CAN-Scan: A multi-omic phenotype-driven precision oncology platform identifies prognostic biomarkers of therapy response for colorectal cancer.

ABSTRACT: Application of machine learning (ML) on cancer-specific pharmacogenomic datasets shows immense promise for identifying predictive response biomarkers to enable personalized treatment. We introduce CAN-Scan, a precision oncology platform, which applies ML on next-generation pharmacogenomic datasets generated from a freeze-viable biobank of patient-derived primary cell lines (PDCs). These PDCs are screened against 84 Food and Drug Administration (FDA)-approved drugs at clinically relevant doses (C_max), focusing on colorectal cancer (CRC) as a model system. CAN-Scan uncovers prognostic biomarkers and alternative treatment strategies, particularly for patients unresponsive to first-line chemotherapy. Specifically, it identifies gene expression signatures linked to resistance against

SUBMITTER: Chia S 

PROVIDER: S-EPMC12047494 | biostudies-literature | 2025 Apr

REPOSITORIES: biostudies-literature