Spatially resolved multiomics profiling of glioblastoma reveals molecular signatures of neuropathology and immuno-oncology architecture using CosMx SMI

Glioblastoma (GBM) is a highly heterogeneous and aggressive brain tumor with limited therapeutic success, underscoring the need for advanced approaches to decode its complex molecular landscape. Here, we employed the CosMx® Spatial Molecular Imager to perform same-cell spatial multiomics profiling on serial sections from a human GBM tissue block, integrating the whole-transcriptome RNA panel (~19,000 genes) with two high-plex protein panels encompassing 64 neuropathology or immuno-oncology markers. This comprehensive dataset enables correlative mapping of transcriptomic and proteomic features across tumor and peri-tumoral regions. We identified five GBM tumor cell subtypes - astrocyte-like, OPC-like, mesenchymal-like, stem-like, and proliferating cells - each exhibiting distinct spatial localization and transcriptional signatures. Concurrent protein profiling uncovered regionally enriched phospho-Tau variants (e.g., p-Tau S214, S396, S404), whose accumulation marked hypoxic and epithelial-mesenchymal transition (EMT) active tumor microenvironments. Spatial regression analyses linked elevated neighborhood p-Tau scores to coordinated upregulation of hypoxia-responsive genes (e.g., HIF1A, VEGFA) and metabolic stress pathways, revealing a localized molecular response to cellular stress. Integration of the immuno-oncology protein panel highlighted spatially restricted immune checkpoint expression, including PD-L1, B7-H3, and TIM-3, delineating immune-evasive niches within distinct tumor neighborhoods. Tumor niches driven by divergent subtype GBM cells adopted unique immune evasion strategies, suggesting microenvironment-specific mechanisms of immune suppression. Overall, this study demonstrates the power of spatially resolved, same-cell multiomics to dissect GBM's transcriptional and proteomic heterogeneity at unprecedented resolution. The findings establish a mechanistic link between phospho-Tau-associated stress adaptation, metabolic remodeling, and immune modulation in GBM. This scalable framework offers a blueprint for future multi-sample spatial oncology studies aimed at uncovering therapeutic vulnerabilities, stratifying tumors by microenvironmental features, and identifying biomarkers predictive of treatment response.