CBIO-27. INTEGRATED FUNCTIONAL AND MOLECULAR CHARACTERIZATION OF THE INTRINSIC APOPTOTIC MACHINERY IDENTIFIES THERAPEUTIC VULNERABILITIES IN GLIOBLASTOMA. (12th November 2021)

• Record Type: Journal Article
• Authors: Fernandez, Elizabeth; Mia, Wilson; Bayley, Nicholas; Zhu, Henan; Tse, Christopher; Liau, Linda; Cloughesy, Timothy; Nathanson, David
• Is Part Of: Neuro-oncology. Volume 23: Supplement 6(2021)
• Page Start: vi32
• Page End: vi32
• Publication Date: 2021-11-12
• Subjects: Brain Neoplasms -- Periodicals; Brain -- Tumors -- Periodicals; Brain -- Cancer -- Periodicals; Nervous system -- Cancer -- Periodicals; 616.99481
• DOI: 10.1093/neuonc/noab196.125
• Languages: English
• ISSNs: 1522-8517

Abstract

Abstract: Molecular profiling frequently fails to predict therapeutic outcomes in cancer. This is in part due to the myriad of genetic alterations comprising a tumor which enable rapid rewiring of cancer signaling pathways. Functional profiling ascertains signaling dynamics and has emerged as an alternative method to predict drug responses. It is unknown whether incorporating molecular with functional profiling offers superior insight into specific tumor dependencies and consequently therapeutic susceptibilities. Here we performed integrated molecular and functional characterization (via BH3 profiling) of the intrinsic apoptotic machinery in 50 GBM patient specimens. We found that treatment with standard of care (e.g., temozolomide or radiation) rewired the apoptotic machinery in a p53 dependent manner, eliciting an exclusive survival dependency on BCL-xL in a genetically defined subset of GBM tumors. However, functional BH3 profiling of 'apoptotic priming' was required to predict response to combined IR/TMZ and BCL-xL inhibition in p53 WT GBM tumors. Accordingly, a composite of genetic and functional profiling predicted the response of patient derived GBM models to IR/TMZ with a novel GBM specific BCLxL antagonist. Collectively, these studies identify the mechanisms of intrinsic apoptosis resistance in GBM and demonstrate how functional and molecular data can be complementary to robustly predict therapy-induced cell death.