Abstract
We developed a multiplexed label-free quantification strategy, which integrates an efficient gel-assisted digestion protocol, high-performance liquid chromatography tandem MS analysis, and a bioinformatics alignment method to determine personalized proteomic profiles for membrane proteins in human tissues. This strategy provided accurate (6% error) and reproducible (34% relative S.D.) quantification of three independently purified membrane fractions from the same human colorectal cancer (CRC) tissue. Using CRC as a model, we constructed the personalized membrane protein atlas of paired tumor and adjacent normal tissues from 28 patients with different stages of CRC. Without fractionation, this strategy confidently quantified 856 proteins (≥2 unique peptides) across different patients, including the first and robust detection (Mascot score: 22,074) of the well-documented CRC marker, carcinoembryonic antigen 5 by a discovery-type proteomics approach. Further validation of a panel of proteins, annexin A4, neutrophils defensin A1, and claudin 3, confirmed differential expression levels and high occurrences (48–70%) in 60 CRC patients. The most significant discovery is the overexpression of stomatin-like 2 (STOML2) for early diagnostic and prognostic potential. Increased expression of STOML2 was associated with decreased CRC-related survival; the mean survival period was 34.77 ± 2.03 months in patients with high STOML2 expression, whereas 53.67 ± 3.46 months was obtained for patients with low STOML2 expression. Further analysis by ELISA verified that plasma concentrations of STOML2 in early-stage CRC patients were elevated as compared with those of healthy individuals (p < 0.001), suggesting that STOML2 may be a noninvasive serological biomarker for early CRC diagnosis. The overall sensitivity of STOML2 for CRC detection was 71%, which increased to 87% when combined with CEA measurements. This study demonstrated a sensitive, label-free strategy for differential analysis of tissue membrane proteome, which may provide a roadmap for the subsequent identification of molecular target candidates of multiple cancer types.
Highlights
Among published Colorectal cancer (CRC)-related proteomics literature, the most widely used proteomics approach for identification of differentially expressed proteins in individual CRC patient was based on two-dimensional (2D) PAGE and the more sophisticated technique of two-dimensional differential gel electrophoresis coupled with MS [17,18,19,20,21,22,23,24]
By analyzing paired tumor and adjacent normal tissues from patients, these gel-based methods have led to discovery of a variety of proteins involving in signal transduction, cellular reorganization, and tissue hypoxia as potential biomarkers for CRC
Membrane proteins were first purified from paired tumor and adjacent normal tissues, mixed with internal standard protein (BSA), and subjected to our recently reported gel-assisted digestion [31]
Summary
Materials—Protease inhibitor was obtained from Merck (Darmstadt, Germany). Monomeric acrylamide/bisacrylamide solution (40%, 29:1) was purchased from Bio-Rad (Hercules, CA). Slides were incubated with anti-human STOML2 primary antibody (mouse, 1:250 dilution; ProteinTech, Inc., Chicago, IL) for 30 min at room temperature. Following washing with PBS (pH 7.4), slides were incubated with HRP-conjugated anti-mouse IgG secondary antibody (rabbit, 1:2000 dilution; Abcam, Inc., Cambridge, UK) for 30 min at room temperature and developed using 3,3Ј-diaminobenzidine (Sigma, St Louis, MO). ELISA—Briefly, monoclonal anti-human STOML2 (Protein Tech Group Inc., Chicago, IL) in coating buffer (pH 9.5; 15 mmol/l Na2CO3, 35 mmol/l NaHCO3 in distilled water) was added to 96-well microtiter plates (Costar, Illinois, IL) at 100 ng/well and incubated overnight at 4 °C. A subset of plasma samples and purified recombinant STOML2 proteins (50, 40, 30, 20, 10, and 5 ng/ml) was assayed in every ELISA batch for quality control and quantification, respectively (supplemental Fig. 2). The diagnostic potential of a specific marker was evaluated by performing the receiver operating characteristic (ROC) curve analysis and the discriminative efficacy of an individual biomarker was calculated by the area under the ROC curve (AUC)
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