A microphysiological spheroid system for modeling glioblastoma structure and therapy response

Glioblastoma (GBM) is a lethal, highly aggressive primary brain tumor. Even with maximal surgical resection, chemo, and radiotherapy, the median survival is less than 15 months with universal recurrence. Recalcitrance of GBM arises from its cellular, genetic, epigenetic, and microenvironment heterogeneity that evolves spontaneously over time and as a result of treatment. The primary objective of this study was to create and characterize a tunable, heterocellular 3D spheroid platform that mirrors the cell-cell interactions of the GBM niche and to utilize this model to investigate mechanisms of resistance to standard therapy. We established three spheroid models of increasing complexity: tumor-only (G1), tumor-microglia (G2), and a full niche model including astrocytes (G3). These spheroids exhibited realistic growth dynamics, viability, and morphometric properties. Spheroids were treated with chemotherapeutic drugs: Doxorubicin and Carboplatin. Interestingly, while drug treatment induced cell death in the simpler G1 and G2 models, the inclusion of SVG astrocytes in Group 3 resulted in a marked reduction in efficacy of Doxorubicin. The significant shift from high drug sensitivity in G1 to survival in G3 provides direct evidence of environment-mediated drug resistance, where the glial niche confers a protective metabolic and structural shield to the tumor cells. Our findings may validate the heterocellular spheroid as a high-fidelity model for some aspects of the GBM microenvironment. The transition from high sensitivity in monocultures to resistance in multi-lineage model (G3) underscores the protective role of glia within the tumor microenvironment. This platform provides a robust tool for high-throughput screening of sensitizing agents designed to disrupt these protective interactions to overcome chemoresistance in brain tumors as well as enabling dissection of heterocellular interactions, molecular signaling, and therapeutic responses in a physiologically accurate 3D context.