Genome-Wide molecular epidemiology of treatment outcome and cancer risk

描述(由申请人提供)：这项职业发展指导奖申请的目标是将我在实验室和临床药理学、人类遗传学和临床调查方面的不同培训经验整合到一个重点研究计划中，该研究计划的主题是“基因组范围内治疗结果和癌症风险的分子流行病学”。该计划的目的将是发现和测试新的生殖系遗传变异的生物学功能，这些变异可能作为1)接受化疗的癌症患者的严重毒性和生存以及2)癌症易感性的标志。这些标记将通过全基因组(GW)关联研究(GWAS)来识别，我之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。这一计划将通过一系列临床、流行病学和实验室研究来构建。我建议使用无偏见的基因组方法来发现新的候选基因作为化疗结果的标志。同样的方法也将被应用于通过受益于来自非癌症对照个体的公开可用的GW信息资源来确定癌症易感性的新候选对象。GW数据产生的信息的丰富将来自对在GWAs中显示显著关联的基因组区域进行额外的基因分型和/或重新测序。GWAs中显著的单核苷酸多态(SNPs)很可能不具有既定的分子功能，将使用几种策略来支持所观察到的临床相关性。 拟议的研究计划和随后的研究将大大增加对人类可遗传遗传信息的多效性效应的理解。这项工作将为使用高度精选的信息标记设计治疗结果和癌症风险的受控复制研究提供一个知识框架。这些应用可以为旨在确定癌症化疗的风险-收益比并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.