Glioblastoma (GBM), the most malignant tumor of the central nervous system, is marked by its dynamic response to microenvironmental niches. In particular, this cellular plasticity contributes to the development of an immediate resistance during tumor treatment. Novel insights into the developmental trajectory exhibited by GBM show a strong capability to respond to its microenvironment by clonal selection of specific phenotypes. Using the same mechanisms, malignant GBM do develop intrinsic mechanisms to resist chemotherapeutic treatments. This resistance was reported to be sustained by the paracrine and autocrine glutamate signaling via ionotropic and metabotropic receptors. However, the extent to which glutamatergic signaling modulates the chemoresistance and transcriptional profile of the GBM remains unexplored. In this study we aimed to map the manifold effects of glutamate signaling in GBM as the basis to further discover the regulatory role and interactions of specific receptors, within the GBM microenvironment. Our work provides insights into glutamate release dynamics, representing its importance for GBM growth, viability, and migration. Based on newly published multi-omic datasets, we explored the and characterized the functions of different ionotropic and metabotropic glutamate receptors, of which the metabotropic receptor 3 (GRM3) is highlighted through its modulatory role in maintaining the ability of GBM cells to evade standard alkylating chemotherapeutics. We addressed the clinical relevance of GRM3 receptor expression in GBM and provide a proof of concept where we manipulate intrinsic mechanisms of chemoresistance, driving GBM towards chemo-sensitization through GRM3 receptor inhibition. Finally, we validated our findings in our novel human organotypic section-based tumor model, where GBM growth and proliferation was significantly reduced when GRM3 inhibition was combined with temozolomide application. Our findings present a new picture of how glutamate signaling via mGluR3 interacts with the phenotypical GBM transcriptional programs in light of recently published GBM cell-state discoveries.
© 2021. The Author(s).