ArticleInternational journal of molecular sciences2025
An MHC-Related Gene's Signature Predicts Prognosis and Immune Microenvironment Infiltration in Glioblastoma.
Article in International journal of molecular sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
1 citing paper in PubMed.
- Identification of immune-related gene signature for predicting prognosis of glioblastoma patients.Translational cancer research · 2026Article
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Authors and funding
7 authors.
Funding
Abstract
Glioma is the most common primary malignant intracranial tumor with limited treatment options and a dismal prognosis. This study aimed to develop a robust gene expression-based prognostic signature for GBM using the Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) datasets. Using WGCNA and LASSO algorithms, we identified four MHC-related genes (TNFSF14, MXRA5, FCGR2B, and TNFRSF9) as prognostic biomarkers for glioma. A risk model based on these genes effectively stratified patients into high- and low-risk groups with distinct survival outcomes across TCGA and CGGA cohorts. This signature correlated with immune pathways and glioma progression mechanisms, showing strong associations with immune function and tumor microenvironment infiltration patterns. The risk score reflected tumor microenvironment remodeling, suggesting its prognostic relevance. We further propose I-BET-762 and Enzastaurin as potential therapeutic candidates for glioma. In conclusion, the four-gene signature we identified and the corresponding risk score model constructed from it provide valuable tools for the prognosis prediction of glioblastoma multiforme (GBM) and may guide personalized treatment strategies. The least absolute shrinkage and selection operator (LASSO) risk score has demonstrated significant prognostic evaluation utility in clinical GBM patients, bringing potential implications for patient stratification and the optimization of treatment regimens.
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Registered trials
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