New Study Published on Metabolite Biomarkers for Predicting Cabozantinib Efficacy in Advanced Renal Cell Carcinoma

A research group including Assistant Professor Izumi Sakamoto, Associate Professor Yoshihide Kawasaki, and Professor Akihiro Ito from the Department of Urology at Tohoku University Graduate School of Medicine, alongside Assistant Professor Eiji Hishinuma (Clinical Phenome Group) and Associate Professor Masamitsu Maekawa (Clinical Pharmacogenomics and Drug Discovery Group) from INGEM, conducted metabolomic analysis using serum from patients with advanced renal cell carcinoma. The team identified candidate metabolite biomarkers to predict the therapeutic efficacy of the molecular targeted drug cabozantinib and validated their utility through experiments using renal cancer cell lines.

Although cabozantinib is widely used as a standard treatment for advanced renal cell carcinoma, therapeutic efficacy varies significantly among individual patients, and no reliable biomarker has been established to predict its effectiveness prior to administration. Consequently, there is a strong demand for new indicators that can predict drug efficacy before treatment onset, enabling the selection of optimal personalized therapeutic approaches.

In this study, untargeted metabolomic analysis using liquid chromatography-mass spectrometry was performed on pre-treatment serum samples from 19 patients with advanced renal cell carcinoma. The results identified seven metabolic pathways associated with poor therapeutic response (methylhistamine metabolism, caffeine metabolism, β-alanine metabolism, histidine metabolism, glycine/serine metabolism, tryptophan metabolism, and purine metabolism) and five specific metabolites (methylhistidine, kynurenic acid, xanthine, 7-methylxanthine, and 2-amino-3-oxobutanoic acid). Furthermore, by establishing cabozantinib-resistant renal cancer cell lines and conducting targeted metabolomic analysis, the researchers confirmed that these metabolic pathways and metabolites are directly linked to drug resistance. They also constructed a predictive model for poor therapeutic response by combining the five identified metabolites.

These research findings demonstrate the potential of pre-treatment serum metabolomic analysis to predict the therapeutic efficacy of cabozantinib. Although further validation in larger patient cohorts is required, these results are expected to contribute significantly to the realization of personalized medicine in advanced renal cell carcinoma and its application to Future medicine, enabling the selection of optimal treatments tailored to individual patients.

This paper was published online in Cancer Medicine on July 31, 2026.