Literature DB >> 22716024

Strategy for SRM-based verification of biomarker candidates discovered by iTRAQ method in limited breast cancer tissue samples.

Satoshi Muraoka1, Hideaki Kume, Shio Watanabe, Jun Adachi, Masayoshi Kuwano, Misako Sato, Naoko Kawasaki, Yoshio Kodera, Makoto Ishitobi, Hideo Inaji, Yasuhide Miyamoto, Kikuya Kato, Takeshi Tomonaga.   

Abstract

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.

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Year:  2012        PMID: 22716024     DOI: 10.1021/pr300322q

Source DB:  PubMed          Journal:  J Proteome Res        ISSN: 1535-3893            Impact factor:   4.466


  16 in total

1.  Discovery of colorectal cancer biomarker candidates by membrane proteomic analysis and subsequent verification using selected reaction monitoring (SRM) and tissue microarray (TMA) analysis.

Authors:  Hideaki Kume; Satoshi Muraoka; Takahisa Kuga; Jun Adachi; Ryohei Narumi; Shio Watanabe; Masayoshi Kuwano; Yoshio Kodera; Kazuyuki Matsushita; Junya Fukuoka; Takeshi Masuda; Yasushi Ishihama; Hisahiro Matsubara; Fumio Nomura; Takeshi Tomonaga
Journal:  Mol Cell Proteomics       Date:  2014-03-31       Impact factor: 5.911

2.  Targeted Proteomics for Multiplexed Verification of Markers of Colorectal Tumorigenesis.

Authors:  Anuli Christiana Uzozie; Nathalie Selevsek; Asa Wahlander; Paolo Nanni; Jonas Grossmann; Achim Weber; Federico Buffoli; Giancarlo Marra
Journal:  Mol Cell Proteomics       Date:  2017-01-04       Impact factor: 5.911

3.  Comparative membrane proteomic analysis between lung adenocarcinoma and normal tissue by iTRAQ labeling mass spectrometry.

Authors:  Xuede Zhang; Wei Li; Yanli Hou; Zequn Niu; Yujie Zhong; Yuping Zhang; Shuanying Yang
Journal:  Am J Transl Res       Date:  2014-05-15       Impact factor: 4.060

Review 4.  The clinical impact of recent advances in LC-MS for cancer biomarker discovery and verification.

Authors:  Hui Wang; Tujin Shi; Wei-Jun Qian; Tao Liu; Jacob Kagan; Sudhir Srivastava; Richard D Smith; Karin D Rodland; David G Camp
Journal:  Expert Rev Proteomics       Date:  2015-12-19       Impact factor: 3.940

5.  Differential Proteome Analysis Identifies TGF-β-Related Pro-Metastatic Proteins in a 4T1 Murine Breast Cancer Model.

Authors:  Misako Sato; Tsutomu Matsubara; Jun Adachi; Yuuki Hashimoto; Kazuna Fukamizu; Marina Kishida; Yu-An Yang; Lalage M Wakefield; Takeshi Tomonaga
Journal:  PLoS One       Date:  2015-05-18       Impact factor: 3.240

6.  Quantitative proteomic analysis of cultured skin fibroblast cells derived from patients with triglyceride deposit cardiomyovasculopathy.

Authors:  Yasuhiro Hara; Naoko Kawasaki; Ken-ichi Hirano; Yuuki Hashimoto; Jun Adachi; Shio Watanabe; Takeshi Tomonaga
Journal:  Orphanet J Rare Dis       Date:  2013-12-21       Impact factor: 4.123

7.  Quantitative iTRAQ LC-MS/MS proteomics reveals the proteome profiles of DF-1 cells after infection with subgroup J Avian leukosis virus.

Authors:  Xiaofei Li; Qi Wang; Yanni Gao; Xiaole Qi; Yongqiang Wang; Honglei Gao; Yulong Gao; Xiaomei Wang
Journal:  Biomed Res Int       Date:  2015-01-08       Impact factor: 3.411

8.  Comparative proteomics reveals that central metabolism changes are associated with resistance against Sporisorium scitamineum in sugarcane.

Authors:  Yachun Su; Liping Xu; Zhuqing Wang; Qiong Peng; Yuting Yang; Yun Chen; Youxiong Que
Journal:  BMC Genomics       Date:  2016-10-12       Impact factor: 3.969

9.  Experimental verification and molecular basis of active immunization against fungal pathogens in termites.

Authors:  Long Liu; Ganghua Li; Pengdong Sun; Chaoliang Lei; Qiuying Huang
Journal:  Sci Rep       Date:  2015-10-13       Impact factor: 4.379

10.  Contemporary network proteomics and its requirements.

Authors:  Wilson Wen Bin Goh; Limsoon Wong; Judy Chia Ghee Sng
Journal:  Biology (Basel)       Date:  2013-12-20
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