Abstract
Hypoxia as a hallmark of solid malignancies compromises therapeutic efficacy and prognosis. This study deciphers the functional role of hypoxia-induced ferroptosis in glioma prognosis. Hypoxia-related transcripts and ferroptosis markers were curated from public databases. ConsensusClusterPlus identify hypoxia-based molecular subtypes, while LASSO-penalized Cox regression integrated with limma-based differential expression analysis screened prognostic ferroptosis genes. Subsequent risk modeling was validated against clinical parameters and extended through nomogram construction. Protein-protein interaction networks centered on HIF-1αidentified high-confidence interactors, with parallel immune correlation analysis completing the systems-level investigation.Based on 27 hypoxia-associated genes, we stratified samples into three distinct hypoxic clusters. Differential analysis of 123 ferroptosis markers across clusters, combined with univariate Cox regression and LASSO regression, identified 23 hypoxia-induced ferroptosis genes for constructing a prognostic model. The model demonstrated robust predictive accuracy with AUC values of 0.80 (1-year), 0.86 (3-year), and 0.86 (5-year). GSEA revealed significant enrichment in ECM-receptor interactions, focal adhesion, JAK-STAT signaling, and p53 signaling pathways, suggesting their involvement in hypoxia-induced ferroptosis. Our risk model significantly outperformed conventional clinical parameters (pathology, grade, age, primary/recurrent status). Protein-protein interaction analysis incorporating HIF-1αand the 23-model genes identified XBP1 and VEGFA co-expression as significant positive prognostic factor. The immune infiltration analysis further indicated that M0 macrophages may participate in the regulation of the prognosis of VEGFA-XBP1.Hypoxia-induced ferroptosis modulation emerges as a prognostic factor in gliomas, with XBP1 and VEGFA representing druggable nodes for novel combination therapies.