P04.04 Optimizing dasatinib for glioblastoma treatment. (9th September 2021)

• Record Type: Journal Article
• Authors: Alhalabi, O; Göttmann, M; Gold, M; Fletcher, M; Hielscher, T; Iskar, M; Kessler, T; Wittmann, E; Schlue, S; Rahman, S; Hai, L; Hansen-Palmus, L; Puccio, L; Nakano, I; Herold-Mende, C; Baumgartner, U; Day, B; Wick, W; Sahm, F; Fraenkel, E; Phillips, E; Goidts, V
• Is Part Of: Neuro-oncology. Volume 23: Supplement 2 (2021)
• Page Start: ii19
• Page End: ii19
• Publication Date: 2021-09-09
• Subjects: Brain Neoplasms -- Periodicals; Brain -- Tumors -- Periodicals; Brain -- Cancer -- Periodicals; Nervous system -- Cancer -- Periodicals; 616.99481
• DOI: 10.1093/neuonc/noab180.061
• Languages: English
• ISSNs: 1522-8517

Abstract

Abstract: BACKGROUND: Glioblastoma is the most common primary malignancy of the central nervous system with a dismal prognosis, even with surgical and chemoradiotherapy. Expression profiling studies classify IDH-wildtype Glioblastoma into three subtypes: Proneural (PN), mesenchymal (MES) and classical (CL). A promising target to inhibit in Glioblastoma is the non-receptor tyrosine kinase and proto-oncogene SRC. After robust pre-clinical results, SRC inhibitors like dasatinib did not improve survival of Glioblastoma patients after recurrence in clinical trials. MATERIAL AND METHODS: Consolidating efforts to personalize cancer therapy, we use in silico analyses backed by in vitro and in vivo experiments on Glioblastoma stem-like cells (GSCs) derived from primary patient tumors to present a novel stratification strategy for dasatinib therapy in glioblastoma. To further tackle dasatinib resistance in GSCs, a pooled shRNA library against 5000 genes was combined with dasatinib to identify genes whose knockdown sensitizes GSCs to dasatinib. This was integrated with proteomics and phosphoproteomics data of dasatinib inhibited GSCs. RESULTS: We found MES tumors with high expression of SERPINH1 to be sensitive to dasatinib inhibition, compared to the CL and PN subtypes. Interestingly, SRC phosphorylation status did not predict the efficacy of dasatinib inhibition. Computational analyses integrating data from the loss-of-function dropout viability screen and proteomics/phosphoproteomics using a novel modification of the SamNet algorithm identified Wee1, a tyrosine kinase involved in cell-cycle signaling, as a potential combination inhibition target with dasatinib. Further validation experiments showed a robust synergistic effect through combination of dasatinib and the wee1 inhibitor, MK-1775 in PN GSCs. CONCLUSION: This study highlights strategies to optimize dasatinib treatment in different glioblastoma subtypes. While the stratification of patients harboring mesenchymal glioblastoma with SERPINH1 overexpression could provide an option in this particular subtype, combining dasatinib or other SRC inhibitors with Wee1 inhibitors could present an additional possibility for treating resistant proneural tumors