Artikel
Reshaping the GBM landscape to enable targeting of chemo-resistant tumours
Neuordnung der GBM-Landschaft zur gezielten Bekämpfung chemoresistenter Tumore
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Autoren
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Kevin Joseph
- Medical Center, University of Freiburg, Translational neuroOncology Research Group, Freiburg, Deutschland; Medical Center, University of Freiburg, Department of Neurosurgery, Freiburg, Deutschland; Medical Center, University of Freiburg, Freiburg, Deutschland
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Julian Maier
- Medical Center, University of Freiburg, Translational neuroOncology Research Group, Freiburg, Deutschland; Medical Center, University of Freiburg, Department of Neurosurgery, Freiburg, Deutschland; Medical Center, University of Freiburg, Freiburg, Deutschland
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Vidhya Madapusi Ravi
- Medical Center, University of Freiburg, Translational NeuroOncology Research Group, Freiburg, Deutschland; Medical Center, University of Freiburg, Department of Neurosurgery, Freiburg, Deutschland; Medical Center, University of Freiburg, Neuroelectronic Systems, Freiburg, Deutschland; Medical Center, University of Freiburg, Freiburg, Deutschland
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Jürgen Beck
- Medical Center, University of Freiburg, Translational NeuroOncology Research Group, Freiburg, Deutschland; Medical Center, University of Freiburg, Department of Neurosurgery, Freiburg, Deutschland; Medical Center, University of Freiburg, Freiburg, Deutschland
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Ulrich Hofmann
- Medical Center, University of Freiburg, Department of Neurosurgery, Freiburg, Deutschland; Medical Center, University of Freiburg, Neuroelectronic Systems, Freiburg, Deutschland; Medical Center, University of Freiburg, Freiburg, Deutschland
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Oliver Schnell
- Medical Center, University of Freiburg, Translational NeuroOncology Research Group, Freiburg, Deutschland; Medical Center, University of Freiburg, Department of Neurosurgery, Freiburg, Deutschland; Medical Center, University of Freiburg, Freiburg, Deutschland
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Dieter Henrik Heiland
- Medical Center, University of Freiburg, Translational NeuroOncology Research Group, Freiburg, Deutschland; Medical Center, University of Freiburg, Department of Neurosurgery, Freiburg, Deutschland; Medical Center, University of Freiburg, Freiburg, Deutschland
| Veröffentlicht: | 4. Juni 2021 |
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Gliederung
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Objective: Novel insights into the developmental trajectory exhibited by glioblastoma (GBM) has shown that it has the capability to respond to its microenvironment by clonal selection of specific phenotypes. Similarly, malignant GBM develop intrinsic mechanisms to resist chemotherapeutic treatments during the course of the disease. Paracrine and autocrine glutamate signaling via ionotropic and metabotropic receptors have been reported to sustain malignant hallmarks. However, the extent to which glutamatergic signaling modulates the GBM landscape and facilitates chemoresistance remains unknown. In this study we aimed to prove the manifold concept of glutamate signaling in GBM as the basis to further discover the modulatory role and interactions of specific receptors within the GBM microenvironment.
Methods: Human neo cortical slices were inoculated with primary Glioblastoma cell lines and Glutamate release using an enzyme based colorimetric assay. Transcriptomic analysis highlighted the importance of mGlur3 receptor in GBM network maintenance and axonogenesis, which was validated by the usage of LY341495, a specific inhibitor of mGlur3. Glioblastoma innoculated sections were treated with TMZ and with TMZ+LY341495 for the period of 10 days. The sections were imaged on a daily basis to analyze the effect of the treatments on tumor growth and proliferation
Results: We present evidence that the inhibition of mGluR3 through a minimally toxic synthetic antagonist, LY341495, is sufficient to drive the transcriptional profile of chemoresistant GBM to a mesenchymal state that allowed cytotoxic targeting by temozolomide. Ultimately, GBM growth and proliferation were dramatically reduced (p<0.001, n=3) when GRM3 inhibition was combined with temozolomide application. These results were validated in both cell culture and in a human neocortical section based GBM model.
Conclusion: Through the integration of diversified molecular-biological analyses and novel sequencing data analysis we present a new concept, where we not only illustrate mechanisms of resistance, but rather a new picture of how glutamate signaling via mGluR3 interacts with the phenotypical GBM landscape formation in the light of recently published GBM cell-state discoveries.
