Serum metabolomics as a novel diagnostic approach for gastrointestinal cancer

Biomed Chromatogr. 2012 May;26(5):548-58. doi: 10.1002/bmc.1671. Epub 2011 Jul 20.


Conventional tumor markers are unsuitable for detecting carcinoma at an early stage and lack clinical efficacy and utility. In this study, we attempted to investigate the differences in serum metabolite profiles of gastrointestinal cancers and healthy volunteers using a metabolomic approach and searched for sensitive and specific metabolomic biomarker candidates. Human serum samples were obtained esophageal (n = 15), gastric (n = 11), and colorectal (n = 12) cancer patients and healthy volunteers (n = 12). A model for evaluating metabolomic biomarker candidates was constructed using multiple classification analysis, and the results were assessed with receiver operating characteristic curves. Among the 58 metabolites, the levels of nine, five and 12 metabolites were significantly changed in the esophageal, gastric and colorectal cancer patients, respectively, compared with the healthy volunteers. Multiple classification analysis revealed that the variations in the levels of malonic acid and L-serine largely contributed to the separation of esophageal cancer; gastric cancer was characterized by changes in the levels of 3-hydroxypropionic acid and pyruvic acid; and L-alanine, glucuronoic lactone and L-glutamine contributed to the separation of colorectal cancer. Our approach revealed that some metabolites are more sensitive for detecting gastrointestinal cancer than conventional biomarkers. Our study supports the potential of metabolomics as an early diagnostic tool for cancer.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aged
  • Biomarkers, Tumor / blood*
  • Case-Control Studies
  • Female
  • Gas Chromatography-Mass Spectrometry
  • Gastrointestinal Neoplasms / blood*
  • Gastrointestinal Neoplasms / diagnosis
  • Humans
  • Male
  • Metabolome
  • Metabolomics / methods*
  • Middle Aged
  • Principal Component Analysis
  • ROC Curve


  • Biomarkers, Tumor