Asian populations.

PubMed

Ku, Chee-Seng; Pawitan, Yudi; Sim, Xueling; Ong, Rick T H; Seielstad, Mark; Lee, Edmund J D; Teo, Yik-Ying; Chia, Kee-Seng; Salim, Agus

2010-07-01

Research on the role of copy number variations (CNVs) in the genetic risk of diseases in Asian populations has been hampered by a relative lack of reference CNV maps for Asian populations outside the East Asians. In this article, we report the population characteristics of CNVs in Chinese, Malay, and Asian Indian populations in Singapore. Using the Illumina Human 1M Beadchip array, we identify 1,174 CNV loci in these populations that corroborated with findings when the same samples were typed on the Affymetrix 6.0 platform. We identify 441 novel loci not previously reported in the Database of Genomic Variations (DGV). We observe a considerable number of loci that span all three populations and were previously unreported, as well as population-specific loci that are quite common in the respective populations. From this we observe the distribution of CNVs in the Asian Indian population to be considerably different from the Chinese and Malay populations. About half of the deletion loci and three-quarters of duplication loci overlap UCSC genes. Tens of loci show population differentiation and overlap with genes previously known to be associated with genetic risk of diseases. One of these loci is the CYP2A6 deletion, previously linked to reduced susceptibility to lung cancer. (c) 2010 Wiley-Liss, Inc.

Inferences of drug responses in cancer cells from cancer genomic features and compound chemical and therapeutic properties

PubMed Central

Wang, Yongcui; Fang, Jianwen; Chen, Shilong

2016-01-01

Accurately predicting the response of a cancer patient to a therapeutic agent is a core goal of precision medicine. Existing approaches were mainly relied primarily on genomic alterations in cancer cells that have been treated with different drugs. Here we focus on predicting drug response based on integration of the heterogeneously pharmacogenomics data from both cell and drug sides. Through a systematical approach, named as PDRCC (Predict Drug Response in Cancer Cells), the cancer genomic alterations and compound chemical and therapeutic properties were incorporated to determine the chemotherapeutic response in cancer patients. Using the Cancer Cell Line Encyclopedia (CCLE) study as the benchmark dataset, all pharmacogenomics data exhibited their roles in inferring the relationships between cancer cells and drugs. When integrating both genomic resources and compound information, the prediction coverage was significantly increased. The validity of PDRCC was also supported by its effective in uncovering the unknown cell-drug associations with database and literature evidences. It set the stage for clinical testing of novel therapeutic strategies, such as the sensitive association between cancer cell ‘A549_LUNG’ and compound ‘Topotecan’. In conclusion, PDRCC offers the possibility for faster, safer, and cheaper the development of novel anti-cancer therapeutics in the early-stage clinical trails. PMID:27645580

Inferences of drug responses in cancer cells from cancer genomic features and compound chemical and therapeutic properties

NASA Astrophysics Data System (ADS)

Wang, Yongcui; Fang, Jianwen; Chen, Shilong

2016-09-01

Accurately predicting the response of a cancer patient to a therapeutic agent is a core goal of precision medicine. Existing approaches were mainly relied primarily on genomic alterations in cancer cells that have been treated with different drugs. Here we focus on predicting drug response based on integration of the heterogeneously pharmacogenomics data from both cell and drug sides. Through a systematical approach, named as PDRCC (Predict Drug Response in Cancer Cells), the cancer genomic alterations and compound chemical and therapeutic properties were incorporated to determine the chemotherapeutic response in cancer patients. Using the Cancer Cell Line Encyclopedia (CCLE) study as the benchmark dataset, all pharmacogenomics data exhibited their roles in inferring the relationships between cancer cells and drugs. When integrating both genomic resources and compound information, the prediction coverage was significantly increased. The validity of PDRCC was also supported by its effective in uncovering the unknown cell-drug associations with database and literature evidences. It set the stage for clinical testing of novel therapeutic strategies, such as the sensitive association between cancer cell ‘A549_LUNG’ and compound ‘Topotecan’. In conclusion, PDRCC offers the possibility for faster, safer, and cheaper the development of novel anti-cancer therapeutics in the early-stage clinical trails.

Inferences of drug responses in cancer cells from cancer genomic features and compound chemical and therapeutic properties.

PubMed

Wang, Yongcui; Fang, Jianwen; Chen, Shilong

2016-09-20

Accurately predicting the response of a cancer patient to a therapeutic agent is a core goal of precision medicine. Existing approaches were mainly relied primarily on genomic alterations in cancer cells that have been treated with different drugs. Here we focus on predicting drug response based on integration of the heterogeneously pharmacogenomics data from both cell and drug sides. Through a systematical approach, named as PDRCC (Predict Drug Response in Cancer Cells), the cancer genomic alterations and compound chemical and therapeutic properties were incorporated to determine the chemotherapeutic response in cancer patients. Using the Cancer Cell Line Encyclopedia (CCLE) study as the benchmark dataset, all pharmacogenomics data exhibited their roles in inferring the relationships between cancer cells and drugs. When integrating both genomic resources and compound information, the prediction coverage was significantly increased. The validity of PDRCC was also supported by its effective in uncovering the unknown cell-drug associations with database and literature evidences. It set the stage for clinical testing of novel therapeutic strategies, such as the sensitive association between cancer cell 'A549_LUNG' and compound 'Topotecan'. In conclusion, PDRCC offers the possibility for faster, safer, and cheaper the development of novel anti-cancer therapeutics in the early-stage clinical trails.

Genomic landscape of gastric cancer: molecular classification and potential targets.

PubMed

Guo, Jiawei; Yu, Weiwei; Su, Hui; Pang, Xiufeng

2017-02-01

Gastric cancer imposes a considerable health burden worldwide, and its mortality ranks as the second highest for all types of cancers. The limited knowledge of the molecular mechanisms underlying gastric cancer tumorigenesis hinders the development of therapeutic strategies. However, ongoing collaborative sequencing efforts facilitate molecular classification and unveil the genomic landscape of gastric cancer. Several new drivers and tumorigenic pathways in gastric cancer, including chromatin remodeling genes, RhoA-related pathways, TP53 dysregulation, activation of receptor tyrosine kinases, stem cell pathways and abnormal DNA methylation, have been revealed. These newly identified genomic alterations await translation into clinical diagnosis and targeted therapies. Considering that loss-of-function mutations are intractable, synthetic lethality could be employed when discussing feasible therapeutic strategies. Although many challenges remain to be tackled, we are optimistic regarding improvements in the prognosis and treatment of gastric cancer in the near future.

Genomic alterations and molecular subtypes of gastric cancers in Asians.

PubMed

Ye, Xiang S; Yu, Chunping; Aggarwal, Amit; Reinhard, Christoph

2016-05-09

Gastric cancer (GC) is a highly heterogenic disease, and it is the second leading cause of cancer death in the world. Common chemotherapies are not very effective for GC, which often presents as an advanced or metastatic disease at diagnosis. Treatment options are limited, and the prognosis for advanced GCs is poor. The landscape of genomic alterations in GCs has recently been characterized by several international cancer genome programs, including studies that focused exclusively on GCs in Asians. These studies identified major recurrent driver mutations and provided new insights into the mutational heterogeneity and genetic profiles of GCs. An analysis of gene expression data by the Asian Cancer Research Group (ACRG) further uncovered four distinct molecular subtypes with well-defined clinical features and their intersections with actionable genetic alterations to which targeted therapeutic agents are either already available or under clinical development. In this article, we review the ACRG GC project. We also discuss the implications of the genetic and molecular findings from various GC genomic studies with respect to developing more precise diagnoses and treatment approaches for GCs.

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

PubMed Central

2013-01-01

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

Genome scan study of prostate cancer in Arabs: identification of three genomic regions with multiple prostate cancer susceptibility loci in Tunisians.

PubMed

Shan, Jingxuan; Al-Rumaihi, Khalid; Rabah, Danny; Al-Bozom, Issam; Kizhakayil, Dhanya; Farhat, Karim; Al-Said, Sami; Kfoury, Hala; Dsouza, Shoba P; Rowe, Jillian; Khalak, Hanif G; Jafri, Shahzad; Aigha, Idil I; Chouchane, Lotfi

2013-05-13

Large databases focused on genetic susceptibility to prostate cancer have been accumulated from population studies of different ancestries, including Europeans and African-Americans. Arab populations, however, have been only rarely studied. Using Affymetrix Genome-Wide Human SNP Array 6, we conducted a genome-wide association study (GWAS) in which 534,781 single nucleotide polymorphisms (SNPs) were genotyped in 221 Tunisians (90 prostate cancer patients and 131 age-matched healthy controls). TaqMan SNP Genotyping Assays on 11 prostate cancer associated SNPs were performed in a distinct cohort of 337 individuals from Arab ancestry living in Qatar and Saudi Arabia (155 prostate cancer patients and 182 age-matched controls). In-silico expression quantitative trait locus (eQTL) analysis along with mRNA quantification of nearby genes was performed to identify loci potentially cis-regulated by the identified SNPs. Three chromosomal regions, encompassing 14 SNPs, are significantly associated with prostate cancer risk in the Tunisian population (P = 1 × 10-4 to P = 1 × 10-5). In addition to SNPs located on chromosome 17q21, previously found associated with prostate cancer in Western populations, two novel chromosomal regions are revealed on chromosome 9p24 and 22q13. eQTL analysis and mRNA quantification indicate that the prostate cancer associated SNPs of chromosome 17 could enhance the expression of STAT5B gene. Our findings, identifying novel GWAS prostate cancer susceptibility loci, indicate that prostate cancer genetic risk factors could be ethnic specific.

Quantitative High-Resolution Genomic Analysis of Single Cancer Cells

PubMed Central

Hannemann, Juliane; Meyer-Staeckling, Sönke; Kemming, Dirk; Alpers, Iris; Joosse, Simon A.; Pospisil, Heike; Kurtz, Stefan; Görndt, Jennifer; Püschel, Klaus; Riethdorf, Sabine; Pantel, Klaus; Brandt, Burkhard

2011-01-01

During cancer progression, specific genomic aberrations arise that can determine the scope of the disease and can be used as predictive or prognostic markers. The detection of specific gene amplifications or deletions in single blood-borne or disseminated tumour cells that may give rise to the development of metastases is of great clinical interest but technically challenging. In this study, we present a method for quantitative high-resolution genomic analysis of single cells. Cells were isolated under permanent microscopic control followed by high-fidelity whole genome amplification and subsequent analyses by fine tiling array-CGH and qPCR. The assay was applied to single breast cancer cells to analyze the chromosomal region centred by the therapeutical relevant EGFR gene. This method allows precise quantitative analysis of copy number variations in single cell diagnostics. PMID:22140428

Quantitative high-resolution genomic analysis of single cancer cells.

PubMed

Hannemann, Juliane; Meyer-Staeckling, Sönke; Kemming, Dirk; Alpers, Iris; Joosse, Simon A; Pospisil, Heike; Kurtz, Stefan; Görndt, Jennifer; Püschel, Klaus; Riethdorf, Sabine; Pantel, Klaus; Brandt, Burkhard

2011-01-01

During cancer progression, specific genomic aberrations arise that can determine the scope of the disease and can be used as predictive or prognostic markers. The detection of specific gene amplifications or deletions in single blood-borne or disseminated tumour cells that may give rise to the development of metastases is of great clinical interest but technically challenging. In this study, we present a method for quantitative high-resolution genomic analysis of single cells. Cells were isolated under permanent microscopic control followed by high-fidelity whole genome amplification and subsequent analyses by fine tiling array-CGH and qPCR. The assay was applied to single breast cancer cells to analyze the chromosomal region centred by the therapeutical relevant EGFR gene. This method allows precise quantitative analysis of copy number variations in single cell diagnostics.

CPTAC Releases Largest-Ever Ovarian Cancer Proteome Dataset from Previously Genome Characterized Tumors | Office of Cancer Clinical Proteomics Research

Cancer.gov

National Cancer Institute (NCI) Clinical Proteomic Tumor Analysis Consortium (CPTAC) scientists have just released a comprehensive dataset of the proteomic analysis of high grade serous ovarian tumor samples, previously genomically analyzed by The Cancer Genome Atlas (TCGA).  This is one of the largest public datasets covering the proteome, phosphoproteome and glycoproteome with complementary deep genomic sequencing data on the same tumor.

Genomic and epigenomic heterogeneity in molecular subtypes of gastric cancer.

PubMed

Lim, Byungho; Kim, Jong-Hwan; Kim, Mirang; Kim, Seon-Young

2016-01-21

Gastric cancer is a complex disease that is affected by multiple genetic and environmental factors. For the precise diagnosis and effective treatment of gastric cancer, the heterogeneity of the disease must be simplified; one way to achieve this is by dividing the disease into subgroups. Toward this effort, recent advances in high-throughput sequencing technology have revealed four molecular subtypes of gastric cancer, which are classified as Epstein-Barr virus-positive, microsatellite instability, genomically stable, and chromosomal instability subtypes. We anticipate that this molecular subtyping will help to extend our knowledge for basic research purposes and will be valuable for clinical use. Here, we review the genomic and epigenomic heterogeneity of the four molecular subtypes of gastric cancer. We also describe a mutational meta-analysis and a reanalysis of DNA methylation that were performed using previously reported gastric cancer datasets.

Crossing the LINE toward genomic instability: LINE-1 retrotransposition in cancer

NASA Astrophysics Data System (ADS)

Kemp, Jacqueline; Longworth, Michelle

2015-12-01

Retrotransposons are repetitive DNA sequences that are positioned throughout the human genome. Retrotransposons are capable of copying themselves and mobilizing new copies to novel genomic locations in a process called retrotransposition. While most retrotransposon sequences in the human genome are incomplete and incapable of mobilization, the LINE-1 retrotransposon, which comprises approximately 17% of the human genome, remains active. The disruption of cellular mechanisms that suppress retrotransposon activity is linked to the generation of aneuploidy, a potential driver of tumor development. When retrotransposons insert into a novel genomic region, they have the potential to disrupt the coding sequence of endogenous genes and alter gene expression, which can lead to deleterious consequences for the organism. Additionally, increased LINE-1 copy numbers provide more chances for recombination events to occur between retrotransposons, which can lead to chromosomal breaks and rearrangements. LINE-1 activity is increased in various cancer cell lines and in patient tissues resected from primary tumors. LINE-1 activity also correlates with increased cancer metastasis. This review aims to give a brief overview of the connections between LINE-1 retrotransposition and the loss of genome stability. We will also discuss the mechanisms that repress retrotransposition in human cells and their links to cancer.

Dana-Farber Cancer Institute: Identification of Therapeutic Targets Across Cancer Types | Office of Cancer Genomics

Cancer.gov

The Dana Farber Cancer Institute CTD2 Center focuses on the use of high-throughput genetic and bioinformatic approaches to identify and credential oncogenes and co-dependencies in cancers. This Center aims to provide the cancer research community with information that will facilitate the prioritization of targets based on both genomic and functional evidence, inform the most appropriate genetic context for downstream mechanistic and validation studies, and enable the translation of this information into therapeutics and diagnostics.

CPTAC Releases Largest-Ever Breast Cancer Proteome Dataset from Previously Genome Characterized Tumors | Office of Cancer Clinical Proteomics Research

Cancer.gov

National Cancer Institute (NCI) Clinical Proteomic Tumor Analysis Consortium (CPTAC) scientists have released a dataset of proteins and  phosphopeptides identified through deep proteomic and phosphoproteomic analysis of breast tumor samples, previously genomically analyzed by The Cancer Genome Atlas (TCGA).

CTD² in Action: Translating High-Content Genomic Data into New Therapies | Office of Cancer Genomics

Cancer.gov

Large-scale molecular analyses have provided an unprecedented global view of the molecular defects in cancers and promise to revolutionize precision cancer medicine by guiding the development of therapies that are matched to genomic alterations in tumors. Cancer is a heterogeneous disease which explains why there are varying responses to therapy. This heterogeneity poses a daunting challenge for clinicians managing a patient’s disease.

A new generation of cancer genome diagnostics for routine clinical use: overcoming the roadblocks to personalized cancer medicine.

PubMed

Heuckmann, J M; Thomas, R K

2015-09-01

The identification of 'druggable' kinase gene alterations has revolutionized cancer treatment in the last decade by providing new and successfully targetable drug targets. Thus, genotyping tumors for matching the right patients with the right drugs have become a clinical routine. Today, advances in sequencing technology and computational genome analyses enable the discovery of a constantly growing number of genome alterations relevant for clinical decision making. As a consequence, several technological approaches have emerged in order to deal with these rapidly increasing demands for clinical cancer genome analyses. Here, we describe challenges on the path to the broad introduction of diagnostic cancer genome analyses and the technologies that can be applied to overcome them. We define three generations of molecular diagnostics that are in clinical use. The latest generation of these approaches involves deep and thus, highly sensitive sequencing of all therapeutically relevant types of genome alterations-mutations, copy number alterations and rearrangements/fusions-in a single assay. Such approaches therefore have substantial advantages (less time and less tissue required) over PCR-based methods that typically have to be combined with fluorescence in situ hybridization for detection of gene amplifications and fusions. Since these new technologies work reliably on routine diagnostic formalin-fixed, paraffin-embedded specimens, they can help expedite the broad introduction of personalized cancer therapy into the clinic by providing comprehensive, sensitive and accurate cancer genome diagnoses in 'real-time'. © The Author 2015. Published by Oxford University Press on behalf of the European Society for Medical Oncology. All rights reserved. For permissions, please email: journals.permissions@oup.com.

arrayCGHbase: an analysis platform for comparative genomic hybridization microarrays

PubMed Central

Menten, Björn; Pattyn, Filip; De Preter, Katleen; Robbrecht, Piet; Michels, Evi; Buysse, Karen; Mortier, Geert; De Paepe, Anne; van Vooren, Steven; Vermeesch, Joris; Moreau, Yves; De Moor, Bart; Vermeulen, Stefan; Speleman, Frank; Vandesompele, Jo

2005-01-01

Background The availability of the human genome sequence as well as the large number of physically accessible oligonucleotides, cDNA, and BAC clones across the entire genome has triggered and accelerated the use of several platforms for analysis of DNA copy number changes, amongst others microarray comparative genomic hybridization (arrayCGH). One of the challenges inherent to this new technology is the management and analysis of large numbers of data points generated in each individual experiment. Results We have developed arrayCGHbase, a comprehensive analysis platform for arrayCGH experiments consisting of a MIAME (Minimal Information About a Microarray Experiment) supportive database using MySQL underlying a data mining web tool, to store, analyze, interpret, compare, and visualize arrayCGH results in a uniform and user-friendly format. Following its flexible design, arrayCGHbase is compatible with all existing and forthcoming arrayCGH platforms. Data can be exported in a multitude of formats, including BED files to map copy number information on the genome using the Ensembl or UCSC genome browser. Conclusion ArrayCGHbase is a web based and platform independent arrayCGH data analysis tool, that allows users to access the analysis suite through the internet or a local intranet after installation on a private server. ArrayCGHbase is available at . PMID:15910681

Characterization of HPV and host genome interactions in primary head and neck cancers.

PubMed

Parfenov, Michael; Pedamallu, Chandra Sekhar; Gehlenborg, Nils; Freeman, Samuel S; Danilova, Ludmila; Bristow, Christopher A; Lee, Semin; Hadjipanayis, Angela G; Ivanova, Elena V; Wilkerson, Matthew D; Protopopov, Alexei; Yang, Lixing; Seth, Sahil; Song, Xingzhi; Tang, Jiabin; Ren, Xiaojia; Zhang, Jianhua; Pantazi, Angeliki; Santoso, Netty; Xu, Andrew W; Mahadeshwar, Harshad; Wheeler, David A; Haddad, Robert I; Jung, Joonil; Ojesina, Akinyemi I; Issaeva, Natalia; Yarbrough, Wendell G; Hayes, D Neil; Grandis, Jennifer R; El-Naggar, Adel K; Meyerson, Matthew; Park, Peter J; Chin, Lynda; Seidman, J G; Hammerman, Peter S; Kucherlapati, Raju

2014-10-28

Previous studies have established that a subset of head and neck tumors contains human papillomavirus (HPV) sequences and that HPV-driven head and neck cancers display distinct biological and clinical features. HPV is known to drive cancer by the actions of the E6 and E7 oncoproteins, but the molecular architecture of HPV infection and its interaction with the host genome in head and neck cancers have not been comprehensively described. We profiled a cohort of 279 head and neck cancers with next generation RNA and DNA sequencing and show that 35 (12.5%) tumors displayed evidence of high-risk HPV types 16, 33, or 35. Twenty-five cases had integration of the viral genome into one or more locations in the human genome with statistical enrichment for genic regions. Integrations had a marked impact on the human genome and were associated with alterations in DNA copy number, mRNA transcript abundance and splicing, and both inter- and intrachromosomal rearrangements. Many of these events involved genes with documented roles in cancer. Cancers with integrated vs. nonintegrated HPV displayed different patterns of DNA methylation and both human and viral gene expressions. Together, these data provide insight into the mechanisms by which HPV interacts with the human genome beyond expression of viral oncoproteins and suggest that specific integration events are an integral component of viral oncogenesis.

Genomic resources for wild populations of the house mouse, Mus musculus and its close relative Mus spretus

PubMed Central

Harr, Bettina; Karakoc, Emre; Neme, Rafik; Teschke, Meike; Pfeifle, Christine; Pezer, Željka; Babiker, Hiba; Linnenbrink, Miriam; Montero, Inka; Scavetta, Rick; Abai, Mohammad Reza; Molins, Marta Puente; Schlegel, Mathias; Ulrich, Rainer G.; Altmüller, Janine; Franitza, Marek; Büntge, Anna; Künzel, Sven; Tautz, Diethard

2016-01-01

Wild populations of the house mouse (Mus musculus) represent the raw genetic material for the classical inbred strains in biomedical research and are a major model system for evolutionary biology. We provide whole genome sequencing data of individuals representing natural populations of M. m. domesticus (24 individuals from 3 populations), M. m. helgolandicus (3 individuals), M. m. musculus (22 individuals from 3 populations) and M. spretus (8 individuals from one population). We use a single pipeline to map and call variants for these individuals and also include 10 additional individuals of M. m. castaneus for which genomic data are publically available. In addition, RNAseq data were obtained from 10 tissues of up to eight adult individuals from each of the three M. m. domesticus populations for which genomic data were collected. Data and analyses are presented via tracks viewable in the UCSC or IGV genome browsers. We also provide information on available outbred stocks and instructions on how to keep them in the laboratory. PMID:27622383

Integrative Analysis of Complex Cancer Genomics and Clinical Profiles Using the cBioPortal

PubMed Central

Gao, Jianjiong; Aksoy, Bülent Arman; Dogrusoz, Ugur; Dresdner, Gideon; Gross, Benjamin; Sumer, S. Onur; Sun, Yichao; Jacobsen, Anders; Sinha, Rileen; Larsson, Erik; Cerami, Ethan; Sander, Chris; Schultz, Nikolaus

2014-01-01

The cBioPortal for Cancer Genomics (http://cbioportal.org) provides a Web resource for exploring, visualizing, and analyzing multidimensional cancer genomics data. The portal reduces molecular profiling data from cancer tissues and cell lines into readily understandable genetic, epigenetic, gene expression, and proteomic events. The query interface combined with customized data storage enables researchers to interactively explore genetic alterations across samples, genes, and pathways and, when available in the underlying data, to link these to clinical outcomes. The portal provides graphical summaries of gene-level data from multiple platforms, network visualization and analysis, survival analysis, patient-centric queries, and software programmatic access. The intuitive Web interface of the portal makes complex cancer genomics profiles accessible to researchers and clinicians without requiring bioinformatics expertise, thus facilitating biological discoveries. Here, we provide a practical guide to the analysis and visualization features of the cBioPortal for Cancer Genomics. PMID:23550210

Contributing to Tumor Molecular Characterization Projects with a Global Impact | Office of Cancer Genomics

Cancer.gov

My name is Nicholas Griner and I am the Scientific Program Manager for the Cancer Genome Characterization Initiative (CGCI) in the Office of Cancer Genomics (OCG). Until recently, I spent most of my scientific career working in a cancer research laboratory. In my postdoctoral training, my research focused on identifying novel pathways that contribute to both prostate and breast cancers and studying proteins within these pathways that may be targeted with cancer drugs.

Clinical applications of The Cancer Genome Atlas project (TCGA) for squamous cell lung carcinoma.

PubMed

Devarakonda, Siddhartha; Morgensztern, Daniel; Govindan, Ramaswamy

2013-09-01

Very little progress has been made in the treatment of patients with metastatic squamous cell lung cancer over the past 2 decades. Identification of novel molecular alterations for targeted therapies is necessary to improve outcomes. Advances in genomic technology have now made it possible to analyze the genomic landscape of tumor tissues comprehensively. We summarize here key findings from the comprehensive analysis of squamous cell lung cancer by The Cancer Genome Atlas group and discuss the clinical implications of these findings.

Retrovirus Integration Database (RID): a public database for retroviral insertion sites into host genomes.

PubMed

Shao, Wei; Shan, Jigui; Kearney, Mary F; Wu, Xiaolin; Maldarelli, Frank; Mellors, John W; Luke, Brian; Coffin, John M; Hughes, Stephen H

2016-07-04

The NCI Retrovirus Integration Database is a MySql-based relational database created for storing and retrieving comprehensive information about retroviral integration sites, primarily, but not exclusively, HIV-1. The database is accessible to the public for submission or extraction of data originating from experiments aimed at collecting information related to retroviral integration sites including: the site of integration into the host genome, the virus family and subtype, the origin of the sample, gene exons/introns associated with integration, and proviral orientation. Information about the references from which the data were collected is also stored in the database. Tools are built into the website that can be used to map the integration sites to UCSC genome browser, to plot the integration site patterns on a chromosome, and to display provirus LTRs in their inserted genome sequence. The website is robust, user friendly, and allows users to query the database and analyze the data dynamically. https://rid.ncifcrf.gov ; or http://home.ncifcrf.gov/hivdrp/resources.htm .

Managing the genomic revolution in cancer diagnostics.

PubMed

Nguyen, Doreen; Gocke, Christopher D

2017-08-01

Molecular tumor profiling is now a routine part of patient care, revealing targetable genomic alterations and molecularly distinct tumor subtypes with therapeutic and prognostic implications. The widespread adoption of next-generation sequencing technologies has greatly facilitated clinical implementation of genomic data and opened the door for high-throughput multigene-targeted sequencing. Herein, we discuss the variability of cancer genetic profiling currently offered by clinical laboratories, the challenges of applying rapidly evolving medical knowledge to individual patients, and the need for more standardized population-based molecular profiling.

Human Papillomavirus Genome Integration and Head and Neck Cancer.

PubMed

Pinatti, L M; Walline, H M; Carey, T E

2018-06-01

We conducted a critical review of human papillomavirus (HPV) integration into the host genome in oral/oropharyngeal cancer, reviewed the literature for HPV-induced cancers, and obtained current data for HPV-related oral and oropharyngeal cancers. In addition, we performed studies to identify HPV integration sites and the relationship of integration to viral-host fusion transcripts and whether integration is required for HPV-associated oncogenesis. Viral integration of HPV into the host genome is not required for the viral life cycle and might not be necessary for cellular transformation, yet HPV integration is frequently reported in cervical and head and neck cancer specimens. Studies of large numbers of early cervical lesions revealed frequent viral integration into gene-poor regions of the host genome with comparatively rare integration into cellular genes, suggesting that integration is a stochastic event and that site of integration may be largely a function of chance. However, more recent studies of head and neck squamous cell carcinomas (HNSCCs) suggest that integration may represent an additional oncogenic mechanism through direct effects on cancer-related gene expression and generation of hybrid viral-host fusion transcripts. In HNSCC cell lines as well as primary tumors, integration into cancer-related genes leading to gene disruption has been reported. The studies have shown that integration-induced altered gene expression may be associated with tumor recurrence. Evidence from several studies indicates that viral integration into genic regions is accompanied by local amplification, increased expression in some cases, interruption of gene expression, and likely additional oncogenic effects. Similarly, reported examples of viral integration near microRNAs suggest that altered expression of these regulatory molecules may also contribute to oncogenesis. Future work is indicated to identify the mechanisms of these events on cancer cell behavior.

Facilitating a culture of responsible and effective sharing of cancer genome data.

PubMed

Siu, Lillian L; Lawler, Mark; Haussler, David; Knoppers, Bartha Maria; Lewin, Jeremy; Vis, Daniel J; Liao, Rachel G; Andre, Fabrice; Banks, Ian; Barrett, J Carl; Caldas, Carlos; Camargo, Anamaria Aranha; Fitzgerald, Rebecca C; Mao, Mao; Mattison, John E; Pao, William; Sellers, William R; Sullivan, Patrick; Teh, Bin Tean; Ward, Robyn L; ZenKlusen, Jean Claude; Sawyers, Charles L; Voest, Emile E

2016-05-05

Rapid and affordable tumor molecular profiling has led to an explosion of clinical and genomic data poised to enhance the diagnosis, prognostication and treatment of cancer. A critical point has now been reached at which the analysis and storage of annotated clinical and genomic information in unconnected silos will stall the advancement of precision cancer care. Information systems must be harmonized to overcome the multiple technical and logistical barriers to data sharing. Against this backdrop, the Global Alliance for Genomic Health (GA4GH) was established in 2013 to create a common framework that enables responsible, voluntary and secure sharing of clinical and genomic data. This Perspective from the GA4GH Clinical Working Group Cancer Task Team highlights the data-aggregation challenges faced by the field, suggests potential collaborative solutions and describes how GA4GH can catalyze a harmonized data-sharing culture.

Getting Personal: Head and Neck Cancer Management in the Era of Genomic Medicine

PubMed Central

Birkeland, Andrew C.; Uhlmann, Wendy R.; Brenner, J. Chad; Shuman, Andrew G.

2015-01-01

Background Genetic testing is rapidly becoming an important tool in the management of patients with head and neck cancer. As we enter the era of genomics and personalized medicine, providers should be aware of testing options, counseling resources, and the benefits, limitations and future of personalized therapy. Methods This manuscript offers a primer to assist clinicians treating patients in anticipating and managing the inherent practical and ethical challenges of cancer care in the genomic era. Results Clinical applications of genomics for head and neck cancer are emerging. We discuss the indications for genetic testing, types of testing available, implications for care, privacy/disclosure concerns and ethical considerations. Hereditary genetic syndromes associated with head and neck neoplasms are reviewed, and online genetics resources are provided. Conclusions This article summarizes and contextualizes the evolving diagnostic and therapeutic options that impact the care of patients with head and neck cancer in the genomic era. PMID:25995036

Noncoding Genomics in Gastric Cancer and the Gastric Precancerous Cascade: Pathogenesis and Biomarkers

PubMed Central

Garcia-Bloj, Benjamin; Fry, Jacqueline; Wichmann, Ignacio

2015-01-01

Gastric cancer is the fifth most common cancer and the third leading cause of cancer-related death, whose patterns vary among geographical regions and ethnicities. It is a multifactorial disease, and its development depends on infection by Helicobacter pylori (H. pylori) and Epstein-Barr virus (EBV), host genetic factors, and environmental factors. The heterogeneity of the disease has begun to be unraveled by a comprehensive mutational evaluation of primary tumors. The low-abundance of mutations suggests that other mechanisms participate in the evolution of the disease, such as those found through analyses of noncoding genomics. Noncoding genomics includes single nucleotide polymorphisms (SNPs), regulation of gene expression through DNA methylation of promoter sites, miRNAs, other noncoding RNAs in regulatory regions, and other topics. These processes and molecules ultimately control gene expression. Potential biomarkers are appearing from analyses of noncoding genomics. This review focuses on noncoding genomics and potential biomarkers in the context of gastric cancer and the gastric precancerous cascade. PMID:26379360

State of the Art: Response Assessment in Lung Cancer in the Era of Genomic Medicine

PubMed Central

Hatabu, Hiroto; Johnson, Bruce E.; McLoud, Theresa C.

2014-01-01

Tumor response assessment has been a foundation for advances in cancer therapy. Recent discoveries of effective targeted therapy for specific genomic abnormalities in lung cancer and their clinical application have brought revolutionary advances in lung cancer therapy and transformed the oncologist’s approach to patients with lung cancer. Because imaging is a major method of response assessment in lung cancer both in clinical trials and practice, radiologists must understand the genomic alterations in lung cancer and the rapidly evolving therapeutic approaches to effectively communicate with oncology colleagues and maintain the key role in lung cancer care. This article describes the origin and importance of tumor response assessment, presents the recent genomic discoveries in lung cancer and therapies directed against these genomic changes, and describes how these discoveries affect the radiology community. The authors then summarize the conventional Response Evaluation Criteria in Solid Tumors and World Health Organization guidelines, which continue to be the major determinants of trial endpoints, and describe their limitations particularly in an era of genomic-based therapy. More advanced imaging techniques for lung cancer response assessment are presented, including computed tomography tumor volume and perfusion, dynamic contrast material–enhanced and diffusion-weighted magnetic resonance imaging, and positron emission tomography with fluorine 18 fluorodeoxyglucose and novel tracers. State-of-art knowledge of lung cancer biology, treatment, and imaging will help the radiology community to remain effective contributors to the personalized care of lung cancer patients. © RSNA, 2014 PMID:24661292

Early Onset Malignancies - Genomic Study of Cancer Disparities

Cancer.gov

The Early Onset Malignancies Initiative studies the genomic basis of six cancers that develop at an earlier age, occur in higher rates, and are typically more aggressive in certain minority populations.

Analyzing Somatic Genome Rearrangements in Human Cancers by Using Whole-Exome Sequencing | Office of Cancer Genomics

Cancer.gov

Although exome sequencing data are generated primarily to detect single-nucleotide variants and indels, they can also be used to identify a subset of genomic rearrangements whose breakpoints are located in or near exons. Using >4,600 tumor and normal pairs across 15 cancer types, we identified over 9,000 high confidence somatic rearrangements, including a large number of gene fusions.

Xenopatients 2.0: reprogramming the epigenetic landscapes of patient-derived cancer genomes.

PubMed

Menendez, Javier A; Alarcón, Tomás; Corominas-Faja, Bruna; Cuyàs, Elisabet; López-Bonet, Eugeni; Martin, Angel G; Vellon, Luciano

2014-01-01

In the science-fiction thriller film Minority Report, a specialized police department called "PreCrime" apprehends criminals identified in advance based on foreknowledge provided by 3 genetically altered humans called "PreCogs". We propose that Yamanaka stem cell technology can be similarly used to (epi)genetically reprogram tumor cells obtained directly from cancer patients and create self-evolving personalized translational platforms to foresee the evolutionary trajectory of individual tumors. This strategy yields a large stem cell population and captures the cancer genome of an affected individual, i.e., the PreCog-induced pluripotent stem (iPS) cancer cells, which are immediately available for experimental manipulation, including pharmacological screening for personalized "stemotoxic" cancer drugs. The PreCog-iPS cancer cells will re-differentiate upon orthotopic injection into the corresponding target tissues of immunodeficient mice (i.e., the PreCrime-iPS mouse avatars), and this in vivo model will run through specific cancer stages to directly explore their biological properties for drug screening, diagnosis, and personalized treatment in individual patients. The PreCog/PreCrime-iPS approach can perform sets of comparisons to directly observe changes in the cancer-iPS cell line vs. a normal iPS cell line derived from the same human genetic background. Genome editing of PreCog-iPS cells could create translational platforms to directly investigate the link between genomic expression changes and cellular malignization that is largely free from genetic and epigenetic noise and provide proof-of-principle evidence for cutting-edge "chromosome therapies" aimed against cancer aneuploidy. We might infer the epigenetic marks that correct the tumorigenic nature of the reprogrammed cancer cell population and normalize the malignant phenotype in vivo. Genetically engineered models of conditionally reprogrammable mice to transiently express the Yamanaka stemness factors

TARGET Publication Guidelines | Office of Cancer Genomics

Cancer.gov

Like other NCI large-scale genomics initiatives, TARGET is a community resource project and data are made available rapidly after validation for use by other researchers. To act in accord with the Fort Lauderdale principles and support the continued prompt public release of large-scale genomic data prior to publication, researchers who plan to prepare manuscripts containing descriptions of TARGET pediatric cancer data that would be of comparable scope to an initial TARGET disease-specific comprehensive, global analysis publication, and journal editors who receive such manuscripts, are

The application of genome-wide 5-hydroxymethylcytosine studies in cancer research.

