ArticleNature communications2023
Spatial cellular architecture predicts prognosis in glioblastoma.
Article in Nature communications, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 99 papers.
What it found
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Who cites it
99 citing papers in PubMed.
- Early experience with cerebrospinal fluid cell-free DNA molecular profiling in a neuro-oncology practice.Journal of neuro-oncology · 2026Article
- A Spatial Atlas of Muscle-Invasive Bladder Cancer Reveals Lineage-Specific Vulnerabilities and Immune Architecture.Cancer discovery · 2026Article
- Article
- The spatial architecture of tumor immunity: Emerging predictive biomarkers across cancer.Immunologic research · 2026Review
- The Invasive Margin of Glioblastoma as a Molecular Ecosystem: Spatial Heterogeneity, Tumor-Host Interactions, and Therapeutic Opportunities.International journal of molecular sciences · 2026Review
- A benchmark study of vision and pathology foundation models for computational pathology.Nature communications · 2026Article
- Multimodal spatial omics: From data acquisition to computational integration.Patterns (New York, N.Y.) · 2026Review
- DNA-PKcs inhibition sensitizes glioblastoma to radiotherapy through reprogramming of tumor cell states and immune microenvironment cell types.Research square · 2026Article
- Tunable Technologies for the Glioma Tumor Microenvironment: A Comprehensive Review on Bench-to-Bedside Neurosurgical Advances.Brain sciences · 2026Review
- A longitudinal single-cell and spatial multiomic atlas of pediatric high-grade glioma.Cell reports. Medicine · 2026Article
- Astrocyte-associated immunosuppressive programs in brain tumors: a STAT3-centered perspective.Cancer metastasis reviews · 2026Review
- A Synaptogenesis-Associated Histomorphologic Signature from H&E Whole-Slide Images Predicts Glioma Prognosis and IdentifiesInternational journal of molecular sciences · 2026Article
- Neuroactive ligand-receptor interaction in gastric cancer: a comprehensive spatial single-cell analysis.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026Article
- Modeling glioblastoma relapse in vitro: a critical journey from 2D models to organ-on-chip alternatives.NPJ precision oncology · 2026Review
- Vascular invasion-associated gene expression is detectable in pre-surgical biopsies of stage I lung adenocarcinoma.Nature communications · 2026Article
- Precision Immunotherapeutics for Glioblastoma: Current Approaches and Emerging Strategies in 2026.Cells · 2026Review
- Spatially defined danger zone shapes gastric cancer progression through CCDC80Apoptosis : an international journal on programmed cell death · 2026Article
- Tumor microenvironment shapes the spatial organization of glioblastoma cell states.Neuro-oncology · 2026Review
- Prognostic value of a combined model integrating clinical and PET radiomics parameters in metastatic melanoma: A dual-center retrospective study.Annals of nuclear medicine · 2026Article
- AI-Based Methods in Neuropathology for Diagnosis and Treatment of Brain Tumors.European journal of neurology · 2026Review
39 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
Intra-tumoral heterogeneity and cell-state plasticity are key drivers for the therapeutic resistance of glioblastoma. Here, we investigate the association between spatial cellular organization and glioblastoma prognosis. Leveraging single-cell RNA-seq and spatial transcriptomics data, we develop a deep learning model to predict transcriptional subtypes of glioblastoma cells from histology images. Employing this model, we phenotypically analyze 40 million tissue spots from 410 patients and identify consistent associations between tumor architecture and prognosis across two independent cohorts. Patients with poor prognosis exhibit higher proportions of tumor cells expressing a hypoxia-induced transcriptional program. Furthermore, a clustering pattern of astrocyte-like tumor cells is associated with worse prognosis, while dispersion and connection of the astrocytes with other transcriptional subtypes correlate with decreased risk. To validate these results, we develop a separate deep learning model that utilizes histology images to predict prognosis. Applying this model to spatial transcriptomics data reveal survival-associated regional gene expression programs. Overall, our study presents a scalable approach to unravel the transcriptional heterogeneity of glioblastoma and establishes a critical connection between spatial cellular architecture and clinical outcomes.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.