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image of Single-Cell and Bulk Transcriptomic Integration Reveals a Stemness-Related Astrocyte Subpopulation for Prognostic Risk Stratification in Glioblastoma

Abstract

Introduction

Glioblastoma (GBM) is an aggressive brain tumor with pronounced heterogeneity. Stemness-related cell subpopulations are crucial for progression and therapy resistance, but their prognostic role remains unclear.

Methods

We integrated single-cell RNA sequencing (scRNA-seq) and bulk RNA-seq data to identify a stemness-high astrocyte subpopulation. Key genes were selected to construct a prognostic risk model using Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression, which was validated in The Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA) cohorts. Tumor microenvironment and pathway analyses were performed. functional assays were conducted on GBM cell lines.

Results

A four-gene signature ( and ) was established. The risk model robustly stratified patients into high- and low-risk groups with distinct overall survival in both cohorts. Importantly, multivariate Cox regression confirmed the RiskScore as an independent prognostic factor beyond age and isocitrate dehydrogenase (IDH) mutation status. Functional validation revealed that knockdown significantly suppressed GBM cell proliferation and migration . Further analyses showed that high-risk tumors were characterized by elevated immune/stromal scores, immunosuppressive cell infiltration, and activation of stemness-related pathways, including EGFR/MAPK, NF-κB, and VEGF-mediated angiogenesis.

Discussion

This integrated analysis identified a stemness-associated astrocyte subpopulation in GBM. The four-gene signature provides an independent prognostic tool and reflects immune microenvironment remodeling, offering insights into risk stratification and potential targeted therapy.

Conclusion

We developed a stemness-associated four-gene signature that enables risk stratification in GBM and reveals an immunosuppressive microenvironment in high-risk tumors, providing new directions for prognosis and targeted therapy.

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2026-04-06
2026-04-17
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