Pancreatic cancer is the fourth leading cause of cancer death in the United State. One of the major obstacles for improving the outcome in pancreatic cancer treatment arises from the difficulty in diagnosing the disease at an early stage, a goal that could markedly improve the survival rate. Abnormal glycosylation of proteins is often associated with malignant transformation, and has been recognized as a hallmark of pancreatic cancer. In this proposal, we will first apply quantitative proteomics to reveal dysregulated glycosylations associated with pancreatic cancer in plasma. We will then apply a highly sensitive platform technology to quantitatively detect aberrant glycosylations associated with pancreatic cancer in a cohort of cases and controls, and test the hypothesis of using aberrant glycosylation pattern as a molecular fingerprint for pancreatic cancer recognition.
Pancreatic cancer is the fourth leading cause of cancer death in the United State and it is very difficult to diagnosis at an early stage when the disease is curable. Biomarkers are desperately needed for early diagnosis of pancreatic cancer. Aberrant protein glycosylation associated with pancreatic cancer can potentially serve as a molecular signature for pancreatic cancer recognition.
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