PubMed

Thomson, John P; Meehan, Richard R

2017-01-01

Early detection and characterization of molecular events associated with tumorgenesis remain high priorities. Genome-wide epigenetic assays are promising diagnostic tools, as aberrant epigenetic events are frequent and often cancer specific. The deposition and analysis of multiple patient-derived cancer epigenomic profiles contributes to our appreciation of the underlying biology; aiding the detection of novel identifiers for cancer subtypes. Modifying enzymes and co-factors regulating these epigenetic marks are frequently mutated in cancers, and as epigenetic modifications themselves are reversible, this makes their study very attractive with respect to pharmaceutical intervention. Here we focus on the novel modified base, 5-hydoxymethylcytosine, and discuss how genome-wide 5-hydoxymethylcytosine profiling expedites our molecular understanding of cancer, serves as a lineage tracer, classifies the mode of action of potentially carcinogenic agents and clarifies the roles of potential novel cancer drug targets; thus assisting the development of new diagnostic/prognostic tools.

CGCI Investigators Reveal Comprehensive Landscape of Diffuse Large B-Cell Lymphoma (DLBCL) Genomes | Office of Cancer Genomics

Cancer.gov

Researchers from British Columbia Cancer Agency used whole genome sequencing to analyze 40 DLBCL cases and 13 cell lines in order to fill in the gaps of the complex landscape of DLBCL genomes. Their analysis, “Mutational and structural analysis of diffuse large B-cell lymphoma using whole genome sequencing,” was published online in Blood on May 22. The authors are Ryan Morin, Marco Marra, and colleagues.  

Connecting genomic alterations to cancer biology with proteomics: the NCI Clinical Proteomic Tumor Analysis Consortium.

PubMed

Ellis, Matthew J; Gillette, Michael; Carr, Steven A; Paulovich, Amanda G; Smith, Richard D; Rodland, Karin K; Townsend, R Reid; Kinsinger, Christopher; Mesri, Mehdi; Rodriguez, Henry; Liebler, Daniel C

2013-10-01

The National Cancer Institute (NCI) Clinical Proteomic Tumor Analysis Consortium is applying the latest generation of proteomic technologies to genomically annotated tumors from The Cancer Genome Atlas (TCGA) program, a joint initiative of the NCI and the National Human Genome Research Institute. By providing a fully integrated accounting of DNA, RNA, and protein abnormalities in individual tumors, these datasets will illuminate the complex relationship between genomic abnormalities and cancer phenotypes, thus producing biologic insights as well as a wave of novel candidate biomarkers and therapeutic targets amenable to verification using targeted mass spectrometry methods. ©2013 AACR.

Distinct p53 genomic binding patterns in normal and cancer-derived human cells

PubMed Central

McCorkle, Sean R; McCombie, WR; Dunn, John J

2011-01-01

Here, we report genome-wide analysis of the tumor suppressor p53 binding sites in normal human cells. 743 high-confidence ChIP-seq peaks representing putative genomic binding sites were identified in normal IMR90 fibroblasts using a reference chromatin sample. More than 40% were located within 2 kb of a transcription start site (TSS), a distribution similar to that documented for individually studied, functional p53 binding sites and, to date, not observed by previous p53 genome-wide studies. Nearly half of the high-confidence binding sites in the IMR90 cells reside in CpG islands in marked contrast to sites reported in cancer-derived cells. The distinct genomic features of the IMR90 binding sites do not reflect a distinct preference for specific sequences, since the de novo developed p53 motif based on our study is similar to those reported by genome-wide studies of cancer cells. More likely, the different chromatin landscape in normal, compared with cancer-derived cells, influences p53 binding via modulating availability of the sites. We compared the IMR90 ChIP-seq peaks to the recently published IMR90 methylome1 and demonstrated that they are enriched at hypomethylated DNA. Our study represents the first genome-wide, de novo mapping of p53 binding sites in normal human cells and reveals that p53 binding sites reside in distinct genomic landscapes in normal and cancer-derived human cells. PMID:22127205

Cancer biology and genomics: translating discoveries, transforming pathology.

PubMed

Ladanyi, Marc; Hogendoorn, Pancras C W

2011-01-01

Advances in our understanding of cancer biology and discoveries emerging from cancer genomics are being translated into real clinical benefits for patients with cancer. The 2011 Journal of Pathology Annual Review Issue provides a snapshot of recent rapid progress on multiple fronts in the war on cancer or, more precisely, the wars on cancers. Indeed, perhaps the most notable recent shift is reflected by the sharp increase in understanding the biology of multiple specific cancers and using these new insights to inform rationally targeted therapies, with often striking successes. These recent developments, as reviewed in this issue, show how the long-term investments in basic cancer research are finally beginning to bear fruit. Copyright © 2010 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

PIK3CA mutant tumors depend on oxoglutarate dehydrogenase | Office of Cancer Genomics

Cancer.gov

Oncogenic PIK3CA mutations are found in a significant fraction of human cancers, but therapeutic inhibition of PI3K has only shown limited success in clinical trials. To understand how mutant PIK3CA contributes to cancer cell proliferation, we used genome scale loss-of-function screening in a large number of genomically annotated cancer cell lines. As expected, we found that PIK3CA mutant cancer cells require PIK3CA but also require the expression of the TCA cycle enzyme 2-oxoglutarate dehydrogenase (OGDH).

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas.

PubMed

Schaub, Franz X; Dhankani, Varsha; Berger, Ashton C; Trivedi, Mihir; Richardson, Anne B; Shaw, Reid; Zhao, Wei; Zhang, Xiaoyang; Ventura, Andrea; Liu, Yuexin; Ayer, Donald E; Hurlin, Peter J; Cherniack, Andrew D; Eisenman, Robert N; Bernard, Brady; Grandori, Carla

2018-03-28

Although the MYC oncogene has been implicated in cancer, a systematic assessment of alterations of MYC, related transcription factors, and co-regulatory proteins, forming the proximal MYC network (PMN), across human cancers is lacking. Using computational approaches, we define genomic and proteomic features associated with MYC and the PMN across the 33 cancers of The Cancer Genome Atlas. Pan-cancer, 28% of all samples had at least one of the MYC paralogs amplified. In contrast, the MYC antagonists MGA and MNT were the most frequently mutated or deleted members, proposing a role as tumor suppressors. MYC alterations were mutually exclusive with PIK3CA, PTEN, APC, or BRAF alterations, suggesting that MYC is a distinct oncogenic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such as immune response and growth factor signaling; chromatin, translation, and DNA replication/repair were conserved pan-cancer. This analysis reveals insights into MYC biology and is a reference for biomarkers and therapeutics for cancers with alterations of MYC or the PMN. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Actomyosin drives cancer cell nuclear dysmorphia and threatens genome stability.

PubMed

Takaki, Tohru; Montagner, Marco; Serres, Murielle P; Le Berre, Maël; Russell, Matt; Collinson, Lucy; Szuhai, Karoly; Howell, Michael; Boulton, Simon J; Sahai, Erik; Petronczki, Mark

2017-07-24

Altered nuclear shape is a defining feature of cancer cells. The mechanisms underlying nuclear dysmorphia in cancer remain poorly understood. Here we identify PPP1R12A and PPP1CB, two subunits of the myosin phosphatase complex that antagonizes actomyosin contractility, as proteins safeguarding nuclear integrity. Loss of PPP1R12A or PPP1CB causes nuclear fragmentation, nuclear envelope rupture, nuclear compartment breakdown and genome instability. Pharmacological or genetic inhibition of actomyosin contractility restores nuclear architecture and genome integrity in cells lacking PPP1R12A or PPP1CB. We detect actin filaments at nuclear envelope rupture sites and define the Rho-ROCK pathway as the driver of nuclear damage. Lamin A protects nuclei from the impact of actomyosin activity. Blocking contractility increases nuclear circularity in cultured cancer cells and suppresses deformations of xenograft nuclei in vivo. We conclude that actomyosin contractility is a major determinant of nuclear shape and that unrestrained contractility causes nuclear dysmorphia, nuclear envelope rupture and genome instability.

Actomyosin drives cancer cell nuclear dysmorphia and threatens genome stability

PubMed Central

Takaki, Tohru; Montagner, Marco; Serres, Murielle P.; Le Berre, Maël; Russell, Matt; Collinson, Lucy; Szuhai, Karoly; Howell, Michael; Boulton, Simon J.; Sahai, Erik; Petronczki, Mark

2017-01-01

Altered nuclear shape is a defining feature of cancer cells. The mechanisms underlying nuclear dysmorphia in cancer remain poorly understood. Here we identify PPP1R12A and PPP1CB, two subunits of the myosin phosphatase complex that antagonizes actomyosin contractility, as proteins safeguarding nuclear integrity. Loss of PPP1R12A or PPP1CB causes nuclear fragmentation, nuclear envelope rupture, nuclear compartment breakdown and genome instability. Pharmacological or genetic inhibition of actomyosin contractility restores nuclear architecture and genome integrity in cells lacking PPP1R12A or PPP1CB. We detect actin filaments at nuclear envelope rupture sites and define the Rho-ROCK pathway as the driver of nuclear damage. Lamin A protects nuclei from the impact of actomyosin activity. Blocking contractility increases nuclear circularity in cultured cancer cells and suppresses deformations of xenograft nuclei in vivo. We conclude that actomyosin contractility is a major determinant of nuclear shape and that unrestrained contractility causes nuclear dysmorphia, nuclear envelope rupture and genome instability. PMID:28737169

Health psychology and translational genomic research: bringing innovation to cancer-related behavioral interventions.

PubMed

McBride, Colleen M; Birmingham, Wendy C; Kinney, Anita Y

2015-01-01

The past decade has witnessed rapid advances in human genome sequencing technology and in the understanding of the role of genetic and epigenetic alterations in cancer development. These advances have raised hopes that such knowledge could lead to improvements in behavioral risk reduction interventions, tailored screening recommendations, and treatment matching that together could accelerate the war on cancer. Despite this optimism, translation of genomic discovery for clinical and public health applications has moved relatively slowly. To date, health psychologists and the behavioral sciences generally have played a very limited role in translation research. In this report we discuss what we mean by genomic translational research and consider the social forces that have slowed translational research, including normative assumptions that translation research must occur downstream of basic science, thus relegating health psychology and other behavioral sciences to a distal role. We then outline two broad priority areas in cancer prevention, detection, and treatment where evidence will be needed to guide evaluation and implementation of personalized genomics: (a) effective communication, to broaden dissemination of genomic discovery, including patient-provider communication and familial communication, and (b) the need to improve the motivational impact of behavior change interventions, including those aimed at altering lifestyle choices and those focusing on decision making regarding targeted cancer treatments and chemopreventive adherence. We further discuss the role that health psychologists can play in interdisciplinary teams to shape translational research priorities and to evaluate the utility of emerging genomic discoveries for cancer prevention and control. PsycINFO Database Record (c) 2015 APA, all rights reserved.

Cooperative genomic alteration network reveals molecular classification across 12 major cancer types

PubMed Central

Zhang, Hongyi; Deng, Yulan; Zhang, Yong; Ping, Yanyan; Zhao, Hongying; Pang, Lin; Zhang, Xinxin; Wang, Li; Xu, Chaohan; Xiao, Yun; Li, Xia

2017-01-01

The accumulation of somatic genomic alterations that enables cells to gradually acquire growth advantage contributes to tumor development. This has the important implication of the widespread existence of cooperative genomic alterations in the accumulation process. Here, we proposed a computational method HCOC that simultaneously consider genetic context and downstream functional effects on cancer hallmarks to uncover somatic cooperative events in human cancers. Applying our method to 12 TCGA cancer types, we totally identified 1199 cooperative events with high heterogeneity across human cancers, and then constructed a pan-cancer cooperative alteration network. These cooperative events are associated with genomic alterations of some high-confident cancer drivers, and can trigger the dysfunction of hallmark associated pathways in a co-defect way rather than single alterations. We found that these cooperative events can be used to produce a prognostic classification that can provide complementary information with tissue-of-origin. In a further case study of glioblastoma, using 23 cooperative events identified, we stratified patients into molecularly relevant subtypes with a prognostic significance independent of the Glioma-CpG Island Methylator Phenotype (GCIMP). In summary, our method can be effectively used to discover cancer-driving cooperative events that can be valuable clinical markers for patient stratification. PMID:27899621

Micro-Scale Genomic DNA Copy Number Aberrations as Another Means of Mutagenesis in Breast Cancer

PubMed Central

Chao, Hann-Hsiang; He, Xiaping; Parker, Joel S.; Zhao, Wei; Perou, Charles M.

2012-01-01

Introduction In breast cancer, the basal-like subtype has high levels of genomic instability relative to other breast cancer subtypes with many basal-like-specific regions of aberration. There is evidence that this genomic instability extends to smaller scale genomic aberrations, as shown by a previously described micro-deletion event in the PTEN gene in the Basal-like SUM149 breast cancer cell line. Methods We sought to identify if small regions of genomic DNA copy number changes exist by using a high density, gene-centric Comparative Genomic Hybridizations (CGH) array on cell lines and primary tumors. A custom tiling array for CGH (244,000 probes, 200 bp tiling resolution) was created to identify small regions of genomic change, which was focused on previously identified basal-like-specific, and general cancer genes. Tumor genomic DNA from 94 patients and 2 breast cancer cell lines was labeled and hybridized to these arrays. Aberrations were called using SWITCHdna and the smallest 25% of SWITCHdna-defined genomic segments were called micro-aberrations (<64 contiguous probes, ∼ 15 kb). Results Our data showed that primary tumor breast cancer genomes frequently contained many small-scale copy number gains and losses, termed micro-aberrations, most of which are undetectable using typical-density genome-wide aCGH arrays. The basal-like subtype exhibited the highest incidence of these events. These micro-aberrations sometimes altered expression of the involved gene. We confirmed the presence of the PTEN micro-amplification in SUM149 and by mRNA-seq showed that this resulted in loss of expression of all exons downstream of this event. Micro-aberrations disproportionately affected the 5′ regions of the affected genes, including the promoter region, and high frequency of micro-aberrations was associated with poor survival. Conclusion Using a high-probe-density, gene-centric aCGH microarray, we present evidence of small-scale genomic aberrations that can contribute to

Genomics at the Ontario Institute for Cancer Research

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

Ali, Johar

Johar Ali of the Ontario Institute for Cancer Research discusses genomics and next-gen applications at the OICR on June 2, 2010 at the "Sequencing, Finishing, Analysis in the Future" meeting in Santa Fe, NM.

Cloud-Scale Genomic Signals Processing for Robust Large-Scale Cancer Genomic Microarray Data Analysis.

PubMed

Harvey, Benjamin Simeon; Ji, Soo-Yeon

2017-01-01

As microarray data available to scientists continues to increase in size and complexity, it has become overwhelmingly important to find multiple ways to bring forth oncological inference to the bioinformatics community through the analysis of large-scale cancer genomic (LSCG) DNA and mRNA microarray data that is useful to scientists. Though there have been many attempts to elucidate the issue of bringing forth biological interpretation by means of wavelet preprocessing and classification, there has not been a research effort that focuses on a cloud-scale distributed parallel (CSDP) separable 1-D wavelet decomposition technique for denoising through differential expression thresholding and classification of LSCG microarray data. This research presents a novel methodology that utilizes a CSDP separable 1-D method for wavelet-based transformation in order to initialize a threshold which will retain significantly expressed genes through the denoising process for robust classification of cancer patients. Additionally, the overall study was implemented and encompassed within CSDP environment. The utilization of cloud computing and wavelet-based thresholding for denoising was used for the classification of samples within the Global Cancer Map, Cancer Cell Line Encyclopedia, and The Cancer Genome Atlas. The results proved that separable 1-D parallel distributed wavelet denoising in the cloud and differential expression thresholding increased the computational performance and enabled the generation of higher quality LSCG microarray datasets, which led to more accurate classification results.

A systems approach defining constraints of the genome architecture on lineage selection and evolvability during somatic cancer evolution

PubMed Central

Rübben, Albert; Nordhoff, Ole

2013-01-01

Summary Most clinically distinguishable malignant tumors are characterized by specific mutations, specific patterns of chromosomal rearrangements and a predominant mechanism of genetic instability but it remains unsolved whether modifications of cancer genomes can be explained solely by mutations and selection through the cancer microenvironment. It has been suggested that internal dynamics of genomic modifications as opposed to the external evolutionary forces have a significant and complex impact on Darwinian species evolution. A similar situation can be expected for somatic cancer evolution as molecular key mechanisms encountered in species evolution also constitute prevalent mutation mechanisms in human cancers. This assumption is developed into a systems approach of carcinogenesis which focuses on possible inner constraints of the genome architecture on lineage selection during somatic cancer evolution. The proposed systems approach can be considered an analogy to the concept of evolvability in species evolution. The principal hypothesis is that permissive or restrictive effects of the genome architecture on lineage selection during somatic cancer evolution exist and have a measurable impact. The systems approach postulates three classes of lineage selection effects of the genome architecture on somatic cancer evolution: i) effects mediated by changes of fitness of cells of cancer lineage, ii) effects mediated by changes of mutation probabilities and iii) effects mediated by changes of gene designation and physical and functional genome redundancy. Physical genome redundancy is the copy number of identical genetic sequences. Functional genome redundancy of a gene or a regulatory element is defined as the number of different genetic elements, regardless of copy number, coding for the same specific biological function within a cancer cell. Complex interactions of the genome architecture on lineage selection may be expected when modifications of the genome

Personal Genomic Testing for Cancer Risk: Results From the Impact of Personal Genomics Study.

PubMed

Gray, Stacy W; Gollust, Sarah E; Carere, Deanna Alexis; Chen, Clara A; Cronin, Angel; Kalia, Sarah S; Rana, Huma Q; Ruffin, Mack T; Wang, Catharine; Roberts, J Scott; Green, Robert C

2017-02-20

Purpose Significant concerns exist regarding the potential for unwarranted behavior changes and the overuse of health care resources in response to direct-to-consumer personal genomic testing (PGT). However, little is known about customers' behaviors after PGT. Methods Longitudinal surveys were given to new customers of 23andMe (Mountain View, CA) and Pathway Genomics (San Diego, CA). Survey data were linked to individual-level PGT results through a secure data transfer process. Results Of the 1,042 customers who completed baseline and 6-month surveys (response rate, 71.2%), 762 had complete cancer-related data and were analyzed. Most customers reported that learning about their genetic risk of cancers was a motivation for testing (colorectal, 88%; prostate, 95%; breast, 94%). No customers tested positive for pathogenic mutations in highly penetrant cancer susceptibility genes. A minority of individuals received elevated single nucleotide polymorphism-based PGT cancer risk estimates (colorectal, 24%; prostate, 24%; breast, 12%). At 6 months, customers who received elevated PGT cancer risk estimates were not significantly more likely to change their diet, exercise, or advanced planning behaviors or engage in cancer screening, compared with individuals at average or reduced risk. Men who received elevated PGT prostate cancer risk estimates changed their vitamin and supplement use more than those at average or reduced risk (22% v 7.6%, respectively; adjusted odds ratio, 3.41; 95% CI, 1.44 to 8.18). Predictors of 6-month behavior include baseline behavior (exercise, vitamin or supplement use, and screening), worse health status (diet and vitamin or supplement use), and older age (advanced planning, screening). Conclusion Most adults receiving elevated direct-to-consumer PGT single nucleotide polymorphism-based cancer risk estimates did not significantly change their diet, exercise, advanced care planning, or cancer screening behaviors.

Personal Genomic Testing for Cancer Risk: Results From the Impact of Personal Genomics Study

PubMed Central

Gollust, Sarah E.; Carere, Deanna Alexis; Chen, Clara A.; Cronin, Angel; Kalia, Sarah S.; Rana, Huma Q.; Ruffin, Mack T.; Wang, Catharine; Roberts, J. Scott; Green, Robert C.

2017-01-01

Purpose Significant concerns exist regarding the potential for unwarranted behavior changes and the overuse of health care resources in response to direct-to-consumer personal genomic testing (PGT). However, little is known about customers’ behaviors after PGT. Methods Longitudinal surveys were given to new customers of 23andMe (Mountain View, CA) and Pathway Genomics (San Diego, CA). Survey data were linked to individual-level PGT results through a secure data transfer process. Results Of the 1,042 customers who completed baseline and 6-month surveys (response rate, 71.2%), 762 had complete cancer-related data and were analyzed. Most customers reported that learning about their genetic risk of cancers was a motivation for testing (colorectal, 88%; prostate, 95%; breast, 94%). No customers tested positive for pathogenic mutations in highly penetrant cancer susceptibility genes. A minority of individuals received elevated single nucleotide polymorphism-based PGT cancer risk estimates (colorectal, 24%; prostate, 24%; breast, 12%). At 6 months, customers who received elevated PGT cancer risk estimates were not significantly more likely to change their diet, exercise, or advanced planning behaviors or engage in cancer screening, compared with individuals at average or reduced risk. Men who received elevated PGT prostate cancer risk estimates changed their vitamin and supplement use more than those at average or reduced risk (22% v 7.6%, respectively; adjusted odds ratio, 3.41; 95% CI, 1.44 to 8.18). Predictors of 6-month behavior include baseline behavior (exercise, vitamin or supplement use, and screening), worse health status (diet and vitamin or supplement use), and older age (advanced planning, screening). Conclusion Most adults receiving elevated direct-to-consumer PGT single nucleotide polymorphism-based cancer risk estimates did not significantly change their diet, exercise, advanced care planning, or cancer screening behaviors. PMID:27937091

Cancer Genome Interpreter annotates the biological and clinical relevance of tumor alterations.

PubMed

Tamborero, David; Rubio-Perez, Carlota; Deu-Pons, Jordi; Schroeder, Michael P; Vivancos, Ana; Rovira, Ana; Tusquets, Ignasi; Albanell, Joan; Rodon, Jordi; Tabernero, Josep; de Torres, Carmen; Dienstmann, Rodrigo; Gonzalez-Perez, Abel; Lopez-Bigas, Nuria

2018-03-28

While tumor genome sequencing has become widely available in clinical and research settings, the interpretation of tumor somatic variants remains an important bottleneck. Here we present the Cancer Genome Interpreter, a versatile platform that automates the interpretation of newly sequenced cancer genomes, annotating the potential of alterations detected in tumors to act as drivers and their possible effect on treatment response. The results are organized in different levels of evidence according to current knowledge, which we envision can support a broad range of oncology use cases. The resource is publicly available at http://www.cancergenomeinterpreter.org .

Inferring causal genomic alterations in breast cancer using gene expression data

PubMed Central

2011-01-01

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

Altered mitochondrial genome content signals worse pathology and prognosis in prostate cancer.

PubMed

Kalsbeek, Anton M F; Chan, Eva K F; Grogan, Judith; Petersen, Desiree C; Jaratlerdsiri, Weerachai; Gupta, Ruta; Lyons, Ruth J; Haynes, Anne-Maree; Horvath, Lisa G; Kench, James G; Stricker, Phillip D; Hayes, Vanessa M

2018-01-01

Mitochondrial genome (mtDNA) content is depleted in many cancers. In prostate cancer, there is intra-glandular as well as inter-patient mtDNA copy number variation. In this study, we determine if mtDNA content can be used as a predictor for prostate cancer staging and outcomes. Fresh prostate cancer biopsies from 115 patients were obtained at time of surgery. All cores underwent pathological review, followed by isolation of cancer and normal tissue. DNA was extracted and qPCR performed to quantify the total amount of mtDNA as a ratio to genomic DNA. Differences in mtDNA content were compared for prostate cancer pathology features and disease outcomes. We showed a significantly reduced mtDNA content in prostate cancer compared with normal adjacent prostate tissue (mean difference 1.73-fold, P-value <0.001). Prostate cancer with increased mtDNA content showed unfavorable pathologic characteristics including, higher disease stage (PT2 vs PT3 P-value = 0.018), extracapsular extension (P-value = 0.02) and a trend toward an increased Gleason score (P-value = 0.064). No significant association was observed between changes in mtDNA content and biochemical recurrence (median follow up of 107 months). Contrary to other cancer types, prostate cancer tissue shows no universally depleted mtDNA content. Rather, the change in mtDNA content is highly variable, mirroring known prostate cancer genome heterogeneity. Patients with high mtDNA content have an unfavorable pathology, while a high mtDNA content in normal adjacent prostate tissue is associated with worse prognosis. © 2017 Wiley Periodicals, Inc.

Enhancing knowledge discovery from cancer genomics data with Galaxy

PubMed Central

Albuquerque, Marco A.; Grande, Bruno M.; Ritch, Elie J.; Pararajalingam, Prasath; Jessa, Selin; Krzywinski, Martin; Grewal, Jasleen K.; Shah, Sohrab P.; Boutros, Paul C.

2017-01-01

Abstract The field of cancer genomics has demonstrated the power of massively parallel sequencing techniques to inform on the genes and specific alterations that drive tumor onset and progression. Although large comprehensive sequence data sets continue to be made increasingly available, data analysis remains an ongoing challenge, particularly for laboratories lacking dedicated resources and bioinformatics expertise. To address this, we have produced a collection of Galaxy tools that represent many popular algorithms for detecting somatic genetic alterations from cancer genome and exome data. We developed new methods for parallelization of these tools within Galaxy to accelerate runtime and have demonstrated their usability and summarized their runtimes on multiple cloud service providers. Some tools represent extensions or refinement of existing toolkits to yield visualizations suited to cohort-wide cancer genomic analysis. For example, we present Oncocircos and Oncoprintplus, which generate data-rich summaries of exome-derived somatic mutation. Workflows that integrate these to achieve data integration and visualizations are demonstrated on a cohort of 96 diffuse large B-cell lymphomas and enabled the discovery of multiple candidate lymphoma-related genes. Our toolkit is available from our GitHub repository as Galaxy tool and dependency definitions and has been deployed using virtualization on multiple platforms including Docker. PMID:28327945

Enhancing knowledge discovery from cancer genomics data with Galaxy.

PubMed

Albuquerque, Marco A; Grande, Bruno M; Ritch, Elie J; Pararajalingam, Prasath; Jessa, Selin; Krzywinski, Martin; Grewal, Jasleen K; Shah, Sohrab P; Boutros, Paul C; Morin, Ryan D

2017-05-01

The field of cancer genomics has demonstrated the power of massively parallel sequencing techniques to inform on the genes and specific alterations that drive tumor onset and progression. Although large comprehensive sequence data sets continue to be made increasingly available, data analysis remains an ongoing challenge, particularly for laboratories lacking dedicated resources and bioinformatics expertise. To address this, we have produced a collection of Galaxy tools that represent many popular algorithms for detecting somatic genetic alterations from cancer genome and exome data. We developed new methods for parallelization of these tools within Galaxy to accelerate runtime and have demonstrated their usability and summarized their runtimes on multiple cloud service providers. Some tools represent extensions or refinement of existing toolkits to yield visualizations suited to cohort-wide cancer genomic analysis. For example, we present Oncocircos and Oncoprintplus, which generate data-rich summaries of exome-derived somatic mutation. Workflows that integrate these to achieve data integration and visualizations are demonstrated on a cohort of 96 diffuse large B-cell lymphomas and enabled the discovery of multiple candidate lymphoma-related genes. Our toolkit is available from our GitHub repository as Galaxy tool and dependency definitions and has been deployed using virtualization on multiple platforms including Docker. © The Author 2017. Published by Oxford University Press.

Conditional Selection of Genomic Alterations Dictates Cancer Evolution and Oncogenic Dependencies.

PubMed

Mina, Marco; Raynaud, Franck; Tavernari, Daniele; Battistello, Elena; Sungalee, Stephanie; Saghafinia, Sadegh; Laessle, Titouan; Sanchez-Vega, Francisco; Schultz, Nikolaus; Oricchio, Elisa; Ciriello, Giovanni

2017-08-14

Cancer evolves through the emergence and selection of molecular alterations. Cancer genome profiling has revealed that specific events are more or less likely to be co-selected, suggesting that the selection of one event depends on the others. However, the nature of these evolutionary dependencies and their impact remain unclear. Here, we designed SELECT, an algorithmic approach to systematically identify evolutionary dependencies from alteration patterns. By analyzing 6,456 genomes from multiple tumor types, we constructed a map of oncogenic dependencies associated with cellular pathways, transcriptional readouts, and therapeutic response. Finally, modeling of cancer evolution shows that alteration dependencies emerge only under conditional selection. These results provide a framework for the design of strategies to predict cancer progression and therapeutic response. Copyright © 2017 Elsevier Inc. All rights reserved.

Dana-Farber Cancer Institute: Identification of Therapeutic Targets in KRAS Driven Lung Cancer | Office of Cancer Genomics

Cancer.gov

The CTD2 Center at Dana Farber Cancer Institute focuses on the use of high-throughput genetic and bioinformatic approaches to identify and credential oncogenes and co-dependencies in cancers. This Center aims to provide the cancer research community with information that will facilitate the prioritization of targets based on both genomic and functional evidence, inform the most appropriate genetic context for downstream mechanistic and validation studies, and enable the translation of this information into therapeutics and diagnostics.

Potential Links between Hepadnavirus and Bornavirus Sequences in the Host Genome and Cancer.

PubMed

Honda, Tomoyuki

2017-01-01

Various viruses leave their sequences in the host genomes during infection. Such events occur mainly in retrovirus infection but also sometimes in DNA and non-retroviral RNA virus infections. If viral sequences are integrated into the genomes of germ line cells, the sequences can become inherited as endogenous viral elements (EVEs). The integration events of viral sequences may have oncogenic potential. Because proviral integrations of some retroviruses and/or reactivation of endogenous retroviruses are closely linked to cancers, viral insertions related to non-retroviral viruses also possibly contribute to cancer development. This article focuses on genomic viral sequences derived from two non-retroviral viruses, whose endogenization is already reported, and discusses their possible contributions to cancer. Viral insertions of hepatitis B virus play roles in the development of hepatocellular carcinoma. Endogenous bornavirus-like elements, the only non-retroviral RNA virus-related EVEs found in the human genome, may also be involved in cancer formation. In addition, the possible contribution of the interactions between viruses and retrotransposons, which seem to be a major driving force for generating EVEs related to non-retroviral RNA viruses, to cancers will be discussed. Future studies regarding the possible links described here may open a new avenue for the development of novel therapeutics for tumor virus-related cancers and/or provide novel insights into EVE functions.

An integrated clinical and genomic information system for cancer precision medicine.

PubMed

Jang, Yeongjun; Choi, Taekjin; Kim, Jongho; Park, Jisub; Seo, Jihae; Kim, Sangok; Kwon, Yeajee; Lee, Seungjae; Lee, Sanghyuk

2018-04-20

Increasing affordability of next-generation sequencing (NGS) has created an opportunity for realizing genomically-informed personalized cancer therapy as a path to precision oncology. However, the complex nature of genomic information presents a huge challenge for clinicians in interpreting the patient's genomic alterations and selecting the optimum approved or investigational therapy. An elaborate and practical information system is urgently needed to support clinical decision as well as to test clinical hypotheses quickly. Here, we present an integrated clinical and genomic information system (CGIS) based on NGS data analyses. Major components include modules for handling clinical data, NGS data processing, variant annotation and prioritization, drug-target-pathway analysis, and population cohort explorer. We built a comprehensive knowledgebase of genes, variants, drugs by collecting annotated information from public and in-house resources. Structured reports for molecular pathology are generated using standardized terminology in order to help clinicians interpret genomic variants and utilize them for targeted cancer therapy. We also implemented many features useful for testing hypotheses to develop prognostic markers from mutation and gene expression data. Our CGIS software is an attempt to provide useful information for both clinicians and scientists who want to explore genomic information for precision oncology.

Harnessing the genome for characterization of GPCRs in cancer pathogenesis

PubMed Central

Feigin, Michael E.

2014-01-01

G-protein coupled receptors (GPCRs) mediate numerous physiological processes and represent the targets for a vast array of therapeutics for diseases ranging from depression to hypertension to reflux. Despite the recognition that GPCRs can act as oncogenes and tumor suppressors by regulating oncogenic signaling networks, few drugs targeting GPCRs are utilized in cancer therapy. Recent large-scale genome-wide analyses of multiple human tumors have uncovered novel GPCRs altered in cancer. However, the work of determining which GPCRs from these lists are drivers of tumorigenesis, and hence valid therapeutic targets, remains a formidable challenge. In this review I will highlight recent studies providing evidence that GPCRs are relevant targets for cancer therapy through their effects on known cancer signaling pathways, tumor progression, invasion and metastasis, and the microenvironment. Furthermore, I will explore how genomic analysis is beginning to shine a light on GPCRs as therapeutic targets in the age of personalized medicine. PMID:23927072

Implications of genome-wide association studies in cancer therapeutics.

PubMed

Patel, Jai N; McLeod, Howard L; Innocenti, Federico

2013-09-01

Genome wide association studies (GWAS) provide an agnostic approach to identifying potential genetic variants associated with disease susceptibility, prognosis of survival and/or predictive of drug response. Although these techniques are costly and interpretation of study results is challenging, they do allow for a more unbiased interrogation of the entire genome, resulting in the discovery of novel genes and understanding of novel biological associations. This review will focus on the implications of GWAS in cancer therapy, in particular germ-line mutations, including findings from major GWAS which have identified predictive genetic loci for clinical outcome and/or toxicity. Lessons and challenges in cancer GWAS are also discussed, including the need for functional analysis and replication, as well as future perspectives for biological and clinical utility. Given the large heterogeneity in response to cancer therapeutics, novel methods of identifying mechanisms and biology of variable drug response and ultimately treatment individualization will be indispensable. © 2013 The British Pharmacological Society.

Building the Evidence Base for Decision-making in Cancer Genomic Medicine Using Comparative Effectiveness Research

PubMed Central

Goddard, Katrina A.B.; Knaus, William A.; Whitlock, Evelyn; Lyman, Gary H.; Feigelson, Heather Spencer; Schully, Sheri D.; Ramsey, Scott; Tunis, Sean; Freedman, Andrew N.; Khoury, Muin J.; Veenstra, David L.

