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Background Glioblastoma (GBM) remains an aggressive, lethal form of brain cancer. Current treatments offer limited efficacy, necessitating development of novel therapeutic strategies. This is particularly true in immunotherapy, given restricted success of immune-based approaches focused on Immune Checkpoint Inhibitors or Adoptive Cell Therapies. This underscores the urgent need for a deeper, spatially resolved understanding of underlying immunobiology of GBM, to identify vulnerable targets for novel immunotherapies.Methods We employ a two-tiered approach to interrogate GBM tumor microenvironment, aiming to uncover novel immunotherapy approaches. We first deployed the Phenocycler Fusion platform to stain and image 42 tumor-associated markers on a single tissue slide. This ultrahigh-plex panel allowed for broad characterization of five key aspects: 1) diverse tumor cell populations (including elusive cancer stem cells and their differentiated progeny), 2) markers indicative of tumor aggressiveness and prognosis, 3) patterns of tumor-associated protein dysregulation and cellular stress, 4) the integrity of tumor vasculature and dynamic immune cell trafficking, and 5) the intricate adaptive and innate immune response. Image analysis methods included first applying cell and tissue segmentation, to identify location of individual cells and specific tissue architectural components. Cells were phenotyped by identifying cell subtypes via marker combinations. Spatial co-localization was interrogated using neighborhood analysis, identifying signatures potentially associated with therapeutic targets.Results This high-plex analysis revealed markers with high relative abundance, differential spatial distribution, and strong correlations with disease progression. This subset of markers were then applied to a wider, independent set of GBM samples, using more targeted PhenoCode Signature Panels. These panels leverage a backbone of five crucial preset markers combined with a custom sixth, target-specific marker. Advanced image analysis was employed to validate which spatial signatures identified in the high-plex panel were recapitulated in the PhenoCode Signature Panels, and extend those high-plex spatial findings to the wider cohort of GBM samples. Spatial patterns of expression and cell distribution were quantitatively measured, generating robust datasets for validation.Conclusions This discovery-to-translational strategy, transitioning from ultrahigh-plex spatial phenotyping to high-throughput statistical validation, allows for novel recognition of complex spatial relationships between immune biomarkers and tumor cells within tumor microenvironment. This dual-platform approach facilitates discovery of critical insights into GBM biology, enabling deeper interrogation and validation. This approach blends robustness of high-throughput panels with adaptability of a high-plex discovery solution. Such an approach, broadly applicable to multiple solid cancers, accelerates oncology research by facilitating rapid and precise identification of disease-specific markers, enabling discovery of more effective immunotherapeutic targets.