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带来了技术的快速进步以及大量的基因组数据。这一巨大的成就引发了令人难以置信的国际社会努力对人类遗传变异进行编目，并将这种变异与人类表型联系起来，最终获得更个性化的医学回报。虽然最新技术提供了进行全基因组关联研究（GWAS）以鉴定给定人类疾病的个体易感性基因座的前所未有的能力，但GWAS在筛选赋予人类易感性的多个基因-基因相互作用方面的能力不足（由于多假设检验问题）。为了克服这一限制，在本申请中，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，以确定人类乳腺癌易感性的基因-基因和途径-途径相互作用。具体而言，我们假设细胞对DNA损伤的敏感性可以用作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以产生人类乳腺癌易感性。在目标1中，我们将利用酵母全基因组筛选的现有和新出现的数据（R 01 CA 129604- 01 A1基于表型的方法，以发现乳腺癌风险的基因相互作用; PI：Paulovich），以确定可能导致人类乳腺癌易感性的基因-基因相互作用。将使用复杂的数据分析工具来鉴定相互作用的酵母基因的推定的人类直系同源物。然后，将使用整合基因组学分析，基于来自人类乳腺癌的基因组学数据集和网络，进一步优先考虑具有高概率促成乳腺癌易感性的基因对。虽然可以改变模式生物的基因，并操纵其环境，以检验关于特定基因变异对风险的影响的预测，但单一或多个基因敲除或突变方法作为检验预测的唯一手段存在局限性;因此，在目的2中，我们将测试合成或协同基因在人乳腺上皮细胞（HMEC）中的功能意义，在酵母中发现的基因相互作用，并在Aim 1中优先考虑。在目标3中，将使用现有和新出现的人类乳腺癌GWAS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。使用对DNA损伤的敏感性作为中间表型的前提是合理的，因为有大量证据表明该途径中的缺陷会导致乳腺癌的生殖系易感性。这项工作将补充和扩展目前的GWAS研究，因为风险的显着增加可能只有在组合考虑变异等位基因时才是明显的（上位性），因此这些风险等位基因将经常在GWA研究中被遗漏。 公共卫生相关性：该提案与公共卫生相关，原因有二。首先，它将测试一种新的范式，用于发现人类乳腺癌易感性的基因-基因和途径-途径相互作用。这是重要的，因为我们目前无法检测基因-基因相互作用是鉴定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。虽然早期发现降低了该病的死亡率，但对广大人口进行筛查的费用是一个巨大的公共卫生负担;最近的一项分析集中在与乳腺癌筛查，随访，和治疗发现，从1990年到2000年，美国的筛查模式导致了170万夸脱的额外成本，625亿与没有筛查相比。确定个体的易感性将有助于根据个体的风险状况制定具有成本效益的癌症筛查计划，确定最能从预防策略中受益的女性，并阐明潜在的疾病机制，可能导致靶向治疗或化学预防剂。最终，这些信息可能有助于在人群中设计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.