Genome-Wide molecular epidemiology of treatment outcome and cancer risk

治疗结果和癌症风险的全基因组分子流行病学

• 批准号: 7937079
• 负责人: FEDERICO INNOCENTI
• 金额: $ 2.17万
• 依托单位: UNIVERSITY OF CHICAGO
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-23 至 2010-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7937079
• 关键词: Address; Angiogenesis Inhibitors; Bioinformatics; Biological; Biological Process; Cancer Patient; Candidate Disease Gene; Carcinogens; Chemotherapy-Oncologic Procedure; Clinical; Clinical Pharmacology; Clinical Trials; Computer Simulation; DNA Resequencing; Data; Genes; Genetic; Genetic Variation; Genomics; Genotype; Goals; Human; Human Genetics; In Vitro; Individual; Investigation; K-Series Research Career Programs; Knowledge; Laboratories; Laboratory Study; Malignant Neoplasms; Mentors; Molecular; Molecular Epidemiology; Molecular Genetics; Outcome; Pathway interactions; Pattern; Pharmaceutical Preparations; Phase III Clinical Trials; Population; Predisposition; Prevalence; Randomized; Research; Research Training; Resources; Role; Series; Single Nucleotide Polymorphism; Surveys; Techniques; Technology; Testing; Toxic effect; Training; Treatment outcome; Variant; Work; angiogenesis; antiangiogenesis therapy; base; cancer risk; chemotherapy; clinical epidemiology; design; experience; genetic epidemiology; genome wide association study; genome-wide; novel; programs; risk benefit ratio; therapy design; therapy outcome

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.

描述（由申请人提供）：此指导性职业发展奖申请的目标是将我在实验室和临床药理学、人类遗传学和临床研究方面的多样化培训经验整合到“治疗结果和癌症风险的全基因组分子流行病学”的重点研究项目中。该计划的目的是发现和测试新型种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率以及 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、遗传学、流行病学和生物信息学技术相结合的研究，我将需要将这些技术应用于基因组群体数据。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来发现新的候选基因作为化疗结果的标记。同样的方法也将用于通过受益于来自未患有癌症的对照个体的公开可用的 GW 信息资源来识别癌症易感性的新候选者。 GW 数据生成的信息的丰富将来自于 GWAS 中显示显着关联的基因组区域的额外基因分型和/或重新测序。 GWAS 中的显着单核苷酸多态性 (SNP) 很可能不具有已确定的分子功能，并且将使用多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信息多效性影响的理解。这项工作将为使用精心挑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效益比并降低人群中癌症患病率的干预措施提供信息。