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Statistical and Computational Methods for Pharmacogenetic Epidemiology of Cancer

癌症药物遗传学流行病学的统计和计算方法

基本信息

批准号：
9053792
负责人：
JAYA M SATAGOPAN
金额：
$ 2万
依托单位：
SLOAN-KETTERING INST CAN RESEARCH
依托单位国家：
美国
项目类别：
财政年份：
2016
资助国家：
美国
起止时间：
2016-07-01 至 2017-06-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9053792
关键词：
Address Area Biological Markers Bupropion Cancer Etiology Cancer-Predisposing Gene Candidate Disease Gene Case-Control Studies Characteristics Chemoprevention Clinical Clinical Research Cohort Studies Collaborations Communities Computing Methodologies Coupled Data Development Educational workshop Environment Environmental Carcinogens Environmental Risk Factor Epidemiologic Studies Epidemiologist Etiology Female Fostering Future Genes Genetic Genome Genomics Gleevec Goals Human Individual Inherited Intervention Investigation Journals Malignant Neoplasms Measures Methods Minority Modeling Molecular Nicotine Dependence Oncologist Paper Pharmaceutical Preparations Pharmacogenetics Pharmacology Play Postdoctoral Fellow Preventive Intervention Proteins Publishing Research Design Research Personnel Risk Role Staging Statistical Methods Techniques Technology The Cancer Genome Atlas Therapeutic Intervention Trastuzumab Tumor Tissue Underrepresented Minority Variant Woman Work anticancer research anticancer treatment base cancer epidemiology cancer risk cancer therapy clinical epidemiology clinically actionable curative treatments data mining database of Genotypes and Phenotypes design disorder subtype gene interaction genetic epidemiology genetic risk factor genetic variant genome wide association study graduate student high risk improved inhibitor/antagonist innovation nicotine replacement novel novel therapeutics oncology programs public health relevance response symposium trait treatment response treatment strategy tumor progression user friendly software

项目摘要

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.