DDDR-79. A novel, pooled, high-throughput screening of a CNS penetrant compound library identifies potential biomarker-driven therapeutics for glioblastoma

Abstract Identifying drug sensitivities that will translate to clinical practice for patients with glioblastoma (GBM) necessitates the use of a variety of cell models that recapitulate the heterogeneity of the disease. Screening of large drug libraries against numerous models is challenging due to both cost and complexity. We utilized a barcode-labeled, pooled system (CARPOOL) of a 23-member set of genomically characterized glioma spheroid cell (GSC) models to evaluate the in vitro response of a library of 728 brain-penetrant compounds. Responses were validated using individual, representative GSCs. The library included 164 drugs associated with oncologic applications, and almost two-thirds of the compounds have been or are currently in clinical development. A total of 450 (61.8%) showed response in at least a subset of models, with only 8 (1.8%) demonstrating broad vs. selective/differential response. Of the drugs previously unknown in oncology, 299 (53%) exhibited differential responses across the GSCs. Clustering compounds based on response across GSCs closely grouped those with shared mechanisms of action. Interestingly, potential, often novel, off-target responses were identified, including TIC10 (ONC201, dordaviprone) clustering with microtubule inhibitors, and an NPY1R inhibitor clustering with an MDM2-p53 inhibitor. Further genomic analyses identified specific associations with response, both previously known and novel, including RB1 mutation and alterations in response to CDK4/6 inhibitors. Interrogation of reverse phase protein array (RPPA) data from the GSCs identified associations between drug response and protein levels, such as Cyclin E1 levels with CDK4/6 response, and phosphorylated c-Raf with histone deacetylase inhibitor response. Furthermore, select compounds were tested in combination with radiotherapy to identify potential radiosensitizers that could enhance therapeutic synergy. Our study presents a novel approach for advancing drug discovery for rapid preclinical evaluation and identifies not only responding subsets but also potential selective, molecular biomarkers for downstream incorporation into clinical trials.