High-throughput identification of repurposable neuroactive drugs with potent anti-glioblastoma activity
Sohyon Lee1, Tobias Weiss2, Marcel Bühler2
1Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland.
Abstract:
Glioblastoma, the most aggressive primary brain cancer, has a dismal prognosis, yet systemic treatment is limited to DNA-alkylating chemotherapies. New therapeutic strategies may emerge from exploring neurodevelopmental and neurophysiological vulnerabilities of glioblastoma. To this end, we systematically screened repurposable neuroactive drugs in glioblastoma patient surgery material using a clinically concordant and single-cell resolved platform. Profiling more than 2,500 ex vivo drug responses across 27 patients and 132 drugs identified class-diverse neuroactive drugs with potent anti-glioblastoma efficacy that were validated across model systems. Interpretable molecular machine learning of drug-target networks revealed neuroactive convergence on AP-1/BTG-driven glioblastoma suppression, enabling expanded in silico screening of more than 1 million compounds with high patient validation accuracy. Deep multimodal profiling confirmed Ca2+-driven AP-1/BTG-pathway induction as a neuro-oncological glioblastoma vulnerability, epitomized by the anti-depressant vortioxetine synergizing with current standard-of-care chemotherapies in vivo. These findings establish an actionable framework for glioblastoma treatment rooted in its neural etiology.
Insights
Neuroactive drugs show potent anti-glioblastoma efficacy by targeting neural vulnerabilities. Repurposing these drugs, like vortioxetine, offers a new therapeutic framework for brain cancer treatment.
Area of Science:
- Neuro-oncology
- Cancer Therapeutics
- Drug Discovery
Background:
- Glioblastoma (GBM) is an aggressive brain cancer with limited treatment options, primarily DNA-alkylating chemotherapies.
- Exploring the neurodevelopmental and neurophysiological aspects of GBM offers potential for novel therapeutic strategies.
Purpose of the Study:
- To systematically screen repurposable neuroactive drugs for anti-glioblastoma efficacy.
- To identify molecular mechanisms underlying neuroactive drug effectiveness in GBM.
- To establish a framework for developing new GBM treatments based on its neural origins.
Main Methods:
- Screening of over 132 repurposable neuroactive drugs against glioblastoma patient surgery material using a single-cell resolved platform.
- Profiling more than 2,500 ex vivo drug responses across 27 patients.
- Utilizing interpretable molecular machine learning to analyze drug-target networks and identify key pathways.
- Deep multimodal profiling to confirm molecular mechanisms and validate drug efficacy in vitro and in vivo.
Main Results:
- Identification of diverse neuroactive drugs with potent anti-GBM activity, validated across multiple model systems.
- Machine learning analysis revealed a convergence on AP-1/BTG-driven glioblastoma suppression by neuroactive drugs.
- In silico screening of over 1 million compounds based on identified pathways showed high patient validation accuracy.
- Calcium ion (Ca2+)-driven AP-1/BTG pathway induction was confirmed as a critical neuro-oncological vulnerability.
- The antidepressant vortioxetine demonstrated synergy with standard chemotherapies in vivo.
Conclusions:
- Neuroactive drugs targeting neural vulnerabilities represent a promising therapeutic avenue for glioblastoma.
- The AP-1/BTG pathway, modulated by Ca2+ signaling, is a key target for glioblastoma suppression.
- Vortioxetine, in combination with standard therapies, offers a potential new treatment strategy for glioblastoma.
- This study provides an actionable framework for glioblastoma treatment grounded in its neural etiology.
