"Identification of Pancreatic Cancer Biomarkers in Mouse Models Representing Various Stages of Disease Progression."
Pancreatic ductal adenocarcinoma (PDA) kills more than 30,000 people in the U.S. each year. Unfortunately, rates of incidence and mortality are almost identical because symptoms do not present until the disease is already metastatic. Thus, it is important to better characterize PDA to improve early detection methods and adopt more effective therapies. Mouse models that represent human disease allow for the tracking of disease progression from preinvasive to metastatic stages while maintaining important non-cell autonomous interactions. I propose to use a highly faithful mouse model that genetically and pathologically recapitulates human PDA, in conjunction with a high-throughput antibody array to identify cancer biomarkers associated with different stages of progression to PDA. Tissue and plasma derived from mice at preinvasive, invasive and metastatic stages of disease progression will be hybridized to arrays printed with ~1,600 full length commercial antibodies that recognize a wide variety of phosphorylated signaling proteins (over 300), cytokines and growth factors as well as ~4,000 single chain antibody fragments (scFv’s) that recognize mouse serum proteins. Candidate markers will then be identified biostatistically based on their ability to distinguish case animals from controls. Subsequent histologic and cell culture experiments with tissue samples and primary cells derived from mouse tissues, will then determine the tissue of origin and the molecular changes responsible for the biomarkers identified, as well as the relevance of these proteins to the disease state. The goal is for these markers to further characterize the functional changes that contribute to disease etiology and progression.
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