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.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Exploratory/Developmental Grants (R21)
Project #
5R21CA149772-02
Application #
8209066
Study Section
Cancer Biomarkers Study Section (CBSS)
Program Officer
Thurin, Magdalena
Project Start
2011-01-01
Project End
2013-12-31
Budget Start
2012-01-01
Budget End
2013-12-31
Support Year
2
Fiscal Year
2012
Total Cost
$208,128
Indirect Cost
$60,347
Name
University of Washington
Department
Pathology
Type
Schools of Medicine
DUNS #
605799469
City
Seattle
State
WA
Country
United States
Zip Code
98195
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 (2014) Quantitative glycoproteomics for N-glycoproteome profiling. Methods Mol Biol 1156:379-88
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
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; Chen, Ru; Stevens, Tyler et al. (2011) Proteomics portrait of archival lesions of chronic pancreatitis. PLoS One 6:e27574
Pan, Sheng; Chen, Ru; Crispin, David A et al. (2011) Protein alterations associated with pancreatic cancer and chronic pancreatitis found in human plasma using global quantitative proteomics profiling. J Proteome Res 10:2359-76