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ABSTRACT

PURPOSE:

Gastric cancer is a commonly occurring cancer in Asia and one of the leading causes of cancer deaths. However, there is no reliable blood-based screening test for this cancer. Identifying proteins secreted from tumor cells could lead to the discovery of clinically useful biomarkers for early detection of gastric cancer. EXPERIMENTAL

DESIGN:

A SILAC-based quantitative proteomic approach was employed to identify secreted proteins that were differentially expressed between neoplastic and non-neoplastic gastric epithelial cells. Proteins from the secretome were subjected to SDS-PAGE and SCX-based fractionation, followed by mass spectrometric analysis on an LTQ-Orbitrap Velos mass spectrometer. Immunohistochemical labeling was employed to validate a subset of candidates using tissue microarrays.

RESULTS:

We identified 2205 proteins in the gastric cancer secretome of which 263 proteins were overexpressed greater than fourfold in gastric cancer-derived cell lines as compared to non-neoplastic gastric epithelial cells. Three candidate proteins, proprotein convertase subtilisin/kexin type 9 (PCSK9), lectin mannose binding 2 (LMAN2), and PDGFA-associated protein 1 (PDAP1) were validated by immunohistochemical labeling. CONCLUSIONS AND CLINICAL RELEVANCE We report here the largest cancer secretome described to date. The novel biomarkers identified in the current study are excellent candidates for further testing as early detection biomarkers for gastric adenocarcinoma.
Subject(s)

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Stomach Neoplasms / Adenocarcinoma / Proteins / Proteomics / Amino Acids Type of study: Prognostic_studies / Screening_studies Limits: Humans Language: En Journal: Proteomics Clin Appl Year: 2013 Document type: Article

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Stomach Neoplasms / Adenocarcinoma / Proteins / Proteomics / Amino Acids Type of study: Prognostic_studies / Screening_studies Limits: Humans Language: En Journal: Proteomics Clin Appl Year: 2013 Document type: Article