Comprehensive identification of germline-somatic interactions

癌症仍然是世界范围内发病率和死亡率的重要来源。下一代技术的进展 测序技术已经允许对存在于肿瘤中的基因变异进行广泛的剖析，并揭示了 令人望而生畏的肿瘤间异质性水平。肿瘤基因组数据集已被广泛挖掘以揭示 生殖系风险变异和表征导致肿瘤的躯体改变的异质性模式 进步。然而，遗传背景和体细胞之间的相互作用却很少受到关注。 变化，这可能是异质性的一个主要驱动因素。新证据表明，生殖系-体细胞 相互作用很普遍，我们的初步数据支持，一些这样的相互作用直接影响 个体疾病风险和对治疗反应的潜力。这项提议将开发计算策略 鉴定种系-体细胞的相互作用，并在分子和临床的背景下描述它们的特征 表型，使人们对它们在肿瘤间异质性中的作用有了新的理解。 由于可获得的数据量有限，种系-体细胞相互作用的研究一直具有挑战性。至 为了应对这一挑战，我们从公共来源汇编了肿瘤基因组数据，以扩大我们的样本量 近45,000个肿瘤全外显子组和全基因组序列。我们的分析将集中在三大力量上 它塑造了肿瘤基因组：(I)产生体细胞突变的突变过程，(Ii)分子 确定可有效驱动癌症的基因的致癌途径的组织，以及(Iii) 免疫系统在整个肿瘤发展过程中起着选择性作用。我们将重点研究假设检验 根据严格的标准选择可能相互作用的生殖系变异和体细胞改变的基因 建立了肿瘤生物学。为了确定和描述生殖系-体细胞的相互作用，我们将： 1)阐明影响人类癌症体细胞突变格局的生殖系变异 2)揭示修改标志致癌途径的体细胞激活的生殖系变体 3)确定路径特定的变异负荷在癌症易感性、总体存活率和反应中的作用 到免疫治疗 我们的合作调查团队在突变过程分析方面拥有强大的互补专业知识， 遗传变异对分子通路和免疫、癌症生物学、统计方法和 生物信息学软件传播。将仔细考虑包括电力在内的统计因素， 控制错误发现率，并在独立数据集中进行验证。这项建议将产生A)小说 专为检测和注释生殖系-体细胞相互作用而设计的生物信息学工具，B)新 了解生殖系变异对肿瘤进展的贡献，以及C)一套经过验证的种系-- 躯体相互作用影响癌症风险、肿瘤进化和免疫治疗反应。

Cancer remains a significant source of morbidity and mortality worldwide. Advances in next generation sequencing technologies have allowed extensive profiling of the genetic variants present in tumors and revealed daunting levels of inter-tumoral heterogeneity. Tumor genomic datasets have been extensively mined to reveal germline risk variants and to characterize heterogeneous patterns of somatic alteration that drive tumor progression. However, little attention has been given to interactions between genetic background and somatic changes, which could represent a major driver of heterogeneity. New evidence suggests that germline-somatic interactions are prevalent and our preliminary data support that some such interactions directly influence individual disease risk and potential to respond to therapies. This proposal will develop computational strategies to identify germline-somatic interactions and to characterize them in the context of molecular and clinical phenotypes, enabling new understanding of their role in inter-tumoral heterogeneity. Germline-somatic interactions have been challenging to study due to the limited amount of available data. To address this challenge, we have compiled tumor genomic data from public sources to boost our sample size to almost 45,000 tumor whole-exome and whole-genome sequences. Our analysis will focus on three major forces that shape the tumor genome: (i) the mutational processes that generate somatic mutations, (ii) the molecular organization of oncogenic pathways which determines the genes that can effectively drive cancer, and (iii) the immune system which acts as a selective force throughout tumor development. We will focus hypothesis testing with strict criteria for selecting germline variants and somatically altered genes likely to interact based on established tumor biology. To identify and characterize germline-somatic interactions we will: 1) Elucidate germline variants affecting the somatic mutational landscapes of human cancers 2) Reveal germline variants that modify somatic activation of hallmark oncogenic pathways 3) Establish the role of pathway-specific variant burden in cancer predisposition, overall survival, and response to immunotherapy Our team of co-investigators includes strong complementary expertise in analysis of mutational processes, genetic variation effects on molecular pathways and immunity, cancer biology, statistical methods and bioinformatic software dissemination. Careful attention will be given to statistical considerations including power, controlling false discovery rates, and validation in independent datasets. This proposal will produce A) novel bioinformatics tools designed specifically to detect and annotate germline-somatic interactions, B) new understanding of the contribution of germline variation to tumor progression, and C) a set of validated germline- somatic interactions affecting cancer risk, tumor evolution and immunotherapy response.