INTRODUCTION: colorectal cancer (CRC) continues to be difficult to diagnose due to the lack of reliable and predictive biomarkers. OBJECTIVE: to identify blood-based biomarkers that can be used to distinguish CRC cases from controls. METHODS: a workflow for untargeted followed by targeted metabolic profiling was conducted on the plasma samples of 26 CRC cases and ten healthy volunteers (controls) using liquid chromatography-mass spectrometry (LCMS). The data acquired in the untargeted scan was processed and analyzed using MarkerView™ software. The significantly different ions that distinguish CRC cases from the controls were identified using a mass-based human metabolome search. The result was further used to inform the targeted scan workflow. RESULTS: the untargeted scan yielded putative biomarkers some of which were related to the folate-dependent one-carbon metabolism (FOCM). Analysis of the targeted scan found the plasma levels of nine FOCM metabolites to be significantly different between cases and controls. The classification models of the cases and controls, in both the targeted and untargeted approaches, each yielded a 97.2% success rate after cross-validation. CONCLUSION: we have identified plasma metabolites with screening potential to discriminate between CRC cases and controls.
INTRODUCTION:colorectal cancer (CRC) continues to be difficult to diagnose due to the lack of reliable and predictive biomarkers. OBJECTIVE: to identify blood-based biomarkers that can be used to distinguish CRC cases from controls. METHODS: a workflow for untargeted followed by targeted metabolic profiling was conducted on the plasma samples of 26 CRC cases and ten healthy volunteers (controls) using liquid chromatography-mass spectrometry (LCMS). The data acquired in the untargeted scan was processed and analyzed using MarkerView™ software. The significantly different ions that distinguish CRC cases from the controls were identified using a mass-based human metabolome search. The result was further used to inform the targeted scan workflow. RESULTS: the untargeted scan yielded putative biomarkers some of which were related to the folate-dependent one-carbon metabolism (FOCM). Analysis of the targeted scan found the plasma levels of nine FOCM metabolites to be significantly different between cases and controls. The classification models of the cases and controls, in both the targeted and untargeted approaches, each yielded a 97.2% success rate after cross-validation. CONCLUSION: we have identified plasma metabolites with screening potential to discriminate between CRC cases and controls.
Authors: Maria Pufulete; Reyad Al-Ghnaniem; Andrew J M Leather; Paul Appleby; Sally Gout; Catherine Terry; Peter W Emery; Thomas A B Sanders Journal: Gastroenterology Date: 2003-05 Impact factor: 22.682
Authors: M Pufulete; R Al-Ghnaniem; J A Rennie; P Appleby; N Harris; S Gout; P W Emery; T A Sanders Journal: Br J Cancer Date: 2005-03-14 Impact factor: 7.640
Authors: Guoxue Zhu; Yi Wang; Wang Wang; Fang Shang; Bin Pei; Yang Zhao; Desong Kong; Zhimin Fan Journal: Front Oncol Date: 2021-11-04 Impact factor: 6.244