2013-01-01

Background The clinical utility is uncertain for many cancer genomic applications. Comparative effectiveness research (CER) can provide evidence to clarify this uncertainty. Objectives To identify approaches to help stakeholders make evidence-based decisions, and to describe potential challenges and opportunities using CER to produce evidence-based guidance. Methods We identified general CER approaches for genomic applications through literature review, the authors’ experiences, and lessons learned from a recent, seven-site CER initiative in cancer genomic medicine. Case studies illustrate the use of CER approaches. Results Evidence generation and synthesis approaches include comparative observational and randomized trials, patient reported outcomes, decision modeling, and economic analysis. We identified significant challenges to conducting CER in cancer genomics: the rapid pace of innovation, the lack of regulation, the limited evidence for clinical utility, and the beliefs that genomic tests could have personal utility without having clinical utility. Opportunities to capitalize on CER methods in cancer genomics include improvements in the conduct of evidence synthesis, stakeholder engagement, increasing the number of comparative studies, and developing approaches to inform clinical guidelines and research prioritization. Conclusions CER offers a variety of methodological approaches to address stakeholders’ needs. Innovative approaches are needed to ensure an effective translation of genomic discoveries. PMID:22516979

Characterizing the cancer genome in lung adenocarcinoma

PubMed Central

Weir, Barbara A.; Woo, Michele S.; Getz, Gad; Perner, Sven; Ding, Li; Beroukhim, Rameen; Lin, William M.; Province, Michael A.; Kraja, Aldi; Johnson, Laura A.; Shah, Kinjal; Sato, Mitsuo; Thomas, Roman K.; Barletta, Justine A.; Borecki, Ingrid B.; Broderick, Stephen; Chang, Andrew C.; Chiang, Derek Y.; Chirieac, Lucian R.; Cho, Jeonghee; Fujii, Yoshitaka; Gazdar, Adi F.; Giordano, Thomas; Greulich, Heidi; Hanna, Megan; Johnson, Bruce E.; Kris, Mark G.; Lash, Alex; Lin, Ling; Lindeman, Neal; Mardis, Elaine R.; McPherson, John D.; Minna, John D.; Morgan, Margaret B.; Nadel, Mark; Orringer, Mark B.; Osborne, John R.; Ozenberger, Brad; Ramos, Alex H.; Robinson, James; Roth, Jack A.; Rusch, Valerie; Sasaki, Hidefumi; Shepherd, Frances; Sougnez, Carrie; Spitz, Margaret R.; Tsao, Ming-Sound; Twomey, David; Verhaak, Roel G. W.; Weinstock, George M.; Wheeler, David A.; Winckler, Wendy; Yoshizawa, Akihiko; Yu, Soyoung; Zakowski, Maureen F.; Zhang, Qunyuan; Beer, David G.; Wistuba, Ignacio I.; Watson, Mark A.; Garraway, Levi A.; Ladanyi, Marc; Travis, William D.; Pao, William; Rubin, Mark A.; Gabriel, Stacey B.; Gibbs, Richard A.; Varmus, Harold E.; Wilson, Richard K.; Lander, Eric S.; Meyerson, Matthew

2008-01-01

Somatic alterations in cellular DNA underlie almost all human cancers1. The prospect of targeted therapies2 and the development of high-resolution, genome-wide approaches3–8 are now spurring systematic efforts to characterize cancer genomes. Here we report a large-scale project to characterize copy-number alterations in primary lung adenocarcinomas. By analysis of a large collection of tumors (n = 371) using dense single nucleotide polymorphism arrays, we identify a total of 57 significantly recurrent events. We find that 26 of 39 autosomal chromosome arms show consistent large-scale copy-number gain or loss, of which only a handful have been linked to a specific gene. We also identify 31 recurrent focal events, including 24 amplifications and 7 homozygous deletions. Only six of these focal events are currently associated with known mutations in lung carcinomas. The most common event, amplification of chromosome 14q13.3, is found in ~12% of samples. On the basis of genomic and functional analyses, we identify NKX2-1 (NK2 homeobox 1, also called TITF1), which lies in the minimal 14q13.3 amplification interval and encodes a lineage-specific transcription factor, as a novel candidate proto-oncogene involved in a significant fraction of lung adenocarcinomas. More generally, our results indicate that many of the genes that are involved in lung adenocarcinoma remain to be discovered. PMID:17982442

Genome-wide chemical mutagenesis screens allow unbiased saturation of the cancer genome and identification of drug resistance mutations.

PubMed

Brammeld, Jonathan S; Petljak, Mia; Martincorena, Inigo; Williams, Steven P; Alonso, Luz Garcia; Dalmases, Alba; Bellosillo, Beatriz; Robles-Espinoza, Carla Daniela; Price, Stacey; Barthorpe, Syd; Tarpey, Patrick; Alifrangis, Constantine; Bignell, Graham; Vidal, Joana; Young, Jamie; Stebbings, Lucy; Beal, Kathryn; Stratton, Michael R; Saez-Rodriguez, Julio; Garnett, Mathew; Montagut, Clara; Iorio, Francesco; McDermott, Ultan

2017-04-01

Drug resistance is an almost inevitable consequence of cancer therapy and ultimately proves fatal for the majority of patients. In many cases, this is the consequence of specific gene mutations that have the potential to be targeted to resensitize the tumor. The ability to uniformly saturate the genome with point mutations without chromosome or nucleotide sequence context bias would open the door to identify all putative drug resistance mutations in cancer models. Here, we describe such a method for elucidating drug resistance mechanisms using genome-wide chemical mutagenesis allied to next-generation sequencing. We show that chemically mutagenizing the genome of cancer cells dramatically increases the number of drug-resistant clones and allows the detection of both known and novel drug resistance mutations. We used an efficient computational process that allows for the rapid identification of involved pathways and druggable targets. Such a priori knowledge would greatly empower serial monitoring strategies for drug resistance in the clinic as well as the development of trials for drug-resistant patients. © 2017 Brammeld et al.; Published by Cold Spring Harbor Laboratory Press.

The rise of genomic profiling in ovarian cancer

PubMed Central

Previs, Rebecca A.; Sood, Anil K.; Mills, Gordon B.; Westin, Shannon N.

2017-01-01

Introduction Next-generation sequencing and advances in ‘omics technology have rapidly increased our understanding of the molecular landscape of epithelial ovarian cancers. Areas covered Once characterized only by histologic appearance and clinical behavior, we now understand many of the molecular phenotypes that underlie the different ovarian cancer subtypes. While the current approach to treatment involves standard cytotoxic therapies after cytoreductive surgery for all ovarian cancers regardless of histologic or molecular characteristics, focus has shifted beyond a ‘one size fits all’ approach to ovarian cancer. Expert commentary Genomic profiling offers potentially ‘actionable’ opportunities for development of targeted therapies and a more individualized approach to treatment with concomitant improved outcomes and decreased toxicity. PMID:27828713

Returning individual research results for genome sequences of pancreatic cancer

PubMed Central

2014-01-01

Background Disclosure of individual results to participants in genomic research is a complex and contentious issue. There are many existing commentaries and opinion pieces on the topic, but little empirical data concerning actual cases describing how individual results have been returned. Thus, the real life risks and benefits of disclosing individual research results to participants are rarely if ever presented as part of this debate. Methods The Australian Pancreatic Cancer Genome Initiative (APGI) is an Australian contribution to the International Cancer Genome Consortium (ICGC), that involves prospective sequencing of tumor and normal genomes of study participants with pancreatic cancer in Australia. We present three examples that illustrate different facets of how research results may arise, and how they may be returned to individuals within an ethically defensible and clinically practical framework. This framework includes the necessary elements identified by others including consent, determination of the significance of results and which to return, delineation of the responsibility for communication and the clinical pathway for managing the consequences of returning results. Results Of 285 recruited patients, we returned results to a total of 25 with no adverse events to date. These included four that were classified as medically actionable, nine as clinically significant and eight that were returned at the request of the treating clinician. Case studies presented depict instances where research results impacted on cancer susceptibility, current treatment and diagnosis, and illustrate key practical challenges of developing an effective framework. Conclusions We suggest that return of individual results is both feasible and ethically defensible but only within the context of a robust framework that involves a close relationship between researchers and clinicians. PMID:24963353

Cells Comprising the Prostate Cancer Microenvironment Lack Recurrent Clonal Somatic Genomic Aberrations

PubMed Central

Bianchi-Frias, Daniella; Basom, Ryan; Delrow, Jeffrey J; Coleman, Ilsa M; Dakhova, Olga; Qu, Xiaoyu; Fang, Min; Franco, Omar E.; Ericson, Nolan G.; Bielas, Jason H.; Hayward, Simon W.; True, Lawrence; Morrissey, Colm; Brown, Lisha; Bhowmick, Neil A.; Rowley, David; Ittmann, Michael; Nelson, Peter S.

2017-01-01

Prostate cancer-associated stroma (CAS) plays an active role in malignant transformation, tumor progression, and metastasis. Molecular analyses of CAS have demonstrated significant changes in gene expression; however, conflicting evidence exists on whether genomic alterations in benign cells comprising the tumor microenvironment (TME) underlie gene expression changes and oncogenic phenotypes. This study evaluates the nuclear and mitochondrial DNA integrity of prostate carcinoma cells, CAS, matched benign epithelium and benign epithelium-associated stroma by whole genome copy number analyses, targeted sequencing of TP53, and fluorescence in situ hybridization. Comparative genomic hybridization (aCGH) of CAS revealed a copy-neutral diploid genome with only rare and small somatic copy number aberrations (SCNAs). In contrast, several expected recurrent SCNAs were evident in the adjacent prostate carcinoma cells, including gains at 3q, 7p, and 8q, and losses at 8p and 10q. No somatic TP53 mutations were observed in CAS. Mitochondrial DNA (mtDNA) extracted from carcinoma cells and stroma identified 23 somatic mtDNA mutations in neoplastic epithelial cells but only one mutation in stroma. Finally, genomic analyses identified no SCNAs, no loss of heterozygosity (LOH) or copy-neutral LOH in cultured cancer-associated fibroblasts (CAFs), which are known to promote prostate cancer progression in vivo. PMID:26753621

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

Cancer.gov

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

TCGA Workflow: Analyze cancer genomics and epigenomics data using Bioconductor packages

PubMed Central

Bontempi, Gianluca; Ceccarelli, Michele; Noushmehr, Houtan

2016-01-01

Biotechnological advances in sequencing have led to an explosion of publicly available data via large international consortia such as The Cancer Genome Atlas (TCGA), The Encyclopedia of DNA Elements (ENCODE), and The NIH Roadmap Epigenomics Mapping Consortium (Roadmap). These projects have provided unprecedented opportunities to interrogate the epigenome of cultured cancer cell lines as well as normal and tumor tissues with high genomic resolution. The Bioconductor project offers more than 1,000 open-source software and statistical packages to analyze high-throughput genomic data. However, most packages are designed for specific data types (e.g. expression, epigenetics, genomics) and there is no one comprehensive tool that provides a complete integrative analysis of the resources and data provided by all three public projects. A need to create an integration of these different analyses was recently proposed. In this workflow, we provide a series of biologically focused integrative analyses of different molecular data. We describe how to download, process and prepare TCGA data and by harnessing several key Bioconductor packages, we describe how to extract biologically meaningful genomic and epigenomic data. Using Roadmap and ENCODE data, we provide a work plan to identify biologically relevant functional epigenomic elements associated with cancer. To illustrate our workflow, we analyzed two types of brain tumors: low-grade glioma (LGG) versus high-grade glioma (glioblastoma multiform or GBM). This workflow introduces the following Bioconductor packages: AnnotationHub, ChIPSeeker, ComplexHeatmap, pathview, ELMER, GAIA, MINET, RTCGAToolbox,  TCGAbiolinks. PMID:28232861

TCGA Workflow: Analyze cancer genomics and epigenomics data using Bioconductor packages.

PubMed

Silva, Tiago C; Colaprico, Antonio; Olsen, Catharina; D'Angelo, Fulvio; Bontempi, Gianluca; Ceccarelli, Michele; Noushmehr, Houtan

2016-01-01

Biotechnological advances in sequencing have led to an explosion of publicly available data via large international consortia such as The Cancer Genome Atlas (TCGA), The Encyclopedia of DNA Elements (ENCODE), and The NIH Roadmap Epigenomics Mapping Consortium (Roadmap). These projects have provided unprecedented opportunities to interrogate the epigenome of cultured cancer cell lines as well as normal and tumor tissues with high genomic resolution. The Bioconductor project offers more than 1,000 open-source software and statistical packages to analyze high-throughput genomic data. However, most packages are designed for specific data types (e.g. expression, epigenetics, genomics) and there is no one comprehensive tool that provides a complete integrative analysis of the resources and data provided by all three public projects. A need to create an integration of these different analyses was recently proposed. In this workflow, we provide a series of biologically focused integrative analyses of different molecular data. We describe how to download, process and prepare TCGA data and by harnessing several key Bioconductor packages, we describe how to extract biologically meaningful genomic and epigenomic data. Using Roadmap and ENCODE data, we provide a work plan to identify biologically relevant functional epigenomic elements associated with cancer. To illustrate our workflow, we analyzed two types of brain tumors: low-grade glioma (LGG) versus high-grade glioma (glioblastoma multiform or GBM). This workflow introduces the following Bioconductor packages: AnnotationHub, ChIPSeeker, ComplexHeatmap, pathview, ELMER, GAIA, MINET, RTCGAToolbox,  TCGAbiolinks.

Modeling cancer metabolism on a genome scale

PubMed Central

Yizhak, Keren; Chaneton, Barbara; Gottlieb, Eyal; Ruppin, Eytan

2015-01-01

Cancer cells have fundamentally altered cellular metabolism that is associated with their tumorigenicity and malignancy. In addition to the widely studied Warburg effect, several new key metabolic alterations in cancer have been established over the last decade, leading to the recognition that altered tumor metabolism is one of the hallmarks of cancer. Deciphering the full scope and functional implications of the dysregulated metabolism in cancer requires both the advancement of a variety of omics measurements and the advancement of computational approaches for the analysis and contextualization of the accumulated data. Encouragingly, while the metabolic network is highly interconnected and complex, it is at the same time probably the best characterized cellular network. Following, this review discusses the challenges that genome-scale modeling of cancer metabolism has been facing. We survey several recent studies demonstrating the first strides that have been done, testifying to the value of this approach in portraying a network-level view of the cancer metabolism and in identifying novel drug targets and biomarkers. Finally, we outline a few new steps that may further advance this field. PMID:26130389

AACR precision medicine series: Highlights of the integrating clinical genomics and cancer therapy meeting.

PubMed

Maggi, Elaine; Montagna, Cristina

2015-12-01

The American Association for Cancer Research (AACR) Precision Medicine Series "Integrating Clinical Genomics and Cancer Therapy" took place June 13-16, 2015 in Salt Lake City, Utah. The conference was co-chaired by Charles L. Sawyers form Memorial Sloan Kettering Cancer Center in New York, Elaine R. Mardis form Washington University School of Medicine in St. Louis, and Arul M. Chinnaiyan from University of Michigan in Ann Arbor. About 500 clinicians, basic science investigators, bioinformaticians, and postdoctoral fellows joined together to discuss the current state of Clinical Genomics and the advances and challenges of integrating Next Generation Sequencing (NGS) technologies into clinical practice. The plenary sessions and panel discussions covered current platforms and sequencing approaches adopted for NGS assays of cancer genome at several national and international institutions, different approaches used to map and classify targetable sequence variants, and how information acquired with the sequencing of the cancer genome is used to guide treatment options. While challenges still exist from a technological perspective, it emerged that there exists considerable need for the development of tools to aid the identification of the therapy most suitable based on the mutational profile of the somatic cancer genome. The process to match patients to ongoing clinical trials is still complex. In addition, the need for centralized data repositories, preferably linked to well annotated clinical records, that aid sharing of sequencing information is central to begin understanding the contribution of variants of unknown significance to tumor etiology and response to therapy. Here we summarize the highlights of this stimulating four-day conference with a major emphasis on the open problems that the clinical genomics community is currently facing and the tools most needed for advancing this field. Copyright © 2015. Published by Elsevier B.V. All rights reserved.

Comprehensive Genomic Profiling Aids in Distinguishing Metastatic Recurrence from Second Primary Cancers

PubMed Central

Weinberg, Benjamin A.; Gowen, Kyle; Lee, Thomas K.; Ou, Sai‐Hong Ignatius; Bristow, Robert; Krill, Lauren; Almira‐Suarez, M. Isabel; Ali, Siraj M.; Miller, Vincent A.; Liu, Stephen V.

2017-01-01

Abstract Background. Metastatic recurrence after treatment for locoregional cancer is a major cause of morbidity and cancer‐specific mortality. Distinguishing metastatic recurrence from the development of a second primary cancer has important prognostic and therapeutic value and represents a difficult clinical scenario. Advances beyond histopathological comparison are needed. We sought to interrogate the ability of comprehensive genomic profiling (CGP) to aid in distinguishing between these clinical scenarios. Materials and Methods. We identified three prospective cases of recurrent tumors in patients previously treated for localized cancers in which histologic analyses suggested subsequent development of a distinct second primary. Paired samples from the original primary and recurrent tumor were subjected to hybrid capture next‐generation sequencing‐based CGP to identify base pair substitutions, insertions, deletions, copy number alterations (CNA), and chromosomal rearrangements. Genomic profiles between paired samples were compared using previously established statistical clonality assessment software to gauge relatedness beyond global CGP similarities. Results. A high degree of similarity was observed among genomic profiles from morphologically distinct primary and recurrent tumors. Genomic information suggested reclassification as recurrent metastatic disease, and patients received therapy for metastatic disease based on the molecular determination. Conclusions. Our cases demonstrate an important adjunct role for CGP technologies in separating metastatic recurrence from development of a second primary cancer. Larger series are needed to confirm our observations, but comparative CGP may be considered in patients for whom distinguishing metastatic recurrence from a second primary would alter the therapeutic approach. Implications for Practice. Distinguishing a metastatic recurrence from a second primary cancer can represent a difficult clinicopathologic

Attitudes regarding privacy of genomic information in personalized cancer therapy

PubMed Central

Rogith, Deevakar; Yusuf, Rafeek A; Hovick, Shelley R; Peterson, Susan K; Burton-Chase, Allison M; Li, Yisheng; Meric-Bernstam, Funda; Bernstam, Elmer V

2014-01-01

Objective To evaluate attitudes regarding privacy of genomic data in a sample of patients with breast cancer. Methods Female patients with breast cancer (n=100) completed a questionnaire assessing attitudes regarding concerns about privacy of genomic data. Results Most patients (83%) indicated that genomic data should be protected. However, only 13% had significant concerns regarding privacy of such data. Patients expressed more concern about insurance discrimination than employment discrimination (43% vs 28%, p<0.001). They expressed less concern about research institutions protecting the security of their molecular data than government agencies or drug companies (20% vs 38% vs 44%; p<0.001). Most did not express concern regarding the association of their genomic data with their name and personal identity (49% concerned), billing and insurance information (44% concerned), or clinical data (27% concerned). Significantly fewer patients were concerned about the association with clinical data than other data types (p<0.001). In the absence of direct benefit, patients were more willing to consent to sharing of deidentified than identified data with researchers not involved in their care (76% vs 60%; p<0.001). Most (85%) patients were willing to consent to DNA banking. Discussion While patients are opposed to indiscriminate release of genomic data, privacy does not appear to be their primary concern. Furthermore, we did not find any specific predictors of privacy concerns. Conclusions Patients generally expressed low levels of concern regarding privacy of genomic data, and many expressed willingness to consent to sharing their genomic data with researchers. PMID:24737606

Towards a Quantitative Endogenous Network Theory of Cancer Genesis and Progression: beyond ``cancer as diseases of genome''

NASA Astrophysics Data System (ADS)

Ao, Ping

2011-03-01

There has been a tremendous progress in cancer research. However, it appears the current dominant cancer research framework of regarding cancer as diseases of genome leads impasse. Naturally questions have been asked that whether it is possible to develop alternative frameworks such that they can connect both to mutations and other genetic/genomic effects and to environmental factors. Furthermore, such framework can be made quantitative and with predictions experimentally testable. In this talk, I will present a positive answer to this calling. I will explain on our construction of endogenous network theory based on molecular-cellular agencies as dynamical variable. Such cancer theory explicitly demonstrates a profound connection to many fundamental concepts in physics, as such stochastic non-equilibrium processes, ``energy'' landscape, metastability, etc. It suggests that neneath cancer's daunting complexity may lie a simplicity that gives grounds for hope. The rationales behind such theory, its predictions, and its initial experimental verifications will be presented. Supported by USA NIH and China NSF.

Biological and Genomic Differences of ERG Oncoprotein-Stratified Prostate Cancers from African and Caucasian Americans

DTIC Science & Technology

2015-10-01

AWARD NUMBER: W81XWH-13-2-0096 TITLE: Biological and Genomic Differences of ERG Oncoprotein-Stratified Prostate Cancers from African and...Biological and Genomic Differences of ERG Oncoprotein-Stratified Prostate Cancers from African and Caucasian Americans Sb. GRANT NUMBER W81 XWH-13-2...differences in the distribution of key clinico-pathologic patient features and molecular determinants for both ERG positive and ERG negative prostate cancer

The Broad Institute: Screening for Dependencies in Cancer Cell Lines Using Small Molecules | Office of Cancer Genomics

Cancer.gov

Using cancer cell-line profiling, we established an ongoing resource to identify, as comprehensively as possible, the drug-targetable dependencies that specific genomic alterations impart on human cancers. We measured the sensitivity of hundreds of genetically characterized cancer cell lines to hundreds of small-molecule probes and drugs that have highly selective interactions with their targets, and that collectively modulate many distinct nodes in cancer cell circuitry.

Five endometrial cancer risk loci identified through genome-wide association analysis.

PubMed

Cheng, Timothy Ht; Thompson, Deborah J; O'Mara, Tracy A; Painter, Jodie N; Glubb, Dylan M; Flach, Susanne; Lewis, Annabelle; French, Juliet D; Freeman-Mills, Luke; Church, David; Gorman, Maggie; Martin, Lynn; Hodgson, Shirley; Webb, Penelope M; Attia, John; Holliday, Elizabeth G; McEvoy, Mark; Scott, Rodney J; Henders, Anjali K; Martin, Nicholas G; Montgomery, Grant W; Nyholt, Dale R; Ahmed, Shahana; Healey, Catherine S; Shah, Mitul; Dennis, Joe; Fasching, Peter A; Beckmann, Matthias W; Hein, Alexander; Ekici, Arif B; Hall, Per; Czene, Kamila; Darabi, Hatef; Li, Jingmei; Dörk, Thilo; Dürst, Matthias; Hillemanns, Peter; Runnebaum, Ingo; Amant, Frederic; Schrauwen, Stefanie; Zhao, Hui; Lambrechts, Diether; Depreeuw, Jeroen; Dowdy, Sean C; Goode, Ellen L; Fridley, Brooke L; Winham, Stacey J; Njølstad, Tormund S; Salvesen, Helga B; Trovik, Jone; Werner, Henrica Mj; Ashton, Katie; Otton, Geoffrey; Proietto, Tony; Liu, Tao; Mints, Miriam; Tham, Emma; Consortium, Chibcha; Jun Li, Mulin; Yip, Shun H; Wang, Junwen; Bolla, Manjeet K; Michailidou, Kyriaki; Wang, Qin; Tyrer, Jonathan P; Dunlop, Malcolm; Houlston, Richard; Palles, Claire; Hopper, John L; Peto, Julian; Swerdlow, Anthony J; Burwinkel, Barbara; Brenner, Hermann; Meindl, Alfons; Brauch, Hiltrud; Lindblom, Annika; Chang-Claude, Jenny; Couch, Fergus J; Giles, Graham G; Kristensen, Vessela N; Cox, Angela; Cunningham, Julie M; Pharoah, Paul D P; Dunning, Alison M; Edwards, Stacey L; Easton, Douglas F; Tomlinson, Ian; Spurdle, Amanda B

2016-06-01

We conducted a meta-analysis of three endometrial cancer genome-wide association studies (GWAS) and two follow-up phases totaling 7,737 endometrial cancer cases and 37,144 controls of European ancestry. Genome-wide imputation and meta-analysis identified five new risk loci of genome-wide significance at likely regulatory regions on chromosomes 13q22.1 (rs11841589, near KLF5), 6q22.31 (rs13328298, in LOC643623 and near HEY2 and NCOA7), 8q24.21 (rs4733613, telomeric to MYC), 15q15.1 (rs937213, in EIF2AK4, near BMF) and 14q32.33 (rs2498796, in AKT1, near SIVA1). We also found a second independent 8q24.21 signal (rs17232730). Functional studies of the 13q22.1 locus showed that rs9600103 (pairwise r(2) = 0.98 with rs11841589) is located in a region of active chromatin that interacts with the KLF5 promoter region. The rs9600103[T] allele that is protective in endometrial cancer suppressed gene expression in vitro, suggesting that regulation of the expression of KLF5, a gene linked to uterine development, is implicated in tumorigenesis. These findings provide enhanced insight into the genetic and biological basis of endometrial cancer.

Cross Cancer Genomic Investigation of Inflammation Pathway for Five Common Cancers: Lung, Ovary, Prostate, Breast, and Colorectal Cancer.

PubMed

Hung, Rayjean J; Ulrich, Cornelia M; Goode, Ellen L; Brhane, Yonathan; Muir, Kenneth; Chan, Andrew T; Marchand, Loic Le; Schildkraut, Joellen; Witte, John S; Eeles, Rosalind; Boffetta, Paolo; Spitz, Margaret R; Poirier, Julia G; Rider, David N; Fridley, Brooke L; Chen, Zhihua; Haiman, Christopher; Schumacher, Fredrick; Easton, Douglas F; Landi, Maria Teresa; Brennan, Paul; Houlston, Richard; Christiani, David C; Field, John K; Bickeböller, Heike; Risch, Angela; Kote-Jarai, Zsofia; Wiklund, Fredrik; Grönberg, Henrik; Chanock, Stephen; Berndt, Sonja I; Kraft, Peter; Lindström, Sara; Al Olama, Ali Amin; Song, Honglin; Phelan, Catherine; Wentzensen, Nicholas; Peters, Ulrike; Slattery, Martha L; Sellers, Thomas A; Casey, Graham; Gruber, Stephen B; Hunter, David J; Amos, Christopher I; Henderson, Brian

2015-11-01

Inflammation has been hypothesized to increase the risk of cancer development as an initiator or promoter, yet no large-scale study of inherited variation across cancer sites has been conducted. We conducted a cross-cancer genomic analysis for the inflammation pathway based on 48 genome-wide association studies within the National Cancer Institute GAME-ON Network across five common cancer sites, with a total of 64 591 cancer patients and 74 467 control patients. Subset-based meta-analysis was used to account for possible disease heterogeneity, and hierarchical modeling was employed to estimate the effect of the subcomponents within the inflammation pathway. The network was visualized by enrichment map. All statistical tests were two-sided. We identified three pleiotropic loci within the inflammation pathway, including one novel locus in Ch12q24 encoding SH2B3 (rs3184504), which reached GWAS significance with a P value of 1.78 x 10(-8), and it showed an association with lung cancer (P = 2.01 x 10(-6)), colorectal cancer (GECCO P = 6.72x10(-6); CORECT P = 3.32x10(-5)), and breast cancer (P = .009). We also identified five key subpathway components with genetic variants that are relevant for the risk of these five cancer sites: inflammatory response for colorectal cancer (P = .006), inflammation related cell cycle gene for lung cancer (P = 1.35x10(-6)), and activation of immune response for ovarian cancer (P = .009). In addition, sequence variations in immune system development played a role in breast cancer etiology (P = .001) and innate immune response was involved in the risk of both colorectal (P = .022) and ovarian cancer (P = .003). Genetic variations in inflammation and its related subpathway components are keys to the development of lung, colorectal, ovary, and breast cancer, including SH2B3, which is associated with lung, colorectal, and breast cancer. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e

Cross Cancer Genomic Investigation of Inflammation Pathway for Five Common Cancers: Lung, Ovary, Prostate, Breast, and Colorectal Cancer

PubMed Central

Ulrich, Cornelia M.; Goode, Ellen L.; Brhane, Yonathan; Muir, Kenneth; Chan, Andrew T.; Marchand, Loic Le; Schildkraut, Joellen; Witte, John S.; Eeles, Rosalind; Boffetta, Paolo; Spitz, Margaret R.; Poirier, Julia G.; Rider, David N.; Fridley, Brooke L.; Chen, Zhihua; Haiman, Christopher; Schumacher, Fredrick; Easton, Douglas F.; Landi, Maria Teresa; Brennan, Paul; Houlston, Richard; Christiani, David C.; Field, John K.; Bickeböller, Heike; Risch, Angela; Kote-Jarai, Zsofia; Wiklund, Fredrik; Grönberg, Henrik; Chanock, Stephen; Berndt, Sonja I.; Kraft, Peter; Lindström, Sara; Al Olama, Ali Amin; Song, Honglin; Phelan, Catherine; Wentzensen, Nicholas; Peters, Ulrike; Slattery, Martha L.; Sellers, Thomas A.; Casey, Graham; Gruber, Stephen B.; Hunter, David J.; Amos, Christopher I.; Henderson, Brian

2015-01-01

Background: Inflammation has been hypothesized to increase the risk of cancer development as an initiator or promoter, yet no large-scale study of inherited variation across cancer sites has been conducted. Methods: We conducted a cross-cancer genomic analysis for the inflammation pathway based on 48 genome-wide association studies within the National Cancer Institute GAME-ON Network across five common cancer sites, with a total of 64 591 cancer patients and 74 467 control patients. Subset-based meta-analysis was used to account for possible disease heterogeneity, and hierarchical modeling was employed to estimate the effect of the subcomponents within the inflammation pathway. The network was visualized by enrichment map. All statistical tests were two-sided. Results: We identified three pleiotropic loci within the inflammation pathway, including one novel locus in Ch12q24 encoding SH2B3 (rs3184504), which reached GWAS significance with a P value of 1.78 x 10–8, and it showed an association with lung cancer (P = 2.01 x 10–6), colorectal cancer (GECCO P = 6.72x10-6; CORECT P = 3.32x10-5), and breast cancer (P = .009). We also identified five key subpathway components with genetic variants that are relevant for the risk of these five cancer sites: inflammatory response for colorectal cancer (P = .006), inflammation related cell cycle gene for lung cancer (P = 1.35x10-6), and activation of immune response for ovarian cancer (P = .009). In addition, sequence variations in immune system development played a role in breast cancer etiology (P = .001) and innate immune response was involved in the risk of both colorectal (P = .022) and ovarian cancer (P = .003). Conclusions: Genetic variations in inflammation and its related subpathway components are keys to the development of lung, colorectal, ovary, and breast cancer, including SH2B3, which is associated with lung, colorectal, and breast cancer. PMID:26319099

Genome Science and Personalized Cancer Treatment (LBNL Summer Lecture Series)

ScienceCinema

Gray, Joe [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Life Sciences Division and Associate Lab. Director for Life and Environmental Sciences

2018-05-04

Summer Lecture Series 2009: Results from the Human Genome Project are enabling scientists to understand how individual cancers form and progress. This information, when combined with newly developed drugs, can optimize the treatment of individual cancers. Joe Gray, director of Berkeley Labs Life Sciences Division and Associate Laboratory Director for Life and Environmental Sciences, will focus on this approach, its promise, and its current roadblocks — particularly with regard to breast cancer.

CPTAC researchers report first large-scale integrated proteomic and genomic analysis of a human cancer | Office of Cancer Clinical Proteomics Research

Cancer.gov

Investigators from the National Cancer Institute's Clinical Proteomic Tumor Analysis Consortium (CPTAC) who comprehensively analyzed 95 human colorectal tumor samples, have determined how gene alterations identified in previous analyses of the same samples are expressed at the protein level. The integration of proteomic and genomic data, or proteogenomics, provides a more comprehensive view of the biological features that drive cancer than genomic analysis alone and may help identify the most important targets for cancer detection and intervention.

Towards a global cancer knowledge network: dissecting the current international cancer genomic sequencing landscape.

PubMed

Vis, D J; Lewin, J; Liao, R G; Mao, M; Andre, F; Ward, R L; Calvo, F; Teh, B T; Camargo, A A; Knoppers, B M; Sawyers, C L; Wessels, L F A; Lawler, M; Siu, L L; Voest, E

2017-05-01

While next generation sequencing has enhanced our understanding of the biological basis of malignancy, current knowledge on global practices for sequencing cancer samples is limited. To address this deficiency, we developed a survey to provide a snapshot of current sequencing activities globally, identify barriers to data sharing and use this information to develop sustainable solutions for the cancer research community. A multi-item survey was conducted assessing demographics, clinical data collection, genomic platforms, privacy/ethics concerns, funding sources and data sharing barriers for sequencing initiatives globally. Additionally, respondents were asked as to provide the primary intent of their initiative (clinical diagnostic, research or combination). Of 107 initiatives invited to participate, 59 responded (response rate = 55%). Whole exome sequencing (P = 0.03) and whole genome sequencing (P = 0.01) were utilized less frequently in clinical diagnostic than in research initiatives. Procedures to identify cancer-specific variants were heterogeneous, with bioinformatics pipelines employing different mutation calling/variant annotation algorithms. Measurement of treatment efficacy varied amongst initiatives, with time on treatment (57%) and RECIST (53%) being the most common; however, other parameters were also employed. Whilst 72% of initiatives indicated data sharing, its scope varied, with a number of restrictions in place (e.g. transfer of raw data). The largest perceived barriers to data harmonization were the lack of financial support (P < 0.01) and bioinformatics concerns (e.g. lack of interoperability) (P = 0.02). Capturing clinical data was more likely to be perceived as a barrier to data sharing by larger initiatives than by smaller initiatives (P = 0.01). These results identify the main barriers, as perceived by the cancer sequencing community, to effective sharing of cancer genomic and clinical data. They highlight the need

Genome-wide gene–environment interaction analysis for asbestos exposure in lung cancer susceptibility

PubMed Central

Wei, Qingyi Wei

2012-01-01

Asbestos exposure is a known risk factor for lung cancer. Although recent genome-wide association studies (GWASs) have identified some novel loci for lung cancer risk, few addressed genome-wide gene–environment interactions. To determine gene–asbestos interactions in lung cancer risk, we conducted genome-wide gene–environment interaction analyses at levels of single nucleotide polymorphisms (SNPs), genes and pathways, using our published Texas lung cancer GWAS dataset. This dataset included 317 498 SNPs from 1154 lung cancer cases and 1137 cancer-free controls. The initial SNP-level P-values for interactions between genetic variants and self-reported asbestos exposure were estimated by unconditional logistic regression models with adjustment for age, sex, smoking status and pack-years. The P-value for the most significant SNP rs13383928 was 2.17×10–6, which did not reach the genome-wide statistical significance. Using a versatile gene-based test approach, we found that the top significant gene was C7orf54, located on 7q32.1 (P = 8.90×10–5). Interestingly, most of the other significant genes were located on 11q13. When we used an improved gene-set-enrichment analysis approach, we found that the Fas signaling pathway and the antigen processing and presentation pathway were most significant (nominal P < 0.001; false discovery rate < 0.05) among 250 pathways containing 17 572 genes. We believe that our analysis is a pilot study that first describes the gene–asbestos interaction in lung cancer risk at levels of SNPs, genes and pathways. Our findings suggest that immune function regulation-related pathways may be mechanistically involved in asbestos-associated lung cancer risk. Abbreviations:CIconfidence intervalEenvironmentFDRfalse discovery rateGgeneGSEAgene-set-enrichment analysisGWASgenome-wide association studiesi-GSEAimproved gene-set-enrichment analysis approachORodds ratioSNPsingle nucleotide polymorphism PMID:22637743

Genetics, Genomics and Cancer Risk Assessment: State of the art and future directions in the era of personalized medicine

PubMed Central

Weitzel, Jeffrey N.; Blazer, Kathleen R.; MacDonald, Deborah J.; Culver, Julie O.; Offit, Kenneth

2012-01-01

Scientific and technologic advances are revolutionizing our approach to genetic cancer risk assessment, cancer screening and prevention, and targeted therapy, fulfilling the promise of personalized medicine. In this monograph we review the evolution of scientific discovery in cancer genetics and genomics, and describe current approaches, benefits and barriers to the translation of this information to the practice of preventive medicine. Summaries of known hereditary cancer syndromes and highly penetrant genes are provided and contrasted with recently-discovered genomic variants associated with modest increases in cancer risk. We describe the scope of knowledge, tools, and expertise required for the translation of complex genetic and genomic test information into clinical practice. The challenges of genomic counseling include the need for genetics and genomics professional education and multidisciplinary team training, the need for evidence-based information regarding the clinical utility of testing for genomic variants, the potential dangers posed by premature marketing of first-generation genomic profiles, and the need for new clinical models to improve access to and responsible communication of complex disease-risk information. We conclude that given the experiences and lessons learned in the genetics era, the multidisciplinary model of genetic cancer risk assessment and management will serve as a solid foundation to support the integration of personalized genomic information into the practice of cancer medicine. PMID:21858794

Histone demethylase JARID1C inactivation triggers genomic instability in sporadic renal cancer

PubMed Central

Rondinelli, Beatrice; Rosano, Dalia; Antonini, Elena; Frenquelli, Michela; Montanini, Laura; Huang, DaChuan; Segalla, Simona; Yoshihara, Kosuke; Amin, Samir B.; Lazarevic, Dejan; The, Bin Tean; Verhaak, Roel G.W.; Futreal, P. Andrew; Di Croce, Luciano; Chin, Lynda; Cittaro, Davide; Tonon, Giovanni

2015-01-01

Mutations in genes encoding chromatin-remodeling proteins are often identified in a variety of cancers. For example, the histone demethylase JARID1C is frequently inactivated in patients with clear cell renal cell carcinoma (ccRCC); however, it is largely unknown how JARID1C dysfunction promotes cancer. Here, we determined that JARID1C binds broadly to chromatin domains characterized by the trimethylation of lysine 9 (H3K9me3), which is a histone mark enriched in heterochromatin. Moreover, we found that JARID1C localizes on heterochromatin, is required for heterochromatin replication, and forms a complex with established players of heterochromatin assembly, including SUV39H1 and HP1α, as well as with proteins not previously associated with heterochromatin assembly, such as the cullin 4 (CUL4) complex adaptor protein DDB1. Transcription on heterochromatin is tightly suppressed to safeguard the genome, and in ccRCC cells, JARID1C inactivation led to the unrestrained expression of heterochromatic noncoding RNAs (ncRNAs) that in turn triggered genomic instability. Moreover, ccRCC patients harboring JARID1C mutations exhibited aberrant ncRNA expression and increased genomic rearrangements compared with ccRCC patients with tumors endowed with other genetic lesions. Together, these data suggest that inactivation of JARID1C in renal cancer leads to heterochromatin disruption, genomic rearrangement, and aggressive ccRCCs. Moreover, our results shed light on a mechanism that underlies genomic instability in sporadic cancers. PMID:26551685

Provision of personalized genomic diagnostic technologies for breast and colorectal cancer: an analysis of patient needs, expectations and priorities.

