TP53 and RB1 are predictive genetic biomarkers for sensitivity to cytarabine in gliomas

Abstract

Therapeutic progress in glioma, one of the most lethal human cancers, has been limited by molecular heterogeneity and lack of biomarker-driven drug deployment. Here we used a proprietary large-scale CRISPRi screening in primary patient-derived glioma tumorspheres to identify genetic vulnerabilities and nominate pharmacologically tractable targets. DNA polymerase-linked dependencies emerged as top-ranked hits, which we validated through orthogonal viability assays. Network-based integration of dependency data with drug-target relationships nominated cytarabine, a nucleoside analogue already approved for intrathecal use, as a candidate agent targeting this axis. Dose-response profiling across molecularly diverse glioma models revealed substantial heterogeneity in cytarabine sensitivity (IC50 range: 0.04-9.8 {micro}M). Machine learning analysis of whole-genome sequencing data identified TP53 wild-type and RB1-wild-type status as dominant predictors of response, with double wild-type lines showing three standard deviations (3 s.d.) increased sensitivity compared to altered models. Prospective validation in an independent cohort confirmed that TP53/RB1 genotype stratifies cytarabine activity. These findings establish a mechanistically anchored, biomarker-restricted repurposing opportunity for cytarabine in leptomeningeal glioma, enabling rational prioritisation of an accessible therapy in a molecularly defined patient subset.