Metabolomics-derived prostate cancer biomarkers: Fact or fiction?

Deepak Kumar, Ashish Gupta, Anil Mandhani, Satya Narain Sankhwar

Research output: Contribution to journalArticle

Abstract

Despite continuing research for precise probing and grading of prostate cancer (PC) biomarkers, the indexes lack sensitivity and specificity. To search for PC biomarkers, we used proton nuclear magnetic resonance (1H NMR)-derived serum metabolomics. The study comprises 102 serum samples obtained from low-grade (LG, n = 40) and high-grade (HG, n = 30) PC cases and healthy controls (HC, n = 32). 1H NMR-derived serum data were examined using principal component analysis and orthogonal partial least-squares discriminant analysis. The strength of the model was verified by internal cross-validation using the same samples divided into 70% as training and 30% as test data sets. Receiver operating characteristic (ROC) curve examination was also achieved. Serum metabolomics reveals that four biomarkers (alanine, pyruvate, glycine, and sarcosine) were able to accurately (ROC 0.966) differentiate 90.2% of PC cases with 84.4% sensitivity and 92.9% specificity compared with HC. Similarly, three biomarkers, alanine, pyruvate, and glycine, were able to precisely (ROC 0.978) discriminate 92.9% of LG from HG PC with 92.5% sensitivity and 93.3% specificity. The robustness of these biomarkers was confirmed by prediction of the test data set with >99% diagnostic precision for PC determination. These findings demonstrate that 1H NMR-based serum metabolomics is a promising approach for probing and grading PC.

Original languageEnglish (US)
Pages (from-to)1455-1464
Number of pages10
JournalJournal of Proteome Research
Volume14
Issue number3
DOIs
StatePublished - Mar 6 2015
Externally publishedYes

    Fingerprint

Keywords

  • NMR spectroscopy
  • OPLS-DA
  • PCA
  • prostate cancer
  • serum-metabolomics

ASJC Scopus subject areas

  • Biochemistry
  • Chemistry(all)

Cite this