Detection techniques for identifying key regulators of immunoinflammation in meningiomas: A bioinformatics analysis

Objectives: In this study, bioinformatics techniques were used to detect the expression of key regulators of immunoinflammation in meningiomas and analyze their functions. Methods: Two mRNA microarray datasets were selected from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) between meningioma and normal samples were identified using the Limma package. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were conducted with clusterProfiler. Gene set enrichment analysis was applied to the DEGs within key modules. Intersecting genes between DEGs and module genes were used to construct a protein-protein interaction network. The CIBERSORT algorithm was used to evaluate the relationship between the DEGs and the tumor immune microenvironment. Results: A total of 560 DEGs were identified (551 upregulated and 10 downregulated). The inflammatory chemokines C-X-C motif chemokine ligands (CXCL8, CXCL1, CXCL2, CX3CL1, CCL19, CCL20, CXCL3, and CXCL6), angiotensinogen, and pro-platelet basic protein (PPBP) were implicated in meningioma formation. Immune infiltration analysis revealed significant associations of CD8 T cells, plasma cells, activated natural killer cells, resting mast cells, and neutrophils with meningioma. Notably, PPBP and CCL19 emerged as potential biomarkers and therapeutic targets for meningioma. Conclusion: These findings identify novel candidate molecular markers for meningioma pathogenesis, namely, PPBP and CCL19, and highlight the critical role of immunoinflammatory responses in guiding future clinical treatment strategies. JOURNAL/atin/04.03/02274269-990000000-00032/figure1/v/2026-06-11T065823Z/r/image-tiff