PubMed

Issa, Amalia M; Hutchinson, Janis F; Tufail, Waqas; Fletcher, Erica; Ajike, Roseline; Tenorio, Jose

2011-07-01

Several novel pharmacogenomic diagnostic tests are commercially available for breast and colorectal cancer, and are increasingly being used in clinical practice for improving treatment decisions. However, there is little evidence evaluating the value of these new genomic technologies from the perspective of patients. As part of an ongoing effort to understand the continuum of the process of adoption of genomic diagnostics, our aim in this study was to examine the value of genomic diagnostics to breast and colorectal cancer patients, and their willingness to adopt and use genomic diagnostics. We conducted six focus groups of breast and colorectal cancer patients from the oncology clinics at The Methodist Hospital, Houston, TX, USA. An adapted Q-sort instrument was also administered to focus group participants. The majority of breast and colorectal cancer patients are interested in using novel genomic diagnostics for deciding about treatment options. Most participants in our study expressed a willingness to pay out-of-pocket for genomic testing (z = 0.736). Reliability and validity of genomic testing were of significant concern (z = 1.32) for the majority of breast and colorectal cancer patients. Participants identified several facilitators and barriers within health systems that might either facilitate or impede the widespread adoption and use of genomic diagnostics in healthcare delivery. This study demonstrates breast and colorectal cancer patients' willingness to adopt and pay for novel genomic diagnostics, as well as identifies several salient factors associated with patient preferences for genomic diagnostics.

Identification of genes associated with renal cell carcinoma using gene expression profiling analysis.

PubMed

Yao, Ting; Wang, Qinfu; Zhang, Wenyong; Bian, Aihong; Zhang, Jinping

2016-07-01

Renal cell carcinoma (RCC) is the most common type of kidney cancer in adults and accounts for ~80% of all kidney cancer cases. However, the pathogenesis of RCC has not yet been fully elucidated. To interpret the pathogenesis of RCC at the molecular level, gene expression data and bio-informatics methods were used to identify RCC associated genes. Gene expression data was downloaded from Gene Expression Omnibus (GEO) database and identified differentially coexpressed genes (DCGs) and dysfunctional pathways in RCC patients compared with controls. In addition, a regulatory network was constructed using the known regulatory data between transcription factors (TFs) and target genes in the University of California Santa Cruz (UCSC) Genome Browser (http://genome.ucsc.edu) and the regulatory impact factor of each TF was calculated. A total of 258,0427 pairs of DCGs were identified. The regulatory network contained 1,525 pairs of regulatory associations between 126 TFs and 1,259 target genes and these genes were mainly enriched in cancer pathways, ErbB and MAPK. In the regulatory network, the 10 most strongly associated TFs were FOXC1, GATA3, ESR1, FOXL1, PATZ1, MYB, STAT5A, EGR2, EGR3 and PELP1. GATA3, ERG and MYB serve important roles in RCC while FOXC1, ESR1, FOXL1, PATZ1, STAT5A and PELP1 may be potential genes associated with RCC. In conclusion, the present study constructed a regulatory network and screened out several TFs that may be used as molecular biomarkers of RCC. However, future studies are needed to confirm the findings of the present study.

Identification of genes associated with renal cell carcinoma using gene expression profiling analysis

PubMed Central

YAO, TING; WANG, QINFU; ZHANG, WENYONG; BIAN, AIHONG; ZHANG, JINPING

2016-01-01

Renal cell carcinoma (RCC) is the most common type of kidney cancer in adults and accounts for ~80% of all kidney cancer cases. However, the pathogenesis of RCC has not yet been fully elucidated. To interpret the pathogenesis of RCC at the molecular level, gene expression data and bio-informatics methods were used to identify RCC associated genes. Gene expression data was downloaded from Gene Expression Omnibus (GEO) database and identified differentially coexpressed genes (DCGs) and dysfunctional pathways in RCC patients compared with controls. In addition, a regulatory network was constructed using the known regulatory data between transcription factors (TFs) and target genes in the University of California Santa Cruz (UCSC) Genome Browser (http://genome.ucsc.edu) and the regulatory impact factor of each TF was calculated. A total of 258,0427 pairs of DCGs were identified. The regulatory network contained 1,525 pairs of regulatory associations between 126 TFs and 1,259 target genes and these genes were mainly enriched in cancer pathways, ErbB and MAPK. In the regulatory network, the 10 most strongly associated TFs were FOXC1, GATA3, ESR1, FOXL1, PATZ1, MYB, STAT5A, EGR2, EGR3 and PELP1. GATA3, ERG and MYB serve important roles in RCC while FOXC1, ESR1, FOXL1, PATZ1, STAT5A and PELP1 may be potential genes associated with RCC. In conclusion, the present study constructed a regulatory network and screened out several TFs that may be used as molecular biomarkers of RCC. However, future studies are needed to confirm the findings of the present study. PMID:27347102

The complete mitochondrial genome of a chronic hepatitis associated liver cancer LEC rat strain.

PubMed

Zhang, Sihao; Jiang, Zhaoming; Zhang, Shuai; Xia, Mingfeng; Tian, Fang; Tian, Hu

2016-05-01

We sequenced a complete mitochondrial genome sequencing of a chronic hepatitis-associated liver cancer disease LEC rat strain for the first time. The total length of the mitogenome was 16,316 bp with 13 protein-coding genes, two ribosomal RNA genes and 22 transfer RNA genes. This mitochondrial genome sequence will provide new genetic resource into liver cancer disease.

Multi-region and single-cell sequencing reveal variable genomic heterogeneity in rectal cancer.

PubMed

Liu, Mingshan; Liu, Yang; Di, Jiabo; Su, Zhe; Yang, Hong; Jiang, Beihai; Wang, Zaozao; Zhuang, Meng; Bai, Fan; Su, Xiangqian

2017-11-23

Colorectal cancer is a heterogeneous group of malignancies with complex molecular subtypes. While colon cancer has been widely investigated, studies on rectal cancer are very limited. Here, we performed multi-region whole-exome sequencing and single-cell whole-genome sequencing to examine the genomic intratumor heterogeneity (ITH) of rectal tumors. We sequenced nine tumor regions and 88 single cells from two rectal cancer patients with tumors of the same molecular classification and characterized their mutation profiles and somatic copy number alterations (SCNAs) at the multi-region and the single-cell levels. A variable extent of genomic heterogeneity was observed between the two patients, and the degree of ITH increased when analyzed on the single-cell level. We found that major SCNAs were early events in cancer development and inherited steadily. Single-cell sequencing revealed mutations and SCNAs which were hidden in bulk sequencing. In summary, we studied the ITH of rectal cancer at regional and single-cell resolution and demonstrated that variable heterogeneity existed in two patients. The mutational scenarios and SCNA profiles of two patients with treatment naïve from the same molecular subtype are quite different. Our results suggest each tumor possesses its own architecture, which may result in different diagnosis, prognosis, and drug responses. Remarkable ITH exists in the two patients we have studied, providing a preliminary impression of ITH in rectal cancer.

Landscape of somatic mutations in 560 breast cancer whole-genome sequences

DOE PAGES

Nik-Zainal, Serena; Davies, Helen; Staaf, Johan; ...

2016-05-02

Here, we analysed whole-genome sequences of 560 breast cancers to advance understanding of the driver mutations conferring clonal advantage and the mutational processes generating somatic mutations. We found that 93 protein-coding cancer genes carried probable driver mutations. Some non-coding regions exhibited high mutation frequencies, but most have distinctive structural features probably causing elevated mutation rates and do not contain driver mutations. Mutational signature analysis was extended to genome rearrangements and revealed twelve base substitution and six rearrangement signatures. Three rearrangement signatures, characterized by tandem duplications or deletions, appear associated with defective homologous-recombination-based DNA repair: one with deficient BRCA1 function, anothermore » with deficient BRCA1 or BRCA2 function, the cause of the third is unknown. This analysis of all classes of somatic mutation across exons, introns and intergenic regions highlights the repertoire of cancer genes and mutational processes operating, and progresses towards a comprehensive account of the somatic genetic basis of breast cancer.« less

Landscape of somatic mutations in 560 breast cancer whole-genome sequences

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

Nik-Zainal, Serena; Davies, Helen; Staaf, Johan

Here, we analysed whole-genome sequences of 560 breast cancers to advance understanding of the driver mutations conferring clonal advantage and the mutational processes generating somatic mutations. We found that 93 protein-coding cancer genes carried probable driver mutations. Some non-coding regions exhibited high mutation frequencies, but most have distinctive structural features probably causing elevated mutation rates and do not contain driver mutations. Mutational signature analysis was extended to genome rearrangements and revealed twelve base substitution and six rearrangement signatures. Three rearrangement signatures, characterized by tandem duplications or deletions, appear associated with defective homologous-recombination-based DNA repair: one with deficient BRCA1 function, anothermore » with deficient BRCA1 or BRCA2 function, the cause of the third is unknown. This analysis of all classes of somatic mutation across exons, introns and intergenic regions highlights the repertoire of cancer genes and mutational processes operating, and progresses towards a comprehensive account of the somatic genetic basis of breast cancer.« less

Landscape of somatic mutations in 560 breast cancer whole genome sequences

PubMed Central

Nik-Zainal, Serena; Davies, Helen; Staaf, Johan; Ramakrishna, Manasa; Glodzik, Dominik; Zou, Xueqing; Martincorena, Inigo; Alexandrov, Ludmil B.; Martin, Sancha; Wedge, David C.; Van Loo, Peter; Ju, Young Seok; Smid, Marcel; Brinkman, Arie B; Morganella, Sandro; Aure, Miriam R.; Lingjærde, Ole Christian; Langerød, Anita; Ringnér, Markus; Ahn, Sung-Min; Boyault, Sandrine; Brock, Jane E.; Broeks, Annegien; Butler, Adam; Desmedt, Christine; Dirix, Luc; Dronov, Serge; Fatima, Aquila; Foekens, John A.; Gerstung, Moritz; Hooijer, Gerrit KJ; Jang, Se Jin; Jones, David R.; Kim, Hyung-Yong; King, Tari A.; Krishnamurthy, Savitri; Lee, Hee Jin; Lee, Jeong-Yeon; Li, Yilong; McLaren, Stuart; Menzies, Andrew; Mustonen, Ville; O’Meara, Sarah; Pauporté, Iris; Pivot, Xavier; Purdie, Colin A.; Raine, Keiran; Ramakrishnan, Kamna; Rodríguez-González, F. Germán; Romieu, Gilles; Sieuwerts, Anieta M.; Simpson, Peter T; Shepherd, Rebecca; Stebbings, Lucy; Stefansson, Olafur A; Teague, Jon; Tommasi, Stefania; Treilleux, Isabelle; Van den Eynden, Gert G.; Vermeulen, Peter; Vincent-Salomon, Anne; Yates, Lucy; Caldas, Carlos; van’t Veer, Laura; Tutt, Andrew; Knappskog, Stian; Tan, Benita Kiat Tee; Jonkers, Jos; Borg, Åke; Ueno, Naoto T; Sotiriou, Christos; Viari, Alain; Futreal, P. Andrew; Campbell, Peter J; Span, Paul N.; Van Laere, Steven; Lakhani, Sunil R; Eyfjord, Jorunn E.; Thompson, Alastair M.; Birney, Ewan; Stunnenberg, Hendrik G; van de Vijver, Marc J; Martens, John W.M.; Børresen-Dale, Anne-Lise; Richardson, Andrea L.; Kong, Gu; Thomas, Gilles; Stratton, Michael R.

2016-01-01

We analysed whole genome sequences of 560 breast cancers to advance understanding of the driver mutations conferring clonal advantage and the mutational processes generating somatic mutations. 93 protein-coding cancer genes carried likely driver mutations. Some non-coding regions exhibited high mutation frequencies but most have distinctive structural features probably causing elevated mutation rates and do not harbour driver mutations. Mutational signature analysis was extended to genome rearrangements and revealed 12 base substitution and six rearrangement signatures. Three rearrangement signatures, characterised by tandem duplications or deletions, appear associated with defective homologous recombination based DNA repair: one with deficient BRCA1 function; another with deficient BRCA1 or BRCA2 function; the cause of the third is unknown. This analysis of all classes of somatic mutation across exons, introns and intergenic regions highlights the repertoire of cancer genes and mutational processes operative, and progresses towards a comprehensive account of the somatic genetic basis of breast cancer. PMID:27135926

A national study of breast and colorectal cancer patients' decision-making for novel personalized medicine genomic diagnostics.

PubMed

Issa, Amalia M; Tufail, Waqas; Atehortua, Nelson; McKeever, John

2013-05-01

Molecular diagnostics are increasingly being used to help guide decision-making for personalized medical treatment of breast and colorectal cancer patients. The main aim of this study was to better understand and determine breast and colorectal cancer patients' decision-making strategies and the trade-offs they make in deciding about characteristics of molecular genomic diagnostics for breast and colorectal cancer. We surveyed a nationally representative sample of 300 breast and colorectal cancer patients using a previously developed web-administered instrument. Eligibility criteria included patients aged 18 years and older with either breast or colorectal cancer. We explored several attributes and attribute levels of molecular genomic diagnostics in 20 scenarios. Our analysis revealed that both breast and colorectal cancer patients weighted the capability of molecular genomic diagnostics to determine the probability of treatment efficacy as being of greater importance than information provided to detect adverse events. The probability of either false-positive or -negative results was ranked highly as a potential barrier by both breast and colorectal patients. However, 78.6% of breast cancer patients ranked the possibility of a 'false-negative test result leading to undertreatment' higher than the 'chance of a false positive, which may lead to overtreatment' (68%). This finding contrasted with the views of colorectal cancer patients who ranked the chance of a false positive as being of greater concern than a false negative (72.8 vs 63%). Overall, cancer patients exhibited a high willingness to accept and pay for genomic diagnostic tests, especially among breast cancer patients. Cancer patients seek a test accuracy rate of 90% or higher. Breast and colorectal cancer patients' decisions about genomic diagnostics are influenced more by the probability of being cured than by avoiding potential severe adverse events. This study provides insights into the relative weight

A site specific model and analysis of the neutral somatic mutation rate in whole-genome cancer data.

PubMed

Bertl, Johanna; Guo, Qianyun; Juul, Malene; Besenbacher, Søren; Nielsen, Morten Muhlig; Hornshøj, Henrik; Pedersen, Jakob Skou; Hobolth, Asger

2018-04-19

Detailed modelling of the neutral mutational process in cancer cells is crucial for identifying driver mutations and understanding the mutational mechanisms that act during cancer development. The neutral mutational process is very complex: whole-genome analyses have revealed that the mutation rate differs between cancer types, between patients and along the genome depending on the genetic and epigenetic context. Therefore, methods that predict the number of different types of mutations in regions or specific genomic elements must consider local genomic explanatory variables. A major drawback of most methods is the need to average the explanatory variables across the entire region or genomic element. This procedure is particularly problematic if the explanatory variable varies dramatically in the element under consideration. To take into account the fine scale of the explanatory variables, we model the probabilities of different types of mutations for each position in the genome by multinomial logistic regression. We analyse 505 cancer genomes from 14 different cancer types and compare the performance in predicting mutation rate for both regional based models and site-specific models. We show that for 1000 randomly selected genomic positions, the site-specific model predicts the mutation rate much better than regional based models. We use a forward selection procedure to identify the most important explanatory variables. The procedure identifies site-specific conservation (phyloP), replication timing, and expression level as the best predictors for the mutation rate. Finally, our model confirms and quantifies certain well-known mutational signatures. We find that our site-specific multinomial regression model outperforms the regional based models. The possibility of including genomic variables on different scales and patient specific variables makes it a versatile framework for studying different mutational mechanisms. Our model can serve as the neutral null model

Scanning the Human Genome for Novel Therapeutic Targets for Breast Cancer

DTIC Science & Technology

2005-04-01

colon cancer genome, in sum representing only 34 annotated genes (Figure 3A). Consistent with its role in the pathogenesis of human cancers ( Ruas and...high-confidence list includes two previously established tumor suppressors, p16INKaA and TGFI3RII (Derynck et al., 2001; Ruas and Peters, 1998; Siegel...cancer. Nat Rev Cancer 4, 118-132. Chong, J. A., Tapia- Ramirez , J., Kim, S., Toledo-Aral, J. J., Zheng, Y., Boutros, M. C.. Altshuller, Y. M., Frohman

Clinical Actionability of Comprehensive Genomic Profiling for Management of Rare or Refractory Cancers

PubMed Central

Hirshfield, Kim M.; Tolkunov, Denis; Zhong, Hua; Ali, Siraj M.; Stein, Mark N.; Murphy, Susan; Vig, Hetal; Vazquez, Alexei; Glod, John; Moss, Rebecca A.; Belyi, Vladimir; Chan, Chang S.; Chen, Suzie; Goodell, Lauri; Foran, David; Yelensky, Roman; Palma, Norma A.; Sun, James X.; Miller, Vincent A.; Stephens, Philip J.; Ross, Jeffrey S.; Kaufman, Howard; Poplin, Elizabeth; Mehnert, Janice; Tan, Antoinette R.; Bertino, Joseph R.; Aisner, Joseph; DiPaola, Robert S.

2016-01-01

Background. The frequency with which targeted tumor sequencing results will lead to implemented change in care is unclear. Prospective assessment of the feasibility and limitations of using genomic sequencing is critically important. Methods. A prospective clinical study was conducted on 100 patients with diverse-histology, rare, or poor-prognosis cancers to evaluate the clinical actionability of a Clinical Laboratory Improvement Amendments (CLIA)-certified, comprehensive genomic profiling assay (FoundationOne), using formalin-fixed, paraffin-embedded tumors. The primary objectives were to assess utility, feasibility, and limitations of genomic sequencing for genomically guided therapy or other clinical purpose in the setting of a multidisciplinary molecular tumor board. Results. Of the tumors from the 92 patients with sufficient tissue, 88 (96%) had at least one genomic alteration (average 3.6, range 0–10). Commonly altered pathways included p53 (46%), RAS/RAF/MAPK (rat sarcoma; rapidly accelerated fibrosarcoma; mitogen-activated protein kinase) (45%), receptor tyrosine kinases/ligand (44%), PI3K/AKT/mTOR (phosphatidylinositol-4,5-bisphosphate 3-kinase; protein kinase B; mammalian target of rapamycin) (35%), transcription factors/regulators (31%), and cell cycle regulators (30%). Many low frequency but potentially actionable alterations were identified in diverse histologies. Use of comprehensive profiling led to implementable clinical action in 35% of tumors with genomic alterations, including genomically guided therapy, diagnostic modification, and trigger for germline genetic testing. Conclusion. Use of targeted next-generation sequencing in the setting of an institutional molecular tumor board led to implementable clinical action in more than one third of patients with rare and poor-prognosis cancers. Major barriers to implementation of genomically guided therapy were clinical status of the patient and drug access. Early and serial sequencing in the clinical

An online database for informing ecological network models: http://kelpforest.ucsc.edu.

PubMed

Beas-Luna, Rodrigo; Novak, Mark; Carr, Mark H; Tinker, Martin T; Black, August; Caselle, Jennifer E; Hoban, Michael; Malone, Dan; Iles, Alison

2014-01-01

Ecological network models and analyses are recognized as valuable tools for understanding the dynamics and resiliency of ecosystems, and for informing ecosystem-based approaches to management. However, few databases exist that can provide the life history, demographic and species interaction information necessary to parameterize ecological network models. Faced with the difficulty of synthesizing the information required to construct models for kelp forest ecosystems along the West Coast of North America, we developed an online database (http://kelpforest.ucsc.edu/) to facilitate the collation and dissemination of such information. Many of the database's attributes are novel yet the structure is applicable and adaptable to other ecosystem modeling efforts. Information for each taxonomic unit includes stage-specific life history, demography, and body-size allometries. Species interactions include trophic, competitive, facilitative, and parasitic forms. Each data entry is temporally and spatially explicit. The online data entry interface allows researchers anywhere to contribute and access information. Quality control is facilitated by attributing each entry to unique contributor identities and source citations. The database has proven useful as an archive of species and ecosystem-specific information in the development of several ecological network models, for informing management actions, and for education purposes (e.g., undergraduate and graduate training). To facilitate adaptation of the database by other researches for other ecosystems, the code and technical details on how to customize this database and apply it to other ecosystems are freely available and located at the following link (https://github.com/kelpforest-cameo/databaseui).

Data Mining Approaches for Genomic Biomarker Development: Applications Using Drug Screening Data from the Cancer Genome Project and the Cancer Cell Line Encyclopedia.

PubMed

Covell, David G

2015-01-01

Developing reliable biomarkers of tumor cell drug sensitivity and resistance can guide hypothesis-driven basic science research and influence pre-therapy clinical decisions. A popular strategy for developing biomarkers uses characterizations of human tumor samples against a range of cancer drug responses that correlate with genomic change; developed largely from the efforts of the Cancer Cell Line Encyclopedia (CCLE) and Sanger Cancer Genome Project (CGP). The purpose of this study is to provide an independent analysis of this data that aims to vet existing and add novel perspectives to biomarker discoveries and applications. Existing and alternative data mining and statistical methods will be used to a) evaluate drug responses of compounds with similar mechanism of action (MOA), b) examine measures of gene expression (GE), copy number (CN) and mutation status (MUT) biomarkers, combined with gene set enrichment analysis (GSEA), for hypothesizing biological processes important for drug response, c) conduct global comparisons of GE, CN and MUT as biomarkers across all drugs screened in the CGP dataset, and d) assess the positive predictive power of CGP-derived GE biomarkers as predictors of drug response in CCLE tumor cells. The perspectives derived from individual and global examinations of GEs, MUTs and CNs confirm existing and reveal unique and shared roles for these biomarkers in tumor cell drug sensitivity and resistance. Applications of CGP-derived genomic biomarkers to predict the drug response of CCLE tumor cells finds a highly significant ROC, with a positive predictive power of 0.78. The results of this study expand the available data mining and analysis methods for genomic biomarker development and provide additional support for using biomarkers to guide hypothesis-driven basic science research and pre-therapy clinical decisions.

Possible Human Papillomavirus 38 Contamination of Endometrial Cancer RNA Sequencing Samples in The Cancer Genome Atlas Database

PubMed Central

Kazemian, Majid; Ren, Min; Lin, Jian-Xin; Liao, Wei; Spolski, Rosanne

2015-01-01

ABSTRACT Viruses are causally associated with a number of human malignancies. In this study, we sought to identify new virus-cancer associations by searching RNA sequencing data sets from >2,000 patients, encompassing 21 cancers from The Cancer Genome Atlas (TCGA), for the presence of viral sequences. In agreement with previous studies, we found human papillomavirus 16 (HPV16) and HPV18 in oropharyngeal cancer and hepatitis B and C viruses in liver cancer. Unexpectedly, however, we found HPV38, a cutaneous form of HPV associated with skin cancer, in 32 of 168 samples from endometrial cancer. In 12 of the HPV38-positive (HPV38+) samples, we observed at least one paired read that mapped to both human and HPV38 genomes, indicative of viral integration into the host DNA, something not previously demonstrated for HPV38. The expression levels of HPV38 transcripts were relatively low, and all 32 HPV38+ samples belonged to the same experimental batch of 40 samples, whereas none of the other 128 endometrial carcinoma samples were HPV38+, raising doubts about the significance of the HPV38 association. Moreover, the HPV38+ samples contained the same 10 novel single nucleotide variations (SNVs), leading us to hypothesize that one patient was infected with this new isolate of HPV38, which was integrated into his/her genome and may have cross-contaminated other TCGA samples within batch 228. Based on our analysis, we propose guidelines to examine the batch effect, virus expression level, and SNVs as part of next-generation sequencing (NGS) data analysis for evaluating the significance of viral/pathogen sequences in clinical samples. IMPORTANCE High-throughput RNA sequencing (RNA-Seq), followed by computational analysis, has vastly accelerated the identification of viral and other pathogenic sequences in clinical samples, but cross-contamination during the processing of the samples remain a major problem that can lead to erroneous conclusions. We found HPV38 sequences

Characterization of Human Cancer Cell Lines by Reverse-phase Protein Arrays* | Office of Cancer Genomics

Cancer.gov

Cancer cell lines are major model systems for mechanistic investigation and drug development. However, protein expression data linked to high-quality DNA, RNA, and drug-screening data have not been available across a large number of cancer cell lines. Using reverse-phase protein arrays, we measured expression levels of ∼230 key cancer-related proteins in >650 independent cell lines, many of which have publically available genomic, transcriptomic, and drug-screening data.

Funding Opportunity: Genomic Data Centers

Cancer.gov

Funding Opportunity CCG, Funding Opportunity Center for Cancer Genomics, CCG, Center for Cancer Genomics, CCG RFA, Center for cancer genomics rfa, genomic data analysis network, genomic data analysis network centers,

Keeping genome organized creates opportunities for damage | Center for Cancer Research

Cancer.gov

Packing an entire genome inside the cramped quarters of a cell nucleus can put chromosomes at risk for damage, according to new research led by André Nussenzweig, Ph.D., Chief of CCR’s Laboratory of Genomic Integrity. The findings, reported July 20, 2017, in Cell, suggest that DNA breaks are routinely introduced and then repaired as a cell folds and organizes its genome, and that when repair processes fail, these breaks can give rise to chromosomal abnormalities characteristic of cancer cells. 

University of Texas MD Anderson Cancer Center: High-Throughput Screening Identifying Driving Mutations in Endometrial Cancer | Office of Cancer Genomics

Cancer.gov

Recent advances in next-generation sequencing technology have enabled the unprecedented characterization of a full spectrum of somatic alterations in cancer genomes. Given the large numbers of somatic mutations typically detected by this approach, a key challenge in the downstream analysis is to distinguish “drivers” that functionally contribute to tumorigenesis from “passengers” that occur as the consequence of genomic instability.

Genomic instability in human cancer: Molecular insights and opportunities for therapeutic attack and prevention through diet and nutrition

PubMed Central

Ferguson, Lynnette R.; Chen, Helen; Collins, Andrew R.; Connell, Marisa; Damia, Giovanna; Dasgupta, Santanu; Malhotra, Meenakshi; Meeker, Alan K.; Amedei, Amedeo; Amin, Amr; Ashraf, S. Salman; Aquilano, Katia; Azmi, Asfar S.; Bhakta, Dipita; Bilsland, Alan; Boosani, Chandra S.; Chen, Sophie; Ciriolo, Maria Rosa; Fujii, Hiromasa; Guha, Gunjan; Halicka, Dorota; Helferich, William G.; Keith, W. Nicol; Mohammed, Sulma I.; Niccolai, Elena; Yang, Xujuan; Honoki, Kanya; Parslow, Virginia R.; Prakash, Satya; Rezazadeh, Sarallah; Shackelford, Rodney E.; Sidransky, David; Tran, Phuoc T.; Yang, Eddy S.; Maxwell, Christopher A.

2015-01-01

Genomic instability can initiate cancer, augment progression, and influence the overall prognosis of the affected patient. Genomic instability arises from many different pathways, such as telomere damage, centrosome amplification, epigenetic modifications, and DNA damage from endogenous and exogenous sources, and can be perpetuating, or limiting, through the induction of mutations or aneuploidy, both enabling and catastrophic. Many cancer treatments induce DNA damage to impair cell division on a global scale but it is accepted that personalized treatments, those that are tailored to the particular patient and type of cancer, must also be developed. In this review, we detail the mechanisms from which genomic instability arises and can lead to cancer, as well as treatments and measures that prevent genomic instability or take advantage of the cellular defects caused by genomic instability. In particular, we identify and discuss five priority targets against genomic instability: (1) prevention of DNA damage; (2) enhancement of DNA repair; (3) targeting deficient DNA repair; (4) impairing centrosome clustering; and, (5) inhibition of telomerase activity. Moreover, we highlight vitamin D and B, selenium, carotenoids, PARP inhibitors, resveratrol, and isothiocyanates as priority approaches against genomic instability. The prioritized target sites and approaches were cross validated to identify potential synergistic effects on a number of important areas of cancer biology. PMID:25869442

CGI: Java Software for Mapping and Visualizing Data from Array-based Comparative Genomic Hybridization and Expression Profiling

PubMed Central

Gu, Joyce Xiuweu-Xu; Wei, Michael Yang; Rao, Pulivarthi H.; Lau, Ching C.; Behl, Sanjiv; Man, Tsz-Kwong

2007-01-01

With the increasing application of various genomic technologies in biomedical research, there is a need to integrate these data to correlate candidate genes/regions that are identified by different genomic platforms. Although there are tools that can analyze data from individual platforms, essential software for integration of genomic data is still lacking. Here, we present a novel Java-based program called CGI (Cytogenetics-Genomics Integrator) that matches the BAC clones from array-based comparative genomic hybridization (aCGH) to genes from RNA expression profiling datasets. The matching is computed via a fast, backend MySQL database containing UCSC Genome Browser annotations. This program also provides an easy-to-use graphical user interface for visualizing and summarizing the correlation of DNA copy number changes and RNA expression patterns from a set of experiments. In addition, CGI uses a Java applet to display the copy number values of a specific BAC clone in aCGH experiments side by side with the expression levels of genes that are mapped back to that BAC clone from the microarray experiments. The CGI program is built on top of extensible, reusable graphic components specifically designed for biologists. It is cross-platform compatible and the source code is freely available under the General Public License. PMID:19936083

CGI: Java software for mapping and visualizing data from array-based comparative genomic hybridization and expression profiling.

PubMed

Gu, Joyce Xiuweu-Xu; Wei, Michael Yang; Rao, Pulivarthi H; Lau, Ching C; Behl, Sanjiv; Man, Tsz-Kwong

2007-10-06

With the increasing application of various genomic technologies in biomedical research, there is a need to integrate these data to correlate candidate genes/regions that are identified by different genomic platforms. Although there are tools that can analyze data from individual platforms, essential software for integration of genomic data is still lacking. Here, we present a novel Java-based program called CGI (Cytogenetics-Genomics Integrator) that matches the BAC clones from array-based comparative genomic hybridization (aCGH) to genes from RNA expression profiling datasets. The matching is computed via a fast, backend MySQL database containing UCSC Genome Browser annotations. This program also provides an easy-to-use graphical user interface for visualizing and summarizing the correlation of DNA copy number changes and RNA expression patterns from a set of experiments. In addition, CGI uses a Java applet to display the copy number values of a specific BAC clone in aCGH experiments side by side with the expression levels of genes that are mapped back to that BAC clone from the microarray experiments. The CGI program is built on top of extensible, reusable graphic components specifically designed for biologists. It is cross-platform compatible and the source code is freely available under the General Public License.

Integrated genomic analysis of mitochondrial RNA processing in human cancers.

PubMed

Idaghdour, Youssef; Hodgkinson, Alan

2017-04-18

The mitochondrial genome is transcribed as continuous polycistrons of RNA containing multiple genes. As a consequence, post-transcriptional events are critical for the regulation of gene expression and therefore all aspects of mitochondrial function. One particularly important process is the m 1 A/m 1 G RNA methylation of the ninth position of different mitochondrial tRNAs, which allows efficient processing of mitochondrial mRNAs and protein translation, and de-regulation of genes involved in these processes has been associated with altered mitochondrial function. Although mitochondria play a key role in cancer, the status of mitochondrial RNA processing in tumorigenesis is unknown. We measure and assess mitochondrial RNA processing using integrated genomic analysis of RNA sequencing and genotyping data from 1226 samples across 12 different cancer types. We focus on the levels of m 1 A and m 1 G RNA methylation in mitochondrial tRNAs in normal and tumor samples and use supervised and unsupervised statistical analysis to compare the levels of these modifications to patient whole genome genotypes, nuclear gene expression, and survival outcomes. We find significant changes to m 1 A and m 1 G RNA methylation levels in mitochondrial tRNAs in tumor tissues across all cancers. Pathways of RNA processing are strongly associated with methylation levels in normal tissues (P = 3.27 × 10 -31 ), yet these associations are lost in tumors. Furthermore, we report 18 gene-by-disease-state interactions where altered RNA methylation levels occur under cancer status conditional on genotype, implicating genes associated with mitochondrial function or cancer (e.g., CACNA2D2, LMO2, and FLT3) and suggesting that nuclear genetic variation can potentially modulate an individual's ability to maintain unaltered rates of mitochondrial RNA processing under cancer status. Finally, we report a significant association between the magnitude of methylation level changes in tumors and

Genomic characterization of a Helicobacter pylori isolate from a patient with gastric cancer in China

PubMed Central

2014-01-01

Background Helicobacter pylori is well known for its relationship with the occurrence of several severe gastric diseases. The mechanisms of pathogenesis triggered by H. pylori are less well known. In this study, we report the genome sequence and genomic characterizations of H. pylori strain HLJ039 that was isolated from a patient with gastric cancer in the Chinese province of Heilongjiang, where there is a high incidence of gastric cancer. To investigate potential genomic features that may be involved in pathogenesis of carcinoma, the genome was compared to three previously sequenced genomes in this area. Result We obtained 42 contigs with a total length of 1,611,192 bp and predicted 1,687 coding sequences. Compared to strains isolated from gastritis and ulcers in this area, 10 different regions were identified as being unique for HLJ039; they mainly encoded type II restriction-modification enzyme, type II m6A methylase, DNA-cytosine methyltransferase, DNA methylase, and hypothetical proteins. A unique 547-bp fragment sharing 93% identity with a hypothetical protein of Helicobacter cinaedi ATCC BAA-847 was not present in any other previous H. pylori strains. Phylogenetic analysis based on core genome single nucleotide polymorphisms shows that HLJ039 is defined as hspEAsia subgroup, which belongs to the hpEastAsia group. Conclusion DNA methylations, variations of the genomic regions involved in restriction and modification systems, are the “hot” regions that may be related to the mechanism of H. pylori-induced gastric cancer. The genome sequence will provide useful information for the deep mining of potential mechanisms related to East Asian gastric cancer. PMID:24565107

Mutation of Breast Cancer Cell Genomic DNA by APOBEC3B

DTIC Science & Technology

2013-09-01

lethal prostate cancers. Proc. Natl Acad. Sci. USA 108, 17087–17092 (2011). 5. Parsons, D. W. et al. The genetic landscape of the childhood cancer...7. Stransky, N. et al. The mutational landscape of head and neck squamous cell carcinoma. Science 333, 1157–1160 (2011). 8. Nik-Zainal, S. et al...Mutational processes molding the genomes of 21 breast cancers. Cell 149, 979–993 (2012). 9. Stephens, P. J. et al. The landscape of cancer genes and

Frequent somatic transfer of mitochondrial DNA into the nuclear genome of human cancer cells.

