Abstract B005: Accelerating epigenetic vulnerability mapping for drug-repurposing and combination design in glioblastoma

Abstract Glioblastoma is the most common and most lethal primary brain tumour in adults. Despite decades of intensive research, standard-of-care therapy has remained largely unchanged, with all patients experiencing recurrence and a median survival of ∼15 months. Glioblastoma hijacks developmental programmes and contains a population of glioma-initiating cells (GICs) that repopulate the tumour following surgery and exhibit stem-like properties, including self-renewal and therapeutic resistance. Neural stem cells (NSCs) are considered a likely cell of origin for glioblastoma and represent the closest non-malignant comparator to GICs. We previously demonstrated that epigenetic and transcriptional comparison of patient-derived GICs to syngeneic induced NSCs (iNSCs), a strategy we term SYNGN, can identify patient-specific therapeutic vulnerabilities with low predicted toxicity to normal neural cells. However, clinical translation of SYNGN requires a substantially accelerated workflow capable of delivering safe and effective drug-repurposing predictions within a clinically actionable timeframe. Here, we present an updated and streamlined SYNGN pipeline incorporating Sendai virus–based reprogramming of patient-matched fibroblasts and peripheral blood mononuclear cells (PBMCs). This approach reduces iNSC derivation time from ∼4.5 months to under 2 months, while PBMC reprogramming enables pre-operative sampling, further shortening the time to therapeutic prediction. Reprogrammed iPSCs and iNSCs were validated by immunofluorescence and qPCR, followed by RNA-sequencing and DNA methylation profiling. Differential expression and methylation analyses between GICs and syngeneic iNSCs were used to identify concurrently upregulated and hypomethylated target genes, which were then leveraged to nominate candidate repurposed drugs based on novelty, FDA-approval status, and blood–brain barrier penetrance. Given the lack of therapeutic options for recurrent glioblastoma, we focused validation efforts on recurrent GIC models. Predicted candidate drugs were tested using in vitro growth assays and in vivo orthotopic xenograft models, demonstrating robust anti-tumour activity. Finally, to address glioblastoma’s extreme intratumoural heterogeneity and epigenetic plasticity, we explore two strategies to rationally design combination therapies. First, we screen our bulk-generated SYNGN drug repurposing predictions and mine the scientific literature for evidence of their synergistic combination in other cancer settings. Second, we use single cell transcriptome and methylome profiling to perform subpopulation-specific drug repurposing predictions and design therapy combinations to concurrently target multiple tumour subpopulations. Validation of rationally designed combinations is ongoing using in vitro and 3D organoid co-culture synergy assays. Collectively, this work establishes a scalable experimental and analytical framework to support epigenetic drug repurposing and combination therapy design in glioblastoma, laying the groundwork for future precision-medicine trials. Citation Format: James G. Nicholson, Sara Lucchini, Xinyu Zhang, Agatha Ryabova, Yau Lim, Niamh Baker, Thomas Millner, Sebastian Brandner, Silvia Marino. Accelerating epigenetic vulnerability mapping for drug-repurposing and combination design in glioblastoma [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Brain Cancer; 2026 Mar 23-25; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2026;86(6_Suppl):Abstract nr B005.