Immune-related hallmark pathway heterogeneity identifies a prognostic risk signature with independent external validation in glioblastoma

Abstract

Glioblastoma (GBM) is the most aggressive primary malignant brain tumor in adults and remains associated with poor clinical outcomes despite advances in surgery, radiotherapy, and chemotherapy. Increasing evidence suggests that the glioblastoma immune microenvironment and coordinated oncogenic signaling pathways play critical roles in tumor progression, therapeutic resistance, and survival heterogeneity. However, the prognostic relevance of pathway-level immune activity in GBM remains incompletely understood. In this study, we performed a comprehensive transcriptomic and pathway-centered analysis of glioblastoma using RNA-sequencing data and clinical information obtained from The Cancer Genome Atlas (TCGA-GBM) cohort. Single-sample gene set enrichment analysis (ssGSEA) was applied to quantify hallmark pathway activity across tumors, followed by immune subtype clustering, survival analysis, Cox regression modeling, machine learning-based pathway prioritization, and prognostic risk signature construction. The reproducibility of the developed prognostic model was subsequently evaluated using an independent Chinese Glioma Genome Atlas (CGGA) validation cohort. Our analysis demonstrated substantial inter-patient variability in immune-related and oncogenic hallmark signaling pathways. Inflammatory and mesenchymal-associated pathways, including TNF-α/NF-κB signaling, IL6/JAK/STAT3 signaling, interferon responses, epithelial–mesenchymal transition, hypoxia, complement activation, and KRAS signaling, showed marked differences across patients and were strongly associated with aggressive disease phenotypes. Two immune-associated molecular subtypes with distinct pathway activation patterns were identified. Furthermore, multiple hallmark pathways demonstrated significant prognostic associations and were integrated into a pathway-derived prognostic risk signature that successfully stratified patients into high-risk and low-risk groups with significantly different overall survival outcomes. Multivariate Cox regression analysis confirmed that the calculated risk score retained independent prognostic significance after adjustment for clinical variables. Importantly, external validation using the CGGA cohort demonstrated stable prognostic performance and reproducibility across independent patient populations. Taken together, these findings demonstrate that immune-related hallmark pathway activity contributes substantially to glioblastoma biological heterogeneity and patient prognosis. The proposed pathway-based prognostic framework provides a biologically interpretable approach for survival stratification and may support future efforts toward precision oncology and pathway-oriented therapeutic investigation in glioblastoma.