PubMed

Ju, Young Seok; Tubio, Jose M C; Mifsud, William; Fu, Beiyuan; Davies, Helen R; Ramakrishna, Manasa; Li, Yilong; Yates, Lucy; Gundem, Gunes; Tarpey, Patrick S; Behjati, Sam; Papaemmanuil, Elli; Martin, Sancha; Fullam, Anthony; Gerstung, Moritz; Nangalia, Jyoti; Green, Anthony R; Caldas, Carlos; Borg, Åke; Tutt, Andrew; Lee, Ming Ta Michael; van't Veer, Laura J; Tan, Benita K T; Aparicio, Samuel; Span, Paul N; Martens, John W M; Knappskog, Stian; Vincent-Salomon, Anne; Børresen-Dale, Anne-Lise; Eyfjörd, Jórunn Erla; Myklebost, Ola; Flanagan, Adrienne M; Foster, Christopher; Neal, David E; Cooper, Colin; Eeles, Rosalind; Bova, Steven G; Lakhani, Sunil R; Desmedt, Christine; Thomas, Gilles; Richardson, Andrea L; Purdie, Colin A; Thompson, Alastair M; McDermott, Ultan; Yang, Fengtang; Nik-Zainal, Serena; Campbell, Peter J; Stratton, Michael R

2015-06-01

Mitochondrial genomes are separated from the nuclear genome for most of the cell cycle by the nuclear double membrane, intervening cytoplasm, and the mitochondrial double membrane. Despite these physical barriers, we show that somatically acquired mitochondrial-nuclear genome fusion sequences are present in cancer cells. Most occur in conjunction with intranuclear genomic rearrangements, and the features of the fusion fragments indicate that nonhomologous end joining and/or replication-dependent DNA double-strand break repair are the dominant mechanisms involved. Remarkably, mitochondrial-nuclear genome fusions occur at a similar rate per base pair of DNA as interchromosomal nuclear rearrangements, indicating the presence of a high frequency of contact between mitochondrial and nuclear DNA in some somatic cells. Transmission of mitochondrial DNA to the nuclear genome occurs in neoplastically transformed cells, but we do not exclude the possibility that some mitochondrial-nuclear DNA fusions observed in cancer occurred years earlier in normal somatic cells. © 2015 Ju et al.; Published by Cold Spring Harbor Laboratory Press.

Frequent somatic transfer of mitochondrial DNA into the nuclear genome of human cancer cells

PubMed Central

Ju, Young Seok; Tubio, Jose M.C.; Mifsud, William; Fu, Beiyuan; Davies, Helen R.; Ramakrishna, Manasa; Li, Yilong; Yates, Lucy; Gundem, Gunes; Tarpey, Patrick S.; Behjati, Sam; Papaemmanuil, Elli; Martin, Sancha; Fullam, Anthony; Gerstung, Moritz; Nangalia, Jyoti; Green, Anthony R.; Caldas, Carlos; Borg, Åke; Tutt, Andrew; Lee, Ming Ta Michael; van't Veer, Laura J.; Tan, Benita K.T.; Aparicio, Samuel; Span, Paul N.; Martens, John W.M.; Knappskog, Stian; Vincent-Salomon, Anne; Børresen-Dale, Anne-Lise; Eyfjörd, Jórunn Erla; Flanagan, Adrienne M.; Foster, Christopher; Neal, David E.; Cooper, Colin; Eeles, Rosalind; Lakhani, Sunil R.; Desmedt, Christine; Thomas, Gilles; Richardson, Andrea L.; Purdie, Colin A.; Thompson, Alastair M.; McDermott, Ultan; Yang, Fengtang; Nik-Zainal, Serena; Campbell, Peter J.; Stratton, Michael R.

2015-01-01

Mitochondrial genomes are separated from the nuclear genome for most of the cell cycle by the nuclear double membrane, intervening cytoplasm, and the mitochondrial double membrane. Despite these physical barriers, we show that somatically acquired mitochondrial-nuclear genome fusion sequences are present in cancer cells. Most occur in conjunction with intranuclear genomic rearrangements, and the features of the fusion fragments indicate that nonhomologous end joining and/or replication-dependent DNA double-strand break repair are the dominant mechanisms involved. Remarkably, mitochondrial-nuclear genome fusions occur at a similar rate per base pair of DNA as interchromosomal nuclear rearrangements, indicating the presence of a high frequency of contact between mitochondrial and nuclear DNA in some somatic cells. Transmission of mitochondrial DNA to the nuclear genome occurs in neoplastically transformed cells, but we do not exclude the possibility that some mitochondrial-nuclear DNA fusions observed in cancer occurred years earlier in normal somatic cells. PMID:25963125

Genomic Copy Number Dictates a Gene-Independent Cell Response to CRISPR/Cas9 Targeting | Office of Cancer Genomics

Cancer.gov

The CRISPR/Cas9 system enables genome editing and somatic cell genetic screens in mammalian cells. We performed genome-scale loss-of-function screens in 33 cancer cell lines to identify genes essential for proliferation/survival and found a strong correlation between increased gene copy number and decreased cell viability after genome editing. Within regions of copy-number gain, CRISPR/Cas9 targeting of both expressed and unexpressed genes, as well as intergenic loci, led to significantly decreased cell proliferation through induction of a G2 cell-cycle arrest.

How may targeted proteomics complement genomic data in breast cancer?

PubMed

Guerin, Mathilde; Gonçalves, Anthony; Toiron, Yves; Baudelet, Emilie; Audebert, Stéphane; Boyer, Jean-Baptiste; Borg, Jean-Paul; Camoin, Luc

2017-01-01

Breast cancer (BC) is the most common female cancer in the world and was recently deconstructed in different molecular entities. Although most of the recent assays to characterize tumors at the molecular level are genomic-based, proteins are the actual executors of cellular functions and represent the vast majority of targets for anticancer drugs. Accumulated data has demonstrated an important level of quantitative and qualitative discrepancies between genomic/transcriptomic alterations and their protein counterparts, mostly related to the large number of post-translational modifications. Areas covered: This review will present novel proteomics technologies such as Reverse Phase Protein Array (RPPA) or mass-spectrometry (MS) based approaches that have emerged and that could progressively replace old-fashioned methods (e.g. immunohistochemistry, ELISA, etc.) to validate proteins as diagnostic, prognostic or predictive biomarkers, and eventually monitor them in the routine practice. Expert commentary: These different targeted proteomic approaches, able to complement genomic data in BC and characterize tumors more precisely, will permit to go through a more personalized treatment for each patient and tumor.

The Impact of Genomic Changes on Treatment of Lung Cancer

PubMed Central

Cardarella, Stephanie

2013-01-01

The remarkable success of epidermal growth factor receptor (EGFR) and anaplastic lymphoma kinase (ALK) tyrosine kinase inhibitors in patients with EGFR mutations and ALK rearrangements, respectively, introduced the era of targeted therapy in advanced non-small cell lung cancer (NSCLC), shifting treatment from platinum-based combination chemotherapy to molecularly tailored therapy. Recent genomic studies in lung adenocarcinoma identified other potential therapeutic targets, including ROS1 rearrangements, RET fusions, MET amplification, and activating mutations in BRAF, HER2, and KRAS in frequencies exceeding 1%. Lung cancers that harbor these genomic changes can potentially be targeted with agents approved for other indications or under clinical development. The need to generate increasing amounts of genomic information should prompt health-care providers to be mindful of the amounts of tissue needed for these assays when planning diagnostic procedures. In this review, we summarize oncogenic drivers in NSCLC that can be currently detected, highlight their potential therapeutic implications, and discuss practical considerations for successful application of tumor genotyping in clinical decision making. PMID:23841470

A genome-wide pleiotropy scan for prostate cancer risk.

PubMed

Panagiotou, Orestis A; Travis, Ruth C; Campa, Daniele; Berndt, Sonja I; Lindstrom, Sara; Kraft, Peter; Schumacher, Fredrick R; Siddiq, Afshan; Papatheodorou, Stefania I; Stanford, Janet L; Albanes, Demetrius; Virtamo, Jarmo; Weinstein, Stephanie J; Diver, W Ryan; Gapstur, Susan M; Stevens, Victoria L; Boeing, Heiner; Bueno-de-Mesquita, H Bas; Barricarte Gurrea, Aurelio; Kaaks, Rudolf; Khaw, Kay-Tee; Krogh, Vittorio; Overvad, Kim; Riboli, Elio; Trichopoulos, Dimitrios; Giovannucci, Edward; Stampfer, Meir; Haiman, Christopher; Henderson, Brian; Le Marchand, Loic; Gaziano, J Michael; Hunter, David J; Koutros, Stella; Yeager, Meredith; Hoover, Robert N; Chanock, Stephen J; Wacholder, Sholom; Key, Timothy J; Tsilidis, Konstantinos K

2015-04-01

No single-nucleotide polymorphisms (SNPs) specific for aggressive prostate cancer have been identified in genome-wide association studies (GWAS). To test if SNPs associated with other traits may also affect the risk of aggressive prostate cancer. SNPs implicated in any phenotype other than prostate cancer (p≤10(-7)) were identified through the catalog of published GWAS and tested in 2891 aggressive prostate cancer cases and 4592 controls from the Breast and Prostate Cancer Cohort Consortium (BPC3). The 40 most significant SNPs were followed up in 4872 aggressive prostate cancer cases and 24,534 controls from the Prostate Cancer Association Group to Investigate Cancer Associated Alterations in the Genome (PRACTICAL) consortium. Odds ratios (ORs) and 95% confidence intervals (CIs) for aggressive prostate cancer were estimated. A total of 4666 SNPs were evaluated by the BPC3. Two signals were seen in regions already reported for prostate cancer risk. rs7014346 at 8q24.21 was marginally associated with aggressive prostate cancer in the BPC3 trial (p=1.6×10(-6)), whereas after meta-analysis by PRACTICAL the summary OR was 1.21 (95% CI 1.16-1.27; p=3.22×10(-18)). rs9900242 at 17q24.3 was also marginally associated with aggressive disease in the meta-analysis (OR 0.90, 95% CI 0.86-0.94; p=2.5×10(-6)). Neither of these SNPs remained statistically significant when conditioning on correlated known prostate cancer SNPs. The meta-analysis by BPC3 and PRACTICAL identified a third promising signal, marked by rs16844874 at 2q34, independent of known prostate cancer loci (OR 1.12, 95% CI 1.06-1.19; p=4.67×10(-5)); it has been shown that SNPs correlated with this signal affect glycine concentrations. The main limitation is the heterogeneity in the definition of aggressive prostate cancer between BPC3 and PRACTICAL. We did not identify new SNPs for aggressive prostate cancer. However, rs16844874 may provide preliminary genetic evidence on the role of the glycine pathway in

Genome-wide association study identifies multiple loci associated with bladder cancer risk

PubMed Central

Figueroa, Jonine D.; Ye, Yuanqing; Siddiq, Afshan; Garcia-Closas, Montserrat; Chatterjee, Nilanjan; Prokunina-Olsson, Ludmila; Cortessis, Victoria K.; Kooperberg, Charles; Cussenot, Olivier; Benhamou, Simone; Prescott, Jennifer; Porru, Stefano; Dinney, Colin P.; Malats, Núria; Baris, Dalsu; Purdue, Mark; Jacobs, Eric J.; Albanes, Demetrius; Wang, Zhaoming; Deng, Xiang; Chung, Charles C.; Tang, Wei; Bas Bueno-de-Mesquita, H.; Trichopoulos, Dimitrios; Ljungberg, Börje; Clavel-Chapelon, Françoise; Weiderpass, Elisabete; Krogh, Vittorio; Dorronsoro, Miren; Travis, Ruth; Tjønneland, Anne; Brenan, Paul; Chang-Claude, Jenny; Riboli, Elio; Conti, David; Gago-Dominguez, Manuela; Stern, Mariana C.; Pike, Malcolm C.; Van Den Berg, David; Yuan, Jian-Min; Hohensee, Chancellor; Rodabough, Rebecca; Cancel-Tassin, Geraldine; Roupret, Morgan; Comperat, Eva; Chen, Constance; De Vivo, Immaculata; Giovannucci, Edward; Hunter, David J.; Kraft, Peter; Lindstrom, Sara; Carta, Angela; Pavanello, Sofia; Arici, Cecilia; Mastrangelo, Giuseppe; Kamat, Ashish M.; Lerner, Seth P.; Barton Grossman, H.; Lin, Jie; Gu, Jian; Pu, Xia; Hutchinson, Amy; Burdette, Laurie; Wheeler, William; Kogevinas, Manolis; Tardón, Adonina; Serra, Consol; Carrato, Alfredo; García-Closas, Reina; Lloreta, Josep; Schwenn, Molly; Karagas, Margaret R.; Johnson, Alison; Schned, Alan; Armenti, Karla R.; Hosain, G.M.; Andriole, Gerald; Grubb, Robert; Black, Amanda; Ryan Diver, W.; Gapstur, Susan M.; Weinstein, Stephanie J.; Virtamo, Jarmo; Haiman, Chris A.; Landi, Maria T.; Caporaso, Neil; Fraumeni, Joseph F.; Vineis, Paolo; Wu, Xifeng; Silverman, Debra T.; Chanock, Stephen; Rothman, Nathaniel

2014-01-01

Candidate gene and genome-wide association studies (GWAS) have identified 11 independent susceptibility loci associated with bladder cancer risk. To discover additional risk variants, we conducted a new GWAS of 2422 bladder cancer cases and 5751 controls, followed by a meta-analysis with two independently published bladder cancer GWAS, resulting in a combined analysis of 6911 cases and 11 814 controls of European descent. TaqMan genotyping of 13 promising single nucleotide polymorphisms with P < 1 × 10−5 was pursued in a follow-up set of 801 cases and 1307 controls. Two new loci achieved genome-wide statistical significance: rs10936599 on 3q26.2 (P = 4.53 × 10−9) and rs907611 on 11p15.5 (P = 4.11 × 10−8). Two notable loci were also identified that approached genome-wide statistical significance: rs6104690 on 20p12.2 (P = 7.13 × 10−7) and rs4510656 on 6p22.3 (P = 6.98 × 10−7); these require further studies for confirmation. In conclusion, our study has identified new susceptibility alleles for bladder cancer risk that require fine-mapping and laboratory investigation, which could further understanding into the biological underpinnings of bladder carcinogenesis. PMID:24163127

Segtor: Rapid Annotation of Genomic Coordinates and Single Nucleotide Variations Using Segment Trees

PubMed Central

Renaud, Gabriel; Neves, Pedro; Folador, Edson Luiz; Ferreira, Carlos Gil; Passetti, Fabio

2011-01-01

Various research projects often involve determining the relative position of genomic coordinates, intervals, single nucleotide variations (SNVs), insertions, deletions and translocations with respect to genes and their potential impact on protein translation. Due to the tremendous increase in throughput brought by the use of next-generation sequencing, investigators are routinely faced with the need to annotate very large datasets. We present Segtor, a tool to annotate large sets of genomic coordinates, intervals, SNVs, indels and translocations. Our tool uses segment trees built using the start and end coordinates of the genomic features the user wishes to use instead of storing them in a database management system. The software also produces annotation statistics to allow users to visualize how many coordinates were found within various portions of genes. Our system currently can be made to work with any species available on the UCSC Genome Browser. Segtor is a suitable tool for groups, especially those with limited access to programmers or with interest to analyze large amounts of individual genomes, who wish to determine the relative position of very large sets of mapped reads and subsequently annotate observed mutations between the reads and the reference. Segtor (http://lbbc.inca.gov.br/segtor/) is an open-source tool that can be freely downloaded for non-profit use. We also provide a web interface for testing purposes. PMID:22069465

Mutational load of the mitochondrial genome predicts pathological features and biochemical recurrence in prostate cancer.

PubMed

Kalsbeek, Anton M F; Chan, Eva F K; Grogan, Judith; Petersen, Desiree C; Jaratlerdsiri, Weerachai; Gupta, Ruta; Lyons, Ruth J; Haynes, Anne-Maree; Horvath, Lisa G; Kench, James G; Stricker, Phillip D; Hayes, Vanessa M

2016-10-05

Prostate cancer management is complicated by extreme disease heterogeneity, which is further limited by availability of prognostic biomarkers. Recognition of prostate cancer as a genetic disease has prompted a focus on the nuclear genome for biomarker discovery, with little attention given to the mitochondrial genome. While it is evident that mitochondrial DNA (mtDNA) mutations are acquired during prostate tumorigenesis, no study has evaluated the prognostic value of mtDNA variation. Here we used next-generation sequencing to interrogate the mitochondrial genomes from prostate tissue biopsies and matched blood of 115 men having undergone a radical prostatectomy for which there was a mean of 107 months clinical follow-up. We identified 74 unique prostate cancer specific somatic mtDNA variants in 50 patients, providing significant expansion to the growing catalog of prostate cancer mtDNA mutations. While no single variant or variant cluster showed recurrence across multiple patients, we observe a significant positive correlation between the total burden of acquired mtDNA variation and elevated Gleason Score at diagnosis and biochemical relapse. We add to accumulating evidence that total acquired genomic burden, rather than specific mtDNA mutations, has diagnostic value. This is the first study to demonstrate the prognostic potential of mtDNA mutational burden in prostate cancer.

A comprehensive assessment of somatic mutation detection in cancer using whole-genome sequencing

PubMed Central

Alioto, Tyler S.; Buchhalter, Ivo; Derdak, Sophia; Hutter, Barbara; Eldridge, Matthew D.; Hovig, Eivind; Heisler, Lawrence E.; Beck, Timothy A.; Simpson, Jared T.; Tonon, Laurie; Sertier, Anne-Sophie; Patch, Ann-Marie; Jäger, Natalie; Ginsbach, Philip; Drews, Ruben; Paramasivam, Nagarajan; Kabbe, Rolf; Chotewutmontri, Sasithorn; Diessl, Nicolle; Previti, Christopher; Schmidt, Sabine; Brors, Benedikt; Feuerbach, Lars; Heinold, Michael; Gröbner, Susanne; Korshunov, Andrey; Tarpey, Patrick S.; Butler, Adam P.; Hinton, Jonathan; Jones, David; Menzies, Andrew; Raine, Keiran; Shepherd, Rebecca; Stebbings, Lucy; Teague, Jon W.; Ribeca, Paolo; Giner, Francesc Castro; Beltran, Sergi; Raineri, Emanuele; Dabad, Marc; Heath, Simon C.; Gut, Marta; Denroche, Robert E.; Harding, Nicholas J.; Yamaguchi, Takafumi N.; Fujimoto, Akihiro; Nakagawa, Hidewaki; Quesada, Víctor; Valdés-Mas, Rafael; Nakken, Sigve; Vodák, Daniel; Bower, Lawrence; Lynch, Andrew G.; Anderson, Charlotte L.; Waddell, Nicola; Pearson, John V.; Grimmond, Sean M.; Peto, Myron; Spellman, Paul; He, Minghui; Kandoth, Cyriac; Lee, Semin; Zhang, John; Létourneau, Louis; Ma, Singer; Seth, Sahil; Torrents, David; Xi, Liu; Wheeler, David A.; López-Otín, Carlos; Campo, Elías; Campbell, Peter J.; Boutros, Paul C.; Puente, Xose S.; Gerhard, Daniela S.; Pfister, Stefan M.; McPherson, John D.; Hudson, Thomas J.; Schlesner, Matthias; Lichter, Peter; Eils, Roland; Jones, David T. W.; Gut, Ivo G.

2015-01-01

As whole-genome sequencing for cancer genome analysis becomes a clinical tool, a full understanding of the variables affecting sequencing analysis output is required. Here using tumour-normal sample pairs from two different types of cancer, chronic lymphocytic leukaemia and medulloblastoma, we conduct a benchmarking exercise within the context of the International Cancer Genome Consortium. We compare sequencing methods, analysis pipelines and validation methods. We show that using PCR-free methods and increasing sequencing depth to ∼100 × shows benefits, as long as the tumour:control coverage ratio remains balanced. We observe widely varying mutation call rates and low concordance among analysis pipelines, reflecting the artefact-prone nature of the raw data and lack of standards for dealing with the artefacts. However, we show that, using the benchmark mutation set we have created, many issues are in fact easy to remedy and have an immediate positive impact on mutation detection accuracy. PMID:26647970

Cancer Therapy Directed by Comprehensive Genomic Profiling: A Single Center Study.

PubMed

Wheler, Jennifer J; Janku, Filip; Naing, Aung; Li, Yali; Stephen, Bettzy; Zinner, Ralph; Subbiah, Vivek; Fu, Siqing; Karp, Daniel; Falchook, Gerald S; Tsimberidou, Apostolia M; Piha-Paul, Sarina; Anderson, Roosevelt; Ke, Danxia; Miller, Vincent; Yelensky, Roman; Lee, J Jack; Hong, David S; Kurzrock, Razelle

2016-07-01

Innovative molecular diagnostics deployed in the clinic enable new ways to stratify patients into appropriate treatment regimens. These approaches may resolve a major challenge for early-phase clinical trials, which is to recruit patients who, while having failed previous treatments, may nevertheless respond to molecularly targeted drugs. We report the findings of a prospective, single-center study conducted in patients with diverse refractory cancers who underwent comprehensive genomic profiling (CGP; next-generation sequencing, 236 genes). Of the 500 patients enrolled, 188 (37.6%) received either matched (N = 122/188, 65%) or unmatched therapy (N = 66/188, 35%). The most common reasons that patients were not evaluable for treatment included insufficient tissue, death, or hospice transfer. The median number of molecular alterations per patient was five (range, 1-14); median number of prior therapies, four. The most common diagnoses were ovarian cancer (18%), breast cancer (16%), sarcoma (13%), and renal cancer (7%). Of the 339 successfully profiled patients, 317 (93.5%) had at least one potentially actionable alteration. By calculating matching scores, based on the number of drug matches and genomic aberrations per patient, we found that high scores were independently associated with a greater frequency of stable disease ≥6 months/partial/complete remission [22% (high scores) vs. 9% (low scores), P = 0.024], longer time-to-treatment failure [hazard ratio (HR) = 0.52; 95% confidence interval (CI) = 0.36-0.74; P = 0.0003], and survival (HR = 0.65; 95% CI = 0.43-1.0; P = 0.05). Collectively, this study offers a clinical proof of concept for the utility of CGP in assigning therapy to patients with refractory malignancies, especially in those patients with multiple genomic aberrations for whom combination therapies could be implemented. Cancer Res; 76(13); 3690-701. ©2016 AACR. ©2016 American Association for Cancer Research.

Sequencing the head and neck cancer genome: implications for therapy

PubMed Central

Sun, Wenyue; Califano, Joseph A.

2015-01-01

Head and neck squamous cell carcinoma (HNSCC) is a disease with significant morbidity and mortality. The advancement of next-generation sequencing technologies now enables the landscape of genetic alterations in HNSCCs to be deciphered. In this review, we describe the mutation spectrum discovered in HNSCCs, especially human papilloma virus (HPV)- and/or tobacco smoke exposure–associated HNSCCs. We also describe related research from two independent investigators and from the Cancer Genome Atlas (TCGA). Emphasis is placed on the therapeutic implications of genes frequently altered in HNSCCs (i.e., TP53, PIK3CA, and NOTCH1) and their corresponding pathways, with a particular focus on recent findings of NOTCH pathway activation in HNSCC. We also discuss the application of integrated genomic pathway–based analysis for precision cancer therapy in HNSCC. PMID:25440877

A-to-I RNA Editing Contributes to Proteomic Diversity in Cancer. | Office of Cancer Genomics

Cancer.gov

Adenosine (A) to inosine (I) RNA editing introduces many nucleotide changes in cancer transcriptomes. However, due to the complexity of post-transcriptional regulation, the contribution of RNA editing to proteomic diversity in human cancers remains unclear. Here, we performed an integrated analysis of TCGA genomic data and CPTAC proteomic data. Despite limited site diversity, we demonstrate that A-to-I RNA editing contributes to proteomic diversity in breast cancer through changes in amino acid sequences. We validate the presence of editing events at both RNA and protein levels.

Integrative clinical genomics of advanced prostate cancer.

PubMed

Robinson, Dan; Van Allen, Eliezer M; Wu, Yi-Mi; Schultz, Nikolaus; Lonigro, Robert J; Mosquera, Juan-Miguel; Montgomery, Bruce; Taplin, Mary-Ellen; Pritchard, Colin C; Attard, Gerhardt; Beltran, Himisha; Abida, Wassim; Bradley, Robert K; Vinson, Jake; Cao, Xuhong; Vats, Pankaj; Kunju, Lakshmi P; Hussain, Maha; Feng, Felix Y; Tomlins, Scott A; Cooney, Kathleen A; Smith, David C; Brennan, Christine; Siddiqui, Javed; Mehra, Rohit; Chen, Yu; Rathkopf, Dana E; Morris, Michael J; Solomon, Stephen B; Durack, Jeremy C; Reuter, Victor E; Gopalan, Anuradha; Gao, Jianjiong; Loda, Massimo; Lis, Rosina T; Bowden, Michaela; Balk, Stephen P; Gaviola, Glenn; Sougnez, Carrie; Gupta, Manaswi; Yu, Evan Y; Mostaghel, Elahe A; Cheng, Heather H; Mulcahy, Hyojeong; True, Lawrence D; Plymate, Stephen R; Dvinge, Heidi; Ferraldeschi, Roberta; Flohr, Penny; Miranda, Susana; Zafeiriou, Zafeiris; Tunariu, Nina; Mateo, Joaquin; Perez-Lopez, Raquel; Demichelis, Francesca; Robinson, Brian D; Schiffman, Marc; Nanus, David M; Tagawa, Scott T; Sigaras, Alexandros; Eng, Kenneth W; Elemento, Olivier; Sboner, Andrea; Heath, Elisabeth I; Scher, Howard I; Pienta, Kenneth J; Kantoff, Philip; de Bono, Johann S; Rubin, Mark A; Nelson, Peter S; Garraway, Levi A; Sawyers, Charles L; Chinnaiyan, Arul M

2015-05-21

Toward development of a precision medicine framework for metastatic, castration-resistant prostate cancer (mCRPC), we established a multi-institutional clinical sequencing infrastructure to conduct prospective whole-exome and transcriptome sequencing of bone or soft tissue tumor biopsies from a cohort of 150 mCRPC affected individuals. Aberrations of AR, ETS genes, TP53, and PTEN were frequent (40%-60% of cases), with TP53 and AR alterations enriched in mCRPC compared to primary prostate cancer. We identified new genomic alterations in PIK3CA/B, R-spondin, BRAF/RAF1, APC, β-catenin, and ZBTB16/PLZF. Moreover, aberrations of BRCA2, BRCA1, and ATM were observed at substantially higher frequencies (19.3% overall) compared to those in primary prostate cancers. 89% of affected individuals harbored a clinically actionable aberration, including 62.7% with aberrations in AR, 65% in other cancer-related genes, and 8% with actionable pathogenic germline alterations. This cohort study provides clinically actionable information that could impact treatment decisions for these affected individuals. Copyright © 2015 Elsevier Inc. All rights reserved.

Integrative clinical genomics of advanced prostate cancer

PubMed Central

Dan, Robinson; Van Allen, Eliezer M.; Wu, Yi-Mi; Schultz, Nikolaus; Lonigro, Robert J.; Mosquera, Juan-Miguel; Montgomery, Bruce; Taplin, Mary-Ellen; Pritchard, Colin C; Attard, Gerhardt; Beltran, Himisha; Abida, Wassim M.; Bradley, Robert K.; Vinson, Jake; Cao, Xuhong; Vats, Pankaj; Kunju, Lakshmi P.; Hussain, Maha; Feng, Felix Y.; Tomlins, Scott A.; Cooney, Kathleen A.; Smith, David C.; Brennan, Christine; Siddiqui, Javed; Mehra, Rohit; Chen, Yu; Rathkopf, Dana E.; Morris, Michael J.; Solomon, Stephen B.; Durack, Jeremy C.; Reuter, Victor E.; Gopalan, Anuradha; Gao, Jianjiong; Loda, Massimo; Lis, Rosina T.; Bowden, Michaela; Balk, Stephen P.; Gaviola, Glenn; Sougnez, Carrie; Gupta, Manaswi; Yu, Evan Y.; Mostaghel, Elahe A.; Cheng, Heather H.; Mulcahy, Hyojeong; True, Lawrence D.; Plymate, Stephen R.; Dvinge, Heidi; Ferraldeschi, Roberta; Flohr, Penny; Miranda, Susana; Zafeiriou, Zafeiris; Tunariu, Nina; Mateo, Joaquin; Lopez, Raquel Perez; Demichelis, Francesca; Robinson, Brian D.; Schiffman, Marc A.; Nanus, David M.; Tagawa, Scott T.; Sigaras, Alexandros; Eng, Kenneth W.; Elemento, Olivier; Sboner, Andrea; Heath, Elisabeth I.; Scher, Howard I.; Pienta, Kenneth J.; Kantoff, Philip; de Bono, Johann S.; Rubin, Mark A.; Nelson, Peter S.; Garraway, Levi A.; Sawyers, Charles L.; Chinnaiyan, Arul M.

2015-01-01

SUMMARY Toward development of a precision medicine framework for metastatic, castration resistant prostate cancer (mCRPC), we established a multi-institutional clinical sequencing infrastructure to conduct prospective whole exome and transcriptome sequencing of bone or soft tissue tumor biopsies from a cohort of 150 mCRPC affected individuals. Aberrations of AR, ETS genes, TP53 and PTEN were frequent (40–60% of cases), with TP53 and AR alterations enriched in mCRPC compared to primary prostate cancer. We identified novel genomic alterations in PIK3CA/B, R-spondin, BRAF/RAF1, APC, β-catenin and ZBTB16/PLZF. Aberrations of BRCA2, BRCA1 and ATM were observed at substantially higher frequencies (19.3% overall) than seen in primary prostate cancers. 89% of affected individuals harbored a clinically actionable aberration including 62.7% with aberrations in AR, 65% in other cancer-related genes, and 8% with actionable pathogenic germline alterations. This cohort study provides evidence that clinical sequencing in mCRPC is feasible and could impact treatment decisions in significant numbers of affected individuals. PMID:26000489

The Emerging Genomic Landscape of Endometrial Cancer

PubMed Central

Le Gallo, Matthieu; Bell, Daphne W.

2014-01-01

BACKGROUND Endometrial cancer is responsible for ~74,000 deaths amongst women worldwide each year. It is a heterogeneous disease that consists of multiple different histological subtypes. In the United States, the majority of deaths from endometrial carcinoma are attributed to the serous and endometrioid subtypes. An understanding of the fundamental genomic alterations that drive serous and endometrioid endometrial carcinomas lays the foundation for the identification of molecular markers that could improve the clinical management of patients presenting with these tumors. CONTENT Herein we review the current state of knowledge of the somatic genomic alterations that are present in serous and endometrioid endometrial tumors. We present this knowledge in a historical context – reviewing the genomic alterations that have been identified over the past two decades or more, from studies of individual genes and proteins, followed by a review of very recent studies that have conducted comprehensive, systematic surveys of genomic, exomic, transcriptomic, epigenomic, and proteomic alterations in serous and endometrioid endometrial carcinomas. SUMMARY The recent mapping of the genomic landscape of serous and endometrioid endometrial carcinomas has resulted in the first comprehensive molecular classification of these tumors and has distinguished four molecular subgroups: a POLE ultramutated subgroup, a hypermutated/microsatellite unstable subgroup, a copy number low/microsatellite stable subgroup, and a copy number high subgroup. This molecular classification may ultimately serve to refine the diagnosis and treatment of women with endometrioid and serous endometrial tumors. PMID:24170611

Discovery of Genomic Breakpoints Affecting Breast Cancer Progression and Prognosis

DTIC Science & Technology

2010-10-01

mutations compared to those detected by the 5Kbp method alone. Fosmid diTag method also reveals much higher proportion of gene fusions and truncations...observed highly similar structural mutational spectra affecting different sets of genes , pointing to similar histories of genomic instability against... mutations have been identified in non-BRCA1/2 multiethnic breast cancer cases (45,46), no truncating mutation of the RAP80 gene in breast cancer has

A review of estrogen receptor/androgen receptor genomics in male breast cancer.

PubMed

Severson, Tesa M; Zwart, Wilbert

2017-03-01

Male breast cancer is a rare disease, of which little is known. In contrast to female breast cancer, the very vast majority of all cases are positive for estrogen receptor alpha (ERα), implicating the function of this steroid hormone receptor in tumor development and progression. Consequently, adjuvant treatment of male breast cancer revolves around inhibition of ERα. In addition, the androgen receptor (AR) gradually receives more attention as a relevant novel target in breast cancer treatment. Importantly, the rationale of treatment decision making is strongly based on parallels with female breast cancer. Yet, prognostic indicators are not necessarily the same in breast cancer between both genders, complicating translatability of knowledge developed in female breast cancer toward male patients. Even though ERα and AR are expressed both in female and male disease, are the genomic functions of both steroid hormone receptors conserved between genders? Recent studies have reported on mutational and epigenetic similarities and differences between male and female breast cancer, further suggesting that some features are strongly conserved between the two diseases, whereas others are not. This review critically discusses the recent developments in the study of male breast cancer in relation to ERα and AR action and highlights the potential future studies to further elucidate the genomic regulation of this rare disease. © 2017 Society for Endocrinology.

Possible Human Papillomavirus 38 Contamination of Endometrial Cancer RNA Sequencing Samples in The Cancer Genome Atlas Database.

PubMed

Kazemian, Majid; Ren, Min; Lin, Jian-Xin; Liao, Wei; Spolski, Rosanne; Leonard, Warren J

2015-09-01

Viruses are causally associated with a number of human malignancies. In this study, we sought to identify new virus-cancer associations by searching RNA sequencing data sets from >2,000 patients, encompassing 21 cancers from The Cancer Genome Atlas (TCGA), for the presence of viral sequences. In agreement with previous studies, we found human papillomavirus 16 (HPV16) and HPV18 in oropharyngeal cancer and hepatitis B and C viruses in liver cancer. Unexpectedly, however, we found HPV38, a cutaneous form of HPV associated with skin cancer, in 32 of 168 samples from endometrial cancer. In 12 of the HPV38-positive (HPV38(+)) samples, we observed at least one paired read that mapped to both human and HPV38 genomes, indicative of viral integration into the host DNA, something not previously demonstrated for HPV38. The expression levels of HPV38 transcripts were relatively low, and all 32 HPV38(+) samples belonged to the same experimental batch of 40 samples, whereas none of the other 128 endometrial carcinoma samples were HPV38(+), raising doubts about the significance of the HPV38 association. Moreover, the HPV38(+) samples contained the same 10 novel single nucleotide variations (SNVs), leading us to hypothesize that one patient was infected with this new isolate of HPV38, which was integrated into his/her genome and may have cross-contaminated other TCGA samples within batch 228. Based on our analysis, we propose guidelines to examine the batch effect, virus expression level, and SNVs as part of next-generation sequencing (NGS) data analysis for evaluating the significance of viral/pathogen sequences in clinical samples. High-throughput RNA sequencing (RNA-Seq), followed by computational analysis, has vastly accelerated the identification of viral and other pathogenic sequences in clinical samples, but cross-contamination during the processing of the samples remain a major problem that can lead to erroneous conclusions. We found HPV38 sequences specifically present in

Integrated genomic and molecular characterization of cervical cancer.

