A new NMR-based metabolomics approach for the diagnosis of biliary tract cancer

J Hepatol. 2010 Feb;52(2):228-33. doi: 10.1016/j.jhep.2009.11.002. Epub 2009 Nov 27.

Abstract

Background & aims: Biliary tract cancer is highly lethal at presentation, with increasing mortality worldwide. Current diagnostic measures employing multiple criteria such as imaging, cytology, and serum tumor markers are not satisfactory, and a new diagnostic tool is needed. Because bile is a cognate metabolite-rich bio-fluid in the biliary ductal system, we tested a new metabolomic approach to develop an effective diagnostic tool.

Methods: Biles were collected prospectively from patients with cancer (n=17) or benign biliary tract diseases (n=21) with percutaneous or endoscopic methods. Nuclear magnetic resonance spectra (NMR) of these biles were analyzed using orthogonal partial least square discriminant analysis (OPLS-DA).

Results: The metabolomic 2-D score plot showed good separation between cancer and benign groups. The contributing NMR signals were analyzed using a statistical TOCSY approach. The diagnostic performance assessed by leave-one-out analysis exhibited 88% sensitivity and 81% specificity, better than the conventional markers (CEA, CA19-9, and bile cytology).

Conclusion: The NMR-based metabolomics approach provides good performance in discriminating cancer and benign biliary duct diseases. The excellent predictability of the method suggests that it can, at least, augment the currently available diagnostic approaches.

Publication types

  • Evaluation Study
  • Research Support, Non-U.S. Gov't
  • Validation Study

MeSH terms

  • Adult
  • Aged
  • Aged, 80 and over
  • Bile / metabolism*
  • Biliary Tract Diseases / diagnosis
  • Biliary Tract Diseases / metabolism
  • Biliary Tract Neoplasms / diagnosis*
  • Biliary Tract Neoplasms / metabolism*
  • Female
  • Humans
  • Least-Squares Analysis
  • Magnetic Resonance Spectroscopy / methods*
  • Magnetic Resonance Spectroscopy / statistics & numerical data
  • Male
  • Metabolomics / methods*
  • Metabolomics / statistics & numerical data
  • Middle Aged
  • Multivariate Analysis
  • Prospective Studies