Spatial Omics Technologies in Glioblastoma Research: Principles, Applications, and Best Practices

Glioblastoma (GBM) remains the most aggressive primary brain tumor in adults, characterized by inevitable recurrence, extensive inter-and intratumoral heterogeneity, and resistance to current therapies. A defining feature of GBM is the dynamic interplay between malignant cells and a diverse tumor microenvironment (TME), which together drive disease progression, therapeutic adaptation, and relapse. Understanding these complex cellular ecosystems has therefore become a major focus of glioblastoma research. Recent advances in spatial omics technologies have transformed our ability to investigate GBM biology directly within intact tissue architectures. Over the past five years, an expanding array of spatial transcriptomic, proteomic, and multi-omic platforms has enabled high-dimensional characterization of cellular states, cell-cell interactions, and tissue niches while preserving spatial context. These approaches have generated unprecedented insights into tumor organization, cellular plasticity, immune landscapes, vascular niches, and treatment-induced ecosystem remodeling.

In this review, we provide an overview of spatial omics applications in glioblastoma research so far.

We summarize the technologies employed, the types and numbers of patient samples analyzed, and the major biological and clinical insights generated. We compare the strengths and limitations of different spatial platforms, discuss key considerations for study design and data interpretation, and highlight emerging trends in multimodal and longitudinal analyses.

By integrating both technological and biological perspectives, this review serves as a practical resource for researchers seeking to implement spatial omics approaches in glioblastoma studies and to advance precision neuro-oncology.