NMR-based metabolomic techniques identify potential urinary biomarkers for early colorectal cancer detection
| Autor: | Xingmu Liu, Zhening Wang, Jurong Yang, Changchun Ma, Yan Lin, Jiahao Liang, Yao Huang |
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| Jazyk: | angličtina |
| Rok vydání: | 2017 |
| Předmět: |
0301 basic medicine
Colorectal cancer Metabolite Urinary system colorectal cancer Urine 03 medical and health sciences chemistry.chemical_compound 0302 clinical medicine Metabolomics Medicine Glycolysis 1H NMR spectroscopy business.industry medicine.disease metabolomics urine Biomarker (cell) 030104 developmental biology Oncology chemistry 030220 oncology & carcinogenesis Urea cycle Cancer research biomarker business Research Paper |
| Zdroj: | Oncotarget |
| ISSN: | 1949-2553 |
| Popis: | Better early detection methods are needed to improve the outcomes of patients with colorectal cancer (CRC). Proton nuclear magnetic resonance spectroscopy (1H-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 1H-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. |
| Databáze: | OpenAIRE |
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