PubMed

2017-03-16

Cervical cancer remains one of the leading causes of cancer-related deaths worldwide. Here we report the extensive molecular characterization of 228 primary cervical cancers, one of the largest comprehensive genomic studies of cervical cancer to date. We observed notable APOBEC mutagenesis patterns and identified SHKBP1, ERBB3, CASP8, HLA-A and TGFBR2 as novel significantly mutated genes in cervical cancer. We also discovered amplifications in immune targets CD274 (also known as PD-L1) and PDCD1LG2 (also known as PD-L2), and the BCAR4 long non-coding RNA, which has been associated with response to lapatinib. Integration of human papilloma virus (HPV) was observed in all HPV18-related samples and 76% of HPV16-related samples, and was associated with structural aberrations and increased target-gene expression. We identified a unique set of endometrial-like cervical cancers, comprised predominantly of HPV-negative tumours with relatively high frequencies of KRAS, ARID1A and PTEN mutations. Integrative clustering of 178 samples identified keratin-low squamous, keratin-high squamous and adenocarcinoma-rich subgroups. These molecular analyses reveal new potential therapeutic targets for cervical cancers.

Knowledge boosting: a graph-based integration approach with multi-omics data and genomic knowledge for cancer clinical outcome prediction

PubMed Central

Kim, Dokyoon; Joung, Je-Gun; Sohn, Kyung-Ah; Shin, Hyunjung; Park, Yu Rang; Ritchie, Marylyn D; Kim, Ju Han

2015-01-01

Objective Cancer can involve gene dysregulation via multiple mechanisms, so no single level of genomic data fully elucidates tumor behavior due to the presence of numerous genomic variations within or between levels in a biological system. We have previously proposed a graph-based integration approach that combines multi-omics data including copy number alteration, methylation, miRNA, and gene expression data for predicting clinical outcome in cancer. However, genomic features likely interact with other genomic features in complex signaling or regulatory networks, since cancer is caused by alterations in pathways or complete processes. Methods Here we propose a new graph-based framework for integrating multi-omics data and genomic knowledge to improve power in predicting clinical outcomes and elucidate interplay between different levels. To highlight the validity of our proposed framework, we used an ovarian cancer dataset from The Cancer Genome Atlas for predicting stage, grade, and survival outcomes. Results Integrating multi-omics data with genomic knowledge to construct pre-defined features resulted in higher performance in clinical outcome prediction and higher stability. For the grade outcome, the model with gene expression data produced an area under the receiver operating characteristic curve (AUC) of 0.7866. However, models of the integration with pathway, Gene Ontology, chromosomal gene set, and motif gene set consistently outperformed the model with genomic data only, attaining AUCs of 0.7873, 0.8433, 0.8254, and 0.8179, respectively. Conclusions Integrating multi-omics data and genomic knowledge to improve understanding of molecular pathogenesis and underlying biology in cancer should improve diagnostic and prognostic indicators and the effectiveness of therapies. PMID:25002459

Knowledge boosting: a graph-based integration approach with multi-omics data and genomic knowledge for cancer clinical outcome prediction.

PubMed

Kim, Dokyoon; Joung, Je-Gun; Sohn, Kyung-Ah; Shin, Hyunjung; Park, Yu Rang; Ritchie, Marylyn D; Kim, Ju Han

2015-01-01

Cancer can involve gene dysregulation via multiple mechanisms, so no single level of genomic data fully elucidates tumor behavior due to the presence of numerous genomic variations within or between levels in a biological system. We have previously proposed a graph-based integration approach that combines multi-omics data including copy number alteration, methylation, miRNA, and gene expression data for predicting clinical outcome in cancer. However, genomic features likely interact with other genomic features in complex signaling or regulatory networks, since cancer is caused by alterations in pathways or complete processes. Here we propose a new graph-based framework for integrating multi-omics data and genomic knowledge to improve power in predicting clinical outcomes and elucidate interplay between different levels. To highlight the validity of our proposed framework, we used an ovarian cancer dataset from The Cancer Genome Atlas for predicting stage, grade, and survival outcomes. Integrating multi-omics data with genomic knowledge to construct pre-defined features resulted in higher performance in clinical outcome prediction and higher stability. For the grade outcome, the model with gene expression data produced an area under the receiver operating characteristic curve (AUC) of 0.7866. However, models of the integration with pathway, Gene Ontology, chromosomal gene set, and motif gene set consistently outperformed the model with genomic data only, attaining AUCs of 0.7873, 0.8433, 0.8254, and 0.8179, respectively. Integrating multi-omics data and genomic knowledge to improve understanding of molecular pathogenesis and underlying biology in cancer should improve diagnostic and prognostic indicators and the effectiveness of therapies. © The Author 2014. Published by Oxford University Press on behalf of the American Medical Informatics Association.

An Online Database for Informing Ecological Network Models: http://kelpforest.ucsc.edu

PubMed Central

Beas-Luna, Rodrigo; Novak, Mark; Carr, Mark H.; Tinker, Martin T.; Black, August; Caselle, Jennifer E.; Hoban, Michael; Malone, Dan; Iles, Alison

2014-01-01

Ecological network models and analyses are recognized as valuable tools for understanding the dynamics and resiliency of ecosystems, and for informing ecosystem-based approaches to management. However, few databases exist that can provide the life history, demographic and species interaction information necessary to parameterize ecological network models. Faced with the difficulty of synthesizing the information required to construct models for kelp forest ecosystems along the West Coast of North America, we developed an online database (http://kelpforest.ucsc.edu/) to facilitate the collation and dissemination of such information. Many of the database's attributes are novel yet the structure is applicable and adaptable to other ecosystem modeling efforts. Information for each taxonomic unit includes stage-specific life history, demography, and body-size allometries. Species interactions include trophic, competitive, facilitative, and parasitic forms. Each data entry is temporally and spatially explicit. The online data entry interface allows researchers anywhere to contribute and access information. Quality control is facilitated by attributing each entry to unique contributor identities and source citations. The database has proven useful as an archive of species and ecosystem-specific information in the development of several ecological network models, for informing management actions, and for education purposes (e.g., undergraduate and graduate training). To facilitate adaptation of the database by other researches for other ecosystems, the code and technical details on how to customize this database and apply it to other ecosystems are freely available and located at the following link (https://github.com/kelpforest-cameo/databaseui). PMID:25343723

An online database for informing ecological network models: http://kelpforest.ucsc.edu

USGS Publications Warehouse

Beas-Luna, Rodrigo; Tinker, M. Tim; Novak, Mark; Carr, Mark H.; Black, August; Caselle, Jennifer E.; Hoban, Michael; Malone, Dan; Iles, Alison C.

2014-01-01

Ecological network models and analyses are recognized as valuable tools for understanding the dynamics and resiliency of ecosystems, and for informing ecosystem-based approaches to management. However, few databases exist that can provide the life history, demographic and species interaction information necessary to parameterize ecological network models. Faced with the difficulty of synthesizing the information required to construct models for kelp forest ecosystems along the West Coast of North America, we developed an online database (http://kelpforest.ucsc.edu/) to facilitate the collation and dissemination of such information. Many of the database's attributes are novel yet the structure is applicable and adaptable to other ecosystem modeling efforts. Information for each taxonomic unit includes stage-specific life history, demography, and body-size allometries. Species interactions include trophic, competitive, facilitative, and parasitic forms. Each data entry is temporally and spatially explicit. The online data entry interface allows researchers anywhere to contribute and access information. Quality control is facilitated by attributing each entry to unique contributor identities and source citations. The database has proven useful as an archive of species and ecosystem-specific information in the development of several ecological network models, for informing management actions, and for education purposes (e.g., undergraduate and graduate training). To facilitate adaptation of the database by other researches for other ecosystems, the code and technical details on how to customize this database and apply it to other ecosystems are freely available and located at the following link (https://github.com/kelpforest-cameo/data​baseui).

Genomic Data Commons and Genomic Cloud Pilots - Google Hangout

Cancer.gov

Join us for a live, moderated discussion about two NCI efforts to expand access to cancer genomics data: the Genomic Data Commons and Genomic Cloud Pilots. NCI subject matters experts will include Louis M. Staudt, M.D., Ph.D., Director Center for Cancer Genomics, Warren Kibbe, Ph.D., Director, NCI Center for Biomedical Informatics and Information Technology, and moderated by Anthony Kerlavage, Ph.D., Chief, Cancer Informatics Branch, Center for Biomedical Informatics and Information Technology. We welcome your questions before and during the Hangout on Twitter using the hashtag #AskNCI.

Detection of inherited mutations for breast and ovarian cancer using genomic capture and massively parallel sequencing

PubMed Central

Walsh, Tom; Lee, Ming K.; Casadei, Silvia; Thornton, Anne M.; Stray, Sunday M.; Pennil, Christopher; Nord, Alex S.; Mandell, Jessica B.; Swisher, Elizabeth M.; King, Mary-Claire

2010-01-01

Inherited loss-of-function mutations in the tumor suppressor genes BRCA1, BRCA2, and multiple other genes predispose to high risks of breast and/or ovarian cancer. Cancer-associated inherited mutations in these genes are collectively quite common, but individually rare or even private. Genetic testing for BRCA1 and BRCA2 mutations has become an integral part of clinical practice, but testing is generally limited to these two genes and to women with severe family histories of breast or ovarian cancer. To determine whether massively parallel, “next-generation” sequencing would enable accurate, thorough, and cost-effective identification of inherited mutations for breast and ovarian cancer, we developed a genomic assay to capture, sequence, and detect all mutations in 21 genes, including BRCA1 and BRCA2, with inherited mutations that predispose to breast or ovarian cancer. Constitutional genomic DNA from subjects with known inherited mutations, ranging in size from 1 to >100,000 bp, was hybridized to custom oligonucleotides and then sequenced using a genome analyzer. Analysis was carried out blind to the mutation in each sample. Average coverage was >1200 reads per base pair. After filtering sequences for quality and number of reads, all single-nucleotide substitutions, small insertion and deletion mutations, and large genomic duplications and deletions were detected. There were zero false-positive calls of nonsense mutations, frameshift mutations, or genomic rearrangements for any gene in any of the test samples. This approach enables widespread genetic testing and personalized risk assessment for breast and ovarian cancer. PMID:20616022

The current use and attitudes towards tumor genome sequencing in breast cancer

PubMed Central

Gingras, I.; Sonnenblick, A.; de Azambuja, E.; Paesmans, M.; Delaloge, S.; Aftimos, Philippe; Piccart, M. J.; Sotiriou, C.; Ignatiadis, M.; Azim, H. A.

2016-01-01

There is increasing availability of technologies that can interrogate the genomic landscape of an individual tumor; however, their impact on daily practice remains uncertain. We conducted a 28-item survey to investigate the current attitudes towards the integration of tumor genome sequencing in breast cancer management. A link to the survey was communicated via newsletters of several oncological societies, and dedicated mailing by academic research groups. Multivariable logistic regression modeling was carried out to determine the relationship between predictors and outcomes. 215 physicians participated to the survey. The majority were medical oncologists (88%), practicing in Europe (70%) and working in academic institutions (66%). Tumor genome sequencing was requested by 82 participants (38%), of whom 21% reported low confidence in their genomic knowledge, and 56% considered tumor genome sequencing to be poorly accessible. In multivariable analysis, having time allocated to research (OR 3.37, 95% CI 1.84–6.15, p < 0.0001), working in Asia (OR 5.76, 95% CI 1.57 – 21.15, p = 0.01) and having institutional guidelines for molecular sequencing (OR 2.09, 95% 0.99–4.42, p = 0.05) were associated with a higher probability of use. In conclusion, our survey indicates that tumor genome sequencing is sometimes used, albeit not widely, in guiding management of breast cancer patients. PMID:26931736

A framework for identification of actionable cancer genome dependencies in small cell lung cancer

PubMed Central

Sos, Martin L.; Dietlein, Felix; Peifer, Martin; Schöttle, Jakob; Balke-Want, Hyatt; Müller, Christian; Koker, Mirjam; Richters, André; Heynck, Stefanie; Malchers, Florian; Heuckmann, Johannes M.; Seidel, Danila; Eyers, Patrick A.; Ullrich, Roland T.; Antonchick, Andrey P.; Vintonyak, Viktor V.; Schneider, Peter M.; Ninomiya, Takashi; Waldmann, Herbert; Büttner, Reinhard; Rauh, Daniel; Heukamp, Lukas C.; Thomas, Roman K.

2012-01-01

Small cell lung cancer (SCLC) accounts for about 15% of all lung cancers. The prognosis of SCLC patients is devastating and no biologically targeted therapeutics are active in this tumor type. To develop a framework for development of specific SCLC-targeted drugs we conducted a combined genomic and pharmacological vulnerability screen in SCLC cell lines. We show that SCLC cell lines capture the genomic landscape of primary SCLC tumors and provide genetic predictors for activity of clinically relevant inhibitors by screening 267 compounds across 44 of these cell lines. We show Aurora kinase inhibitors are effective in SCLC cell lines bearing MYC amplification, which occur in 3–7% of SCLC patients. In MYC-amplified SCLC cells Aurora kinase inhibition associates with G2/M-arrest, inactivation of PI3-kinase (PI3K) signaling, and induction of apoptosis. Aurora dependency in SCLC primarily involved Aurora B, required its kinase activity, and was independent of depletion of cytoplasmic levels of MYC. Our study suggests that a fraction of SCLC patients may benefit from therapeutic inhibition of Aurora B. Thus, thorough chemical and genomic exploration of SCLC cell lines may provide starting points for further development of rational targeted therapeutic intervention in this deadly tumor type. PMID:23035247

Structural RNAs of known and unknown function identified in malaria parasites by comparative genomics and RNA analysis

PubMed Central

Chakrabarti, Kausik; Pearson, Michael; Grate, Leslie; Sterne-Weiler, Timothy; Deans, Jonathan; Donohue, John Paul; Ares, Manuel

2007-01-01

As the genomes of more eukaryotic pathogens are sequenced, understanding how molecular differences between parasite and host might be exploited to provide new therapies has become a major focus. Central to cell function are RNA-containing complexes involved in gene expression, such as the ribosome, the spliceosome, snoRNAs, RNase P, and telomerase, among others. In this article we identify by comparative genomics and validate by RNA analysis numerous previously unknown structural RNAs encoded by the Plasmodium falciparum genome, including the telomerase RNA, U3, 31 snoRNAs, as well as previously predicted spliceosomal snRNAs, SRP RNA, MRP RNA, and RNAse P RNA. Furthermore, we identify six new RNA coding genes of unknown function. To investigate the relationships of the RNA coding genes to other genomic features in related parasites, we developed a genome browser for P. falciparum (http://areslab.ucsc.edu/cgi-bin/hgGateway). Additional experiments provide evidence supporting the prediction that snoRNAs guide methylation of a specific position on U4 snRNA, as well as predicting an snRNA promoter element particular to Plasmodium sp. These findings should allow detailed structural comparisons between the RNA components of the gene expression machinery of the parasite and its vertebrate hosts. PMID:17901154

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

PubMed

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

2018-05-01

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

Analysis of renal cancer cell lines from two major resources enables genomics-guided cell line selection

NASA Astrophysics Data System (ADS)

Sinha, Rileen; Winer, Andrew G.; Chevinsky, Michael; Jakubowski, Christopher; Chen, Ying-Bei; Dong, Yiyu; Tickoo, Satish K.; Reuter, Victor E.; Russo, Paul; Coleman, Jonathan A.; Sander, Chris; Hsieh, James J.; Hakimi, A. Ari

2017-05-01

The utility of cancer cell lines is affected by the similarity to endogenous tumour cells. Here we compare genomic data from 65 kidney-derived cell lines from the Cancer Cell Line Encyclopedia and the COSMIC Cell Lines Project to three renal cancer subtypes from The Cancer Genome Atlas: clear cell renal cell carcinoma (ccRCC, also known as kidney renal clear cell carcinoma), papillary (pRCC, also known as kidney papillary) and chromophobe (chRCC, also known as kidney chromophobe) renal cell carcinoma. Clustering copy number alterations shows that most cell lines resemble ccRCC, a few (including some often used as models of ccRCC) resemble pRCC, and none resemble chRCC. Human ccRCC tumours clustering with cell lines display clinical and genomic features of more aggressive disease, suggesting that cell lines best represent aggressive tumours. We stratify mutations and copy number alterations for important kidney cancer genes by the consistency between databases, and classify cell lines into established gene expression-based indolent and aggressive subtypes. Our results could aid investigators in analysing appropriate renal cancer cell lines.

Genome-wide association studies in bladder cancer: first results and potential relevance.

PubMed

Kiemeney, Lambertus A; Grotenhuis, Anne J; Vermeulen, Sita H; Wu, Xifeng

2009-09-01

The role of genetic susceptibility in the development of urinary bladder cancer is unclear, as it is in many other types of cancer. Since 2007, however, an innovative research approach (i.e. genome-wide association studies or GWASs) has led to the identification of numerous genomic loci that harbor susceptibility factors for one or more cancer sites. All GWASs have been published in high-impact journals and the strengths of the design are acknowledged by all experts, but there is criticism about the relevance of the results. Late 2008, the first GWAS in bladder cancer was published. In this review, the principles of GWASs are explained, as well as their strengths and limitations. The study in bladder cancer among 4000 cases and 38,000 controls identified three new susceptibility loci at 8q24, 3q28, and 5p15 that increase the risk of bladder cancer by 22, 19, and 16%, respectively. The results of two other GWASs in bladder cancer are expected to appear this year. Joint analysis of the three studies will probably identify additional susceptibility loci. The results of bladder cancer GWASs may point the way to yet unknown disease mechanisms. So far, the findings are not sufficiently discriminative for risk predictions to be used in clinical care or public health.

ALCHEMIST: Bringing genomic discovery and targeted therapies to early-stage lung cancer.

PubMed

Gerber, D E; Oxnard, G R; Govindan, R

2015-05-01

The identification of druggable molecular alterations represents one of the greatest advances in cancer treatment. Such progress is particularly evident for lung cancer, which now has numerous molecularly defined subsets such as epidermal growth factor receptor (EGFR) mutations and anaplastic lymphoma kinase (ALK) rearrangements. However, understanding of the significance of these genomic alterations is largely limited to incurable, metastatic lung cancer. ALCHEMIST (Adjuvant Lung Cancer Enrichment Marker Identification and Sequencing Trial) is a National Cancer Institute-sponsored initiative to address these questions in earlier-stage disease. © 2015 American Society for Clinical Pharmacology and Therapeutics.

ALCHEMIST: Bringing Genomic Discovery and Targeted Therapies to Early-Stage Lung Cancer

PubMed Central

Gerber, DE; Oxnard, GR; Govindan, R

2016-01-01

The identification of druggable molecular alterations represents one of the greatest advances in cancer treatment. Such progress is particularly evident for lung cancer, which now has numerous molecularly defined subsets such as epidermal growth factor receptor (EGFR) mutations and anaplastic lymphoma kinase (ALK) rearrangements. However, understanding of the significance of these genomic alterations is largely limited to incurable, metastatic lung cancer. ALCHEMIST (Adjuvant Lung Cancer Enrichment Marker Identification and Sequencing Trial) is a National Cancer Institute–sponsored initiative to address these questions in earlier-stage disease. PMID:25677079

Building a semantic web-based metadata repository for facilitating detailed clinical modeling in cancer genome studies.

PubMed

Sharma, Deepak K; Solbrig, Harold R; Tao, Cui; Weng, Chunhua; Chute, Christopher G; Jiang, Guoqian

2017-06-05

Detailed Clinical Models (DCMs) have been regarded as the basis for retaining computable meaning when data are exchanged between heterogeneous computer systems. To better support clinical cancer data capturing and reporting, there is an emerging need to develop informatics solutions for standards-based clinical models in cancer study domains. The objective of the study is to develop and evaluate a cancer genome study metadata management system that serves as a key infrastructure in supporting clinical information modeling in cancer genome study domains. We leveraged a Semantic Web-based metadata repository enhanced with both ISO11179 metadata standard and Clinical Information Modeling Initiative (CIMI) Reference Model. We used the common data elements (CDEs) defined in The Cancer Genome Atlas (TCGA) data dictionary, and extracted the metadata of the CDEs using the NCI Cancer Data Standards Repository (caDSR) CDE dataset rendered in the Resource Description Framework (RDF). The ITEM/ITEM_GROUP pattern defined in the latest CIMI Reference Model is used to represent reusable model elements (mini-Archetypes). We produced a metadata repository with 38 clinical cancer genome study domains, comprising a rich collection of mini-Archetype pattern instances. We performed a case study of the domain "clinical pharmaceutical" in the TCGA data dictionary and demonstrated enriched data elements in the metadata repository are very useful in support of building detailed clinical models. Our informatics approach leveraging Semantic Web technologies provides an effective way to build a CIMI-compliant metadata repository that would facilitate the detailed clinical modeling to support use cases beyond TCGA in clinical cancer study domains.

The interaction between cytosine methylation and processes of DNA replication and repair shape the mutational landscape of cancer genomes

PubMed Central

Poulos, Rebecca C.

2017-01-01

Abstract Methylated cytosines (5mCs) are frequently mutated in the genome. However, no studies have yet comprehensively analysed mutation–methylation associations across cancer types. Here we analyse 916 cancer genomes, together with tissue type-specific methylation and replication timing data. We describe a strong mutation–methylation association across colorectal cancer subtypes, most interestingly in samples with microsatellite instability (MSI) or Polymerase epsilon (POLE) exonuclease domain mutations. By analysing genomic regions with differential mismatch repair (MMR) efficiency, we suggest a possible role for MMR in the correction of 5mC deamination events, potentially accounting for the high rate of 5mC mutation accumulation in MSI tumours. Additionally, we propose that mutant POLE asserts a mutator phenotype specifically at 5mCs, and we find coding mutation hotspots in POLE-mutant cancers at highly-methylated CpGs in the tumour-suppressor genes APC and TP53. Finally, using multivariable regression models, we demonstrate that different cancers exhibit distinct mutation–methylation associations, with DNA repair influencing such associations in certain cancer genomes. Taken together, we find differential associations with methylation that are vital for accurately predicting expected mutation loads across cancer types. Our findings reveal links between methylation and common mutation and repair processes, with these mechanisms defining a key part of the mutational landscape of cancer genomes. PMID:28531315

Genome-wide interaction study of smoking and bladder cancer risk

PubMed Central

Figueroa, Jonine D.; Han, Summer S.; Garcia-Closas, Montserrat; Baris, Dalsu; Jacobs, Eric J.; Kogevinas, Manolis; Schwenn, Molly; Malats, Nuria; Johnson, Alison; Purdue, Mark P.; Caporaso, Neil; Landi, Maria Teresa; Prokunina-Olsson, Ludmila; Wang, Zhaoming; Hutchinson, Amy; Burdette, Laurie; Wheeler, William; Vineis, Paolo; Siddiq, Afshan; Cortessis, Victoria K.; Kooperberg, Charles; Cussenot, Olivier; Benhamou, Simone; Prescott, Jennifer; Porru, Stefano; Bueno-de-Mesquita, H.Bas; Trichopoulos, Dimitrios; Ljungberg, Börje; Clavel-Chapelon, Françoise; Weiderpass, Elisabete; Krogh, Vittorio; Dorronsoro, Miren; Travis, Ruth; Tjønneland, Anne; Brenan, Paul; Chang-Claude, Jenny; Riboli, Elio; Conti, David; Gago-Dominguez, Manuela; Stern, Mariana C.; Pike, Malcolm C.; Van Den Berg, David; Yuan, Jian-Min; Hohensee, Chancellor; Rodabough, Rebecca; Cancel-Tassin, Geraldine; Roupret, Morgan; Comperat, Eva; Chen, Constance; De Vivo, Immaculata; Giovannucci, Edward; Hunter, David J.; Kraft, Peter; Lindstrom, Sara; Carta, Angela; Pavanello, Sofia; Arici, Cecilia; Mastrangelo, Giuseppe; Karagas, Margaret R.; Schned, Alan; Armenti, Karla R.; Hosain, G.M.Monawar; Haiman, Chris A.; Fraumeni, Joseph F.; Chanock, Stephen J.; Chatterjee, Nilanjan; Rothman, Nathaniel; Silverman, Debra T.

2014-01-01

Bladder cancer is a complex disease with known environmental and genetic risk factors. We performed a genome-wide interaction study (GWAS) of smoking and bladder cancer risk based on primary scan data from 3002 cases and 4411 controls from the National Cancer Institute Bladder Cancer GWAS. Alternative methods were used to evaluate both additive and multiplicative interactions between individual single nucleotide polymorphisms (SNPs) and smoking exposure. SNPs with interaction P values < 5 × 10− 5 were evaluated further in an independent dataset of 2422 bladder cancer cases and 5751 controls. We identified 10 SNPs that showed association in a consistent manner with the initial dataset and in the combined dataset, providing evidence of interaction with tobacco use. Further, two of these novel SNPs showed strong evidence of association with bladder cancer in tobacco use subgroups that approached genome-wide significance. Specifically, rs1711973 (FOXF2) on 6p25.3 was a susceptibility SNP for never smokers [combined odds ratio (OR) = 1.34, 95% confidence interval (CI) = 1.20–1.50, P value = 5.18 × 10− 7]; and rs12216499 (RSPH3-TAGAP-EZR) on 6q25.3 was a susceptibility SNP for ever smokers (combined OR = 0.75, 95% CI = 0.67–0.84, P value = 6.35 × 10− 7). In our analysis of smoking and bladder cancer, the tests for multiplicative interaction seemed to more commonly identify susceptibility loci with associations in never smokers, whereas the additive interaction analysis identified more loci with associations among smokers—including the known smoking and NAT2 acetylation interaction. Our findings provide additional evidence of gene–environment interactions for tobacco and bladder cancer. PMID:24662972

Building an International Initiative to Infuse Novel Cancer Models into the Research Community | Office of Cancer Genomics

Cancer.gov

My name is Caitlyn Barrett and I am the Scientific Program Manager for the Human Cancer Model Initiative (HCMI) in the Office of Cancer Genomics (OCG). In my role within the HCMI, I am helping to establish communication pathways and build the foundation for collaboration that will enable the completion of the Initiative’s aim to develop as many as 1000 next-generation cancer models, established from patient tumors and accompanied by clinical and molecular data.

University of Texas MD Anderson Cancer Center (UT-MDACC): High-Throughput Screening Identifying Driving Mutations in Endometrial Cancer | Office of Cancer Genomics

Cancer.gov

Recent advances in next-generation sequencing technology have enabled the unprecedented characterization of a full spectrum of somatic alterations in cancer genomes. Given the large numbers of somatic mutations typically detected by this approach, a key challenge in the downstream analysis is to distinguish “drivers” that functionally contribute to tumorigenesis from “passengers” that occur as the consequence of genomic instability.

Genomic Alterations Observed in Colitis-Associated Cancers Are Distinct From Those Found in Sporadic Colorectal Cancers and Vary by Type of Inflammatory Bowel Disease.

PubMed

Yaeger, Rona; Shah, Manish A; Miller, Vincent A; Kelsen, Judith R; Wang, Kai; Heins, Zachary J; Ross, Jeffrey S; He, Yuting; Sanford, Eric; Yantiss, Rhonda K; Balasubramanian, Sohail; Stephens, Philip J; Schultz, Nikolaus; Oren, Moshe; Tang, Laura; Kelsen, David

2016-08-01

Patients with inflammatory bowel diseases, such as Crohn's disease (CD) and ulcerative colitis (UC), are at increased risk for small bowel or colorectal cancers (colitis-associated cancers [CACs]). We compared the spectrum of genomic alterations in CACs with those of sporadic colorectal cancers (CRCs) and investigated differences between CACs from patients with CD vs UC. We studied tumor tissues from patients with CACs treated at Memorial Sloan Kettering Cancer Center or Weill Cornell Medical College from 2003 through 2015. We performed hybrid capture-based next-generation sequencing analysis of >300 cancer-related genes to comprehensively characterize genomic alterations. We performed genomic analyses of 47 CACs (from 29 patients with UC and 18 with CD; 43 primary tumors and 4 metastases). Primary tumors developed in the ileum (n = 2), right colon (n = 18), left colon (n = 6), and rectosigmoid or rectum (n = 21). We found genomic alterations in TP53, IDH1, and MYC to be significantly more frequent, and mutations in APC to be significantly less frequent, than those reported in sporadic CRCs by The Cancer Genome Atlas or Foundation Medicine. We identified genomic alterations that might be targeted by a therapeutic agent in 17 of 47 (36%) CACs. These included the mutation encoding IDH1 R132; amplification of FGFR1, FGFR2, and ERBB2; and mutations encoding BRAF V600E and an EML4-ALK fusion protein. Alterations in IDH1 and APC were significantly more common in CACs from patients with CD than UC. In an analysis of CACs from 47 patients, we found significant differences in the spectrum of genomic alterations in CACs compared with sporadic CRCs. We observed a high frequency of IDH1 R132 mutations in patients with CD but not UC, as well as a high frequency of MYC amplification in CACs. Many genetic alterations observed in CACs could serve as therapeutic targets. Copyright © 2016 AGA Institute. Published by Elsevier Inc. All rights reserved.

Genomic Alterations Observed in Colitis-associated Cancers are Distinct from Those Found in Sporadic Colorectal Cancers and Vary by Type of Inflammatory Bowel Disease

PubMed Central

Yaeger, Rona; Shah, Manish A.; Miller, Vincent A.; Kelsen, Judith R.; Wang, Kai; Heins, Zachary J.; Ross, Jeffrey S.; He, Yuting; Sanford, Eric; Yantiss, Rhonda K.; Balasubramanian, Sohail; Stephens, Philip J.; Schultz, Nikolaus; Oren, Moshe; Tang, Laura; Kelsen, David

2016-01-01

Background & Aims Patients with inflammatory bowel diseases such as Crohn's disease (CD) or ulcerative colitis (UC) are at increased risk for small bowel or colorectal cancers (colitis-associated cancers, CACs). We compared the spectrum of genomic alterations in CACs with those of sporadic colorectal cancers (CRCs) and investigated differences between CACs from patients with CD vs UC. Methods We studied tumor tissues from patients with CACs, treated at Memorial Sloan Kettering Cancer Center or Weill Cornell Medical College from 2003 through 2015. We performed hybrid capture based next-generation sequencing analysis of over 300 cancer-related genes to comprehensively characterize genomic alterations. Results We performed genomic analyses of 47 CACs (from 29 patients with UC and 18 with CD; 43 primary tumors and 4 metastases). Primary tumors developed in the ileum (n=2), right colon (n=18), left colon (n=6) and rectosigmoid or rectum (n=21). We found genomic alterations in TP53, IDH1, and MYC to be significantly more frequent, and mutations in APC to be significantly less frequent, than those reported in sporadic CRCs by The Cancer Genome Atlas or Foundation Medicine. We identified genomic alterations that might be targeted by a therapeutic agent in 17/47 (36%) of CACs. These included the mutation encoding IDH1 R132; amplification of FGFR1, FGFR2, and ERBB2; and mutations encoding BRAF V600E and an EML4-ALK fusion protein. Alterations in IDH1 and APC were significantly more common in CACs from patients with CD than UC. Conclusions In an analysis of CACs from 47 patients, we found significant differences in the spectrum of genomic alterations in CACs compared to sporadic CRCs. We observed a high frequency of IDH1 R132 mutations in patients with CD but not UC, as well as a high frequency of MYC amplification in CACs. Many genetic alterations observed in CACs could serve as therapeutic targets. PMID:27063727

Phenome-genome association studies of pancreatic cancer: new targets for therapy and diagnosis.

PubMed

Narayanan, Ramaswamy

2015-01-01

Pancreatic cancer, has a very high mortality rate and requires novel molecular targets for diagnosis and therapy. Genetic association studies over databases offer an attractive starting point for gene discovery. The National Center for Biotechnology Information (NCBI) Phenome Genome Integrator (PheGenI) tool was enriched for pancreatic cancer-associated traits. The genes associated with the trait were characterized using diverse bioinformatics tools for Genome-Wide Association (GWA), transcriptome and proteome profile and protein classes for motif and domain. Two hundred twenty-six genes were identified that had a genetic association with pancreatic cancer in the human genome. This included 25 uncharacterized open reading frames (ORFs). Bioinformatics analysis of these ORFs identified putative druggable proteins and biomarkers including enzymes, transporters and G-protein-coupled receptor signaling proteins. Secreted proteins including a neuroendocrine factor and a chemokine were identified. Five out of these ORFs encompassed non coding RNAs. The ORF protein expression was detected in numerous body fluids, such as ascites, bile, pancreatic juice, milk, plasma, serum and saliva. Transcriptome and proteome analyses showed a correlation of mRNA and protein expression for nine ORFs. Analysis of the Catalogue of Somatic Mutations in Cancer (COSMIC) database revealed a strong correlation across copy number variations and mRNA over-expression for four ORFs. Mining of the International Cancer Gene Consortium (ICGC) database identified somatic mutations in a significant number of pancreatic patients' tumors for most of these ORFs. The pancreatic cancer-associated ORFs were also found to be genetically associated with other neoplasms, including leukemia, malignant melanoma, neuroblastoma and prostate carcinomas, as well as other unrelated diseases and disorders, such as Alzheimer's disease, Crohn's disease, coronary diseases, attention deficit disorder and addiction. Based

Cancer prevention, the need to preserve the integrity of the genome at all cost.

PubMed

Okafor, M T; Nwagha, T U; Anusiem, C; Okoli, U A; Nubila, N I; Al-Alloosh, F; Udenyia, I J

2018-05-01

The entire genetic information carried by an organism makes up its genome. Genes have a diverse number of functions. They code different proteins for normal proliferation of cells. However, changes in the base sequence of genes affect their protein by-products which act as messengers for normal cellular functions such as proliferation and repairs. Salient processes for maintaining the integrity of the genome are hinged on intricate mechanisms put in place for the evolution to tackle genomic stresses. To discuss how cells sense and repair damage to their deoxyribonucleic acid (DNA) as well as to highlight how defects in the genes involved in DNA repair contribute to cancer development. Methodology: Online searches on the following databases such as Google Scholar, PubMed, Biomed Central, and SciELO were done. Attempt was made to review articles with keywords such as cancer, cell cycle, tumor suppressor genes, and DNA repair. The cell cycle, tumor suppression genes, DNA repair mechanism, as well as their contribution to cancer development, were discussed and reviewed. Knowledge on how cells detect and repair DNA damage through an array of mechanisms should allay our anxiety as regards cancer development. More studies on DNA damage detection and repair processes are important toward a holistic approach to cancer treatment.

Translocation and deletion breakpoints in cancer genomes are associated with potential non-B DNA-forming sequences.

