Metabolites | 卷:12 |
A Comprehensive Metabolomics Analysis of Fecal Samples from Advanced Adenoma and Colorectal Cancer Patients | |
Joaquin Cubiella1  Luis Bujanda2  Oiana Telleria3  Juan Manuel Falcón-Pérez3  Marc Clos-Garcia4  Oihane E. Alboniga5  Beatriz Nafría-Jimenez6  | |
[1] Department of Gastroenterology, Complexo Hospitalario Universitario de Ourense, Instituto de Investigación Sanitaria Galicia Sur, Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBERehd), 32005 Ourense, Spain; | |
[2] Department of Gastroenterology, Hospital Donostia/Instituto Biodonostia, Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBERehd), Universidad del País Vasco (UPV/EHU), 20014 San Sebastián, Spain; | |
[3] Exosomes Laboratory, CIC bioGUNE-BRTA, CIBERehd, Bizkaia Technology Park, 48160 Bilbao, Spain; | |
[4] LEITAT Technological Center, C/de la Innovació, 2, 08225 Terrassa, Spain; | |
[5] Metabolomics Platform, CIC bioGUNE-BRTA, CIBERehd, Bizkaia Technology Park, 48160 Bilbao, Spain; | |
[6] Osakidetza Basque Health Service, Donostialdea Integrated Health Organisation, Clinical Biochemistry Department, 20014 San Sebastian, Spain; | |
关键词: untargeted metabolomics; colorectal cancer; faecal samples; biomarkers; | |
DOI : 10.3390/metabo12060550 | |
来源: DOAJ |
【 摘 要 】
Accurate diagnosis of colorectal cancer (CRC) still relies on invasive colonoscopy. Noninvasive methods are less sensitive in detecting the disease, particularly in the early stage. In the current work, a metabolomics analysis of fecal samples was carried out by ultra-high-performance liquid chromatography–tandem mass spectroscopy (UPLC-MS/MS). A total of 1380 metabolites were analyzed in a cohort of 120 fecal samples from patients with normal colonoscopy, advanced adenoma (AA) and CRC. Multivariate analysis revealed that metabolic profiles of CRC and AA patients were similar and could be clearly separated from control individuals. Among the 25 significant metabolites, sphingomyelins (SM), lactosylceramides (LacCer), secondary bile acids, polypeptides, formiminoglutamate, heme and cytidine-containing pyrimidines were found to be dysregulated in CRC patients. Supervised random forest (RF) and logistic regression algorithms were employed to build a CRC accurate predicted model consisting of the combination of hemoglobin (Hgb) and bilirubin E,E, lactosyl-N-palmitoyl-sphingosine, glycocholenate sulfate and STLVT with an accuracy, sensitivity and specificity of 91.67% (95% Confidence Interval (CI) 0.7753–0.9825), 0.7 and 1, respectively.
【 授权许可】
Unknown