Workflow Comparison for Label-Free, Quantitative Secretome Proteomics for Cancer Biomarker Discovery: Method Evaluation, Differential Analysis, and Verification in Serum
datasetposted on 05.04.2010, 00:00 by Sander R. Piersma, Ulrike Fiedler, Simone Span, Andreas Lingnau, Thang V. Pham, Steffen Hoffmann, Michael H. G. Kubbutat, Connie R. Jiménez
The cancer cell secretome has emerged as an attractive subproteome for discovery of candidate blood-based biomarkers. To choose the best performing workflow, we assessed the performance of three first-dimension separation strategies prior to nanoLC-MS/MS analysis: (1) 1D gel electrophoresis (1DGE), (2) peptide SCX chromatography, and (3) tC2 protein reversed phase chromatography. 1DGE using 4−12% gradient gels outperformed the SCX and tC2 methods with respect to number of identified proteins (1092 vs 979 and 580, respectively), reproducibility of protein identification (80% vs 70% and 72%, respectively, assessed in biological N = 3). Reproducibility of protein quantitation based on spectral counting was similar for all 3 methods (CV: 26% vs 24% and 24%, respectively). As a proof-of-concept of secretome proteomics for blood-based biomarker discovery, the gradient 1DGE workflow was subsequently applied to identify IGF1R-signaling related proteins in the secretome of mouse embryonic fibroblasts transformed with human IGF1R (MEF/Toff/IGF1R). VEGF and osteopontin were differentially detected by LC-MS/MS and verified in secretomes by ELISA. Follow-up in serum of mice bearing MEF/Toff/IGF1R-induced tumors showed an increase of osteopontin levels paralleling tumor growth, and reduction in the serum of mice in which IGF1R expression was shut off and tumor regressed.