Introduction: Glioblastoma (GBM) is a lethal disease without effective treatments. To advance toward effective therapeutic approaches that are biomarker driven, we need new targeted agents and to develop accurate preclinical cell line models that encompass its cellular and molecular diversity. Experimental Procedures: To identify molecular targets and therapies we profiled across 78 GBM cell lines 381 drugs described in the Cancer Therapeutics Response Portal (CTRP) at 16 different duplicated concentrations. The cell lines consisted of two different models: patient-derived GBM cell lines (PDGCL) and long-term GBM cell lines (LTGCL), the latter of which were previously included in the Cancer Cell Line Encyclopedia (CCLE). Comprehensive characterization of copy number changes, mutations (whole exome sequencing), gene and protein expression was performed. After integrating and correlating systematically molecular alterations with drug sensitivities we yielded 7,948,422 pharmacogenomic interactions. Results: PDGCLs preserve neural and glial marker heterogeneity and exhibit all allelic imbalances seen in human GBMs better than in LTGCLs. All genes known to undergo frequent (>5%) driver mutations among GBMs exhibited at least one mutation among cell lines, with the exception of IDH1. PDGCLs enrich for the proneural molecular phenotype while LTGCL models exhibit mesenchymal expression programs. Among pharmacogenomic interactions NAMPT inhibitors were one of the most active compounds and revealed dependencies associated with enzymatic activities. Cell lines TP53 wild type, overexpressing CDKN1A and OLIG2 were sensitive to MDM2 inhibitors (Nutlins). Testing new MDM2 inhibitors validate “in vitro” previous findings, show increased drug potency, and block tumor growth in intracranial xenografts models. TP53 mutant lines exhibit a lower overall response to the panel of 381 targeted drugs. However, simultaneous genetic disruption of TP53, CDKN2A, and CHK2 trigger a synthetic lethal interaction. The CHK1/2 chemical inhibitor results were phenocopied by shRNA suppression of CHK2. Furthermore, response to chemical inhibitors of proteins involved in G2M checkpoint (ATM/ATR, WEE1, and CDK1 inhibitors) was significantly correlated with response to a CHK1/2 inhibitor. AZD-7762 response and predictive genotypes were associated by gene set enrichments related with E2F targets and G2M checkpoint. Next we identified vulnerabilities involving mutually exclusive complementary functional associations. Mutations in different genes of the PI3K holo-enzyme complex predict sensitivity to a PIK3 inhibitor. Our results suggest that associations between genomic features and response to monotherapies can help to identify effective drug combinations in biomarker-defined subpopulations. As proof of concept we found that proper combination of rationally targeted anticancer therapies displays synergistic effects in right genetic context and the specific molecular insults. Conclusion: Our analyses suggest pharmacologic strategies for genetic subgroups of GBMs and provide molecular insights to drive targeted therapies in the new era of precision medicine.

Citation Format: Ruben Ferrer-Luna, Shakti H. Ramkissoon, Lori A. Ramkissoon, Kristine Pellton, Steven E. Schumacher, Rebecca Lamothe, Jaime H. Cheah, Sam Haidar, Yun J. Kang, David S. Knoff, Cecile L. Maire, Karl H. Olausson, Wenyu Song, Ahmed Idbaih, Mikael L. Rinne, David A. Reardon, Patrick Y. Wen, Paul A. Clemons, Stuart L. Schreiber, Alykhan J. Shamji, Rameen Beroukhim, Keith L. Ligon. Comprehensive molecular characterization and high-throughput chemical screening identifies genetic dependencies and molecular vulnerabilities in glioblastoma cell line models [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; 2017 Oct 26-30; Philadelphia, PA. Philadelphia (PA): AACR; Mol Cancer Ther 2018;17(1 Suppl):Abstract nr B077.