Abstract
Pancreatic cancer is the fourth-leading cause of cancer-related death in the United States. Among individuals who develop pancreatic adenocarcinoma, only 5% will survive 5 years after diagnosis and most patients live for <12 months. Novel strategies for prevention and risk stratification are greatly needed.
Glucose intolerance has emerged as an important predisposing factor for pancreatic adenocarcinoma. Prospective studies have demonstrated an increased risk of pancreatic cancer with increasing body-mass index, a determinant of peripheral insulin resistance and a central risk factor for type II diabetes. Although controversy remains regarding causation versus consequence, diabetes has been associated with pancreatic cancer risk and fasting serum glucose and post-load plasma glucose have been linked with the subsequent risk of pancreatic cancer. Furthermore, studies have linked levels of circulating hormones to pancreatic cancer risk, including insulin, C-peptide and adiponectin. Studies are needed to better understand mechanisms underlying the higher risk of pancreatic cancer among individuals with impaired glucose processing
Metabolism denotes the conversion of food products into energy and the building blocks for cellular functioning. The high-throughput identification and quantification of small molecule metabolites produced by metabolism, including lipids, fatty acids, sugars, nucleotides, and amino acids, has been termed metabolomics. Metabolomics is increasingly being used to evaluate alterations in metabolism and their relationship to human disease. In epidemiologic studies, this technology has particular potential to advance our understanding of disease, as participants have provided information on a variety of exposures and diseases in addition to biologic samples.
Given the strong link between glucose intolerance and pancreatic cancer risk, we pursued a rigorous pilot program of a liquid chromatography/mass spectrometry (LC-MS) metabolomics platform for application to prospectively collected, archived plasma specimens in a nested case-control study of pancreatic adenocarcinoma. This pilot program highlighted important issues relevant to data analysis, including accounting for sample preservative type, sample processing delays, and fasting times. Furthermore, it helped define reproducibility of metabolites using actual archived participant samples. The application of metabolomics to large epidemiologic studies holds promise for defining new biomarkers of disease, including for pancreatic adenocarcinoma.
Citation Format: Brian Matthew Wolpin. Using metabolomics in epidemiologic studies: An example for pancreatic cancer. [abstract]. In: Proceedings of the AACR Special Conference on Post-GWAS Horizons in Molecular Epidemiology: Digging Deeper into the Environment; 2012 Nov 11-14; Hollywood, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2012;21(11 Suppl):Abstract nr IA23.
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