Project description:<p>Discovery, Biology, and Risk of Inherited Variants in Breast Cancer (DRIVE) was one of five projects funded in 2010 as part of the NCI's Genetic Associations and Mechanisms in Oncology (GAME-ON) initiative (<a href="http://epi.grants.cancer.gov/gameon/">http://epi.grants.cancer.gov/gameon/</a>). GAME-ON's overall goal was to foster an intra-disciplinary and collaborative approach to the translation of promising research leads deriving from the initial wave of cancer GWAS. Specific goals included replication of previous GWAS findings and identification of new susceptibility loci through meta analyses of existing GWAS data and fine mapping of identified loci to better pinpoint causal variants; and identify germline variants that are associated with risk of multiple cancers. The other four funded GAME-ON projects were: the ColoRectal TransdisciplinaryStudy (CORECT), Elucidating Loci Involved in Prostate Cancer Susceptibility (ELLIPSE), Follow-up of Ovarian Cancer Genetic Association and Interaction Study (FOCI), and Transdisciplinary Research in Cancer of the Lung (TRICL).</p> <p>To identify additional cancer risk loci, improve the precision of fine-mapping, and facilitate cross-cancer analyses, the GAME-ON projects and other consortia formed the OncoArray network (<a href="http://epi.grants.cancer.gov/oncoarray/">http://epi.grants.cancer.gov/oncoarray/</a>), which developed and genotyped a new custom genotyping array (the "OncoArray") in large numbers of cancer cases and controls (over 400,000 samples). The OncoArray is a custom array manufactured by Illumina. The array includes a backbone of approximately 260,000 SNPs that provide genome-wide coverage of most common variants, together with markers of interest for each of the five GAME-ON cancers identified through genome-wide association studies (GWAS), fine-mapping of known susceptibility regions, sequencing studies, and other approaches. The array also includes loci of interest identified through studies of other cancer types, and other loci of interest to multiple cancer types (including loci associated with cancer related phenotypes, drug metabolism and radiation response). Additionally, SNPs relating to quantitative phenotypes such as body mass index (BMI), height, and breast density that correlate with common cancer risks are also included.</p> <p>The DRIVE data included under this dbGAP submission include OncoArray data from 60,015 breast cancer cases and controls genotyped at the Center for Inherited Disease Research (CIDR), University of Cambridge, National Cancer Institute, University of Copenhagen, University of Southern California and Mayo Clinic. Details on an additional approx. 80,000 breast cancer cases and controls genotyped at other centers can be found at <a href="http://bcac.ccge.medschl.cam.ac.uk/bcacdata/oncoarray/">http://bcac.ccge.medschl.cam.ac.uk/bcacdata/oncoarray/</a>. </p>
Project description:<p>This study consists of whole genome sequencing (target: average 30x coverage) of 110 European-ancestry (EA), early-onset, family-history-positive breast cancer cases, 21 Asian cases, 25 African-American cases, and 24 controls from six studies participating in the Discovery, Biology, and Risk of Inherited Variants in Breast Cancer (DRIVE) consortium, part of the NCI's Genetic Associations and Mechanisms in Oncology (GAME-ON) initiative (<a href="http://epi.grants.cancer.gov/gameon/"> http://epi.grants.cancer.gov/gameon/ </a>) </p>
Project description:<p>Discovery, Biology, and Risk of Inherited Variants in Breast Cancer (DRIVE) was one of five projects funded in 2010 as part of the NCI's Genetic Associations and Mechanisms in Oncology (GAME-ON) initiative (<a href="http://epi.grants.cancer.gov/gameon/">http://epi.grants.cancer.gov/gameon/</a>). GAME-ON's overall goal was to foster an intra-disciplinary and collaborative approach to the translation of promising research leads deriving from the initial wave of cancer GWAS. Specific goals included replication of previous GWAS findings and identification of new susceptibility loci through meta analyses of existing GWAS data and fine mapping of identified loci to better pinpoint causal variants; and identify germline variants that are associated with risk of multiple cancers. The other four funded GAME-ON projects were: the ColoRectal TransdisciplinaryStudy (CORECT), Elucidating Loci Involved in Prostate Cancer Susceptibility (ELLIPSE), Follow-up of Ovarian Cancer Genetic Association and Interaction Study (FOCI), and Transdisciplinary Research in Cancer of the Lung (TRICL).</p> <p>To identify additional cancer risk loci, improve the precision of fine-mapping, and facilitate cross-cancer analyses, DRIVE investigators performed a meta-analysis of eleven genome-wide association studies of breast cancer: The Australian Breast Cancer Family Study (ABCFS), the British Breast Cancer Study (BBCS), the Breast and Prostate Cancer Cohort Consortium (BPC3), the Breast Cancer Family Registries (BCFR), the Dutch Familial Bilateral Breast Cancer Study (DFBBCS), German Consortium for Hereditary Breast and Ovarian Cancer (GC-HBOC), the Helsinki breast cancer family Study (HEBCS), the Mammary Carcinoma Risk factor Investigation (MARIE), the Singapore and Sweden Breast Cancer Study (SASBAC), the Triple Negative Breast Cancer Study (TNBC), and the UK2 GWAS. These studies comprised a total of 16,062 cases and 46,157 controls. Imputation to the 1,000 Genomes Project Phase 1 v3 ALL reference panel was performed by study, and summary statistics from each study were combined using fixed-effect meta analysis. </p>
Project description:Single nucleotide variants (SNVs) in regulatory DNA are linked to inherited cancer risk. Massively parallel reporter assays (MPRA) of 5,031 SNVs linked to 14 neoplasms comprising >90% of human malignancies were performed in pertinent diploid cell types then integrated with matching chromatin accessibility, looping, and eQTL data to identify 411 regulatory SNVs and their putative target eGenes. The latter highlighted specific protein networks in lifetime cancer risk, including mitochondrial translation, proliferation, signaling, adhesion, and immunity. This cancer SNV compendium underscores the importance of studying pathogenic variants in disease-relevant cells and implicates specific dysregulated gene networks in cancer predisposition. It also indicates that inherited cancer risk can impact the same gene via orthogonal genetic mechanisms of dysregulated expression as well as protein coding sequence alteration and demonstrates that a subset of germline-encoded risk genes also enable tumor growth of established cancers.