SILAC-based quantitative proteomic approach to identify potential biomarkers from the esophageal squamous cell carcinoma secretome

 Abstract

The identification of secreted proteins that are differentially expressed between non-neoplastic and esophageal squamous cell carcinoma (ESCC) cells can provide potential biomarkers of ESCC. We used a SILAC-based quantitative proteomic approach to compare the secretome of ESCC cells with that of non-neoplastic esophageal squamous epithelial cells. Proteins were resolved by SDS-PAGE, and tandem mass spectrometry analysis (LC-MS/MS) of in-gel trypsin-digested peptides was carried out on a high-accuracy qTOF mass spectrometer. In total, we identified 441 proteins in the combined secretomes, including 120 proteins with >2-fold upregulation in the ESCC secretome vs. that of non-neoplastic esophageal squamous epithelial cells. In this study, several potential protein biomarkers previously known to be increased in ESCC including matrix metalloproteinase 1, transferrin receptor, and transforming growth factor beta-induced 68 kDa were identified as overexpressed in the ESCC-derived secretome. In addition, we identified several novel proteins that have not been previously reported to be associated with ESCC. Among the novel candidate proteins identified, protein disulfide isomerase family a member 3 (PDIA3), GDP dissociation inhibitor 2 (GDI2), and lectin galactoside binding soluble 3 binding protein (LGALS3BP) were further validated by immunoblot analysis and immunohistochemical labeling using tissue microarrays. This tissue microarray analysis showed overexpression of protein disulfide isomerase family a member 3, GDP dissociation inhibitor 2, and lectin galactoside binding soluble 3 binding protein in 93%, 93% and 87% of 137 ESCC cases, respectively. Hence, we conclude that these potential biomarkers are excellent candidates for further evaluation to test their role and efficacy in the early detection of ESCC.

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Pages
796 - 810
doi
10.4161/cbt.10.8.12914
Type
Research Paper
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SILAC-based quantitative proteomic approach to identify potential biomarkers from the esophageal squamous cell carcinoma secretome