Currently,
pancreatic cancer is the fourth cause of
cancer death. In 2013, it is estimated that ∼38 460 people will die of
pancreatic cancer. Early detection of malignant
cyst (pancreatic cancer precursor) is necessary to help prevent late diagnosis of the
tumor. In this study, we characterized
glycoproteins and nonglycoproteins on pooled mucinous (n = 10) and nonmucinous (n = 10)
pancreatic cyst fluid to identify "
proteins of interest" to differentiate between mucinous
cyst from nonmucinous
cyst and investigate these
proteins as potential
biomarker targets. An automated multilectin affinity chromatography (M-LAC) platform was utilized for
glycoprotein enrichment followed by nano-LC-MS/MS analysis. Spectral count quantitation allowed for the identification of
proteins with significant differential levels in mucinous
cysts from nonmucinous
cysts of which one
protein (
periostin) was confirmed via immunoblotting. To exhaustively evaluate differentially expressed
proteins, we used a number of proteomic tools including gene ontology classification, pathway and network analysis, Novoseek data mining, and chromosome gene mapping. Utilization of complementary proteomic tools revealed that several of the
proteins such as
mucin 6 (MUC6),
bile salt-activated
lipase (CEL), and
pyruvate kinase lysozyme M1/M2 with significant differential expression have strong association with
pancreatic cancer. Furthermore, chromosome gene mapping demonstrated coexpressions and colocalization of some
proteins of interest including
14-3-3 protein epsilon (YWHAE),
pigment epithelium derived factor (SERPINF1), and oncogene p53.