High-throughput identification of repurposable neuroactive drugs with potent anti-glioblastoma activity
Sohyon Lee, Tobias Weiß, Marcel Bühler, Julien Mena, Zuzanna Lottenbach, Rebekka Wegmann, Miaomiao Sun, Michel Bihl, Bartłomiej Augustynek, Sven Baumann, Sandra Goetze, Audrey van Drogen, Patrick G. A. Pedrioli, David Pentón, Yasmin Festl, Alicia Buck, Daniel S. Kirschenbaum, Anna Maria Zeitlberger, Marian C. Neidert, Flavio Vasella, Elisabeth J. Rushing, Bernd Wollscheid, Matthias A. Hediger, Michael Weller, Berend Snijder
Abstract
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 Ca 2+ -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.