Dipg-49. a systems biology approach to defining and targeting cell state-specific master regulator dependencies in diffuse midline glioma

Abstract Diffuse Midline Glioma (DMG) are fatal pediatric brain tumors. We leveraged network-based methodologies to dissect the heterogeneity of DMG tumors and to discover Master Regulator (MR) proteins representing pharmacologically accessible, mechanistic determinants of molecularly distinct cell states. We produced a DMG regulatory network from 122 publicly available RNAseq profiles with ARACNe, and inferred sample-specific MR protein activity with VIPER. A CRISPR/Cas9 KO screen across 3 DMG patient cell lines identified a set of 73/77 essential genes that were enriched in the MR signature of 80% of patient samples (GSEA p=0.000034). FOXM1 emerged as an essential MR, significantly activated across virtually all patients. We then generated RNAseq profiles following perturbation with ~300 oncology drugs in 2 DMG cell lines most representative of patient MR signatures, and used this to identify drugs that invert patient MR activity profiles using the NYS/CA Dept.of Health approved OncoTreat algorithm. OncoTreat predicted sensitivity to HDAC, MEK, CDK, PI3K, and proteosome inhibitors in subsets of patients. 80%of OncoTreat-predicted drugs (p<10-5) from 3 DMG patient tumor biopsies showed in vitro sensitivity in cultured tumor cells from the respective patients, with overall 68% accuracy among 223 drugs evaluated by both OncoTreat and in vitro (Fisher’s Exact Test p=0.0449). Further analysis of DMG intra-tumor heterogeneity via protein activity inference from published scRNAseq profiles identified 6 tumor clusters with unique MR signatures representing distinct cellular states. Targetable MRs and OncoTreat-predicted drugs were distinct between these states. Bulk RNAseq analysis recapitulated predictions seen in the more prevalent Oligodendrocyte progenitor cell-like states, but failed to capture MR and drug predictions for the Astrocyte-like states. Ongoing validations of cell state-specific drug predictions in vivo in subcutaneous patient-derived xenograft and orthotopic syngeneic DMG models have already shown tumor volume and subpopulation differences (e.g. Trametinib-treated). This provides a platform to nominate much-needed novel drugs to treat DMG.