Abstract
BACKGROUND: Oxaliplatin-induced peripheral neuropathy (OIPN) is an important adverse reaction in patients with gastric cancer treated with oxaliplatin, but there is no objective biomarkers for changes in OIPN in patients after multiple rounds of chemotherapy. This research aimed to identify serum metabolic biomarkers using longitudinal untargeted metabolomics for early detection of OIPN progression in gastric cancer patients receiving repeated chemotherapy. METHODS: Eighty-four serum samples of the same gastric cancer patient (n=42) before and after receiving oxaliplatin chemotherapy twice were collected. The metabolic profiles of serum samples were acquired using an untargeted metabolomics approach based on ultra-high-performance liquid chromatography-Q-Exactive Orbitrap tandem mass spectrometry (UHPLC-Q-Exactive Orbitrap-MS/MS). Multivariate statistical analysis, receiver operating characteristic (ROC) curve analysis, SHapley Additive exPlanations (SHAP) analysis, and pathway enrichment analysis were used to identify potential biomarkers and metabolic pathways. RESULTS: A total of 16 differentially expressed metabolites (DEMs) were screened in discovery set, which belonged to amino acids and derivatives, lipids and derivatives, organic acids and derivatives, and others, mainly involved in amino acid metabolism, lipid metabolism, and nervous system metabolism. Four DEMs (including norepinephrine, 9,10-DHOME, 5-hydroxyindoleacetic acid, and procollagen 5-hydroxy-lysine) showed certain predictive ability for OIPN in the same gastric cancer patient before and after receiving oxaliplatin chemotherapy twice. Thirty-three DEMs were discovered in validation set, notably, norepinephrine emerged as a metabolite exhibiting consistent and notable statistical differences in both the discovery and validation sets. CONCLUSIONS: These findings demonstrate the alterations of serum metabolic profiles in patients before and after receiving oxaliplatin chemotherapy, which may deliver valuable biomarkers for early identification and outcome prediction of OIPN progression.