GC-MS and multivariate analysis reveal partial serum metabolome restoration by bevacizumab in a colon cancer rat model: An untargeted metabolomics investigation.

Abstract

Bevacizumab is an anti-angiogenic therapeutic agent that targets vascular endothelial growth factor (VEGF) and has been approved for the treatment of several types of cancer, including colon cancer. Herein, a GC-MS based metabolomics approach was employed to investigate the impact of bevacizumab on the serum metabolome of colon cancer rats. Multivariate chemometric analysis models such as PCA and PLS-DA showed a clear separation between the control, cancer and bevacizumab-treated groups, suggesting that bevacizumab administration induced significant metabolic alterations. Furthermore, pairwise comparisons between the studied groups using the OPLS-DA model in addition to univariate analysis identified several discriminatory metabolites belonged to various chemical classes including amino acids, organic acids and fatty acids that were perturbed between the studied groups. Interestingly, bevacizumab treatment was able to partially restore some of the cancer-induced metabolic disturbances, indicating its potential therapeutic efficacy via improving the tumor vasculature and nutrient delivery. Besides, pathway analysis of the differential metabolites identified key metabolic pathways affected by bevacizumab, which included valine, leucine and isoleucine metabolism, pyruvate metabolism and butanoate metabolism. However, little effects were observed on lipid metabolites such as palmitic acid and stearic acid and consequently their related metabolic pathways such as fatty acid biosynthesis metabolism suggesting that bevacizumab has more prominent effect on energy and amino acid metabolisms as compared to fatty acid metabolism in colon cancer rats. Overall, our study provided novel insights into the metabolic mechanisms underlying the therapeutic effects of bevacizumab in colon cancer rats via the use of a comprehensive GC-MS metabolomics approach.