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Background: Intestinal bacteria significantly contribute to the metabolism of intestinal epithelial tissues. As the occurrence and development of radiation enteritis (RE) depend on the “co-metabolism” microenvironment formed by the host and intestinal microbiota, which involves complex influencing factors and strong correlations, ordinary techniques struggle to fully explain the underlying mechanisms. However, given that it is based on systems biology, metabolomics analysis is well-suited to address these issues. This study aimed to analyze the metabolomic changes in urine, serum, and fecal samples during volumetric modulated arc therapy (VMAT) for cervical cancer and screen for characteristic metabolites of severe acute radiation enteritis (SARE) and RE. Methods: We enrolled 50 patients who received radiotherapy for cervical cancer. Urine, serum, and fecal samples of patients were collected at one day before radiotherapy and the second week, fourth week, and sixth week after the start of radiotherapy. Control group samples were collected during the baseline period. Differential metabolites were identified by metabolomics analysis; co-metabolic pathways were clarified. We used the mini-SOM library for incorporating characteristic metabolites, and established metabolite classification models for predicting SARE and RE. Results: Urine and serum sample data showed remarkable clustering effect; metabolomics data of the fecal supernatant were evidently disturbed. Patient sample analyses during VMAT revealed the following. Urine samples: Downregulation of the pyrimidine and riboflavin metabolism pathways as well as initial upregulation followed by downregulation of arginine and proline metabolism pathways and the arginine biosynthesis pathway. Fecal samples: Upregulation of linoleic acid and phenylalanine metabolic pathways and initial downregulation followed by upregulation of arachidonic acid (AA) metabolic pathways. Serum samples: Initial upregulation followed by downregulation of the arginine biosynthesis pathway and downregulation of glutathione, AA, and arginine and proline metabolic pathways. Conclusion: Patients with cervical cancer exhibited characteristic metabolic pathways and characteristic metabolites predicting RE and SARE were screened out. An effective RE mini-SOM classification model was successfully established. |
