Abstract
BACKGROUND: Glioblastoma (GBM) is the most common and lethal primary brain tumor in adults, with poor prognosis due to its high recurrence rate and resistance to therapy. Despite standard of care treatment, surgical resection followed by radiotherapy and temozolomide chemotherapy, relapse occurs in 80-90% of patients. This is largely attributed to the extensive genetic and cellular heterogeneity of GBM, including a subpopulation of tumor-initiating cells (TICs) that drive therapeutic resistance and tumor regrowth. MATERIAL AND METHODS: To identify therapeutic strategies that bypass tumor-specific mutations, we aimed to repurpose FDA-approved drugs to target common vulnerabilities across diverse TIC populations. We employed patient-derived 3D TIC cultures and orthotopic xenograft (PDX) models to focuse on essential cellular processes such as apoptosis, cell cycle control, protein synthesis, and the DNA damage response. A high-throughput screen of 2,702 FDA-approved compounds was conducted on three heterogeneous TIC models: two derived from matched primary and recurrent GBMs, and one from an independent recurrent tumor. RESULTS: Of the 2,702 FDA-approved compounds screened, only 66 (approximately 2%) demonstrated consistent and significant anti-tumor activity across all TIC models. From this subset, we prioritized three candidates: Homoharringtonine, a protein synthesis inhibitor; Ixazomib Citrate, a proteasome inhibitor; and Panobinostat, a histone deacetylase inhibitor. Notably, Homoharringtonine and Ixazomib have not been previously evaluated in GBM, highlighting their potential as novel therapeutic agents. Although Panobinostat has been explored in prior studies, it exhibited robust efficacy across all tested models. CONCLUSION: These results highlight our TICs panel as a valuable screening platform for real-time therapy monitoring and for identifying promising TIC-targeting drugs for GBM treatment. Ongoing studies will investigate resistance mechanisms through single-cell transcriptomic and epigenomic profiling, with the goal of informing the design of rational, synergistic combination therapies.