Leveraging GxE interaction to understand pancreatic cancer and altered metabolism

描述（由申请人提供）：胰腺癌是一种侵袭性疾病：只有5%的患者在诊断后存活五年。因此，尽管相对罕见， 是美国癌症死亡的第四大原因。超过80%的胰腺癌患者在诊断时患有不治之症，部分原因是对控制早期疾病进展的因素的了解有限。已知的风险等位基因解释了胰腺癌家族聚集的一小部分。研究与临床 风险因素、遗传学和包括代谢组学在内的新兴生物标志物可以识别新的风险因素，揭示疾病机制，并识别可能受益于强化筛查的高风险个体。我们最近进行了大规模的研究，遗传，代谢组学和临床危险因素与胰腺癌。我们建议使用我们为这些先前研究开发的独特数据来鉴定与胰腺癌风险相关的新遗传标记。我们提出了以下具体目标：（1）对与胰腺癌相关的SNP进行候选和全基因组关联扫描，利用与已知风险因素单独和汇总的潜在相互作用;（2）对与83种循环代谢物相关的SNP进行全基因组关联扫描，利用与已知风险因素单独和汇总的潜在相互作用;以及（3）进行分析以评估遗传和环境风险因素的影响是否通过代谢谱的改变来介导。我们已经组建了一个多学科团队，在胰腺癌流行病学和治疗，统计遗传学和基因组学方面具有专业知识。除了我们以前的GWAS和胰腺癌代谢组学分析研究的经验外，团队成员在开发和应用统计方法分析基因-环境相互作用方面具有丰富的经验。该项目将利用现有资源，扩大我们对胰腺癌遗传基础和代谢改变在癌症发展中的作用的认识。这项研究的发现将有助于开发风险和亚临床发展的标志物，这可以为筛查和早期检测提供急需的工具，并将有助于确定潜在治疗的目标。

DESCRIPTION (provided by applicant): Pancreatic cancer is an aggressive disease: only 5% of patients survive five years after diagnosis. As a consequence, despite being relatively rare, it is the fourth leading cause of cancer death in the United States. Over 80% of patients with pancreatic adenocarcinoma have incurable disease at the time of diagnosis, due in part to a limited understanding of the factors that govern early disease progression. Known risk alleles explain a tiny fraction of the familial aggregation of pancreatic cancer. Research linking clinical risk factors, genetics, and emerging biomarkers including metabolomics can identify new risk factors, shed light on disease mechanism, and identify individuals at high-risk who might benefit from intensive screening. We recently conducted large-scale studies of genetic, metabolomics, and clinical risk factors associated with pancreatic cancer. We propose to use the unique data we developed for these previous studies to identify novel genetic markers associated with pancreatic cancer risk. We propose the following specific aims: (1) Conduct candidate and genome-wide association scans for SNPs associated with pancreatic cancer, leveraging potential interactions with known risk factors individually and in aggregate; (2) conduct genome wide association scans for SNPs associated with 83 circulating metabolites, leveraging potential interactions with known risk factors individually and in aggregate; and (3) conduct analyses to assess whether the effects of genetic and environmental risk factors are mediated through alterations in metabolic profiles. We have assembled a multidisciplinary team with expertise in pancreatic cancer epidemiology and treatment, statistical genetics, and genomics. Alongside our experience with previous GWAS and metabolomic profiling studies of pancreatic cancer, team members have extensive experience in the development and application of statistical methods for the analysis of gene-environment interaction. This project will capitalize on existing resources to expand our knowledge of the genetic basis of pancreatic cancer and the role of altered metabolism in cancer development. Findings from this study will help develop markers of risk and subclinical development, which could provide sorely needed tools for screening and early detection, and they will help identify targets for potential treatments.