Abstract The main goal of this study is to develop precision treatments for glioblastoma (GBM). GBM is a deadly brain tumor with few treatment options, mainly due to high intra- and inter-tumoral heterogeneity manifested by diverse genetic alterations and cellular components within an individual tumor or among different patients. Previous efforts targeting molecular features have focused on three molecular subtypes — Classical (CL), Mesenchymal (ME), and Pro-Neural (PN) — but no effective treatments have been developed for each subtype. To overcome this challenge, we recently employed a machine learning algorithm to identify 31 essential survival genes, forming a new GBM progression gene signature (GBM-PGS) that divided patients into high- or low-risk (HR vs LR) of poor prognosis. Because these genes are functionally vital for cancer cell survival/growth, GBM-PGS predicts the progression of GBM patients more accurately than existing biomarkers such as EGFR, MGMT, and IDH1. Given the functional relevance of GBM-PGS to tumor cell survival and disease progression, we hypothesize that combining GBM-PGS with molecular subtyping will stratify GBM patients into distinct treatment groups, enabling the repurposing of FDA-approved drugs for precision medicine in this fatal disease. We stratified TCGA GBM patients and DepMap glioma cell lines into six subgroups: HR-CL, HR-ME, HR-PN, LR-CL, LR-ME, and LR-CL using GBM-PGS and molecular subtyping. The survival of TCGA subgroups was assessed using Kaplan-Meier analysis, and potential drug targets for the HR and LR groups were analyzed using Gene Ontology. Moreover, candidate precision treatments for each subgroup were identified from the DepMap PRISM Repurposing Drug Screen dataset and further verified in a range of GBM cell lines. The LR-PN displayed a significantly better prognosis than the other subgroups. Drugs targeted for HR GBMs were functionally different from those for LR GBMs. The six treatment subgroups exhibited diverse responses to chemical compounds, including FDA-approved drugs. Candidate drugs for each subgroup were validated in GBM cell lines. Our results have verified the crucial roles of GBM-PGS and molecular subtyping in patient stratification and in the development of subgroup-specific precision treatments. Overall, this study has the potential to transform the GBM therapeutic landscape. Citation Format: Lateef Owolabi Anifowose, Zhi Sheng. New precision treatments for glioblastoma abstract. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 2508.
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Anifowose et al. (Fri,) studied this question.
www.synapsesocial.com/papers/69d1fdb0a79560c99a0a3e5d — DOI: https://doi.org/10.1158/1538-7445.am2026-2508
Lateef O. Anifowose
Zhi Sheng
Cancer Research
Carilion Roanoke Memorial Hospital
Professional Education and Research Institute
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