Strategy for SRM-based Verification of Biomarker Candidates Discovered by iTRAQ Method in Limited Breast Cancer Tissue Samples
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- 作者：Satoshi Muraoka ; Hideaki Kume ; Shio Watanabe ; Jun Adachi ; Masayoshi Kuwano ; Misako Sato ; Naoko Kawasaki ; Yoshio Kodera ; Makoto Ishitobi ; Hideo Inaji ; Yasuhide Miyamoto ; Kikuya Kato ; Takeshi Tomonaga
- 刊名：Journal of Proteome Research
- 出版年：2012
- 出版时间：August 3, 2012
- 年：2012
- 卷：11
- 期：8
- 页码：4201-4210
- 全文大小：455K
- 年卷期：v.11,no.8(August 3, 2012)
- ISSN：1535-3907
文摘
Since LC鈥揗S-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.