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Quantitative proteomic profiling of paired cancerous and normal colon epithelial cells isolated freshly from colorectal cancer patients

  • SUNY Buffalo
  • Beijing University of Chinese Medicine
  • Shandong University

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

Abstract

Purpose: The heterogeneous structure in tumor tissues from colorectal cancer (CRC) patients excludes an informative comparison between tumors and adjacent normal tissues. Here, we develop and apply a strategy to compare paired cancerous (CEC) versus normal (NEC) epithelial cells enriched from patients and discover potential biomarkers and therapeutic targets for CRC. Experimental design: CEC and NEC cells are respectively isolated from five different tumor and normal locations in the resected colon tissue from each patient (N = 12 patients) using an optimized epithelial cell adhesion molecule (EpCAM)-based enrichment approach. An ion current-based quantitative method is employed to perform comparative proteomic analysis for each patient. Results: A total of 458 altered proteins that are common among >75% of patients are observed and selected for further investigation. Besides known findings such as deregulation of mitochondrial function, tricarboxylic acid cycle, and RNA post-transcriptional modification, functional analysis further revealed RAN signaling pathway, small nucleolar ribonucleoproteins (snoRNPs), and infection by RNA viruses are altered in CEC cells. A selection of the altered proteins of interest is validated by immunohistochemistry analyses. Conclusion and clinical relevance: The informative comparison between matched CEC and NEC enhances our understanding of molecular mechanisms of CRC development and provides biomarker candidates and new pathways for therapeutic intervention.

Original languageEnglish
Article number1600155
JournalProteomics - Clinical Applications
Volume11
Issue number5-6
DOIs
StatePublished - May 2017

Keywords

  • Biomarker discovery
  • Colorectal cancer
  • Ion current-based analysis
  • Tumor cell enrichment

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