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Brain-wide neurotransmitter-specific network involvement determines outcome in glioblastoma

Koch, P. J.; Forisch, J.; Khatri, R.; Frey, B. M.; Brembach, F.; Zghaibeh, Y.; Feldheim, J.; Hornberger, T.; Quandt, F.; Magnus, T.; Thomalla, G.; Endres, M.; Breckwoldt, M. O.; Venkataramani, V.; Winkler, F.; Monje, M.; Schueller, U.; Mohme, M.; Duehrsen, L.; Frank, K.; Bonn, S.; Drexler, R.; Heiland, D. H.; Schulz, R.; Ricklefs, F. L.

2026-03-25 oncology
10.64898/2026.03.23.26348837 medRxiv
Show abstract

Importance: Glioblastoma (GBM) cells integrate into neuronal circuits, and preclinical work implicates multiple neurotransmitter (NT) networks as key drivers of invasion and treatment resistance. Whether the integration of GBM within NT-defined large-scale brain networks conveys prognostic information for overall survival (OS) is unknown. Objective: To determine whether NT-specific network involvement of GBM is associated with OS in patients with newly diagnosed Isocitrate dehydrogenase (IDH)-wildtype(wt) GBM. Design, Setting, and Participants: In this observational multicenter cohort study, we analyzed two independent cohorts of adults with histopathologically confirmed IDH-wt GBM. Cohort 1 included 153 patients treated at the University Medical Center Hamburg-Eppendorf, Germany (2012-2024), and cohort 2 comprised 264 patients from the University of Pennsylvania Health System, USA (2006-2018). Preoperative contrast-enhanced MRI was used to derive individual tumor masks, which were spatially mapped onto normative NT-informed structural connectomes spanning 19 receptor and transporter systems. Exposures: Preoperative contrast-enhancing GBM lesions, quantified as patient-specific involvement scores (0-1) within each NT-defined brain network. Statistics: We used partial least-squares regression for variable selection and multivariable Cox proportional-hazards models alongside regularized logistic regression with out-of-sample prediction, adjusted for age, methylguanine methyltransferase (MGMT) promoter methylation, and extent of resection, to test associations between NT-specific GBM network involvement and OS. Results: Across 417 patients in two cohorts, greater GBM involvement within cholinergic networks, defined by normative vesicular acetylcholine transporter (VAChT)-weighted as well as dopaminergic D2 receptor involvement, was consistently associated with reduced OS, independent of age, MGMT status, and resection extent. Further, cholinergic network involvement showed the strongest contribution to the prediction models. Other NT networks did not show reproducible prognostic effects across cohorts. Tumor-intrinsic hypomethylation of acetylcholine receptor-associated regions correlated with imaging-based cholinergic network involvement and mirrored its prognostic relevance. Conclusion and Relevance: Tumor integration into neurotransmitter-specific brain networks is an independent predictor of poorer survival in GBM. By combining routine clinical MRI with normative NT-informed connectome data, this approach delineates a novel systems-level marker of tumor aggressiveness and supports cholinergic inhibition as a putative therapeutic target in GBM.

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