A novel ferroptosis-related gene signature for predicting outcomes in cervical cancer
Xingling Qi, Yi‐Peng Fu, Jia Sheng, Meng Zhang, Mingxing Zhang, Yumeng Wang, Guiling Li
Abstract
Ferroptosis, a newly discovered iron-dependent form of cell death, contributes to various pathologies; however, the prognostic value of ferroptosis-related genes (FRGs) in cervical cancer (CC) remains unclear. Herein, we identified 15 differentially expressed FRGs based on data from The Cancer Genome Atlas database. Ten FRGs that correlated with prognosis were screened by univariate Cox regression analysis. The least absolute shrinkage and selection operator regression model was performed to develop a novel prognostic signature. A four-gene model was built to separate samples into high-risk and low-risk groups. Overall survival was lower in the high-risk group than in the low-risk group (p < 0.05). Receiver operating characteristic curve showed a good diagnostic efficiency of the signature. The risk score was identified as an independent prognostic factor via multivariate Cox regression. A functional analysis further revealed a difference in the immune status between the two risk groups. To conclude, we constructed a novel prognostic signature based on FRGs. Targeting ferroptosis may represent a promising approach for the treatment of CC.