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Biomarkers for the Early Detection of Pancreatic Cancer

Ann M Killary

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National Institutes of Health (NIH)
Biomarkers for the early detection of pancreatic cancer are urgently needed. However, individual molecules with the sensitivity and specificity needed for population-based screening have not been discovered. CA-19-9 has been studied extensively and yet has failed to demonstrate the predictive value necessary for early detection and diagnosis. Although many platforms, including proteomic, genomic and transcriptomic approaches have been utilized and biomarker candidates identified, no one platform or molecule has been successfully validated in large population screens. As a part of the National Cancer Institute Early Detection Research Network, we are taking a targeted approach to assemble a panel of biomarker candidates, given that no one biomarker has shown promise for early detection. We hypothesize that a panel of early detection biomarkers for pancreatic cancer could be discovered by the identification of the earliest genetic pathways aberrant in pancreatic cancer. We furthermore hypothesize that genetic pathways involving tumor suppressor genes with loss of function mutations/deletions and dominantly activated/amplified/over expressed oncogenes are critical determinants in the development of the early phases of pancreatic neoplasia. Project 1 is utilizing a functional genomics approach toward biomarker discovery and is targeting the chromosome 3p12 pathway to tumorigenesis in pancreatic cancer. Three separate expression platforms have been utilized to develop a panel of genes differentially expressed in pancreatic tumor/normal samples and which represent potential genes in the 3p pathway as well as a novel tumor suppressor/polarity regulator DEAR1 is being characterized as a pancreatic cancer biomarker. Project 2 is examining copy number altered genes and miRNAs as early detection biomarkers utilizing an integrated functional genomics and pathway network analysis approach. Project 3 is examining a panel of 1,536 SNPs and relevant covariates in 1000 pancreatic cancer patients to develop a risk model to identify those individuals most likely to develop pancreatic cancer at an early age and could be stratified for screening using biomarker panels developed in projects one and two.

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