Genome-Wide molecular epidemiology of treatment outcome and cancer risk

描述（由申请人提供）：这个指导职业发展奖申请的目标是巩固我在实验室和临床药理学，人类遗传学和临床调查的多样化培训经验，并将其纳入“治疗结果和癌症风险的全基因组分子流行病学”的重点研究计划。该计划的目的是发现和测试新的生殖系遗传变异的生物学功能，这些遗传变异可能作为1）接受化疗的癌症患者的严重毒性和生存率以及2）癌症易感性的标志物。这些标记物将通过全基因组（GW）关联研究（GWAS）进行鉴定，我以前的培训和研究经验与GW调查无关。为了进行将GW数据与分子、遗传、流行病学和生物信息学技术相结合的研究，我将被要求将这些技术应用于基因组人口数据。该计划将通过一系列临床，流行病学和实验室研究来构建。我建议使用公正的基因组方法发现新的候选基因作为化疗结果的标志物。同样的方法也将被应用于确定新的候选人的癌症易感性，受益于公众可用的资源GW信息，从控制个人没有癌症。从GW数据生成的信息的丰富将来自GWAS中显示显著关联的基因组区域的额外基因分型和/或重测序。GWAS中显著的单核苷酸多态性（SNP）很可能不具有已确定的分子功能，并且将使用几种策略来支持观察到的临床关联。 拟议的研究计划和后续调查将大大增加对人类遗传遗传信息多效性效应的了解。这项工作将提供一个知识框架，设计控制复制研究的治疗结果和癌症风险，使用高度选择的信息标记。这些应用可以为旨在建立癌症化疗的风险-效益比和降低人群中癌症患病率的干预措施提供信息。

DESCRIPTION (provided by applicant): The goal of this mentored career development award application is to consolidate my diverse training experiences in laboratory and clinical pharmacology, human genetics, and clinical investigation into a focused research program in "Genome-wide molecular epidemiology of treatment outcome and cancer risk". The purpose of this program will be to discover and test the biological function of novel germline genetic variation that might serve as markers of 1) severe toxicity and survival in cancer patients treated with chemotherapy, and 2) cancer susceptibility. These markers will be identified through genome-wide (GW) association studies (GWAS), and my previous training and research experience do not pertain to GW investigations. To undertake research that combines GW data with molecular, genetic, epidemiology and bioinformatics techniques, I will be required to apply these technologies to genomic population data. This program will be constructed through a series of clinical, epidemiology, and laboratory studies. I propose to use unbiased genomic approaches for the discovery of novel candidate genes as markers of outcome of chemotherapy. The same approaches will be also applied to identify novel candidates of cancer susceptibility by benefiting from publicly available resources of GW information from control individuals without cancer. Enrichment of the information generated from the GW data will be derived from additional genotyping and/or resequencing of genomic regions that showed significant associations in the GWAS. It is very likely that the significant single nucleotide polymorphisms (SNPs) in the GWAS will not have an established molecular function, and several strategies will be used to support the observed clinical associations. The proposed research plan and subsequent investigations will substantially increase the understanding of the pleiotropic effects of heritable genetic information in humans. This work will provide a knowledge framework for designing controlled replication studies of treatment outcome and cancer risk using highly selected informative markers. These applications could inform interventions designed to establish the risk-benefit ratio of cancer chemotherapy and to reduce the prevalence of cancer in the population.