ArticleJournal of molecular neuroscience : MN2025
Identification of Key Biomarkers Associated with Glioma Hemorrhage: Evidence from Bioinformatic Analysis and Clinical Validation.
Article in Journal of molecular neuroscience : MN, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Hemorrhagic stroke is a known complication of glioma, yet the underlying mechanisms remain poorly understood. This study aims to investigate key biomarkers of glioma-related hemorrhage to provide insights into glioma molecular therapies. Data were obtained from the Gene Expression Omnibus (GEO) and the Cancer Genome Atlas (TCGA) databases to analyze differentially expressed genes (DEGs) in glioma by contrasting glioblastoma (GBM) with low-grade gliomas (LGGs). We conducted enrichment analyses using the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and Gene Ontology (GO) databases through the Database for Annotation, Visualization, and Integrated Discovery (DAVID). A STRING-based protein-protein interaction (PPI) network was developed to identify hub genes, which were subsequently analyzed for their functions in the GeneCards database. To identify angiogenesis-associated genes, we utilized the Human Protein Atlas (HPA) and Gene Expression Profiling Interactive Analysis (GEPIA) databases. A clinical pathological study was conducted using immunohistochemistry (IHC) staining to confirm the findings. In the GEO database, the GEO Series Experiments GSE26576 and GSE184941 included 4523 and 1471 differentially expressed genes (DEGs), respectively. We identified 2715 DEGs using the cBioPortal within the TCGA database. A Venn diagram identified 39 common DEGs. The KEGG pathways and Gene Ontology (GO) analysis highlighted functions related to angiogenesis. PPI network analyses pinpointed 13 hub genes. Through cross-referencing a gene set related to tumor angiogenesis in the GeneCards database, we identified MMP-2 and EGFR as key genes. In the HPA database, we observed EGFR and MMP-2 expression in the normal cerebral cortex, confirmed by IHC. In GEPIA database, high MMP-2 levels were associated with decreased survival time, while EGFR expression showed no significant differences in survival. A clinical study of 21 patients, 11 in the control group and 10 in the stroke group with glioma hemorrhage, revealed no significant differences in their characteristics or comorbidities. IDH1 positivity was higher in the control group (4/11) vs the stroke group (0/10). Tumor cells exhibited increased MMP-2 and EGFR expression, with stronger staining in the stroke group. Our study concluded that IDH1, MMP-2, and EGFR are implicated in the molecular mechanism of glioma hemorrhage as key biomarkers. MMP-2 and IDH1 are potential targets for molecular therapy.
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