123rd General Meeting of the KCS

Type Symposium
Area Analytical Technologies to Improve Human Health
Room No. Room 202
Time FRI 15:20-15:45
Code ANAL2-3
Subject Gastric Cancer Ascites Proteome for Potential Gastric Cancer Biomarkers Using Targeted Quantitative Methods
Authors Jonghwa Jin
Division of Convergence Technology, New Drug Development Center, Korea
Abstract Gastric cancer is one of the most lethal malignancies, and the lack of specific early screening, diagnostic, and prognostic methods for such patients has necessitated the development of gastric cancer-specific biomarkers. Ascites is an important source of biomarkers, because it contains secreted proteins from malignant cells, growth factors, and cytokines. We performed a comprehensive proteome study using the ascites of patients with inflammatory diseases and gastric cancer. In the discovery stage, we identified 2761 ascites-specific proteins, 234 of which were quantitated by label-free quantitation using normalized spectral abundance factors (NSAFs)—152 and 82 proteins were up- and downregulated, respectively. In the verification stage (68 target proteins), we developed 2 quantitative targeted methods using stable isotope standard (SIS) peptide-based approaches—parallel reaction monitoring (PRM) and multiple reaction monitoring (MRM)—which target peptide fragments selectively and sensitively in complex samples; the PRM-targeted method showed high correlation with the MRM results (approximately 90% of peptides with r > 0.9). In the linear mixed effects analysis of the 2 methods, the expression of 36 proteins differed significantly between benign (N: 15) and cancer ascites (N: 33). Further, we performed a multiplex assay (linear discriminant analysis) using 7 biomarker candidates from the PRM and MRM analysis, resulting in a merged AUC value of 0.97 for PRM and 0.96 for MRM. Although our model requires further validation in a larger sample size, our 6- and 4-protein marker panel can be used as baseline references for the discovery of novel gastric cancer-specific biomarkers.
E-mail jichang011@kbiohealth.kr