Identification of Iron Metabolism-Related Genes as Prognostic Indicators for Lower-Grade Glioma - Xu, Shenbin; Wang, Zefeng; Ye, Juan; Mei, Shuhao; Zhang, Jianmin (Frontiers in Oncology, 2021)
Objective To identify iron metabolism-related genes and construct a prognostic model for low-grade glioma (LGG) . Methods RNA-sequence and clinicopathological data were downloaded. Prognostic iron metabolism-related genes were screened and used to construct a risk-score model. The prognostic significance of the model was evaluated with Kaplan-Meier (KM) survival and receiver operating characteristic (ROC) analysis. Furthermore, a nomogram model with a risk score was developed and validated. Gene set enrichment analysis (GSEA), immune infiltration and immune checkpoint analyses were also investigated. Results We identified 15 genes to construct risk score model, which was significantly associated with survival time. Nomogram model showed good predictive accuracy. GSEA analysis indicated that tumor-associated pathways were enriched in high-risk group. A high risk score correlated with the infiltration immune cells and expression of immune checkpoint. Conclusion Our prognostic model based on iron metabolism-related genes can potentially aid in LGG prognosis, and provides potential targets against gliomas.