Abstract Diffuse midline glioma (DMG) is a devastating pediatric high-grade glioma with a median survival of less than one year and no effective curative therapies. A major barrier to therapeutic progress is the lack of human-relevant preclinical models that recapitulate the complex tumor microenvironment (TME), particularly interactions among tumor cells, neurons, and the brain’s innate immune cells, microglia. Conventional in vitro systems and xenograft models in immunodeficient mice fail to capture these critical neuroimmune dynamics, limiting both mechanistic insight and predictive drug testing. To address this gap, we developed a neuroimmune-competent human brain organoid model of DMG. Microglia-containing brain organoids (MiCBOs) were generated from human stem cell–derived neural progenitors and myeloid precursors, yielding organoids composed of excitatory and inhibitory neurons, astrocytes, and highly motile, GFP-labeled microglia. Fluorescently labeled patient-derived DMG spheroids were fused with MiCBOs to create MiCBO-tumor fusion (MiCBO-TF) models, enabling real-time visualization and quantitative analysis of tumor invasion, microglial behavior, and cell-cell interactions by confocal imaging. MiCBO-TFs faithfully recapitulated the hallmark diffuse infiltrative growth pattern of DMG observed in human brain tissue. Microglia displayed dynamic surveillance, contact, and engulfment behaviors and significantly promoted tumor infiltration, with regional heterogeneity in microglial motility shaped by local tissue context and tumor proximity. Importantly, this platform enabled mechanism-guided therapeutic testing: standard-of-care temozolomide showed minimal efficacy, whereas targeted inhibition of PDGFRA and combined blockade of fatty acid synthesis and PI3K signaling significantly reduced tumor infiltration. Together, this neuroimmune-competent organoid fusion system provides a biologically relevant, reproducible, and scalable human preclinical platform to dissect tumor-neuron-immune crosstalk and to accelerate rational drug discovery for pediatric DMG. This model offers a powerful tool for identifying context-dependent vulnerabilities and prioritizing therapies with improved translational potential.
Sarnow et al. (Tue,) studied this question.