A Biobank Of Similar To 100 Patient-Derived Models Representing Biological Heterogeneity And Distinct Therapeutic Dependencies In Paediatric High Grade Glioma And Dipg

Abstract Paediatric high-grade glioma comprise multiple biological and clinical subgroups, the majority of which urgently require novel therapies. Patient-derived models represent useful tools for mechanistic and preclinical investigations based upon their retention of key genetic/epigenetic features and their amenability to high-throughput approaches. We have collected ~100 in vitro models representing multiple subtypes (H3.3/H3.2/H3.1K27M, H3.3G34R/V, BRAF, MYCN_amp, NTRK_fusion, hypermutator, others) established under 2D (laminin) and/or 3D (neurosphere) conditions, credentialed by phenotypic (growth, invasion/migration) and molecular (methylation array, DNA sequencing, RNAseq) comparison to the original tumour sample. These were derived from patients at our local hospitals (n=29), as part of national co-clinical trials (n=19), from international collaborating centres (n=11), or shared directly by research groups worldwide (n=45). These have variously been subjected to pharmacological (approved/experimental drug libraries) and/or genetic screening (whole-genome CRISPR) to identify specific biological dependencies. Many have been established as orthotopic xenografts in vivo (PDX), with detailed pathological and radiological correlations with the clinical disease, and with tumorigenic latencies ranging from 48–435 days. This resource has allowed us to identify genotype-specific synthetic lethalities and responses to targeted inhibitors, including olaparib (PARP) with ATRX, nutlin-3 (MDM2) with PPM1D, AZD1775 (WEE1) with TP53, and CYC065 (CDK9) with MYCN-amplification. Combinatorial screening highlighted synergies in ACVR1-mutant DIPG between novel ALK2 inhibitors and ONC201 (DRD2). Rapid screening allows for feedback of drug sensitivities to treating clinicians at relapse, whilst mechanistic underpinning of these interactions and use of the models to identify specific mediators of resistance will allow for rational future trial design.