Transdisciplinary Research in Cancer of the Lung- Discovery of Novel Variants

肺癌的跨学科研究——新变异的发现

• 批准号: 8550774
• 负责人: Christopher I. Amos
• 金额: $ 111.03万
• 依托单位: DARTMOUTH COLLEGE
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至 2016-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8550774
• 关键词: Adenocarcinoma; Affect; African American; Alleles; Area; Bayesian Analysis; Bioinformatics; Canada; Caucasians; Caucasoid Race; Chinese People; Clinical; Collection; Complex; DNA Resequencing; Data; Data Set; Development; Disease; Environment; Environmental Exposure; Environmental Health; Epidemiology; Family; France; Genes; Genetic; Genetic Predisposition to Disease; Genotype; German population; Haplotypes; Histology; Iceland; Institutes; International Agency for Research on Cancer; Joints; Knowledge; Malignant neoplasm of lung; Maps; Methods; Modeling; Molecular Genetics; National Cancer Institute; Pathway interactions; Patients; Population; Population Heterogeneity; Probability; Recording of previous events; Research; Risk; Sampling; Small Cell Carcinoma; Squamous cell carcinoma; Subgroup; Sum; Techniques; University of Texas M D Anderson Cancer Center; Validation; Variant; anticancer research; base; cancer risk; cationic antimicrobial protein CAP 37; clinically relevant; cofactor; early onset; follow-up; gene discovery; gene interaction; genetic epidemiology; genetic risk factor; genome wide association study; genome-wide; innovation; interest; never smoker; non-genetic; novel; research study; response

Area 1: Discovery and validation of genetic factors influencing lung cancer risk. While several genetic loci have been identified by genome-wide scans, we hypothesize that additional loci influencing risk for lung cancer development can be identified by joint analyses in which data from multiple studies are combined. In addition, combining genotypic data will allow analysis according to demographic and clinical parameters, and permit studies to identify gene-gene and gene-environment factors that specifically increase lung cancer risk. Genetic loci that have been identified by these pooled analyses warrant further follow-up in world-wide populations to evaluate the extent that the same or other SNPs associate with lung cancer risk. Finally, follow-up studies with additfonal fine mapping and resequencing of selected populations, together with functionalanalyses, will help to identify the specific causal factors that influence cancer risk. In area 1 we are using a large and diverse population to identify genetic risk factors for lung cancer. First we will integrate 8 genome wide studies to form a pooled sample of over 13000 lung cancer cases and 25000 controls. We will perform stratified analyses to identify genes that only affect subsets of lung cancer such as early onset, and histology specific effects. We will also seek to discover significant predictors of lung cancer risk using gene-environment and gene-gene interaction analyses. Pathway analyses will also.be performed to assist in gene discovery. We will perform flne mapping and initial replication of these findings by genotyping an additional 6000 cases and 6000 controls of African-American, Chinese and Caucasian ancestry. We will finally validate our findings in an additional collection of 6000 lung cancer cases and 6000 controls. We anticipate that our studies will allow an exhaustive search of genes that have either main effects on lung cancer risk or that increase risk in combination with genetic or environmental cofactors. Our findings will be used for further functional studies in area 2 of the U19 response and epidemiological characterization in area 3 of the U19 response.

区域1：发现和验证影响肺癌风险的遗传因素。虽然通过全基因组扫描鉴定了几个遗传基因座，但我们假设可以通过联合分析来识别更多影响肺癌发育风险的基因座，在这些分析中，从多个研究中结合了数据。此外，结合基因型数据将允许根据人口统计和临床参数进行分析，并允许研究确定特异性增加肺癌风险的基因基因和基因环境因素。这些合并分析已经确定的遗传基因座需要在全球范围内进一步随访，以评估相同或其他SNP与肺癌风险相关的程度。最后，对选定人群的添加精细映射和重新取证的后续研究以及功能性植物会有助于确定影响癌症风险的特定因果因素。在区域1中，我们正在使用大量多样化的人群来识别肺癌的遗传危险因素。首先，我们将整合8个基因组广泛的研究，以形成13000多个肺癌病例和25000例对照的合并样本。我们将进行分层分析，以鉴定仅影响肺癌亚群的基因，例如早期发作和组织学特异性作用。我们还将寻求使用基因环境和基因 - 基因相互作用分析来发现肺癌风险的重要预测因子。途径分析也将进行。我们将通过对非裔美国人，中国和高加索血统的6000例和6000例控制，对这些发现进行FLNE映射和初步复制。我们最终将在6000例肺癌病例和6000个对照组的其他集合中验证我们的发现。我们预计我们的研究将允许详尽地搜索对肺癌风险有主要影响或与遗传或环境辅助因子相结合的风险的基因。我们的发现将用于在U19响应的U19响应和流行病学表征的2区域进行进一步的功能研究。