HIST1H2BJ is associated with poor prognosis and an immune-altered tumor microenvironment in glioma.

Authors

Lupeng Zhang, Yue Li, Chen Shi, Yong Zhang, Ruijuan Liu, Chiwen Qu, Sihua Peng, Xiaoning Peng

Published in

Frontiers in immunology. Volume 17. Pages 1929885. Epub Sep 16, 2026.

Abstract

Glioma, the most prevalent and aggressive primary malignant brain tumor, is associated with poor clinical outcomes. There is an urgent need for novel biomarkers to predict survival and therapeutic response, as existing markers offer limited prognostic utility.
Single-cell RNA sequencing data from glioma patients were analyzed to identify CD8+ T cell-related genes. Four machine learning algorithms (XGBoost, Gradient Boosting Machine, LASSO, and Random Forest) were employed to screen genes associated with glioma prognosis. The expression of HIST1H2BJ was detected in clinical samples. Flow cytometry was performed to assess cell apoptosis, while Transwell assays were conducted to evaluate cell invasion and migration capabilities, respectively. A novel prognostic model, the Immune and Metabolic Prognostic Model of Glioma (IMPMG), was developed, and its accuracy was evaluated using receiver operating characteristic (ROC) curves and decision curve analysis (DCA). Additionally, potential small-molecule compounds were screened via molecular docking, and the binding stability was evaluated by molecular dynamics (MD) simulations.
HIST1H2BJ was identified as a critical gene associated with glioma prognosis. Functional assays confirmed that HIST1H2BJ knockdown promoted cell apoptosis and inhibited cell invasion and migration. Glioma patients with high HIST1H2BJ expression were closely associated with an immunosuppressive tumor microenvironment, with significantly increased infiltration of M2 macrophages and regulatory T cells (Tregs), as well as upregulated immune checkpoint expression. The IMPMG model, integrating HIST1H2BJ, immune-metabolic genes, and clinical variables, demonstrated superior prognostic accuracy (AUC > 0.86) and clinical utility compared to existing models. Furthermore, molecular docking identified VX-680 and A.770041 as candidate compounds associated with HIST1H2BJ-high drug-sensitivity prediction; their direct binding to HIST1H2BJ was assessed only in silico by molecular docking and dynamics simulations and requires experimental validation.
This study establishes HIST1H2BJ as an independent prognostic factor for glioma patient survival and a candidate prognostic biomarker whose therapeutic relevance requires further functional and preclinical investigation.

PMID:
42818904
Bibliographic data and abstract were imported from PubMed on 02 Oct 2026.

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