To better understand seizure onset in patients with brain tumors, this project will perform digital spatial profiling (DSP), an automated system for multiplexed, spatially-linked RNA transcript and protein expression quantification, and Visium 10x Single-nuclei RNA sequencing on brain tumor specimens to evaluate PNN structure and composition in the TME. The project will then apply machine-learning approaches to analyze these high-dimensional data in order to identify PNN features that relate to a clinical history of seizures. This aim will test the hypothesis that tumor-related PNN degradation in patients is associated with severe neurologic symptoms. It will also result in major development of novel histologic and computational techniques for evaluation of PNN structure and function that can be broadly applied to other, similarly complex biomedical datasets.