PubMed

Bacolla, Albino; Tainer, John A; Vasquez, Karen M; Cooper, David N

2016-07-08

Gross chromosomal rearrangements (including translocations, deletions, insertions and duplications) are a hallmark of cancer genomes and often create oncogenic fusion genes. An obligate step in the generation of such gross rearrangements is the formation of DNA double-strand breaks (DSBs). Since the genomic distribution of rearrangement breakpoints is non-random, intrinsic cellular factors may predispose certain genomic regions to breakage. Notably, certain DNA sequences with the potential to fold into secondary structures [potential non-B DNA structures (PONDS); e.g. triplexes, quadruplexes, hairpin/cruciforms, Z-DNA and single-stranded looped-out structures with implications in DNA replication and transcription] can stimulate the formation of DNA DSBs. Here, we tested the postulate that these DNA sequences might be found at, or in close proximity to, rearrangement breakpoints. By analyzing the distribution of PONDS-forming sequences within ±500 bases of 19 947 translocation and 46 365 sequence-characterized deletion breakpoints in cancer genomes, we find significant association between PONDS-forming repeats and cancer breakpoints. Specifically, (AT)n, (GAA)n and (GAAA)n constitute the most frequent repeats at translocation breakpoints, whereas A-tracts occur preferentially at deletion breakpoints. Translocation breakpoints near PONDS-forming repeats also recur in different individuals and patient tumor samples. Hence, PONDS-forming sequences represent an intrinsic risk factor for genomic rearrangements in cancer genomes. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Significance of genomic instability in breast cancer in atomic bomb survivors: analysis of microarray-comparative genomic hybridization.

PubMed

Oikawa, Masahiro; Yoshiura, Koh-ichiro; Kondo, Hisayoshi; Miura, Shiro; Nagayasu, Takeshi; Nakashima, Masahiro

2011-12-07

It has been postulated that ionizing radiation induces breast cancers among atomic bomb (A-bomb) survivors. We have reported a higher incidence of HER2 and C-MYC oncogene amplification in breast cancers from A-bomb survivors. The purpose of this study was to clarify the effect of A-bomb radiation exposure on genomic instability (GIN), which is an important hallmark of carcinogenesis, in archival formalin-fixed paraffin-embedded (FFPE) tissues of breast cancer by using microarray-comparative genomic hybridization (aCGH). Tumor DNA was extracted from FFPE tissues of invasive ductal cancers from 15 survivors who were exposed at 1.5 km or less from the hypocenter and 13 calendar year-matched non-exposed patients followed by aCGH analysis using a high-density oligonucleotide microarray. The total length of copy number aberrations (CNA) was used as an indicator of GIN, and correlation with clinicopathological factors were statistically tested. The mean of the derivative log ratio spread (DLRSpread), which estimates the noise by calculating the spread of log ratio differences between consecutive probes for all chromosomes, was 0.54 (range, 0.26 to 1.05). The concordance of results between aCGH and fluorescence in situ hybridization (FISH) for HER2 gene amplification was 88%. The incidence of HER2 amplification and histological grade was significantly higher in the A-bomb survivors than control group (P = 0.04, respectively). The total length of CNA tended to be larger in the A-bomb survivors (P = 0.15). Correlation analysis of CNA and clinicopathological factors revealed that DLRSpread was negatively correlated with that significantly (P = 0.034, r = -0.40). Multivariate analysis with covariance revealed that the exposure to A-bomb was a significant (P = 0.005) independent factor which was associated with larger total length of CNA of breast cancers. Thus, archival FFPE tissues from A-bomb survivors are useful for genome-wide aCGH analysis. Our results suggested that A

Significance of genomic instability in breast cancer in atomic bomb survivors: analysis of microarray-comparative genomic hybridization

PubMed Central

2011-01-01

Background It has been postulated that ionizing radiation induces breast cancers among atomic bomb (A-bomb) survivors. We have reported a higher incidence of HER2 and C-MYC oncogene amplification in breast cancers from A-bomb survivors. The purpose of this study was to clarify the effect of A-bomb radiation exposure on genomic instability (GIN), which is an important hallmark of carcinogenesis, in archival formalin-fixed paraffin-embedded (FFPE) tissues of breast cancer by using microarray-comparative genomic hybridization (aCGH). Methods Tumor DNA was extracted from FFPE tissues of invasive ductal cancers from 15 survivors who were exposed at 1.5 km or less from the hypocenter and 13 calendar year-matched non-exposed patients followed by aCGH analysis using a high-density oligonucleotide microarray. The total length of copy number aberrations (CNA) was used as an indicator of GIN, and correlation with clinicopathological factors were statistically tested. Results The mean of the derivative log ratio spread (DLRSpread), which estimates the noise by calculating the spread of log ratio differences between consecutive probes for all chromosomes, was 0.54 (range, 0.26 to 1.05). The concordance of results between aCGH and fluorescence in situ hybridization (FISH) for HER2 gene amplification was 88%. The incidence of HER2 amplification and histological grade was significantly higher in the A-bomb survivors than control group (P = 0.04, respectively). The total length of CNA tended to be larger in the A-bomb survivors (P = 0.15). Correlation analysis of CNA and clinicopathological factors revealed that DLRSpread was negatively correlated with that significantly (P = 0.034, r = -0.40). Multivariate analysis with covariance revealed that the exposure to A-bomb was a significant (P = 0.005) independent factor which was associated with larger total length of CNA of breast cancers. Conclusions Thus, archival FFPE tissues from A-bomb survivors are useful for genome-wide a

Analysis of The Cancer Genome Atlas sequencing data reveals novel properties of the human papillomavirus 16 genome in head and neck squamous cell carcinoma.

PubMed

Nulton, Tara J; Olex, Amy L; Dozmorov, Mikhail; Morgan, Iain M; Windle, Brad

2017-03-14

Human papillomavirus (HPV) DNA is detected in up to 80% of oropharyngeal carcinomas (OPC) and this HPV positive disease has reached epidemic proportions. To increase our understanding of the disease, we investigated the status of the HPV16 genome in HPV-positive head and neck cancers (HNC). Raw RNA-Seq and Whole Genome Sequence data from The Cancer Genome Atlas HNC samples were analyzed to gain a full understanding of the HPV genome status for these tumors. Several remarkable and novel observations were made following this analysis. Firstly, there are three main HPV genome states in these tumors that are split relatively evenly: An episomal only state, an integrated state, and a state in which the viral genome exists as a hybrid episome with human DNA. Secondly, none of the tumors expressed high levels of E6; E6*I is the dominant variant expressed in all tumors. The most striking conclusion from this study is that around three quarters of HPV16 positive HNC contain episomal versions of the viral genome that are likely replicating in an E1-E2 dependent manner. The clinical and therapeutic implications of these observations are discussed.

Investigating Genomic Mechanisms of Treatment Resistance in Castration Resistant Prostate Cancer

DTIC Science & Technology

2015-05-01

and genomically profiled. Figure 3 shows data from a series of cell- line experiments showing that PC3 prostate cancer cells are recoverable and...coursework until the second-half of the grant period. I am enrolled in the UCSF Biomedical Sciences Graduate Program class BMS 255: Genetics : Basic... Genetics and Genomics. This class is set to start in January 2016. Given a large number of clinical, teaching, and research duties I will plan to enroll

Emory University: High-Throughput Protein-Protein Interaction Dataset for Lung Cancer-Associated Genes | Office of Cancer Genomics

Cancer.gov

To discover novel PPI signaling hubs for lung cancer, CTD2 Center at Emory utilized large-scale genomics datasets and literature to compile a set of lung cancer-associated genes. A library of expression vectors were generated for these genes and utilized for detecting pairwise PPIs with cell lysate-based TR-FRET assays in high-throughput screening format. Read the abstract.

Spanning the genomics era: the vital role of a single institution biorepository for childhood cancer research over a decade

PubMed Central

Zhou, Li

2015-01-01

The ‘genomics era’ is considered to have begun with the commencement of the Human Genome Project. As translational genomic studies can only be established when human tissue samples are available for analysis, biospecimens are now proven to be an essential element for their success. During the genomics era the necessity for more extensive biobanking infrastructure has been highlighted. With the increased number of genomic studies into cancer, it is considered that the availability of biospecimens will become the rate limiting step. Despite the efforts in international biobanking, translational genomics is hampered when there low numbers of biospecimens for a particular rare diseases and is most apparent for paediatric cancer. As there is a call for biobanking practice to be responsive to the current experimental needs of the time and for more expansive systems of tissue procurement to be established we have asked the question what role does a single institution biorepository play in the current highly networked world of translational genomics. Here we describe such a case. The Tumour Bank at The Children’s Hospital at Westmead (TB-CHW) in the western suburbs of Sydney was formally established in 1998 as a key resource for translational paediatric cancer research. During the genomics era, we show that the TB-CHW has developed into a key biospecimen repository for the cancer research community, during which time it has increasingly found itself having a vital role in the establishment of translational genomics for paediatric cancer. Here we detail metrics that demonstrate how as a single institution biorepository, the TB-CHW has been a strong participant in the advancement of translational genomics throughout the genomics era. This paper describes the significant contribution of a single institutional hospital embedded tumour biobank to the genomic research community. Despite the increased stringencies placed on biobanking practice, the TB-CHW has shown that a

UCbase 2.0: ultraconserved sequences database (2014 update)

PubMed Central

Lomonaco, Vincenzo; Martoglia, Riccardo; Mandreoli, Federica; Anderlucci, Laura; Emmett, Warren; Bicciato, Silvio; Taccioli, Cristian

2014-01-01

UCbase 2.0 (http://ucbase.unimore.it) is an update, extension and evolution of UCbase, a Web tool dedicated to the analysis of ultraconserved sequences (UCRs). UCRs are 481 sequences >200 bases sharing 100% identity among human, mouse and rat genomes. They are frequently located in genomic regions known to be involved in cancer or differentially expressed in human leukemias and carcinomas. UCbase 2.0 is a platform-independent Web resource that includes the updated version of the human genome annotation (hg19), information linking disorders to chromosomal coordinates based on the Systematized Nomenclature of Medicine classification, a query tool to search for Single Nucleotide Polymorphisms (SNPs) and a new text box to directly interrogate the database using a MySQL interface. To facilitate the interactive visual interpretation of UCR chromosomal positioning, UCbase 2.0 now includes a graph visualization interface directly linked to UCSC genome browser. Database URL: http://ucbase.unimore.it PMID:24951797

UCbase 2.0: ultraconserved sequences database (2014 update).

PubMed

Lomonaco, Vincenzo; Martoglia, Riccardo; Mandreoli, Federica; Anderlucci, Laura; Emmett, Warren; Bicciato, Silvio; Taccioli, Cristian

2014-01-01

UCbase 2.0 (http://ucbase.unimore.it) is an update, extension and evolution of UCbase, a Web tool dedicated to the analysis of ultraconserved sequences (UCRs). UCRs are 481 sequences >200 bases sharing 100% identity among human, mouse and rat genomes. They are frequently located in genomic regions known to be involved in cancer or differentially expressed in human leukemias and carcinomas. UCbase 2.0 is a platform-independent Web resource that includes the updated version of the human genome annotation (hg19), information linking disorders to chromosomal coordinates based on the Systematized Nomenclature of Medicine classification, a query tool to search for Single Nucleotide Polymorphisms (SNPs) and a new text box to directly interrogate the database using a MySQL interface. To facilitate the interactive visual interpretation of UCR chromosomal positioning, UCbase 2.0 now includes a graph visualization interface directly linked to UCSC genome browser. Database URL: http://ucbase.unimore.it. © The Author(s) 2014. Published by Oxford University Press.

CTD² Dashboard: a searchable web interface to connect validated results from the Cancer Target Discovery and Development Network* | Office of Cancer Genomics

Cancer.gov

The Cancer Target Discovery and Development (CTD2) Network aims to use functional genomics to accelerate the translation of high-throughput and high-content genomic and small-molecule data towards use in precision oncology.

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

Cancer.gov

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

tRNAscan-SE On-line: integrating search and context for analysis of transfer RNA genes.

PubMed

Lowe, Todd M; Chan, Patricia P

2016-07-08

High-throughput genome sequencing continues to grow the need for rapid, accurate genome annotation and tRNA genes constitute the largest family of essential, ever-present non-coding RNA genes. Newly developed tRNAscan-SE 2.0 has advanced the state-of-the-art methodology in tRNA gene detection and functional prediction, captured by rich new content of the companion Genomic tRNA Database. Previously, web-server tRNA detection was isolated from knowledge of existing tRNAs and their annotation. In this update of the tRNAscan-SE On-line resource, we tie together improvements in tRNA classification with greatly enhanced biological context via dynamically generated links between web server search results, the most relevant genes in the GtRNAdb and interactive, rich genome context provided by UCSC genome browsers. The tRNAscan-SE On-line web server can be accessed at http://trna.ucsc.edu/tRNAscan-SE/. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Computational discovery of pathway-level genetic vulnerabilities in non-small-cell lung cancer | Office of Cancer Genomics

Cancer.gov

Novel approaches are needed for discovery of targeted therapies for non-small-cell lung cancer (NSCLC) that are specific to certain patients. Whole genome RNAi screening of lung cancer cell lines provides an ideal source for determining candidate drug targets. Unsupervised learning algorithms uncovered patterns of differential vulnerability across lung cancer cell lines to loss of functionally related genes. Such genetic vulnerabilities represent candidate targets for therapy and are found to be involved in splicing, translation and protein folding.

The interaction between cytosine methylation and processes of DNA replication and repair shape the mutational landscape of cancer genomes.

PubMed

Poulos, Rebecca C; Olivier, Jake; Wong, Jason W H

2017-07-27

Methylated cytosines (5mCs) are frequently mutated in the genome. However, no studies have yet comprehensively analysed mutation-methylation associations across cancer types. Here we analyse 916 cancer genomes, together with tissue type-specific methylation and replication timing data. We describe a strong mutation-methylation association across colorectal cancer subtypes, most interestingly in samples with microsatellite instability (MSI) or Polymerase epsilon (POLE) exonuclease domain mutations. By analysing genomic regions with differential mismatch repair (MMR) efficiency, we suggest a possible role for MMR in the correction of 5mC deamination events, potentially accounting for the high rate of 5mC mutation accumulation in MSI tumours. Additionally, we propose that mutant POLE asserts a mutator phenotype specifically at 5mCs, and we find coding mutation hotspots in POLE-mutant cancers at highly-methylated CpGs in the tumour-suppressor genes APC and TP53. Finally, using multivariable regression models, we demonstrate that different cancers exhibit distinct mutation-methylation associations, with DNA repair influencing such associations in certain cancer genomes. Taken together, we find differential associations with methylation that are vital for accurately predicting expected mutation loads across cancer types. Our findings reveal links between methylation and common mutation and repair processes, with these mechanisms defining a key part of the mutational landscape of cancer genomes. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Comparative sequencing analysis reveals high genomic concordance between matched primary and metastatic colorectal cancer lesions.

PubMed

Brannon, A Rose; Vakiani, Efsevia; Sylvester, Brooke E; Scott, Sasinya N; McDermott, Gregory; Shah, Ronak H; Kania, Krishan; Viale, Agnes; Oschwald, Dayna M; Vacic, Vladimir; Emde, Anne-Katrin; Cercek, Andrea; Yaeger, Rona; Kemeny, Nancy E; Saltz, Leonard B; Shia, Jinru; D'Angelica, Michael I; Weiser, Martin R; Solit, David B; Berger, Michael F

2014-08-28

Colorectal cancer is the second leading cause of cancer death in the United States, with over 50,000 deaths estimated in 2014. Molecular profiling for somatic mutations that predict absence of response to anti-EGFR therapy has become standard practice in the treatment of metastatic colorectal cancer; however, the quantity and type of tissue available for testing is frequently limited. Further, the degree to which the primary tumor is a faithful representation of metastatic disease has been questioned. As next-generation sequencing technology becomes more widely available for clinical use and additional molecularly targeted agents are considered as treatment options in colorectal cancer, it is important to characterize the extent of tumor heterogeneity between primary and metastatic tumors. We performed deep coverage, targeted next-generation sequencing of 230 key cancer-associated genes for 69 matched primary and metastatic tumors and normal tissue. Mutation profiles were 100% concordant for KRAS, NRAS, and BRAF, and were highly concordant for recurrent alterations in colorectal cancer. Additionally, whole genome sequencing of four patient trios did not reveal any additional site-specific targetable alterations. Colorectal cancer primary tumors and metastases exhibit high genomic concordance. As current clinical practices in colorectal cancer revolve around KRAS, NRAS, and BRAF mutation status, diagnostic sequencing of either primary or metastatic tissue as available is acceptable for most patients. Additionally, consistency between targeted sequencing and whole genome sequencing results suggests that targeted sequencing may be a suitable strategy for clinical diagnostic applications.

Pan-cancer analysis of the extent and consequences of intratumor heterogeneity | Office of Cancer Genomics

Cancer.gov

Intratumor heterogeneity (ITH) drives neoplastic progression and therapeutic resistance. We used the bioinformatics tools 'expanding ploidy and allele frequency on nested subpopulations' (EXPANDS) and PyClone to detect clones that are present at a ≥10% frequency in 1,165 exome sequences from tumors in The Cancer Genome Atlas. 86% of tumors across 12 cancer types had at least two clones. ITH in the morphology of nuclei was associated with genetic ITH (Spearman's correlation coefficient, ρ = 0.24-0.41; P < 0.001).

BYSTANDERS, ADAPTIVE RESPONSES AND GENOMIC INSTABILITY - POTENTIAL MODIFIERS OF LOW-DOSE CANCER RESPONSES.

EPA Science Inventory

Bystanders, Adaptive Responses and Genomic Instability -Potential Modifiers ofLow-Dose
Cancer Responses
.
There has been a concerted effort in the field of radiation biology to better understand cellular
responses that could have an impact on the estin1ation of cancer...

Open reading frames associated with cancer in the dark matter of the human genome.

PubMed

Delgado, Ana Paula; Brandao, Pamela; Chapado, Maria Julia; Hamid, Sheilin; Narayanan, Ramaswamy

2014-01-01

The uncharacterized proteins (open reading frames, ORFs) in the human genome offer an opportunity to discover novel targets for cancer. A systematic analysis of the dark matter of the human proteome for druggability and biomarker discovery is crucial to mining the genome. Numerous data mining tools are available to mine these ORFs to develop a comprehensive knowledge base for future target discovery and validation. Using the Genetic Association Database, the ORFs of the human dark matter proteome were screened for evidence of association with neoplasms. The Phenome-Genome Integrator tool was used to establish phenotypic association with disease traits including cancer. Batch analysis of the tools for protein expression analysis, gene ontology and motifs and domains was used to characterize the ORFs. Sixty-two ORFs were identified for neoplasm association. The expression Quantitative Trait Loci (eQTL) analysis identified thirteen ORFs related to cancer traits. Protein expression, motifs and domain analysis and genome-wide association studies verified the relevance of these OncoORFs in diverse tumors. The OncoORFs are also associated with a wide variety of human diseases and disorders. Our results link the OncoORFs to diverse diseases and disorders. This suggests a complex landscape of the uncharacterized proteome in human diseases. These results open the dark matter of the proteome to novel cancer target research. Copyright© 2014, International Institute of Anticancer Research (Dr. John G. Delinasios), All rights reserved.

Whole genomes redefine the mutational landscape of pancreatic cancer

PubMed Central

Waddell, Nicola; Pajic, Marina; Patch, Ann-Marie; Chang, David K.; Kassahn, Karin S.; Bailey, Peter; Johns, Amber L.; Miller, David; Nones, Katia; Quek, Kelly; Quinn, Michael C. J.; Robertson, Alan J.; Fadlullah, Muhammad Z. H.; Bruxner, Tim J. C.; Christ, Angelika N.; Harliwong, Ivon; Idrisoglu, Senel; Manning, Suzanne; Nourse, Craig; Nourbakhsh, Ehsan; Wani, Shivangi; Wilson, Peter J; Markham, Emma; Cloonan, Nicole; Anderson, Matthew J.; Fink, J. Lynn; Holmes, Oliver; Kazakoff, Stephen H.; Leonard, Conrad; Newell, Felicity; Poudel, Barsha; Song, Sarah; Taylor, Darrin; Waddell, Nick; Wood, Scott; Xu, Qinying; Wu, Jianmin; Pinese, Mark; Cowley, Mark J.; Lee, Hong C.; Jones, Marc D.; Nagrial, Adnan M.; Humphris, Jeremy; Chantrill, Lorraine A.; Chin, Venessa; Steinmann, Angela M.; Mawson, Amanda; Humphrey, Emily S.; Colvin, Emily K.; Chou, Angela; Scarlett, Christopher J.; Pinho, Andreia V.; Giry-Laterriere, Marc; Rooman, Ilse; Samra, Jaswinder S.; Kench, James G.; Pettitt, Jessica A.; Merrett, Neil D.; Toon, Christopher; Epari, Krishna; Nguyen, Nam Q.; Barbour, Andrew; Zeps, Nikolajs; Jamieson, Nigel B.; Graham, Janet S.; Niclou, Simone P.; Bjerkvig, Rolf; Grützmann, Robert; Aust, Daniela; Hruban, Ralph H.; Maitra, Anirban; Iacobuzio-Donahue, Christine A.; Wolfgang, Christopher L.; Morgan, Richard A.; Lawlor, Rita T.; Corbo, Vincenzo; Bassi, Claudio; Falconi, Massimo; Zamboni, Giuseppe; Tortora, Giampaolo; Tempero, Margaret A.; Gill, Anthony J.; Eshleman, James R.; Pilarsky, Christian; Scarpa, Aldo; Musgrove, Elizabeth A.; Pearson, John V.; Biankin, Andrew V.; Grimmond, Sean M.

2015-01-01

Pancreatic cancer remains one of the most lethal of malignancies and a major health burden. We performed whole-genome sequencing and copy number variation (CNV) analysis of 100 pancreatic ductal adenocarcinomas (PDACs). Chromosomal rearrangements leading to gene disruption were prevalent, affecting genes known to be important in pancreatic cancer (TP53, SMAD4, CDKN2A, ARID1A and ROBO2) and new candidate drivers of pancreatic carcinogenesis (KDM6A and PREX2). Patterns of structural variation (variation in chromosomal structure) classified PDACs into 4 subtypes with potential clinical utility: the subtypes were termed stable, locally rearranged, scattered and unstable. A significant proportion harboured focal amplifications, many of which contained druggable oncogenes (ERBB2, MET, FGFR1, CDK6, PIK3R3 and PIK3CA), but at low individual patient prevalence. Genomic instability co-segregated with inactivation of DNA maintenance genes (BRCA1, BRCA2 or PALB2) and a mutational signature of DNA damage repair deficiency. Of 8 patients who received platinum therapy, 4 of 5 individuals with these measures of defective DNA maintenance responded. PMID:25719666

Whole genomes redefine the mutational landscape of pancreatic cancer.

PubMed

Waddell, Nicola; Pajic, Marina; Patch, Ann-Marie; Chang, David K; Kassahn, Karin S; Bailey, Peter; Johns, Amber L; Miller, David; Nones, Katia; Quek, Kelly; Quinn, Michael C J; Robertson, Alan J; Fadlullah, Muhammad Z H; Bruxner, Tim J C; Christ, Angelika N; Harliwong, Ivon; Idrisoglu, Senel; Manning, Suzanne; Nourse, Craig; Nourbakhsh, Ehsan; Wani, Shivangi; Wilson, Peter J; Markham, Emma; Cloonan, Nicole; Anderson, Matthew J; Fink, J Lynn; Holmes, Oliver; Kazakoff, Stephen H; Leonard, Conrad; Newell, Felicity; Poudel, Barsha; Song, Sarah; Taylor, Darrin; Waddell, Nick; Wood, Scott; Xu, Qinying; Wu, Jianmin; Pinese, Mark; Cowley, Mark J; Lee, Hong C; Jones, Marc D; Nagrial, Adnan M; Humphris, Jeremy; Chantrill, Lorraine A; Chin, Venessa; Steinmann, Angela M; Mawson, Amanda; Humphrey, Emily S; Colvin, Emily K; Chou, Angela; Scarlett, Christopher J; Pinho, Andreia V; Giry-Laterriere, Marc; Rooman, Ilse; Samra, Jaswinder S; Kench, James G; Pettitt, Jessica A; Merrett, Neil D; Toon, Christopher; Epari, Krishna; Nguyen, Nam Q; Barbour, Andrew; Zeps, Nikolajs; Jamieson, Nigel B; Graham, Janet S; Niclou, Simone P; Bjerkvig, Rolf; Grützmann, Robert; Aust, Daniela; Hruban, Ralph H; Maitra, Anirban; Iacobuzio-Donahue, Christine A; Wolfgang, Christopher L; Morgan, Richard A; Lawlor, Rita T; Corbo, Vincenzo; Bassi, Claudio; Falconi, Massimo; Zamboni, Giuseppe; Tortora, Giampaolo; Tempero, Margaret A; Gill, Anthony J; Eshleman, James R; Pilarsky, Christian; Scarpa, Aldo; Musgrove, Elizabeth A; Pearson, John V; Biankin, Andrew V; Grimmond, Sean M

2015-02-26

Pancreatic cancer remains one of the most lethal of malignancies and a major health burden. We performed whole-genome sequencing and copy number variation (CNV) analysis of 100 pancreatic ductal adenocarcinomas (PDACs). Chromosomal rearrangements leading to gene disruption were prevalent, affecting genes known to be important in pancreatic cancer (TP53, SMAD4, CDKN2A, ARID1A and ROBO2) and new candidate drivers of pancreatic carcinogenesis (KDM6A and PREX2). Patterns of structural variation (variation in chromosomal structure) classified PDACs into 4 subtypes with potential clinical utility: the subtypes were termed stable, locally rearranged, scattered and unstable. A significant proportion harboured focal amplifications, many of which contained druggable oncogenes (ERBB2, MET, FGFR1, CDK6, PIK3R3 and PIK3CA), but at low individual patient prevalence. Genomic instability co-segregated with inactivation of DNA maintenance genes (BRCA1, BRCA2 or PALB2) and a mutational signature of DNA damage repair deficiency. Of 8 patients who received platinum therapy, 4 of 5 individuals with these measures of defective DNA maintenance responded.

Integrated Network Analyses for Functional Genomic Studies in Cancer

PubMed Central

Wilson, Jennifer L.; Hemann, Michael T.; Fraenkel, Ernest; Lauffenburger, Douglas A.

2013-01-01

RNA-interference (RNAi) studies hold great promise for functional investigation of the significance of genetic variations and mutations, as well as potential synthetic lethalities, for understanding and treatment of cancer, yet technical and conceptual issues currently diminish the potential power of this approach. While numerous research groups are usefully employing this kind of functional genomic methodology to identify molecular mediators of disease severity, response, and resistance to treatment, findings are generally confounded by “off-target” effects. These effects arise from a variety of issues beyond non-specific reagent behavior, such as biological cross-talk and feedback processes so thus can occur even with specific perturbation. Interpreting RNAi results in a network framework instead of merely as individual “hits” or “targets” leverages contributions from all hit/target contributions to pathways via their relationships with other network nodes. This interpretation can ameliorate dependence on individual reagent performance and increase confidence in biological validation. Here we provide background on RNAi studies in cancer applications, review key challenges with functional genomics, and motivate the use of network models grounded in pathway analyses. PMID:23811269

Functional precision medicine identifies novel druggable targets and therapeutic options in head and neck cancer. | Office of Cancer Genomics

Cancer.gov

Purpose: Head and neck squamous cell carcinoma (HNSCC) is the sixth most common cancer worldwide with high mortality and a lack of targeted therapies. To identify and prioritize druggable targets, we performed genome analysis together with genome-scale siRNA and oncology drug profiling using low passage tumor cells derived from a patient with a treatmentresistant HPV-negative HNSCC.

Genome and transcriptome sequencing in prospective metastatic triple-negative breast cancer uncovers therapeutic vulnerabilities.

PubMed

Craig, David W; O'Shaughnessy, Joyce A; Kiefer, Jeffrey A; Aldrich, Jessica; Sinari, Shripad; Moses, Tracy M; Wong, Shukmei; Dinh, Jennifer; Christoforides, Alexis; Blum, Joanne L; Aitelli, Cristi L; Osborne, Cynthia R; Izatt, Tyler; Kurdoglu, Ahmet; Baker, Angela; Koeman, Julie; Barbacioru, Catalin; Sakarya, Onur; De La Vega, Francisco M; Siddiqui, Asim; Hoang, Linh; Billings, Paul R; Salhia, Bodour; Tolcher, Anthony W; Trent, Jeffrey M; Mousses, Spyro; Von Hoff, Daniel; Carpten, John D

2013-01-01

Triple-negative breast cancer (TNBC) is characterized by the absence of expression of estrogen receptor, progesterone receptor, and HER-2. Thirty percent of patients recur after first-line treatment, and metastatic TNBC (mTNBC) has a poor prognosis with median survival of one year. Here, we present initial analyses of whole genome and transcriptome sequencing data from 14 prospective mTNBC. We have cataloged the collection of somatic genomic alterations in these advanced tumors, particularly those that may inform targeted therapies. Genes mutated in multiple tumors included TP53, LRP1B, HERC1, CDH5, RB1, and NF1. Notable genes involved in focal structural events were CTNNA1, PTEN, FBXW7, BRCA2, WT1, FGFR1, KRAS, HRAS, ARAF, BRAF, and PGCP. Homozygous deletion of CTNNA1 was detected in 2 of 6 African Americans. RNA sequencing revealed consistent overexpression of the FOXM1 gene when tumor gene expression was compared with nonmalignant breast samples. Using an outlier analysis of gene expression comparing one cancer with all the others, we detected expression patterns unique to each patient's tumor. Integrative DNA/RNA analysis provided evidence for deregulation of mutated genes, including the monoallelic expression of TP53 mutations. Finally, molecular alterations in several cancers supported targeted therapeutic intervention on clinical trials with known inhibitors, particularly for alterations in the RAS/RAF/MEK/ERK and PI3K/AKT/mTOR pathways. In conclusion, whole genome and transcriptome profiling of mTNBC have provided insights into somatic events occurring in this difficult to treat cancer. These genomic data have guided patients to investigational treatment trials and provide hypotheses for future trials in this irremediable cancer.

Prioritization in Comparative Effectiveness Research: The CANCERGEN Experience in Cancer Genomics

PubMed Central

Thariani, Rahber; Wong, William; Carlson, Josh J; Garrison, Louis; Ramsey, Scott; Deverka, Patricia A; Esmail, Laura; Rangarao, Sneha; Hoban, Carolyn J; Baker, Laurence H; Veenstra, David L

2012-01-01

Background Systematic approaches to stakeholder-informed research prioritization are a central focus of comparative effectiveness research. Genomic testing in cancer is an ideal area to refine such approaches given rapid innovation and potentially significant impacts on patient outcomes. Objective To develop and pilot-test a stakeholder-informed approach to prioritizing genomic tests for future study in collaboration with the cancer clinical trials consortium SWOG. Methods We conducted a landscape-analysis to identify genomic tests in oncology using a systematic search of published and unpublished studies, and expert consultation. Clinically valid tests suitable for evaluation in a comparative study were presented to an external stakeholder group. Domains to guide the prioritization process were identified with stakeholder input, and stakeholders ranked tests using multiple voting rounds. Results A stakeholder group was created including representatives from patient-advocacy groups, payers, test developers, regulators, policy-makers, and community-based oncologists. We identified nine domains for research prioritization with stakeholder feedback: population impact; current standard of care, strength of association; potential clinical benefits, potential clinical harms, economic impacts, evidence of need, trial feasibility, and market factors. The landscape-analysis identified 635 studies; of 9 tests deemed to have sufficient clinical validity, 6 were presented to stakeholders. Two tests in lung cancer (ERCC1 and EGFR) and one test in breast cancer (CEA/CA15-3/CA27.29) were identified as top research priorities. Conclusions Use of a diverse stakeholder group to inform research prioritization is feasible in a pragmatic and timely manner. Additional research is needed to optimize search strategies, stakeholder group composition and integration with existing prioritization mechanisms. PMID:22274803

Prioritization of anticancer drugs against a cancer using genomic features of cancer cells: A step towards personalized medicine

PubMed Central

Gupta, Sudheer; Chaudhary, Kumardeep; Kumar, Rahul; Gautam, Ankur; Nanda, Jagpreet Singh; Dhanda, Sandeep Kumar; Brahmachari, Samir Kumar; Raghava, Gajendra P. S.

2016-01-01

In this study, we investigated drug profile of 24 anticancer drugs tested against a large number of cell lines in order to understand the relation between drug resistance and altered genomic features of a cancer cell line. We detected frequent mutations, high expression and high copy number variations of certain genes in both drug resistant cell lines and sensitive cell lines. It was observed that a few drugs, like Panobinostat, are effective against almost all types of cell lines, whereas certain drugs are effective against only a limited type of cell lines. Tissue-specific preference of drugs was also seen where a drug is more effective against cell lines belonging to a specific tissue. Genomic features based models have been developed for each anticancer drug and achieved average correlation between predicted and actual growth inhibition of cell lines in the range of 0.43 to 0.78. We hope, our study will throw light in the field of personalized medicine, particularly in designing patient-specific anticancer drugs. In order to serve the scientific community, a webserver, CancerDP, has been developed for predicting priority/potency of an anticancer drug against a cancer cell line using its genomic features (http://crdd.osdd.net/raghava/cancerdp/). PMID:27030518

PolyA_DB 3 catalogs cleavage and polyadenylation sites identified by deep sequencing in multiple genomes

PubMed Central

Wang, Ruijia; Nambiar, Ram; Zheng, Dinghai

2018-01-01

Abstract PolyA_DB is a database cataloging cleavage and polyadenylation sites (PASs) in several genomes. Previous versions were based mainly on expressed sequence tags (ESTs), which had a limited amount and could lead to inaccurate PAS identification due to the presence of internal A-rich sequences in transcripts. Here, we present an updated version of the database based solely on deep sequencing data. First, PASs are mapped by the 3′ region extraction and deep sequencing (3′READS) method, ensuring unequivocal PAS identification. Second, a large volume of data based on diverse biological samples increases PAS coverage by 3.5-fold over the EST-based version and provides PAS usage information. Third, strand-specific RNA-seq data are used to extend annotated 3′ ends of genes to obtain more thorough annotations of alternative polyadenylation (APA) sites. Fourth, conservation information of PAS across mammals sheds light on significance of APA sites. The database (URL: http://www.polya-db.org/v3) currently holds PASs in human, mouse, rat and chicken, and has links to the UCSC genome browser for further visualization and for integration with other genomic data. PMID:29069441

Genome-wide significant association between a sequence variant at 15q15.2 and lung cancer risk

PubMed Central

Rafnar, Thorunn; Sulem, Patrick; Besenbacher, Soren; Gudbjartsson, Daniel F.; Zanon, Carlo; Gudmundsson, Julius; Stacey, Simon N.; Kostic, Jelena P.; Thorgeirsson, Thorgeir E.; Thorleifsson, Gudmar; Bjarnason, Hjordis; Skuladottir, Halla; Gudbjartsson, Tomas; Isaksson, Helgi J.; Isla, Dolores; Murillo, Laura; García-Prats, Maria D.; Panadero, Angeles; Aben, Katja K.H.; Vermeulen, Sita H.; van der Heijden, Henricus F.M.; Feser, William; Miller, York E.; Bunn, Paul A.; Kong, Augustine; Wolf, Holly J.; Franklin, Wilbur A.; Mayordomo, Jose I; Kiemeney, Lambertus A.; Jonsson, Steinn; Thorsteinsdottir, Unnur; Stefansson, Kari

2010-01-01

Genome-wide association studies (GWAS) have identified three genomic regions, at 15q24-25.1, 5p15.33 and 6p21.33, which associate with risk of lung cancer. Large meta-analyses of GWA data have failed to find additional associations of genome-wide significance. In this study, we sought to confirm 7 variants with suggestive association to lung cancer (P<10−5) in a recently published meta-analysis. In a GWA dataset of 1,447 lung cancer cases and 36,256 controls in Iceland, three correlated variants on 15q15.2 (rs504417, rs11853991 and rs748404) showed a significant association with lung cancer whereas rs4254535 on 2p14, rs1530057 on 3p24.1, rs6438347 on 3q13.31 and rs1926203 on 10q23.31 did not. The most significant variant, rs748404, was genotyped in additional 1,299 lung cancer cases and 4,102 controls from the Netherlands, Spain and the USA and the results combined with published GWAS data. In this analysis, the T allele of rs748404 reached genome-wide significance (OR=1.15, P=1.1×10−9). Another variant at the same locus, rs12050604, showed association with lung cancer (OR=1.09, 3.6×10−6) and remained significant after adjustment for rs748404 and vice versa. rs748404 is located 140 kb centromeric of the TP53BP1 gene that has been implicated in lung cancer risk. Two fully correlated, non-synonymous coding variants in TP53BP1, rs2602141 (Q1136K) and rs560191 (E353D), showed association with lung cancer in our sample set; however, this association did not remain significant after adjustment for rs748404. Our data show that one or more lung cancer risk variants of genome-wide significance and distinct from the coding variants in TP53BP1 are located at 15q15.2. PMID:21303977

Characterizing genomic differences of human cancer stratified by the TP53 mutation status.

