Identification of differential metabolic characteristics between tumor and normal tissue from colorectal cancer patients by gas chromatography-mass spectrometry

Biomed Chromatogr. 2017 Nov;31(11). doi: 10.1002/bmc.3999. Epub 2017 Jun 2.

Abstract

Colorectal cancer (CRC) is one of the most common human malignancies and encompasses cancers of the colon and rectum. Although the gold-standard colonoscopy screening method is effective in detecting CRC, this method is invasive and can result in severe complications for patients. The purpose of this study was to determine differences in metabolites between CRC and matched adjacent nontumor tissues from CRC patients, to identify potential biomarkers that may be informative and developed screening methods. Metabolomic analysis was performed on clinically localized CRC tissue and matched adjacent nontumor tissue from 20 CRC patients. Unsupervised analysis, supervised analysis, univariate analysis and pathway analysis were used to identify potential metabolic biomarkers of CRC. The levels of 25 metabolites in CRC tissues were significantly altered compared with the matched adjacent nontumor tissues. Four metabolites (lactic acid, alanine, phosphate and aspartic acid) demonstrated good area under the curve of receiver-operator characteristic with acceptable sensitivities and specificities, indicating their potential as important biomarkers for CRC. Alterations of amino acid metabolism and enhanced glycolysis may be major factors in the development and progression of CRC. Lactic acid, alanine, phosphate, and aspartic acid could be effective diagnostic indicators for CRC.

Keywords: biomarker; colorectal cancer; gas chromatography-mass spectrometry; metabolomics.

MeSH terms

  • Biomarkers, Tumor / analysis*
  • Biomarkers, Tumor / metabolism
  • Colon / chemistry
  • Colon / metabolism*
  • Colorectal Neoplasms / chemistry
  • Colorectal Neoplasms / metabolism*
  • Female
  • Gas Chromatography-Mass Spectrometry / methods*
  • Humans
  • Least-Squares Analysis
  • Male
  • Metabolomics
  • Middle Aged
  • Principal Component Analysis
  • ROC Curve
  • Reproducibility of Results
  • Sensitivity and Specificity

Substances

  • Biomarkers, Tumor