An informatics-assisted label-free approach for personalized tissue membrane proteomics: Case study on colorectal cancer

Chia Li Han, Jinn Shiun Chen, Err Cheng Chan, Chien Peng Wu, Kun Hsing Yu, Kuei Tien Chen, Chih Chiang Tsou, Chia Feng Tsai, Chih Wei Chien, Yung Bin Kuo, Pei Yi Lin, Jau Song Yu, Chuen Hsueh, Min Chi Chen, Chung Chuan Chan, Yu Sun Chang, Yu Ju Chen

Research output: Contribution to journalArticle

47 Citations (Scopus)

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.

Original languageEnglish
JournalMolecular and Cellular Proteomics
Volume10
Issue number4
DOIs
Publication statusPublished - Apr 2011
Externally publishedYes

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Informatics
Proteomics
Labels
Colorectal Neoplasms
Tissue
Membranes
Annexin A4
Membrane Proteins
Claudin-3
Defensins
Carcinoembryonic Antigen
High performance liquid chromatography
Biomarkers
Proteome
Bioinformatics
Fractionation
Tumors
Proteins
Gels
Plasmas

ASJC Scopus subject areas

  • Biochemistry
  • Molecular Biology
  • Analytical Chemistry
  • Medicine(all)

Cite this

An informatics-assisted label-free approach for personalized tissue membrane proteomics : Case study on colorectal cancer. / Han, Chia Li; Chen, Jinn Shiun; Chan, Err Cheng; Wu, Chien Peng; Yu, Kun Hsing; Chen, Kuei Tien; Tsou, Chih Chiang; Tsai, Chia Feng; Chien, Chih Wei; Kuo, Yung Bin; Lin, Pei Yi; Yu, Jau Song; Hsueh, Chuen; Chen, Min Chi; Chan, Chung Chuan; Chang, Yu Sun; Chen, Yu Ju.

In: Molecular and Cellular Proteomics, Vol. 10, No. 4, 04.2011.

Research output: Contribution to journalArticle

Han, CL, Chen, JS, Chan, EC, Wu, CP, Yu, KH, Chen, KT, Tsou, CC, Tsai, CF, Chien, CW, Kuo, YB, Lin, PY, Yu, JS, Hsueh, C, Chen, MC, Chan, CC, Chang, YS & Chen, YJ 2011, 'An informatics-assisted label-free approach for personalized tissue membrane proteomics: Case study on colorectal cancer', Molecular and Cellular Proteomics, vol. 10, no. 4. https://doi.org/10.1074/mcp.M110.003087
Han, Chia Li ; Chen, Jinn Shiun ; Chan, Err Cheng ; Wu, Chien Peng ; Yu, Kun Hsing ; Chen, Kuei Tien ; Tsou, Chih Chiang ; Tsai, Chia Feng ; Chien, Chih Wei ; Kuo, Yung Bin ; Lin, Pei Yi ; Yu, Jau Song ; Hsueh, Chuen ; Chen, Min Chi ; Chan, Chung Chuan ; Chang, Yu Sun ; Chen, Yu Ju. / An informatics-assisted label-free approach for personalized tissue membrane proteomics : Case study on colorectal cancer. In: Molecular and Cellular Proteomics. 2011 ; Vol. 10, No. 4.
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