title: Expression profiling of more than 3500 proteins of MSS-type colorectal cancer by stable isotope labeling and mass spectrometry.
abstract: An efficient means of identifying protein biomarkers is essential to proper cancer management. A well-characterized proteome resource holds special promise for the discovery of novel biomarkers. However, quantification of the differences between physiological conditions together with deep down profiling has become increasingly challenging in proteomics. Here, we perform expression profiling of the colorectal cancer (CRC) proteome by stable isotope labeling and mass spectrometry. Quantitative analysis included performing mTRAQ and cICAT labeling in a pooled sample of three microsatellite stable (MSS) type CRC tissues and a pooled sample of their matched normal tissues. We identified and quantified a total of 3688 proteins. Among them, 1487 proteins were expressed differentially between normal and cancer tissues by higher than 2-fold; 1009 proteins showed increased expression in cancer tissue, whereas 478 proteins showed decreased expression. Bioinformatic analysis revealed that our data were largely consistent with known CRC relevant signaling pathways, such as the Wnt/β-catenin, caveolar-mediated endocytosis, and RAN signaling pathways. Mitochondrial dysfunction, known as the Waburg hypothesis, was also confirmed. Therefore, our data showing alterations in the proteomic profile of CRC constitutes a useful resource that may provide insights into tumor progression with later goal of identifying biologically and clinically relevant marker proteins. This article is part of a Special Issue entitled: Proteomics: The clinical link.
authors.affiliation: BRI, Korea Institute of Science and Technology, Seoul 136-791, Republic of Korea.
authors.forename: Un-Beom
authors.initials: UB
authors.lastname: Kang
authors.forename: Jeonghun
authors.initials: J
authors.lastname: Yeom
authors.forename: Hye-Jung
authors.initials: HJ
authors.lastname: Kim
authors.forename: Hoguen
authors.initials: H
authors.lastname: Kim
authors.forename: Cheolju
authors.initials: C
authors.lastname: Lee
mesh_terms: D000465:Algorithms; D014408:Biomarkers, Tumor / Q000032:analysis / Q000378:metabolism; D002277:Carcinoma / Q000235:genetics / Q000378:metabolism* / Q000473:pathology; D016000:Cluster Analysis; D015179:Colorectal Neoplasms / Q000235:genetics / Q000378:metabolism* / Q000473:pathology; D015972:Gene Expression Regulation, Neoplastic; D006801:Humans; D007553:Isotope Labeling / Q000379:methods*; D013058:Mass Spectrometry / Q000379:methods*; D053858:Metabolic Networks and Pathways / Q000502:physiology; D055442:Metabolome; D053842:Microsatellite Instability; D008954:Models, Biological; D009363:Neoplasm Proteins / Q000032:analysis* / Q000235:genetics / Q000378:metabolism; D020543:Proteome / Q000032:analysis / Q000378:metabolism
chemical_list: D014408:Biomarkers, Tumor; D009363:Neoplasm Proteins; D020543:Proteome