Plasma Endogenous Metabolome as Superior Biomarkers for
Chemotherapy-Related Adverse Effects Compared to Drug and Its
Metabolites: A Proof of Concept Study
Abstract
Background: Adverse effects resulting from Capecitabine-based
chemotherapy pose a significant concern in clinical practice. While the
pharmacokinetics (PK) approach has been commonly used to investigate the
toxicity of Capecitabine, its predictive ability remains limited. This
study aims to assess whether pre-chemotherapy endogenous plasma
metabolome can offer improved predictive values for Capecitabine
chemotherapy-related adverse events (CRAEs). Methods: Plasma samples
were collected from colorectal cancer patients at different time points:
0 hours (before), and 1, 2.5, 4 hours after oral Capecitabine
administration, to assess individual variations in exposure levels of
Capecitabine and its metabolites. Additionally, the endogenous
metabolome profile was analyzed using UHPLC-MS/MS and UHPLC/Q-TOF-MS.
Results: Capecitabine and its metabolites can predict two CRAEs, with
5-FU, 5’-DFCR, and FUH2 exposures being associated with diarrhea and
thrombocytopenia, respectively. In contrast, identified plasma
engougenous biomarker metabolites can predict all seven observed CRAEs.
These CRAE-related endogenous plasma metabolites are involved in various
physiological functions, including cell proliferation, maintenance, and
inflammation. Pre-chemotherapy endogenous plasma metabolites established
superior predictive performance for CRAEs (AUROC values ranging from
0.834 to 0.984) compared to conventional drug exposure (AUROC values
ranging from 0.737 to 0.773). Additionally, the endogenous plasma
metabolome demonstrated a strong correlation with Capecitabine and its
metabolite exposures. Conclusions: Our study demonstrates that
pre-chemotherapy endogenous plasma metabolome serve as superior
biomarkers for predicting Capecitabine-related adverse effects,
surpassing the value of exposures to Capecitabine and its metabolites.
This finding holds significant potential in guiding personalized
medicine approaches.