Strategy for SRM-based Verification of Biomarker Candidates Discovered by iTRAQ Method in Limited Breast Cancer Tissue Samples

Since LC–MS-based quantitative proteomics has
become increasingly applied to a wide range of biological applications
over the past decade, numerous studies have performed relative and/or
absolute abundance determinations across large sets of proteins. In
this study, we discovered prognostic biomarker candidates from limited
breast cancer tissue samples using discovery-through-verification
strategy combining iTRAQ method followed by selected reaction monitoring/multiple
reaction monitoring analysis (SRM/MRM). We identified and quantified
5122 proteins with high confidence in 18 patient tissue samples (pooled
high-risk (n = 9) or low-risk (n = 9)). A total of 2480 proteins (48.4%) of them were annotated as
membrane proteins, 16.1% were plasma membrane and 6.6% were extracellular
space proteins by Gene Ontology analysis. Forty-nine proteins with
>2-fold differences in two groups were chosen for further analysis
and verified in 16 individual tissue samples (high-risk (n = 9) or low-risk (n = 7)) using SRM/MRM. Twenty-three
proteins were differentially expressed among two groups of which MFAP4
and GP2 were further confirmed by Western blotting in 17 tissue samples
(high-risk (n = 9) or low-risk (n = 8)) and Immunohistochemistry (IHC) in 24 tissue samples (high-risk
(n = 12) or low-risk (n = 12)).
These results indicate that the combination of iTRAQ and SRM/MRM proteomics
will be a powerful tool for identification and verification of candidate
protein biomarkers.