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.

Public Health Relevance

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.

National Institute of Health (NIH)
National Cancer Institute (NCI)
Exploratory/Developmental Grants (R21)
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Cancer Biomarkers Study Section (CBSS)
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Thurin, Magdalena
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University of Washington
Schools of Medicine
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Nigjeh, Eslam N; Chen, Ru; Allen-Tamura, Yasuko et al. (2017) Spectral library-based glycopeptide analysis-detection of circulating galectin-3 binding protein in pancreatic cancer. Proteomics Clin Appl 11:
Pan, Sheng; Brentnall, Teresa A; Chen, Ru (2015) Proteomics analysis of bodily fluids in pancreatic cancer. Proteomics 15:2705-15
Chen, Ru; Dawson, David W; Pan, Sheng et al. (2015) Proteins associated with pancreatic cancer survival in patients with resectable pancreatic ductal adenocarcinoma. Lab Invest 95:43-55
Pan, Sheng (2014) Quantitative glycoproteomics for N-glycoproteome profiling. Methods Mol Biol 1156:379-88
Pan, Sheng; Chen, Ru; Tamura, Yasuko et al. (2014) Quantitative glycoproteomics analysis reveals changes in N-glycosylation level associated with pancreatic ductal adenocarcinoma. J Proteome Res 13:1293-306
Pan, Sheng; Brentnall, Teresa A; Kelly, Kimberly et al. (2013) Tissue proteomics in pancreatic cancer study: discovery, emerging technologies, and challenges. Proteomics 13:710-21
Chen, Ru; Pan, Sheng; Ottenhof, Niki A et al. (2012) Stromal galectin-1 expression is associated with long-term survival in resectable pancreatic ductal adenocarcinoma. Cancer Biol Ther 13:899-907
Pan, Sheng; Chen, Ru; Brand, Randall E et al. (2012) Multiplex targeted proteomic assay for biomarker detection in plasma: a pancreatic cancer biomarker case study. J Proteome Res 11:1937-48
Pan, Sheng; Tamura, Yasuko; Chen, Ru et al. (2012) Large-scale quantitative glycoproteomics analysis of site-specific glycosylation occupancy. Mol Biosyst 8:2850-6
Pan, Sheng; Chen, Ru; Stevens, Tyler et al. (2011) Proteomics portrait of archival lesions of chronic pancreatitis. PLoS One 6:e27574

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