Characterizing and targeting glioblastoma neuron-tumor networks with retrograde tracing

Glioblastomas are invasive brain tumors with high therapeutic resistance. Neuron-to-glioma synapses have been shown to promote glioblastoma progression. However, a characterization of tumor-connected neurons has been hampered by a lack of technologies. Here, we adapted retrograde tracing using rabies viruses to investigate and manipulate neuron-tumor networks. Glioblastoma rapidly integrated into neural circuits across the brain, engaging in widespread functional communication, with cholinergic neurons driving glioblastoma invasion. We uncovered patient-specific and tumor-cell-state-dependent differences in synaptogenic gene expression associated with neuron-tumor connectivity and subsequent invasiveness. Importantly, radiotherapy enhanced neuron-tumor connectivity by increased neuronal activity. In turn, simultaneous neuronal activity inhibition and radiotherapy showed increased therapeutic effects, indicative of a role for neuron-to-glioma synapses in contributing to therapeutic resistance. Lastly, rabies-mediated genetic ablation of tumor-connected neurons halted glioblastoma progression, offering a viral strategy to tackle glioblastoma. Together, this study provides a framework to comprehensively characterize neuron-tumor networks and target glioblastoma.

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Publication Details

Journal
Cell
Published
2024-12-06
DOI
https://doi.org/10.1016/j.cell.2024.11.002
Citations
84
Primary Topic
Cell Image Analysis Techniques
Type
article
Field-Weighted Citation Impact
55.64

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article

Characterizing and targeting glioblastoma neuron-tumor networks with retrograde tracing

Ekin Reyhan, Sonja Hänzelmann, Julio Sáez-Rodríguez, Bogdana Suchorska et al.
84 citations
Cell
Cell Image Analysis Techniques
55.64
article

Characterizing and targeting glioblastoma neuron-tumor networks with retrograde tracing

Ekin Reyhan, Sonja Hänzelmann, Julio Sáez-Rodríguez, Bogdana Suchorska, Matthia A. Karreman, Atefeh Pourkhalili Langeroudi, Abigail K. Suwala, Marc Thier, Sascha Conic, Stella J Soyka, Manuel Schröter, Felix Tobias Kurz, Rangel Lyubomirov Pramatarov, Michael O. Breckwoldt, Michael Botz, Niklas Wißmann, Obada Alhalabi, Julia A. Wagner, Nikolas Layer, Fabian Hausmann, C. Peter Bengtson, Marc C. Schubert, Karin Forsberg‐Nilsson, Berin Boztepe, Felix Sahm, Dieter Henrik Heiland, Claudio Acuna, Franz Ricklefs, Amir Abdollahi, Joaquín Campos, Richard Drexler, Svenja Kristin Tetzlaff, Varun Venkataramani, Jovana Bojcevski, Julian Schroers, Yahya Zghaibeh, Nina Drewa, Nirosan Sivapalan, Jonas G. Scheck, Maria C. Puschhof, Anton J Faymonville, Giulia Villa, Verena Buchert, Elena Grabis, Alina Heuer, Elijah Keifert, Tim Wageringel
article en
84 citations

Abstract

Glioblastomas are invasive brain tumors with high therapeutic resistance. Neuron-to-glioma synapses have been shown to promote glioblastoma progression. However, a characterization of tumor-connected neurons has been hampered by a lack of technologies. Here, we adapted retrograde tracing using rabies viruses to investigate and manipulate neuron-tumor networks. Glioblastoma rapidly integrated into neural circuits across the brain, engaging in widespread functional communication, with cholinergic neurons driving glioblastoma invasion. We uncovered patient-specific and tumor-cell-state-dependent differences in synaptogenic gene expression associated with neuron-tumor connectivity and subsequent invasiveness. Importantly, radiotherapy enhanced neuron-tumor connectivity by increased neuronal activity. In turn, simultaneous neuronal activity inhibition and radiotherapy showed increased therapeutic effects, indicative of a role for neuron-to-glioma synapses in contributing to therapeutic resistance. Lastly, rabies-mediated genetic ablation of tumor-connected neurons halted glioblastoma progression, offering a viral strategy to tackle glioblastoma. Together, this study provides a framework to comprehensively characterize neuron-tumor networks and target glioblastoma.

CellVol. 188(2)
Uppsala University (SE), Universität Hamburg (DE), German Cancer Research Center (DE), Friedrich-Alexander-Universität Erlangen-Nürnberg (DE), Heidelberg University (DE), Science for Life Laboratory (SE), University Hospital Heidelberg (DE), ETH Zurich (CH), University Medical Center Hamburg-Eppendorf (DE), National Center for Tumor Diseases (DE), Chica and Heinz Schaller Foundation (DE), Heidelberg Institute for Stem Cell Technology and Experimental Medicine (DE), Stanford University (US)
Vetenskapsrådet, Deutsche Krebshilfe, Center for Innovative Medicine
Openalex Percentile: Top 0%
Cell Image Analysis Techniques
55.64
DOIOpen Access PDFOpenAlex
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