Frontiers in Pharmacology (Sep 2022)

Systematic evaluation of irinotecan-induced intestinal mucositis based on metabolomics analysis

  • Qing-Qing Yu,
  • Qing-Qing Yu,
  • Heng Zhang,
  • Shiyuan Zhao,
  • Dadi Xie,
  • Haibo Zhao,
  • Weidong Chen,
  • Min Pang,
  • Baoqin Han,
  • Baoqin Han,
  • Pei Jiang

DOI
https://doi.org/10.3389/fphar.2022.958882
Journal volume & issue
Vol. 13

Abstract

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Chemotherapy-induced intestinal mucositis (CIM) is a major dose-limiting side effect of chemotherapy, especially in regimens containing irinotecan (CPT-11). Several studies on the pathologic mechanisms of CIM focused on both the genomics and molecular pathways triggered by chemotherapy. However, systematic evaluation of metabolomic analysis in irinotecan-induced intestinal mucositis (IIM) has not been investigated. This study aimed to comprehensively analyze metabolite changes in main tissues of IIM mouse models. Male ICR mice were assigned to two groups: the model group (n = 11) treated with CPT-11 (20 mg/kg daily; i.p.) and the control group (n= 11) with solvent for 9 days. Gas chromatography-mass spectrometry (GC-MS) was used to investigate the metabolic alterations in the serum, intestinal, colonic, hepatic, and splenic samples of mice between two groups by multivariate statistical analyses, including GC–MS data processing, pattern recognition analysis, and pathway analysis. Forty-six metabolites, including hydrocarbons, amino acids, lipids, benzenoids, hydroxy acids, and amines, had significant changes in levels in tissues and sera of IIM mouse models. The most important pathways related to the identified metabolites were the glycerolipid metabolism in the colon and aminoacyl-tRNA biosynthesis; glycine, serine, and threonine metabolism; and glyoxylate and dicarboxylate metabolism in the liver. Our study firstly provided a comprehensive and systematic view of metabolic alterations of IIM using GC-MS analysis. The characterizations of metabolic changes could offer profound and theoretical insight into exploring new biomarkers for diagnosis and treatment of IIM.

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