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Leveraging GxE interaction to understand pancreatic cancer and altered metabolism

Peter Kraft

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National Institutes of Health (NIH)
Pancreatic cancer is an aggressive disease: only 5% of patients survive five years after diagnosis. As a consequence, despite being relatively rare, itis 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 clinicalrisk 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.

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