Workflow Comparison for Label-Free, Quantitative Secretome Proteomics for Cancer Biomarker Discovery: Method Evaluation, Differential Analysis, and Verification in Serum

Abstract

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.

Chemoproteomic Analysis of Intertissue and Interspecies Isoform Diversity of AMP-activated Protein Kinase (AMPK)

“…Relative abundance of the subunit isoforms was assessed by comparing the "spectral counts" of the isoform-unique peptides (Table 1) (37)(38)(39)(40)(41)(42)(43)(44)(45)(46). For instance, in the sample designated healthy hepatocyte-1, ␤1 and ␤2 isoforms were both identified with spectral counts of 6 and 92 (1:15), respectively.…”

Physiological and comparative proteomic analyses of Thai jasmine rice and two check cultivars in response to drought stress

“…With the increased interest in analyzing plant proteomes, shotgun proteomics has been developed for rapid, highly accurate, and effective detection of protein expression under specific conditions (Yates 1998;Delmotte et al 2009;Piersma et al 2010;Tabb et al 2010;Matros et al 2011). However, shotgun proteomics is limited by the complexity of the peptide mixtures (Malmstrom et al 2007).…”

“…Shotgun proteomics can identify more than 1000 peptides within one analysis and also enables the detection of proteins rarely found using 2D-PAGEbased proteomics (Washburn et al 2001). Moreover, shotgun proteomics has proven to be more reproducible in terms of peptide identification and protein quantitation than other techniques (Delmotte et al 2009;Piersma et al 2010;Tabb et al 2010). While the complexity of the peptide mixtures limits the use of shotgun proteomics (Malmstrom et al 2007), this problem can be reduced through the use of gel-based liquid chromatography-tandem mass spectrometry (GeLC-MS/MS) in which proteins are first separated by sodium dodecyl sulfate-PAGE (SDS-PAGE) then the entire gel is sliced into pieces according to protein marker sizes before digestion and analysis by MS/MS (Rezaul et al 2005).…”

Progress in Mining the Human Proteome for Disease Applications

“…Quantitative comparison of the proteome of single islets, containing 2,000-4,000 cells, treated with high or low glucose levels, allowed analysis of a repertoire of proteins involved in diabetes, including novel components. At the subcellular level, the secretome, the cell surface proteome, and the phosphoproteome can be analyzed with exquisite detail using proteomics technologies to identify potential novel diagnostic and therapeutic targets (Chenau et al, 2009;Daub et al, 2008;Faca et al, 2009;Greco et al, 2010;Gundry et al, 2008;Kohnke et al, 2009;Kosako et al, 2009;May, 2009;Piersma et al, 2010;Rinschen et al, 2010;Xu et al, 2010;Xue et al, 2010). Likewise, proteome profiling of tissues has allowed searches for disease alterations in great depths (Beretta, 2009;de la Cuesta et al, 2009;Voshol et al, 2009;Parikh et al, 2010;Sanchez-Carbayo, 2010).…”