Digital patient modeling identifies predictive biomarkers of regorafenib response in elderly metastatic colorectal cancer.

ABSTRACT: In silico clinical trials that simulate individualized mechanisms of action offer a powerful approach to assess drug efficacy across large and diverse patient populations, while also enabling the identification of predictive biomarkers. In this study, we conducted an in silico clinical trial of first-line, single-agent regorafenib in 399 elderly patients with metastatic colorectal cancer (mCRC). Individualized network-based models were constructed using patient-specific differential transcriptomic profiles and employed to simulate the target-specific effects of regorafenib. From this analysis, we identified both predictive and mechanistic biomarkers of treatment response. Notably, four proteins-MARK3, RBCK1, LHCGR, and HSF1-emerged as dual biomarkers, showing associati

SUBMITTER: Garcia-Illarramendi JM 

PROVIDER: S-EPMC12477164 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature