4.3 Article

NMR-based metabolomic techniques identify potential urinary biomarkers for early colorectal cancer detection

Journal

ONCOTARGET
Volume 8, Issue 62, Pages 105819-105831

Publisher

IMPACT JOURNALS LLC
DOI: 10.18632/oncotarget.22402

Keywords

colorectal cancer; metabolomics; H-1 NMR spectroscopy; urine; biomarker

Funding

  1. National Natural Science Foundation of China [81471729, 81101102]
  2. Science and Technology Planning Project of Guangdong Province [2016A020216025]
  3. Research Award Fund for Outstanding Young Teachers in Higher Education Institutions, Guangdong Province [YQ2015245]
  4. National Natural Science Foundation of Guangdong Province [S2011010004973]

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Better early detection methods are needed to improve the outcomes of patients with colorectal cancer (CRC). Proton nuclear magnetic resonance spectroscopy (H-1-NMR), a potential non-invasive early tumor detection method, was used to profile urine metabolites from 55 CRC patients and 40 healthy controls (HCs). Pattern recognition through orthogonal partial least squares-discriminant analysis (OPLS-DA) was applied to H-1-NMR processed data. Model specificity was confirmed by comparison with esophageal cancers (EC, n=18). Unique metabolomic profiles distinguished all CRC stages from HC urine samples. A total of 16 potential biomarker metabolites were identified in stage I/II CRC, indicating amino acid metabolism, glycolysis, tricarboxylic acid (TCA) cycle, urea cycle, choline metabolism, and gut microflora metabolism pathway disruptions. Metabolite profiles from early stage CRC and EC patients were also clearly distinguishable, suggesting that upper and lower gastrointestinal cancers have different metabolomic profiles. Our study assessed important metabolomic variations in CRC patient urine samples, provided information complementary to that collected from other biofluid-based metabolomics analyses, and elucidated potential underlying metabolic mechanisms driving CRC. Our results support the utility of NMR-based urinary metabolomics fingerprinting in early diagnosis of CRC.

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