Complement system-related gene signatures implicated in the recurrence of glioma.

Glioma represents the most common primary malignant tumor of the central nervous system. The complement system, as a key component of the tumor microenvironment (TME), participates in tumor progression by mediating inflammatory responses and immune regulation. However, the specific mechanisms whereby complement system-related genes drive glioma recurrence remain unclear, and robust molecular biomarkers for recurrence prediction are absent. Therefore, this study aims to explore how these genes facilitate glioma progression and recurrence, and to construct a gene signature for recurrence risk prediction. By analyzing data from public databases Genotype-Tissue Expression (GTEx) and Chinese Glioma Genome Atlas (CGGA) and employing differential expression analysis, univariate Cox regression, multivariate Cox regression, and Bioinformatic regression analyses, we identified six core genes (CFI, DIABLO, DLGAP5, FANCL, FCER2, TLR2) and constructed a recurrence risk score model. Furthermore, we externally validated the risk score model using recurrence-free survival (RFS) data from The Cancer Genome Atlas (TCGA) database to assess its predictive performance. Patients in the high-risk group exhibited significantly shorter overall survival (OS). At the mechanistic level, the expression of core genes was potentially closely associated with the C5-C5AR1 complement axis and M2 macrophage infiltration. The observed increase in immune cell infiltration, upregulation of immune checkpoints, and enhanced chemoresistance in the high-risk group suggest that the core genes may promote tumor progression by modulating an immunosuppressive microenvironment via the complement pathway. Analysis of chemotherapeutic drug sensitivity further revealed a more pronounced drug-resistant phenotype in the high-risk group. The prognostic performance of the model was validated using a nomogram, which demonstrated strong predictive ability. This study provides a novel complement system-related gene-based predictive model for glioma recurrence, which may provide a potential biomarker for prognosis assessment and personalized treatment, as well as new insights into the role of the complement system in the immune microenvironment of glioma.