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

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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 (IC 50 range: 0.04-9.8 µM). 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.

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