Quantifying and Characterizing the shared genetic contribution to common cancers

量化和表征对常见癌症的共同遗传贡献

基本信息

批准号：
9270181
负责人：
Sara Lindstroem
金额：
$ 66.44万
依托单位：
UNIVERSITY OF WASHINGTON
依托单位国家：
美国
项目类别：
财政年份：
2015
资助国家：
美国
起止时间：
2015-08-01 至 2018-07-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9270181
关键词：
8q24 Accounting Affect African American Applications Grants Biological Breast Cancer Biology Cancer Etiology Cancer Prognosis Categories Cessation of life Chromosome Mapping Colorectal Cancer Data Data Set Databases Development Diagnosis Disease Estrogen Receptors Ethnic Origin Etiology European Family Future Genetic Genetic Predisposition to Disease Genetic study Genotype Goals Heritability Incidence Individual Inherited Malignant Neoplasms Malignant neoplasm of lung Malignant neoplasm of ovary Malignant neoplasm of prostate Maps Methods Modeling Molecular Parents Pathway interactions Penetrance Phenotype Population Predisposition Probability Property Resources Serous Single Nucleotide Polymorphism Spectrum Analysis Statistical Methods Susceptibility Gene Time Tissues Tumor Subtype Variant cancer diagnosis cancer genome cancer health disparity cancer initiation cancer risk cancer subtypes cancer type design ethnic disparity follow-up genetic variant genome wide association study improved insight malignant breast neoplasm mortality novel offspring population based public health relevance tumor

项目摘要

DESCRIPTION (provided by applicant): Together, breast, colorectal, lung, ovarian and prostate cancer account for more than 850,000 cancer diagnoses and 290,000 deaths annually in the US. Family- and population-based studies have shown that these cancers have a heritable component, and multi-cancer susceptibility regions identified by genome-wide association studies (GWAS), suggests that this heritability is partly shared across cancers. Furthermore, GWAS have also revealed distinct susceptibility regions for specific tumor subtypes (e.g. estrogen receptor (ER)+ vs. ER- breast cancer), offering some insights to ethnic disparities in cancer incidence by tumor aggressiveness and mortality. This proposal will capitalize on the OncoArray data to study the genetic contribution to cancer risk and prognosis. The GAME-ON consortium recently launched the OncoArray initiative with the goal of identifying novel susceptibility loci for breast, colorectal, lung, ovarian and prostate cancer. In total, GWAS data on more than 350,000 individuals across these five GAME-ON cancers is being generated, creating unprecedented opportunities to jointly study multiple cancers in a homogenously derived dataset. We will quantify and functionally characterize the shared genetic contribution to GAME-ON cancers and use this information to fine-map multi-cancer GWAS regions. To accomplish our goals, we will leverage publically available databases (e.g. ENCODE) to functionally partition the shared genetic component, allowing us to assess the relative importance of functional categories (e.g. exonic, regulatory) for cancer development. For breast and prostate cancer, two cancers with ethnic disparities in cancer incidence and mortality, we will assess the genetic correlation between populations of European and African-American ancestry. Functionally characterizing the shared heritability between ethnicities will highlight biological mechanisms and provide insights into differences in disease aggressiveness between ethnicities. We will fine-map multi-cancer GWAS regions and estimate variant-specific posterior probabilities of causality. Our fine-mapping approach is unique in that it jointly models functiona annotations and the genotype-phenotype association while allowing for multiple causal SNPs within a region, greatly improving statistical power if more than one causal variant exist. Finally we will develop statistical methods to quantify the genetic contribution to variation in survival times and apply our methods on a prostate cancer dataset of 60,000 cases (9,000 deaths). Multi-generational studies show that a cancer prognosis is often "inherited" from parent to offspring suggesting a genetic component but lack of adequate statistical methods and empirical datasets have precluded formal assessment of such. This project capitalizes on the large-scale OncoArray initiative, giving us adequate statistical power to obtain precise heritability estimates Our results will elucidate cancer biology, identify novel connections between cancers and cancer subtypes and have long-standing impact on focus and design of futures studies aiming at understanding the mechanisms causing cancer.

描述（由申请人提供）：在美国，每年有超过 850,000 例癌症诊断为乳腺癌、结直肠癌、肺癌、卵巢癌和前列腺癌，导致 290,000 例死亡。基于家庭和人群的研究表明，这些癌症具有遗传性。，以及通过全基因组关联研究（GWAS）确定的多种癌症易感性区域，表明这种遗传性在多种癌症中部分共享。此外， GWAS 还揭示了特定肿瘤亚型（例如雌激素受体 (ER)+ 与 ER- 乳腺癌）的不同易感区域，通过肿瘤侵袭性和死亡率为癌症发病率的种族差异提供了一些见解。 GAME-ON 联盟最近发起了 OncoArray 计划，旨在研究遗传因素对癌症风险和预后的影响，旨在确定乳腺癌、结直肠癌、肺癌、癌症和癌症的新易感位点。卵巢癌和前列腺癌的 GWAS 总计。关于这五种 GAME-ON 癌症的超过 350,000 人的数据正在生成，为在同源数据集中联合研究多种癌症创造了前所未有的机会，我们将量化和功能性地描述对 GAME-ON 癌症的共同遗传贡献，并使用这些信息。精细绘制多癌症 GWAS 区域图谱为了实现我们的目标，我们将利用公开可用的数据库（例如 ENCODE）对共享的遗传成分进行功能分区，从而使我们能够评估相关的遗传成分。对于乳腺癌和前列腺癌这两种在癌症发病率和死亡率方面存在种族差异的癌症，我们将评估欧洲和非洲裔美国人血统之间的遗传相关性。种族之间的共同遗传性将突出生物学机制，并提供对种族之间疾病侵袭性差异的见解。我们将精细绘制多癌症 GWAS 区域，并估计变异特异性的因果关系后验概率。其独特之处在于它联合模拟功能注释和基因型-表型关联，同时允许一个区域内存在多个因果 SNP，如果存在多个因果变异，则大大提高统计能力。最后，我们将开发统计方法来量化遗传对变异的贡献。生存时间并将我们的方法应用于 60,000 例前列腺癌数据集（9,000 例死亡），多代研究表明癌症预后通常从父母“遗传”到后代，这表明存在遗传成分，但缺乏遗传成分。适当的统计方法和经验数据集排除了对此进行正式评估的机会。该项目利用了大规模的 OncoArray 计划，为我们提供了足够的统计能力来获得精确的遗传力估计。我们的结果将阐明癌症生物学，确定癌症与癌症亚型之间的新联系，以及对旨在了解癌症机制的未来研究的焦点和设计具有长期影响。