RESUMO
Background: Colorectal cancer (CRC) is one of the most common malignant tumors with recurrence and metastasis after surgical resection. This study aimed to identify the physiological changes after surgery and explore metabolites and metabolic pathways with potential prognostic value for CRC. Methods: An ultra-high-performance liquid chromatography Q-exactive mass spectrometry was used to profile serum metabolites from 67 CRC patients and 50 healthy volunteers. Principal component analysis (PCA) and orthogonal projections to latent structures-discriminant analysis were used to distinguish the internal characteristics of data in different groups. Multivariate statistics were compiled to screen the significant metabolites and metabolic pathways. Result: A total of 180 metabolites were detected. Under the conditions of variable importance in projection >1 and p-value <0.05, 46 differentially expressed metabolites were screened for further pathway enrichment analysis. Based on the Kyoto Encyclopedia of Genes and Genomes database and Small Molecule Pathway Database, three metabolic pathways-arginine and proline metabolism, ascorbate and aldarate metabolism, and phenylalanine metabolism-were significantly altered after surgical resection and identified as associated with the removal of CRC. Notably, gamma-linolenic acid was upregulated in the CRC preoperative patients compared with those in healthy volunteers but returned to healthy levels after surgery. Conclusion: Through serum-based metabolomics, our study demonstrated the differential metabolic characteristics in CRC patients after surgery compared with those before surgery. Our results suggested that metabonomic analysis may be a powerful method for exploring physiological alterations in CRC patients after surgery as well as a useful tool for identifying candidate biomarkers and monitoring disease recurrence.
RESUMO
BACKGROUND: The screening and early detection of colorectal cancer (CRC) still remain a challenge due to the lack of reliable and effective serum biomarkers. Thus, this study is aimed at identifying serum biomarkers of CRC that could be used to distinguish CRC from healthy controls. METHODS: A prospective 1 : 2 individual matching case-control study was performed which included 50 healthy control subjects and 98 CRC patients. Untargeted metabolomic profiling was conducted with liquid chromatography tandem mass spectrometry (LC-MS/MS) to identify CRC-related metabolites and metabolic pathways. RESULTS: In total, 178 metabolites were detected, and an orthogonal partial least-squares-discriminant analysis (OPLS-DA) model was useful to distinguish CRC patients from healthy controls. Nine metabolites showed significantly differential serum levels in CRC patients under the conditions of variable importance in projection (VIP) > 1, p < 0.05 using Student's t-test, and fold change (FC) ≥ 1.2 or ≤0.5. The above nine metabolites were 3-hydroxybutyric acid, hexadecanedioic acid, succinic acid semialdehyde, 4-dodecylbenzenesulfonic acid, prostaglandin B2, 2-pyrocatechuic acid, xanthoxylin, 12-hydroxydodecanoic acid, and formylanthranilic acid. Four potential biomarkers were identified to diagnose CRC through ROC curves: hexadecanedioic acid, 4-dodecylbenzenesulfonic acid, 2-pyrocatechuic acid, and formylanthranilic acid. All AUC values of these four serum biomarkers were above 0.70. In addition, the exploratory analysis of metabolic pathways revealed the activated states for the vitamin B metabolic pathway and the alanine, aspartate, and glutamate metabolic pathways associated with CRC. CONCLUSION: The 4 identified potential metabolic biomarkers could discriminate CRC patients from healthy controls, and the 2 metabolic pathways may be activated in the CRC tissues.