Statistical and Computational Methods for Pharmacogenetic Epidemiology of Cancer

 描述(申请人提供)：基因组技术的最新进展，加上对环境致癌物质的越来越多的研究，导致在识别各种癌症和癌症相关特征的遗传和环境因素方面取得了革命性的进展。这些调查还表明，特定基因变异的携带者比非携带者更有可能从某些预防和治疗干预中受益。这些发现开启了药物遗传学研究的新纪元，以确定影响人类治疗反应的基因变异，催化向开发有针对性的抗癌治疗和预防性干预策略的转变。统计方法在确定影响治疗和预防性干预反应的遗传因素以及设计和分析有针对性的治疗和干预研究方面发挥着关键作用。目前，为了满足癌症药物遗传流行病学领域的科学需要，新的统计方法的开发激增。这些方法包括(但不限于)：(I)用于评估基因治疗、基因-环境和基因-基因相互作用的分析方法；(Ii)用于对癌症风险进行建模以了解根据遗传因素的治疗效益变化的能量转换方法；以及(Iii)用于识别与癌症病因、进展和抗癌治疗反应相关的获得性和遗传性遗传变异的数据挖掘方法。为有效设计药物遗传学研究，还正在开发新的分层、两阶段和适应性研究设计。因此，为期两天的“癌症药物遗传流行病学的统计和计算方法”研讨会将是重要和及时的。本次研讨会的具体目的是：(1)促进在统计遗传学、数据挖掘方法、药理学、遗传和临床流行病学以及肿瘤学领域的领先和新兴专家之间的讨论和合作，以确定与病因和进展相关的临床可操作的遗传风险因素。 (2)促进建立一个交流想法和专门知识的论坛，以评估各种研究设计产生的数据，包括队列研究、病例对照研究、生物标记物选择和生物标记物浓缩试验；(3)鼓励开发用户友好的软件包，以便实施这些方法；(4)促进利用公开获得的数据来评估这些统计和计算方法；以及(5)在《遗传流行病学》杂志上发表本期讲习班的精选论文。这是一个强调多样性的公开研讨会，将作出广泛努力，将妇女、代表性不足的少数民族和初级研究人员纳入该计划。

 DESCRIPTION (provided by applicant): The recent advances in genomic technology, coupled with increasing investigation of environmental carcinogens, have led to revolutionary progress in identifying genetic and environmental factors for various cancers and cancer-related traits. These investigations have also demonstrated that carriers of specific genetic variants are more likely to benefit from certain preventive and therapeutic interventions than non- carriers. Such findings have ushered in a new era of pharmacogenetics investigations to identify genetic variants that inform therapeutic response in humans, catalyzing a shift towards developing targeted anticancer therapies and preventive intervention strategies. Statistical methods play a pivotal role in identifying genetic factors that inform response to treatment and preventive intervention, and in the design and analysis of studies of targeted treatments and interventions. There is now a surge in the development of novel statistical methods for addressing the scientific needs of the field of pharmacogenetic epidemiology of cancer. These include (but are not limited to): (i) analytic methods for evaluating gene-treatment, gene- environment, and gene-gene interactions; (ii) power transformation methods for modeling cancer risk to understand variation in treatment benefits according to genetic factors; and (iii) data mining methods to identify acquired and inherited genetic variants associated with cancer etiology, progression, and response to anticancer treatment. Novel stratified, two-stage, and adaptive study designs are also being developed for efficient design of pharmacogenetics studies. Therefore, a two-day symposium on "Statistical and Computational Methods for Pharmacogenetic Epidemiology of Cancer" would be important and timely. The Specific Aims of this symposium are: (1) to promote discussions and collaborations among leading and emerging experts in the areas of statistical genetics, data mining methods, pharmacology, genetic and clinical epidemiology, and oncology to identify clinically actionable genetic risk factors associated with the etiology and progression of cancer, and response to treatment and to identify individuals (defined based on their genetic characteristics) who are likely to respond to specific treatment and intervention strategies; (2) t promote a forum for the interchange of ideas and expertise for evaluating data arising from a variety of study designs including cohort studies, case-control studies, and biomarker-selected and biomarker- enriched trials; (3) to encourage the development of user-friendly software packages for implementing these methods; (4) to promote the use of publicly available data to assess these statistical and computational methods; and (5) to publish select papers from this workshop in the journal Genetic Epidemiology. This is an open symposium with an emphasis on diversity, where extensive efforts will be made to include women, under-represented minority, and junior researchers in the program.