Cross-species network approach to predict epistatic cancer susceptibility genes

描述(申请人提供)：人类基因组计划的完成导致了技术的快速进步以及大量的基因组数据。这一巨大成就引发了国际社会令人难以置信的努力，对人类基因变异进行分类，并将这种变异与人类表型联系起来，最终获得更个性化的药物。虽然最新的技术提供了前所未有的能力来进行全基因组关联研究(GWAS)来确定特定人类疾病的个体易感基因，但GWAS在筛选与人类易感性相关的多个基因-基因相互作用方面能力不足(由于多个假设测试问题)。为了克服这一局限，在这一应用中，我们提出了一种新的跨物种(酵母到人类)比较系统遗传学策略来确定导致人类乳腺癌易感性的基因-基因和途径-途径相互作用。具体地说，我们假设细胞对DNA损伤的敏感性可以作为乳腺癌易感性的中间表型，并且与DNA损伤反应途径中的缺陷协同作用的基因和途径也将协同作用产生人类乳腺癌的易感性。在目标1中，我们将利用我们的酵母全基因组筛查的现有和新兴数据(R01 CA 129604-01A1基于表型的方法来寻找乳腺癌风险潜在的基因交互作用；PI：Paulovich)，以确定可能导致人类乳腺癌易感性的基因-基因交互作用。将使用复杂的数据分析工具识别相互作用的酵母基因的假定的人类同源基因。然后，将使用综合基因组学分析，根据来自人类乳腺癌的基因组数据集和网络，进一步优先考虑导致乳腺癌易感性的高概率基因对。尽管模式生物可以被基因改变，它们的环境可以被操纵来测试特定基因变异对风险的贡献的预测，但作为测试预测的唯一手段，单基因或多基因敲除或突变方法存在局限性；因此，在目标2中，我们将测试在酵母中发现的合成或协同基因-基因相互作用在人类乳腺上皮细胞(HMEC)中的功能意义，并在目标1中优先考虑。在目标3中，将使用现有的和新出现的关于人类乳腺癌的GWA数据集，测试在HMEC中功能验证的基因-基因相互作用与乳腺癌易感性的关联。考虑到大量证据表明这一途径的缺陷会导致乳腺癌的胚系易感性，使用对DNA损伤的敏感性作为中间表型的前提是合理的。这项工作将补充和扩展目前的GWA研究，因为只有当变异等位基因被结合考虑(上位性)时，风险的显著增加才可能明显，因此这些风险等位基因在GWA研究中经常被遗漏。 公共卫生相关性：这项提案与公共卫生相关，原因有两个。首先，它将测试一种新的范式，以发现人类乳腺癌易感性的基因-基因和途径-途径相互作用。这一点意义重大，因为我们目前无法检测到基因间的相互作用，这是识别易感基因座的主要障碍。其次，了解乳腺癌风险具有重要的公共卫生意义。尽管早期发现降低了乳腺癌的死亡率，但筛查普通人群的成本是一个巨大的公共卫生负担；最近一项专注于与乳腺癌筛查、随访和治疗相关的直接医疗成本的分析发现，从1990年到2000年，美国的筛查模式导致QALY增加了170万，与不筛查相比，额外成本为625亿美元。确定个人的易感性将有助于根据个人的风险状况量身定做具有成本效益的癌症筛查计划，确定哪些女性将从预防战略中受益最大，并阐明潜在的疾病机制，可能导致有针对性的治疗或化学预防药物。最终，这些信息可能有助于在人类群体中进行有针对性的流行病学研究。

DESCRIPTION (provided by applicant): Completion of the human genome project has resulted in rapid advances in technology as well as a deluge of genomic data. This tremendous accomplishment has sparked an incredible international community effort to catalog human genetic variation and to relate this variation to human phenotypes with the ultimate payoff of more personalized medicine. While the latest technologies provide unprecedented ability to conduct genome- wide association studies (GWAS) to identify individual susceptibility loci for a given human disease, GWAS are underpowered (due to the multiple hypotheses testing problem) to screen for the multiple gene-gene interactions conferring susceptibility in humans. To overcome this limitation, in this application, we propose a novel, cross-species (yeast-to-human) comparative systems genetics strategy to identify gene-gene and pathway-pathway interactions underlying human breast cancer susceptibility. Specifically, we hypothesize that cellular sensitivity to DNA damage can be used as an intermediate phenotype for breast cancer susceptibility, and that genes and pathways that synergize with defects in the DNA damage response pathway will also synergize to produce breast cancer susceptibility in humans. In Aim 1, we will leverage existing and emerging data from our genome-wide screens in yeast (R01 CA 129604-01A1 Phenotype-based approach to find gene interactions underlying breast cancer risk; PI: Paulovich) to identify gene-gene interactions likely to underlie susceptibility for breast cancer in humans. Putative human orthologs of interacting yeast genes will be identified using sophisticated data analysis tools. An integrative genomics analysis will then be used to further prioritize gene pairs with high probability of contributing to breast cancer susceptibility based on genomics datasets and networks derived from human breast cancers. Although model organisms can be genetically altered and their environments manipulated to test predictions about contributions of specific gene variants to risk, there are limitations of single or multiple gene knockout or mutant approaches as the sole means to test predictions; hence in Aim 2 we will test the functional significance in human mammary epithelial cells (HMEC) of synthetic or synergistic gene-gene interactions discovered in yeast and prioritized in Aim 1. In Aim 3, gene- gene interactions functionally verified in HMEC will be tested for association with breast cancer susceptibility using existing and emerging GWAS datasets on human breast cancer. The premise of using sensitivity to DNA damage as an intermediate phenotype is reasonable given the abundance of evidence that defects in this pathway cause germline predisposition to breast cancer. This work will complement and extend the current GWAS studies since significant increases in risk may only be apparent when variant alleles are considered in combination (epistasis), and hence these risk alleles will be frequently missed in GWA studies. PUBLIC HEALTH RELEVANCE: This proposal is relevant to public health for two reasons. First, it will test a novel paradigm for discovering gene-gene and pathway-pathway interactions underlying breast cancer susceptibility in humans. This is significant because our current inability to detect gene-gene interactions is a major impediment to the identification of susceptibility loci. Second, understanding breast cancer risk has important public health implications. Although early detection has reduced mortality from the disease, the cost of screening the population at large is a tremendous public health burden; a recent analysis focusing on the direct medical costs associated with breast cancer screening, follow-up, and treatment found that U.S. screening patterns from 1990 to 2000 resulted in a gain of 1.7 million QALYs for an additional cost of $62.5 billion compared with no screening. Determination of an individual's susceptibility would facilitate cost-effective cancer screening programs tailored to an individual's risk profile, identify women who will most benefit from prevention strategies, and elucidate underlying disease mechanisms, potentially leading to targeted therapeutics or chemoprevention agents. Ultimately, this information may aid the design of targeted epidemiology studies in human populations.