PubMed

Wang, Mengyao; Yang, Chao; Zhang, Xiuqing; Li, Xiangchun

2018-06-01

The key roles of the TP53 mutation in cancer have been well established. TP53 is the most frequently mutated gene, and its inactivation is widespread among human cancer types. However, the landscape of genomic alterations in human cancers stratified by the TP53 mutation has not yet been described. We obtained somatic mutation and copy number change data of 6551 regular-mutated samples from the Cancer Genome Atlas (TCGA) and compared significantly mutated genes (SMGs), copy number alterations, mutational signatures and mutational strand asymmetries between cancer samples with and without the TP53 mutation. We identified 126 SMGs, 30 of which were statistically significant in both the TP53 mutant and wild-type groups. Several SMGs, such as VHL, SMAD4 and PTEN, showed a mutation bias towards the TP53 wild-type group, whereas ATRX, IDH1 and RB1 were more prevalent in the TP53 mutant group. Five mutational signatures were extracted from the combined TCGA dataset on which mutational asymmetry analysis was performed, revealing that the TP53 mutant group exhibited substantially greater replication and transcription biases. Furthermore, we found that alterations of multiple genes in a merged mutually exclusive network composed of BRAF, EGFR, PAK1, PIK3CA, PTEN, APC and TERT were related to shortened survival in the TP53 wild-type group. In summary, we characterized the genomic differences and similarities underlying human cancers stratified by the TP53 mutation and identified multi-gene alterations of a merged mutually exclusive network to be a poor prognostic factor for the TP53 wild-type group.

Genome Wide Methylome Alterations in Lung Cancer.

PubMed

Mullapudi, Nandita; Ye, Bin; Suzuki, Masako; Fazzari, Melissa; Han, Weiguo; Shi, Miao K; Marquardt, Gaby; Lin, Juan; Wang, Tao; Keller, Steven; Zhu, Changcheng; Locker, Joseph D; Spivack, Simon D

2015-01-01

Aberrant cytosine 5-methylation underlies many deregulated elements of cancer. Among paired non-small cell lung cancers (NSCLC), we sought to profile DNA 5-methyl-cytosine features which may underlie genome-wide deregulation. In one of the more dense interrogations of the methylome, we sampled 1.2 million CpG sites from twenty-four NSCLC tumor (T)-non-tumor (NT) pairs using a methylation-sensitive restriction enzyme- based HELP-microarray assay. We found 225,350 differentially methylated (DM) sites in adenocarcinomas versus adjacent non-tumor tissue that vary in frequency across genomic compartment, particularly notable in gene bodies (GB; p<2.2E-16). Further, when DM was coupled to differential transcriptome (DE) in the same samples, 37,056 differential loci in adenocarcinoma emerged. Approximately 90% of the DM-DE relationships were non-canonical; for example, promoter DM associated with DE in the same direction. Of the canonical changes noted, promoter (PR) DM loci with reciprocal changes in expression in adenocarcinomas included HBEGF, AGER, PTPRM, DPT, CST1, MELK; DM GB loci with concordant changes in expression included FOXM1, FERMT1, SLC7A5, and FAP genes. IPA analyses showed adenocarcinoma-specific promoter DMxDE overlay identified familiar lung cancer nodes [tP53, Akt] as well as less familiar nodes [HBEGF, NQO1, GRK5, VWF, HPGD, CDH5, CTNNAL1, PTPN13, DACH1, SMAD6, LAMA3, AR]. The unique findings from this study include the discovery of numerous candidate The unique findings from this study include the discovery of numerous candidate methylation sites in both PR and GB regions not previously identified in NSCLC, and many non-canonical relationships to gene expression. These DNA methylation features could potentially be developed as risk or diagnostic biomarkers, or as candidate targets for newer methylation locus-targeted preventive or therapeutic agents.

Cancer systems biology in the genome sequencing era: part 1, dissecting and modeling of tumor clones and their networks.

PubMed

Wang, Edwin; Zou, Jinfeng; Zaman, Naif; Beitel, Lenore K; Trifiro, Mark; Paliouras, Miltiadis

2013-08-01

Recent tumor genome sequencing confirmed that one tumor often consists of multiple cell subpopulations (clones) which bear different, but related, genetic profiles such as mutation and copy number variation profiles. Thus far, one tumor has been viewed as a whole entity in cancer functional studies. With the advances of genome sequencing and computational analysis, we are able to quantify and computationally dissect clones from tumors, and then conduct clone-based analysis. Emerging technologies such as single-cell genome sequencing and RNA-Seq could profile tumor clones. Thus, we should reconsider how to conduct cancer systems biology studies in the genome sequencing era. We will outline new directions for conducting cancer systems biology by considering that genome sequencing technology can be used for dissecting, quantifying and genetically characterizing clones from tumors. Topics discussed in Part 1 of this review include computationally quantifying of tumor subpopulations; clone-based network modeling, cancer hallmark-based networks and their high-order rewiring principles and the principles of cell survival networks of fast-growing clones. Crown Copyright © 2013. Published by Elsevier Ltd. All rights reserved.

Genomic profiling of 766 cancer-related genes in archived esophageal normal and carcinoma tissues.

PubMed

Chen, Jing; Guo, Liping; Peiffer, Daniel A; Zhou, Lixin; Chan, Owen Tsan Mo; Bibikova, Marina; Wickham-Garcia, Eliza; Lu, Shih-Hsin; Zhan, Qimin; Wang-Rodriguez, Jessica; Jiang, Wei; Fan, Jian-Bing

2008-05-15

We employed the BeadArraytrade mark technology to perform a genetic analysis in 33 formalin-fixed, paraffin-embedded (FFPE) human esophageal carcinomas, mostly squamous-cell-carcinoma (ESCC), and their adjacent normal tissues. A total of 1,432 single nucleotide polymorphisms (SNPs) derived from 766 cancer-related genes were genotyped with partially degraded genomic DNAs isolated from these samples. This directly targeted genomic profiling identified not only previously reported somatic gene amplifications (e.g., CCND1) and deletions (e.g., CDKN2A and CDKN2B) but also novel genomic aberrations. Among these novel targets, the most frequently deleted genomic regions were chromosome 3p (including tumor suppressor genes FANCD2 and CTNNB1) and chromosome 5 (including tumor suppressor gene APC). The most frequently amplified genomic region was chromosome 3q (containing DVL3, MLF1, ABCC5, BCL6, AGTR1 and known oncogenes TNK2, TNFSF10, FGF12). The chromosome 3p deletion and 3q amplification occurred coincidently in nearly all of the affected cases, suggesting a molecular mechanism for the generation of somatic chromosomal aberrations. We also detected significant differences in germline allele frequency between the esophageal cohort of our study and normal control samples from the International HapMap Project for 10 genes (CSF1, KIAA1804, IL2, PMS2, IRF7, FLT3, NTRK2, MAP3K9, ERBB2 and PRKAR1A), suggesting that they might play roles in esophageal cancer susceptibility and/or development. Taken together, our results demonstrated the utility of the BeadArray technology for high-throughput genetic analysis in FFPE tumor tissues and provided a detailed genetic profiling of cancer-related genes in human esophageal cancer. (c) 2008 Wiley-Liss, Inc.

Defining Genomic Changes in Triple-Negative Breast Cancer in Women of African Descent

DTIC Science & Technology

2012-06-01

African and African - American breast cancer cases. Gene Expression Array Studies The 31 triple negative Kijabe samples were... American Adjacent Normal Breast Tissue PI: Pegram & Baumbach Defining Genomic Changes in Triple Negative Breast Cancer in Women of African ...Tissues from African - American and East African Patients with Triple Negative Breast

Validation of Genome-Wide Prostate Cancer Associations in Men of African Descent

PubMed Central

Chang, Bao-Li; Spangler, Elaine; Gallagher, Stephen; Haiman, Christopher A.; Henderson, Brian; Isaacs, William; Benford, Marnita L.; Kidd, LaCreis R.; Cooney, Kathleen; Strom, Sara; Ann Ingles, Sue; Stern, Mariana C.; Corral, Roman; Joshi, Amit D.; Xu, Jianfeng; Giri, Veda N.; Rybicki, Benjamin; Neslund-Dudas, Christine; Kibel, Adam S.; Thompson, Ian M.; Leach, Robin J.; Ostrander, Elaine A.; Stanford, Janet L.; Witte, John; Casey, Graham; Eeles, Rosalind; Hsing, Ann W.; Chanock, Stephen; Hu, Jennifer J.; John, Esther M.; Park, Jong; Stefflova, Klara; Zeigler-Johnson, Charnita; Rebbeck, Timothy R.

2010-01-01

Background Genome-wide association studies (GWAS) have identified numerous prostate cancer susceptibility alleles, but these loci have been identified primarily in men of European descent. There is limited information about the role of these loci in men of African descent. Methods We identified 7,788 prostate cancer cases and controls with genotype data for 47 GWAS-identified loci. Results We identified significant associations for SNP rs10486567 at JAZF1, rs10993994 at MSMB, rs12418451 and rs7931342 at 11q13, and rs5945572 and rs5945619 at NUDT10/11. These associations were in the same direction and of similar magnitude as those reported in men of European descent. Significance was attained at all report prostate cancer susceptibility regions at chromosome 8q24, including associations reaching genome-wide significance in region 2. Conclusion We have validated in men of African descent the associations at some, but not all, prostate cancer susceptibility loci originally identified in European descent populations. This may be due to heterogeneity in genetic etiology or in the pattern of genetic variation across populations. Impact The genetic etiology of prostate cancer in men of African descent differs from that of men of European descent. PMID:21071540

CPTAC Releases Largest-Ever Colorectal Cancer Proteome Dataset from Previously Genome Characterized Tumors | Office of Cancer Clinical Proteomics Research

Cancer.gov

On September 4, 2013, NCI’s Clinical Proteomics Tumor Analysis Consortium (CPTAC) publicly released proteomic data produced from colorectal tumor samples previously analyzed by The Cancer Genome Atlas (TCGA).  This is the initial release of proteomic tumor data designed to complement genomic data on the same tumors. The data is publicly available at the CPTAC data portal.

FISH Oracle 2: a web server for integrative visualization of genomic data in cancer research

PubMed Central

2014-01-01

Background A comprehensive view on all relevant genomic data is instrumental for understanding the complex patterns of molecular alterations typically found in cancer cells. One of the most effective ways to rapidly obtain an overview of genomic alterations in large amounts of genomic data is the integrative visualization of genomic events. Results We developed FISH Oracle 2, a web server for the interactive visualization of different kinds of downstream processed genomics data typically available in cancer research. A powerful search interface and a fast visualization engine provide a highly interactive visualization for such data. High quality image export enables the life scientist to easily communicate their results. A comprehensive data administration allows to keep track of the available data sets. We applied FISH Oracle 2 to published data and found evidence that, in colorectal cancer cells, the gene TTC28 may be inactivated in two different ways, a fact that has not been published before. Conclusions The interactive nature of FISH Oracle 2 and the possibility to store, select and visualize large amounts of downstream processed data support life scientists in generating hypotheses. The export of high quality images supports explanatory data visualization, simplifying the communication of new biological findings. A FISH Oracle 2 demo server and the software is available at http://www.zbh.uni-hamburg.de/fishoracle. PMID:24684958

FISH Oracle 2: a web server for integrative visualization of genomic data in cancer research.

PubMed

Mader, Malte; Simon, Ronald; Kurtz, Stefan

2014-03-31

A comprehensive view on all relevant genomic data is instrumental for understanding the complex patterns of molecular alterations typically found in cancer cells. One of the most effective ways to rapidly obtain an overview of genomic alterations in large amounts of genomic data is the integrative visualization of genomic events. We developed FISH Oracle 2, a web server for the interactive visualization of different kinds of downstream processed genomics data typically available in cancer research. A powerful search interface and a fast visualization engine provide a highly interactive visualization for such data. High quality image export enables the life scientist to easily communicate their results. A comprehensive data administration allows to keep track of the available data sets. We applied FISH Oracle 2 to published data and found evidence that, in colorectal cancer cells, the gene TTC28 may be inactivated in two different ways, a fact that has not been published before. The interactive nature of FISH Oracle 2 and the possibility to store, select and visualize large amounts of downstream processed data support life scientists in generating hypotheses. The export of high quality images supports explanatory data visualization, simplifying the communication of new biological findings. A FISH Oracle 2 demo server and the software is available at http://www.zbh.uni-hamburg.de/fishoracle.

MTAP deletion confers enhanced dependency on the PRMT5 arginine methyltransferase in cancer cells | Office of Cancer Genomics

Cancer.gov

The discovery of cancer dependencies has the potential to inform therapeutic strategies and to identify putative drug targets. Integrating data from comprehensive genomic profiling of cancer cell lines and from functional characterization of cancer cell dependencies, we discovered that loss of the enzyme methylthioadenosine phosphorylase (MTAP) confers a selective dependence on protein arginine methyltransferase 5 (PRMT5) and its binding partner WDR77. MTAP is frequently lost due to its proximity to the commonly deleted tumor suppressor gene, CDKN2A.

Molecular genetics and genomics progress in urothelial bladder cancer.

PubMed

Netto, George J

2013-11-01

The clinical management of solid tumor patients has recently undergone a paradigm shift as the result of the accelerated advances in cancer genetics and genomics. Molecular diagnostics is now an integral part of routine clinical management in lung, colon, and breast cancer patients. In a disappointing contrast, molecular biomarkers remain largely excluded from current management algorithms of urologic malignancies. The need for new treatment alternatives and validated prognostic molecular biomarkers that can help clinicians identify patients in need of early aggressive management is pressing. Identifying robust predictive biomarkers that can stratify response to newly introduced targeted therapeutics is another crucially needed development. The following is a brief discussion of some promising candidate biomarkers that may soon become a part of clinical management of bladder cancers. © 2013 Published by Elsevier Inc.

Whole-genome sequencing of an aggressive BRAF wild-type papillary thyroid cancer identified EML4-ALK translocation as a therapeutic target.

PubMed

Demeure, Michael J; Aziz, Meraj; Rosenberg, Richard; Gurley, Steven D; Bussey, Kimberly J; Carpten, John D

2014-06-01

Recent advances in the treatment of cancer have focused on targeting genomic aberrations with selective therapeutic agents. In radioiodine resistant aggressive papillary thyroid cancers, there remain few effective therapeutic options. A 62-year-old man who underwent multiple operations for papillary thyroid cancer and whose metastases progressed despite standard treatments provided tumor tissue. We analyzed tumor and whole blood DNA by whole genome sequencing, achieving 80× or greater coverage over 94 % of the exome and 90 % of the genome. We determined somatic mutations and structural alterations. We found a total of 57 somatic mutations in 55 genes of the cancer genome. There was notably a lack of mutations in NRAS and BRAF, and no RET/PTC rearrangement. There was a mutation in the TRAPP oncogene and a loss of heterozygosity of the p16, p18, and RB1 tumor suppressor genes. The oncogenic driver for this tumor is a translocation involving the genes for anaplastic lymphoma receptor tyrosine kinase (ALK) and echinoderm microtubule associated protein like 4 (EML4). The EML4-ALK translocation has been reported in approximately 5 % of lung cancers, as well as in pediatric neuroblastoma, and is a therapeutic target for crizotinib. This is the first report of the whole genomic sequencing of a papillary thyroid cancer in which we identified an EML4-ALK translocation of a TRAPP oncogene mutation. These findings suggest that this tumor has a more distinct oncogenesis than BRAF mutant papillary thyroid cancer. Whole genome sequencing can elucidate an oncogenic context and expose potential therapeutic vulnerabilities in rare cancers.

Using Galaxy to Perform Large-Scale Interactive Data Analyses

PubMed Central

Hillman-Jackson, Jennifer; Clements, Dave; Blankenberg, Daniel; Taylor, James; Nekrutenko, Anton

2012-01-01

Innovations in biomedical research technologies continue to provide experimental biologists with novel and increasingly large genomic and high-throughput data resources to be analyzed. As creating and obtaining data has become easier, the key decision faced by many researchers is a practical one: where and how should an analysis be performed? Datasets are large and analysis tool set-up and use is riddled with complexities outside of the scope of core research activities. The authors believe that Galaxy (galaxyproject.org) provides a powerful solution that simplifies data acquisition and analysis in an intuitive web-application, granting all researchers access to key informatics tools previously only available to computational specialists working in Unix-based environments. We will demonstrate through a series of biomedically relevant protocols how Galaxy specifically brings together 1) data retrieval from public and private sources, for example, UCSC’s Eukaryote and Microbial Genome Browsers (genome.ucsc.edu), 2) custom tools (wrapped Unix functions, format standardization/conversions, interval operations) and 3rd party analysis tools, for example, Bowtie/Tuxedo Suite (bowtie-bio.sourceforge.net), Lastz (www.bx.psu.edu/~rsharris/lastz/), SAMTools (samtools.sourceforge.net), FASTX-toolkit (hannonlab.cshl.edu/fastx_toolkit), and MACS (liulab.dfci.harvard.edu/MACS), and creates results formatted for visualization in tools such as the Galaxy Track Browser (GTB, galaxyproject.org/wiki/Learn/Visualization), UCSC Genome Browser (genome.ucsc.edu), Ensembl (www.ensembl.org), and GeneTrack (genetrack.bx.psu.edu). Galaxy rapidly has become the most popular choice for integrated next generation sequencing (NGS) analytics and collaboration, where users can perform, document, and share complex analysis within a single interface in an unprecedented number of ways. PMID:18428782

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

PubMed

Nabavi, Sheida

2016-08-15

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

GENOMIC PREDICTOR OF RESPONSE AND SURVIVAL FOLLOWING TAXANE-ANTHRACYCLINE CHEMOTHERAPY FOR INVASIVE BREAST CANCER

PubMed Central

Hatzis, Christos; Pusztai, Lajos; Valero, Vicente; Booser, Daniel J.; Esserman, Laura; Lluch, Ana; Vidaurre, Tatiana; Holmes, Frankie; Souchon, Eduardo; Martin, Miguel; Cotrina, José; Gomez, Henry; Hubbard, Rebekah; Chacón, J. Ignacio; Ferrer-Lozano, Jaime; Dyer, Richard; Buxton, Meredith; Gong, Yun; Wu, Yun; Ibrahim, Nuhad; Andreopoulou, Eleni; Ueno, Naoto T.; Hunt, Kelly; Yang, Wei; Nazario, Arlene; DeMichele, Angela; O’Shaughnessy, Joyce; Hortobagyi, Gabriel N.; Symmans, W. Fraser

2017-01-01

CONTEXT Accurate prediction of who will (or won’t) have high probability of survival benefit from standard treatments is fundamental for individualized cancer treatment strategies. OBJECTIVE To develop a predictor of response and survival from chemotherapy for newly diagnosed invasive breast cancer. DESIGN Development of different predictive signatures for resistance and response to neoadjuvant chemotherapy (stratified according to estrogen receptor (ER) status) from gene expression microarrays of newly diagnosed breast cancer (310 patients). Then prediction of breast cancer treatment-sensitivity using the combination of signatures for: 1) sensitivity to endocrine therapy, 2) chemo-resistance, and 3) chemo-sensitivity. Independent validation (198 patients) and comparison with other reported genomic predictors of chemotherapy response. SETTING Prospective multicenter study to develop and test genomic predictors for neoadjuvant chemotherapy. PATIENTS Newly diagnosed HER2-negative breast cancer treated with chemotherapy containing sequential taxane and anthracycline-based regimens then endocrine therapy (if hormone receptor-positive). MAIN OUTCOME MEASURES Distant relapse-free survival (DRFS) if predicted treatment-sensitive and absolute risk reduction (ARR, difference in DRFS of the two predicted groups) at median follow-up (3 years), and their 95% confidence intervals (CI). RESULTS Patients in the independent validation cohort (99% clinical Stage II–III) who were predicted to be treatment-sensitive (28% of total) had DRFS of 92% (CI 85–100) and survival benefit compared to others (absolute risk reduction (ARR) 18%; CI 6–28). Predictions were accurate if breast cancer was ER-positive (30% predicted sensitive, DRFS 97%, CI 91–100; ARR 11%, CI 0.1–21) or ER-negative (26% predicted sensitive, DRFS 83%, CI 68–100; ARR 26%, CI 4–28), and were significant in multivariate analysis after adjusting for relevant clinical-pathologic characteristics. Other

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

PubMed

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

2018-03-01

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

Integrated Genomic and Epigenomic Analysis of Breast Cancer Brain Metastasis

PubMed Central

Salhia, Bodour; Kiefer, Jeff; Ross, Julianna T. D.; Metapally, Raghu; Martinez, Rae Anne; Johnson, Kyle N.; DiPerna, Danielle M.; Paquette, Kimberly M.; Jung, Sungwon; Nasser, Sara; Wallstrom, Garrick; Tembe, Waibhav; Baker, Angela; Carpten, John; Resau, Jim; Ryken, Timothy; Sibenaller, Zita; Petricoin, Emanuel F.; Liotta, Lance A.; Ramanathan, Ramesh K.; Berens, Michael E.; Tran, Nhan L.

2014-01-01

The brain is a common site of metastatic disease in patients with breast cancer, which has few therapeutic options and dismal outcomes. The purpose of our study was to identify common and rare events that underlie breast cancer brain metastasis. We performed deep genomic profiling, which integrated gene copy number, gene expression and DNA methylation datasets on a collection of breast brain metastases. We identified frequent large chromosomal gains in 1q, 5p, 8q, 11q, and 20q and frequent broad-level deletions involving 8p, 17p, 21p and Xq. Frequently amplified and overexpressed genes included ATAD2, BRAF, DERL1, DNMTRB and NEK2A. The ATM, CRYAB and HSPB2 genes were commonly deleted and underexpressed. Knowledge mining revealed enrichment in cell cycle and G2/M transition pathways, which contained AURKA, AURKB and FOXM1. Using the PAM50 breast cancer intrinsic classifier, Luminal B, Her2+/ER negative, and basal-like tumors were identified as the most commonly represented breast cancer subtypes in our brain metastasis cohort. While overall methylation levels were increased in breast cancer brain metastasis, basal-like brain metastases were associated with significantly lower levels of methylation. Integrating DNA methylation data with gene expression revealed defects in cell migration and adhesion due to hypermethylation and downregulation of PENK, EDN3, and ITGAM. Hypomethylation and upregulation of KRT8 likely affects adhesion and permeability. Genomic and epigenomic profiling of breast brain metastasis has provided insight into the somatic events underlying this disease, which have potential in forming the basis of future therapeutic strategies. PMID:24489661

Evolution and clinical impact of co-occurring genetic alterations in advanced-stage EGFR-mutant lung cancers. | Office of Cancer Genomics

Cancer.gov

A widespread approach to modern cancer therapy is to identify a single oncogenic driver gene and target its mutant-protein product (for example, EGFR-inhibitor treatment in EGFR-mutant lung cancers). However, genetically driven resistance to targeted therapy limits patient survival. Through genomic analysis of 1,122 EGFR-mutant lung cancer cell-free DNA samples and whole-exome analysis of seven longitudinally collected tumor samples from a patient with EGFR-mutant lung cancer, we identified critical co-occurring oncogenic events present in most advanced-stage EGFR-mutant lung cancers.

Modeling Gene-Wise Dependencies Improves the Identification of Drug Response Biomarkers in Cancer Studies | Office of Cancer Genomics

Cancer.gov

Recent advances in biomedical and sequencing technologies have revealed the genomic landscape of common forms of human cancer in unprecedented detail. Of the genes that drive tumorigenesis when altered, for most cancers it is believed that there exist a small number of “mountains” (genes altered at high frequencies across the population), and a much larger number of “hills” (much less frequently altered genes).

Copy-number and gene dependency analysis reveals partial copy loss of wild-type SF3B1 as a novel cancer vulnerability. | Office of Cancer Genomics

Cancer.gov

Genomic instability is a hallmark of human cancer, and results in widespread somatic copy number alterations. We used a genome-scale shRNA viability screen in human cancer cell lines to systematically identify genes that are essential in the context of particular copy-number alterations (copy-number associated gene dependencies). The most enriched class of copy-number associated gene dependencies was CYCLOPS (Copy-number alterations Yielding Cancer Liabilities Owing to Partial losS) genes, and spliceosome components were the most prevalent.

Non-B DB: a database of predicted non-B DNA-forming motifs in mammalian genomes.

PubMed

Cer, Regina Z; Bruce, Kevin H; Mudunuri, Uma S; Yi, Ming; Volfovsky, Natalia; Luke, Brian T; Bacolla, Albino; Collins, Jack R; Stephens, Robert M

2011-01-01

Although the capability of DNA to form a variety of non-canonical (non-B) structures has long been recognized, the overall significance of these alternate conformations in biology has only recently become accepted en masse. In order to provide access to genome-wide locations of these classes of predicted structures, we have developed non-B DB, a database integrating annotations and analysis of non-B DNA-forming sequence motifs. The database provides the most complete list of alternative DNA structure predictions available, including Z-DNA motifs, quadruplex-forming motifs, inverted repeats, mirror repeats and direct repeats and their associated subsets of cruciforms, triplex and slipped structures, respectively. The database also contains motifs predicted to form static DNA bends, short tandem repeats and homo(purine•pyrimidine) tracts that have been associated with disease. The database has been built using the latest releases of the human, chimp, dog, macaque and mouse genomes, so that the results can be compared directly with other data sources. In order to make the data interpretable in a genomic context, features such as genes, single-nucleotide polymorphisms and repetitive elements (SINE, LINE, etc.) have also been incorporated. The database is accessed through query pages that produce results with links to the UCSC browser and a GBrowse-based genomic viewer. It is freely accessible at http://nonb.abcc.ncifcrf.gov.

Population Sciences, Translational Research and the Opportunities and Challenges for Genomics to Reduce the Burden of Cancer in the 21st Century

PubMed Central

Khoury, Muin J.; Clauser, Steven B.; Freedman, Andrew N.; Gillanders, Elizabeth M.; Glasgow, Russ E.; Klein, William M. P.; Schully, Sheri D.

2011-01-01

Advances in genomics and related fields are promising tools for risk assessment, early detection, and targeted therapies across the entire cancer care continuum. In this commentary, we submit that this promise cannot be fulfilled without an enhanced translational genomics research agenda firmly rooted in the population sciences. Population sciences include multiple disciplines that are needed throughout the translational research continuum. For example, epidemiologic studies are needed not only to accelerate genomic discoveries and new biological insights into cancer etiology and pathogenesis, but to characterize and critically evaluate these discoveries in well defined populations for their potential for cancer prediction, prevention and response to treatments. Behavioral, social and communication sciences are needed to explore genomic-modulated responses to old and new behavioral interventions, adherence to therapies, decision-making across the continuum, and effective use in health care. Implementation science, health services, outcomes research, comparative effectiveness research and regulatory science are needed for moving validated genomic applications into practice and for measuring their effectiveness, cost effectiveness and unintended consequences. Knowledge synthesis, evidence reviews and economic modeling of the effects of promising genomic applications will facilitate policy decisions, and evidence-based recommendations. Several independent and multidisciplinary panels have recently made specific recommendations for enhanced research and policy infrastructure to inform clinical and population research for moving genomic innovations into the cancer care continuum. An enhanced translational genomics and population sciences agenda is urgently needed to fulfill the promise of genomics in reducing the burden of cancer. PMID:21795499

The OncoPPi Portal: an integrative resource to explore and prioritize protein-protein interactions for cancer target discovery. | Office of Cancer Genomics

Cancer.gov

Motivation: As cancer genomics initiatives move toward comprehensive identification of genetic alterations in cancer, attention is now turning to understanding how interactions among these genes lead to the acquisition of tumor hallmarks. Emerging pharmacological and clinical data suggest a highly promising role of cancer-specific protein-protein interactions (PPIs) as druggable cancer targets. However, large-scale experimental identification of cancer-related PPIs remains challenging, and currently available resources to explore oncogenic PPI networks are limited.

The OncoPPi network of cancer-focused protein-protein interactions to inform biological insights and therapeutic strategies* | Office of Cancer Genomics

Cancer.gov

As genomics advances reveal the cancer gene landscape, a daunting task is to understand how these genes contribute to dysregulated oncogenic pathways. Integration of cancer genes into networks offers opportunities to reveal protein–protein interactions (PPIs) with functional and therapeutic significance. Here, we report the generation of a cancer-focused PPI network, termed OncoPPi, and identification of >260 cancer-associated PPIs not in other large-scale interactomes.

Digestive tumor bank protocol: from surgical specimens to genomic studies of digestive cancers.

PubMed

Popescu, I; Stroescu, C; Dumitrascu, T; Herlea, V; Paslaru, Liliana; Lazar, V; Boissin, H; Taieb, J; Horeanga, Ionela

2006-01-01

Cancer is a complex polygenic and multifactorial disease, resulting from successive dynamic changes in the genome of somatic cells and from the accumulation of molecular alterations in both tumour cells and host cells. For the majority of cancers, including many malignancies of the gastrointestinal tract, our current means of diagnosis and treatment of the tumors are grossly insufficient. In recent years the development of several gene expression profiling methods such as comparative genomic hybridization (CGH), differential display, serial analysis of gene expression (SAGE) and DNA arrays, together with the sequencing of the human genome, has provided an opportunity to monitor and investigate the complete cascade of molecular events leading to tumor development and progression. Given the central role played by surgeons in the current management of patients with solid cancers, it is of paramount importance for them to know the principles characterizing this laboratory tools to critically assess the results originating from this biotechnology. We describe in this article the scientific partnership between Fundeni Clinical Institute Bucharest, Romania and RNtech Company, Paris, France for the development of a center of biological resources (Biobank) as well as the standardized protocol of working with the biological samples, the ongoing projects and the future perspectives.

Common structural and epigenetic changes in the genome of castration-resistant prostate cancer.

PubMed

Friedlander, Terence W; Roy, Ritu; Tomlins, Scott A; Ngo, Vy T; Kobayashi, Yasuko; Azameera, Aruna; Rubin, Mark A; Pienta, Kenneth J; Chinnaiyan, Arul; Ittmann, Michael M; Ryan, Charles J; Paris, Pamela L

2012-02-01

Progression of primary prostate cancer to castration-resistant prostate cancer (CRPC) is associated with numerous genetic and epigenetic alterations that are thought to promote survival at metastatic sites. In this study, we investigated gene copy number and CpG methylation status in CRPC to gain insight into specific pathophysiologic pathways that are active in this advanced form of prostate cancer. Our analysis defined and validated 495 genes exhibiting significant differences in CRPC in gene copy number, including gains in androgen receptor (AR) and losses of PTEN and retinoblastoma 1 (RB1). Significant copy number differences existed between tumors with or without AR gene amplification, including a common loss of AR repressors in AR-unamplified tumors. Simultaneous gene methylation and allelic deletion occurred frequently in RB1 and HSD17B2, the latter of which is involved in testosterone metabolism. Lastly, genomic DNA from most CRPC was hypermethylated compared with benign prostate tissue. Our findings establish a comprehensive methylation signature that couples epigenomic and structural analyses, thereby offering insights into the genomic alterations in CRPC that are associated with a circumvention of hormonal therapy. Genes identified in this integrated genomic study point to new drug targets in CRPC, an incurable disease state which remains the chief therapeutic challenge. ©2012 AACR.

Ethical, legal, and social issues related to genomics and cancer research: the impending crisis.

PubMed

Ellerin, Bruce E; Schneider, Robert J; Stern, Arnold; Toniolo, Paolo G; Formenti, Silvia C

2005-11-01

Cancer research is a multibillion-dollar enterprise validated by the clinical trial process and increasingly defined by genomics. The continued success of the endeavor depends on the smooth functioning of the clinical trial system, which in turn depends on human subject participation. Yet human subject participation can exist only in an atmosphere of trust between research participants and research sponsors, and the advent of genomics has raised a multitude of ethical, legal, and social issues that threaten this trust. The authors examine 6 of these issues: (1) informed consent; (2) privacy, confidentiality, and family disclosure dilemmas; (3) property rights in genomic discoveries; (4) individual and institutional conflicts of interest; (5) insurance and employment issues; and (6) litigation under the federal False Claims Act. The authors conclude that failure to resolve these issues may lead to a sufficient impairment of trust in genomics-based clinical trials on the part of potential research participants that the clinical trial system may implode for lack of willing participants, thus threatening the future of cancer research.

The expanding universe of cohesin functions: a new genome stability caretaker involved in human disease and cancer.

PubMed

Mannini, Linda; Menga, Stefania; Musio, Antonio

2010-06-01

Cohesin is responsible for sister chromatid cohesion, ensuring the correct chromosome segregation. Beyond this role, cohesin and regulatory cohesin genes seem to play a role in preserving genome stability and gene transcription regulation. DNA damage is thought to be a major culprit for many human diseases, including cancer. Our present knowledge of the molecular basis underlying genome instability is extremely limited. Mutations in cohesin genes cause human diseases such as Cornelia de Lange syndrome and Roberts syndrome/SC phocomelia, and all the cell lines derived from affected patients show genome instability. Cohesin mutations have also been identified in colorectal cancer. Here, we will discuss the human disorders caused by alterations of cohesin function, with emphasis on the emerging role of cohesin as a genome stability caretaker.

Genome-wide profiles of CtBP link metabolism with genome stability and epithelial reprogramming in breast cancer.

PubMed

Di, Li-Jun; Byun, Jung S; Wong, Madeline M; Wakano, Clay; Taylor, Tara; Bilke, Sven; Baek, Songjoon; Hunter, Kent; Yang, Howard; Lee, Maxwell; Zvosec, Cecilia; Khramtsova, Galina; Cheng, Fan; Perou, Charles M; Miller, C Ryan; Raab, Rachel; Olopade, Olufunmilayo I; Gardner, Kevin

2013-01-01

The C-terminal binding protein (CtBP) is a NADH-dependent transcriptional repressor that links carbohydrate metabolism to epigenetic regulation by recruiting diverse histone-modifying complexes to chromatin. Here global profiling of CtBP in breast cancer cells reveals that it drives epithelial-to-mesenchymal transition, stem cell pathways and genome instability. CtBP expression induces mesenchymal and stem cell-like features, whereas CtBP depletion or caloric restriction reverses gene repression and increases DNA repair. Multiple members of the CtBP-targeted gene network are selectively downregulated in aggressive breast cancer subtypes. Differential expression of CtBP-targeted genes predicts poor clinical outcome in breast cancer patients, and elevated levels of CtBP in patient tumours predict shorter median survival. Finally, both CtBP promoter targeting and gene repression can be reversed by small molecule inhibition. These findings define broad roles for CtBP in breast cancer biology and suggest novel chromatin-based strategies for pharmacologic and metabolic intervention in cancer.

Integrative Genomics Reveals Mechanisms of Copy Number Alterations Responsible for Transcriptional Deregulation in Colorectal Cancer