Colorectal cancer detection using targeted serum metabolic profiling

Jiangjiang Zhu, Danijel Djukovic, Lingli Deng, Haiwei Gu, Farhan Himmati, E. Gabriela Chiorean, Daniel Raftery

Research output: Contribution to journalArticle

105 Scopus citations

Abstract

Colorectal cancer (CRC) is one of the most prevalent and deadly cancers in the world. Despite an expanding knowledge of its molecular pathogenesis during the past two decades, robust biomarkers to enable screening, surveillance, and therapy monitoring of CRC are still lacking. In this study, we present a targeted liquid chromatography-tandem mass spectrometry-based metabolic profiling approach for identifying biomarker candidates that could enable highly sensitive and specific CRC detection using human serum samples. In this targeted approach, 158 metabolites from 25 metabolic pathways of potential significance were monitored in 234 serum samples from three groups of patients (66 CRC patients, 76 polyp patients, and 92 healthy controls). Partial least-squares-discriminant analysis (PLS-DA) models were established, which proved to be powerful for distinguishing CRC patients from both healthy controls and polyp patients. Receiver operating characteristic curves generated based on these PLS-DA models showed high sensitivities (0.96 and 0.89, respectively, for differentiating CRC patients from healthy controls or polyp patients), good specificities (0.80 and 0.88), and excellent areas under the curve (0.93 and 0.95). Monte Carlo cross validation was also applied, demonstrating the robust diagnostic power of this metabolic profiling approach.

Original languageEnglish (US)
Pages (from-to)4120-4130
Number of pages11
JournalJournal of Proteome Research
Volume13
Issue number9
DOIs
StatePublished - Sep 5 2014
Externally publishedYes

Keywords

  • LC-MS/MS
  • colorectal cancer
  • diagnostic biomarkers
  • metabolomics
  • polyps
  • serum metabolites
  • targeted metabolic profiling

ASJC Scopus subject areas

  • Biochemistry
  • Chemistry(all)

Fingerprint Dive into the research topics of 'Colorectal cancer detection using targeted serum metabolic profiling'. Together they form a unique fingerprint.

  • Cite this

    Zhu, J., Djukovic, D., Deng, L., Gu, H., Himmati, F., Chiorean, E. G., & Raftery, D. (2014). Colorectal cancer detection using targeted serum metabolic profiling. Journal of Proteome Research, 13(9), 4120-4130. https://doi.org/10.1021/pr500494u