Abstract
Glioblastoma is an aggressive brain cancer with limited treatment options and poor patient survival, driven in part by cellular diversity within tumors. While individual cell types have been catalogued, how malignant, vascular, and immune cells are spatially organized inside human tumors remains incompletely understood. Here we show a spatially resolved, multi-modal atlas of human glioblastoma that integrates gene expression profiling across tissue sections with matched single-cell and protein measurements at subcellular resolution. Using a targeted 348 gene panel enriched for vascular and stromal markers, we identify less well-characterized endothelial, perivascular, and fibroblast-like cell states and define their spatial associations with malignant and immune compartments. We further identify a distinct oligodendrocyte population restricted to tumor core and perivascular regions that exhibits gene expression patterns associated with tumor recurrence and poor clinical outcome. This publicly accessible atlas provides a high-resolution framework for studying the spatial organization of glioblastoma and highlights region-specific cellular interactions that may represent therapeutically actionable vulnerabilities.
Data availability
Raw single-cell RNA-sequencing data generated in this study have been deposited in the NCBI Sequence Read Archive (SRA) under BioProject accession code PRJNA1337938. Raw Visium spatial transcriptomics data have been deposited under the same Bioproject ID. Processed spatial transcriptomics data, corresponding images, and associated metadata are available on Zenodo under the following DOIs: https://doi.org/10.5281/zenodo.17622242 (Xenium) [https://doi.org/10.5281/zenodo.17622242] and 10.5281/zenodo.17572905 (Visium) [https://doi.org/10.5281/zenodo.17572905]. Single-cell RNA-seq, CITE-seq, and spatial transcriptomics data generated in this study, together with associated cell type annotations, are available via the UCSC Cell Browser under the dataset identifier multiomic-gbm [https://cells.ucsc.edu/?ds=multiomic-gbm]. These data are publicly available and do not require restricted access. Bulk RNA-sequencing datasets analysed in this study were obtained from the following public repositories: • TCGA glioma dataset [https://portal.gdc.cancer.gov/] • CGGA glioma dataset [http://www.cgga.org.cn/] • GLASS consortium glioma dataset [https://glass-consortium.org] Previously published spatial transcriptomics datasets analysed in this study include: • GSE237183 (Greenwald et al., 10x Visium glioblastoma dataset) • Ravi et al. 10x Visium glioblastoma dataset [https://zenodo.org/records/16505469] Previously published single-cell and single-nucleus RNA-sequencing datasets analysed in this study include: • Allen Institute human motor cortex single-nucleus RNA-seq dataset [http://www.brain-map.org] • GSE162631 (Xie et al.) • Winkler et al. vascular single-cell RNA-seq dataset [https://adult-brain-vasc.cells.ucsc.edu/] • GSE131928 (Abdelfattah et al.) • GSE163120 (Pombo Antunes et al., CITE-seq) • GSE163108 (Mathewson et al.) The Source Data files are provided on Zenodo (https://doi.org/10.5281/zenodo.18093125).
Code availability
All the required codes have been deposited on Zenodo (https://doi.org/10.5281/zenodo.17622242) as main_figures_scripts.zip. All annotations required to reproduce the analyses are available through the UCSC Cell Browser under the dataset ID multiomic-gbm (https://cells.ucsc.edu/?ds=multiomic-gbm). Tutorials and videos for accessing annotations and metadata are also provided in GitHub (https://github.com/nameetas/TSKGA).
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Acknowledgements
The authors would like to acknowledge the patients who generously donated the samples that made this study possible. This work was supported by the following grants; N.S.: The Pershing Square Foundation, C.-K.P.: Seoul National University College of Medicine Research Foundation (grant number: 800-20210327), National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (RS-2024-00335143), W.-Y.P.: Bio & Medical Technology Development Program of the National Research Foundation (NRF) funded by the Ministry of Science & ICT (NRF-2017M3A9A7050803), a grant of the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health & Welfare, Republic of Korea (HR20C0025). H.-J.P.: The National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (grant number: RS-2024-00357204). New Faculty Startup Fund from Seoul National University (grant number: 550-20230104). C.K.P.: BRAF LGG consortium research fund, National Institute of Health [17×074] Bio-X Seed Grant, Stanford Cancer Institute, National Institute of Health U54 [CA261717].
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P.S. conducted data analysis, prepared figures, and contributed to manuscript writing. H.J.P. performed experiments, collected data, and contributed to manuscript writing. B.A.S. provided intellectual input and revised the manuscript. K.Y.H., H.J.Y., H.J.K., T.C., J.H.H., S.M.N., Y.H.B., and H.K. performed experiments and collected data. Y.L.X. data and analyses, manuscript revision. J.H.L., S.-T.L., T.M.K., and S.H.C. contributed to clinical analysis. J.-K.W. and S.-H.P. carried out histological and molecular analyses. J.-L.K. established cell lines. S.L. and H.Y. performed genetic analyses. C.K.P. provided intellectual input, resources, mouse model, data, manuscript revision. C.-K.P., W.-Y.P., and N.S. supervised the study, provided conceptual input and critical review; N.S. additionally performed data analysis and manuscript writing. C.-K.P. provided clinical supervision. C.-K.P., W.-Y.P., and N.S. are corresponding authors.
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Sonpatki, P., Park, H.J., Xing, Y.L. et al. A spatially resolved human glioblastoma atlas reveals distinct cellular and molecular patterns of anatomical niches. Nat Commun (2026). https://doi.org/10.1038/s41467-026-69716-2
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DOI: https://doi.org/10.1038/s41467-026-69716-2
