New prognostic models in glioblastoma: based ferroptosis-related genes and immune scores

Background: Glioblastoma multiforme (GBM) has a high degree of malignancy and the clinical outcomes is dismal. Ferroptosis is critical to the development and progression of many diseases, such as cancer, cardiovascular diseases and aging. This study was designed to establish a sensitive prognostic model based on ferroptosis-related genes and immune scores to predict overall survival (OS) in patients with GBM. Methods: : The expression of genes and associated clinical parameters was obtained from the publicly available TCGA , CGGA and GEO database. According to the immune scores, patient samples were assigned into two groups. Their biological function analyses were performed through differently expressed genes. By means of LASSO, unadjusted and adjusted Cox regression analyses, this predictive signature was constructed and validated by external databases. Results: : A total of 4 ferroptosis-related genes (HMOX1,HSPB1,STEAP3,ZEB1)were ultimately screened as associated hub genes and utilized to construct a prognosis model. Then our constructed riskScore model significantly passed the validation in the external datasets of OS (all p < 0.05). Receiver operating characteristic (ROC) curve analysis was conducted. Finding the area under the ROC curves (AUCs) were 0.82 at 1 years, 0.75 at 3 years, 0.67 at 5 years. Functional analysis revealed that immune related processes were different between two risk groups.We also explored its association with immune infiltration. Conclusion: Our study successfully constructed a prognostic model containing 4 hub ferroptosis-related genes for GBM, helping clinicians predict patients’ OS and making the prognostic assessment more standardized. Future prospective studies are required to validate our findings.