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. 2019 Feb 11;15(1):21-29.
doi: 10.1039/c8mo00158h.

Exploratory metabolomic study to identify blood-based biomarkers as a potential screen for colorectal cancer

Affiliations

Exploratory metabolomic study to identify blood-based biomarkers as a potential screen for colorectal cancer

Isaac Asante et al. Mol Omics. .

Abstract

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.

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Conflict of interest statement

Conflicts of Interest

There are no conflicts of interest to declare.

Figures

Figure 1:
Figure 1:
PCA-DA plots showing the clustering the CRC cases (red) from the Controls (blue) using either (a&c) untargeted scan or (b&d) targeted scan. The left pane (a&b) shows the loadings of the plasma samples while the right (c&d) shows the loadings of the features/ metabolites.
Figure 2:
Figure 2:
Volcano plot of controls versus CRC cases showing the log[p-values] against the log[fold change] of mean intensity of features in the two groups. All logarithms have the base of 10. The features that are significantly higher by at least 100- fold in CRC cases are shown in red triangles and those significantly higher by at least 100-fold in controls are shown in blue circles..
Figure 3:
Figure 3:
Box plots showing the plasma concentrations of: (a) THF; (b) 5MTHF; (c) FA; (d) B2; (e) 4PA and (f) PL in CRC cases and controls.
Figure 4
Figure 4
Box plots showing: (a) plasma concentration of SAM; (b) Methylation capacity; (c) plasma concentration of MMA; (d) ratio of FA to THF conversion [indicative of DHFR activity]; (e) Folate distribution and (f) normalized folate distribution compared in CRC cases and controls.

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