ArticleiScience2026
Multi-omics profiling-derived signature links cellular ecosystem to glioblastoma prognosis.
Article in iScience, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Authors and funding
7 authors.
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Abstract
Glioblastoma (GBM) remains a devastating brain malignancy with a dismal prognosis, underscoring the urgent need for robust prognostic biomarkers and therapeutic targets. Here, we developed and validated a seven-gene extracellular matrix-related prognostic signature (ECMSig) using multi-omics data. The ECMSig robustly stratified GBM patients into high- and low-risk groups with distinct overall survival in The Cancer Genome Atlas cohort and Chinese Glioma Genome Atlas cohorts. High ECMSig scores were associated with aggressive molecular features, including upregulation of epithelial-mesenchymal transition and hypoxia, and a tumor-promoting immune microenvironment. Single-cell RNA sequencing analysis identified prognostic Scissor-Positive tumor, myeloid, and endothelial cells exhibiting high ECMSig scores, mesenchymal/immunosuppressive phenotypes, and notable metabolic reprogramming. These cells orchestrate a complex intercellular communication network and spatially co-localize within hypoxic perivascular niches. Furthermore, ECMSig predicted differential drug sensitivities, offering potential therapeutic avenues. The prognostic ECMSig highlights the complex interplay within the GBM ecosystem, paving the way for personalized therapeutic strategies.
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