{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,16]],"date-time":"2026-09-16T06:04:56Z","timestamp":1789538696808,"version":"build-2803163510"},"reference-count":54,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,9,16]],"date-time":"2026-09-16T00:00:00Z","timestamp":1789516800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Immunol."],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>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.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      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\n                      <jats:italic>HIST1H2BJ<\/jats:italic>\n                      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.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      <jats:italic>HIST1H2BJ<\/jats:italic>\n                      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\n                      <jats:italic>HIST1H2BJ<\/jats:italic>\n                      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\n                      <jats:italic>HIST1H2BJ<\/jats:italic>\n                      , immune-metabolic genes, and clinical variables, demonstrated superior prognostic accuracy (AUC &amp;gt; 0.86) and clinical utility compared to existing models. Furthermore, molecular docking identified VX-680 and A.770041 as candidate compounds associated with\n                      <jats:italic>HIST1H2BJ<\/jats:italic>\n                      -high drug-sensitivity prediction; their direct binding to\n                      <jats:italic>HIST1H2BJ<\/jats:italic>\n                      was assessed only in silico by molecular docking and dynamics simulations and requires experimental validation.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>\n                      This study establishes\n                      <jats:italic>HIST1H2BJ<\/jats:italic>\n                      as an independent prognostic factor for glioma patient survival and a candidate prognostic biomarker whose therapeutic relevance requires further functional and preclinical investigation.\n                    <\/jats:p>\n                  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