Rapid mass spectrometric metabolic profiling of blood sera detects ovarian cancer with high accuracy

Cancer Epidemiol Biomarkers Prev. 2010 Sep;19(9):2262-71. doi: 10.1158/1055-9965.EPI-10-0126. Epub 2010 Aug 10.


Background: Ovarian cancer diagnosis is problematic because the disease is typically asymptomatic, especially at the early stages of progression and/or recurrence. We report here the integration of a new mass spectrometric technology with a novel support vector machine computational method for use in cancer diagnostics, and describe the application of the method to ovarian cancer.

Methods: We coupled a high-throughput ambient ionization technique for mass spectrometry (direct analysis in real-time mass spectrometry) to profile relative metabolite levels in sera from 44 women diagnosed with serous papillary ovarian cancer (stages I-IV) and 50 healthy women or women with benign conditions. The profiles were input to a customized functional support vector machine-based machine-learning algorithm for diagnostic classification. Performance was evaluated through a 64-30 split validation test and with a stringent series of leave-one-out cross-validations.

Results: The assay distinguished between the cancer and control groups with an unprecedented 99% to 100% accuracy (100% sensitivity and 100% specificity by the 64-30 split validation test; 100% sensitivity and 98% specificity by leave-one-out cross-validations).

Conclusion: The method has significant clinical potential as a cancer diagnostic tool. Because of the extremely low prevalence of ovarian cancer in the general population (approximately 0.04%), extensive prospective testing will be required to evaluate the test's potential utility in general screening applications. However, more immediate applications might be as a diagnostic tool in higher-risk groups or to monitor cancer recurrence after therapeutic treatment.

Impact: The ability to accurately and inexpensively diagnose ovarian cancer will have a significant positive effect on ovarian cancer treatment and outcome.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Aged
  • Biomarkers, Tumor / blood*
  • Case-Control Studies
  • Female
  • Humans
  • Mass Spectrometry / methods*
  • Metabolome
  • Middle Aged
  • Ovarian Neoplasms / blood*
  • Ovarian Neoplasms / diagnosis
  • Ovarian Neoplasms / pathology


  • Biomarkers, Tumor