Metabolic profiling analysis for clinical urine of colorectal cancer

Aim To demonstrate the little-known metabolic changes and pathways in patients with colorectal cancer (CRC). Methods We used gas chromatography time-of-flight mass spectrometry (GC-TOF/MS) to perform metabolic profiling of urine samples from 163 consecutive patients with CRC and 111 healthy controls without history of gastrointestinal tumors. The metabolic profiles were assayed using multivariate statistical analysis and one-way analysis of variance, and further analyzed to identify potential marker metabolites related to CRC. The GC-TOF/MS-derived models showed clear discriminations in metabolic profiles between the CRC group and healthy control group. Results We demonstrated that 15 metabolites contributed to the differences. Among them, eleven metabolites were significantly upregulated, while other four metabolites were downregulated in the urine samples of CRC patients compared with healthy controls. Pathway analysis revealed changes in energy metabolism of patients with CRC, which are reflected in the upregulation of glycolysis and amino acid metabolism and the downregulation of lipid metabolism. Our study revealed the metabolic profile of urine from CRC patients and indicated that GC-TOF/MS-based methods can distinguish CRC from healthy controls. Conclusion GC-TOF/MS-based metabolomics has the potential to be developed into a novel, non-invasive, and painless clinical tool for CRC diagnosis, and may contribute to an improved understanding of disease mechanisms.

Automated summary

This study aimed to demonstrate the metabolic changes and pathways in patients with colorectal cancer through urine metabolic profiling using GC-TOF/MS. The results showed clear discriminations in metabolic profiles between CRC patients and healthy controls, with significant upregulation of glycolysis and amino acid metabolism and downregulation of lipid metabolism in CRC patients. GC-TOF/MS-based metabolomics has the potential to be a novel, non-invasive tool for CRC diagnosis and understanding disease mechanisms.