A prognostic model for cervical cancer based on ferroptosis-related genes

BACKGROUND: Ferroptosis is widely involved in the occurrence and development of various cancers, but a specific mechanism involving ferroptosis in cervical cancer is still unclear. METHODS: Based on the expressions of ferroptosis-related genes, a prognostic model was constructed using lasso regression, and the overall predictive performance of this model was verified. An in-depth analysis of the prognostic model was then conducted. RESULTS: The prognostic model showed good predictive performance in both the validation and test sets. Mechanism analysis indicated that differences in the tumor microenvironment were the basis of the predictive ability of the model. Notably, CA9 mRNA was significantly overexpressed in cervical carcinoma, tissues but not in normal cervix tissues. A pair of ceRNAs (CA9/ULBP2) could be involved in the carcinogenesis and development of cervical cancer, and the potential target might be hsa-miR-34a. In addition, predicted miRNAs and drugs for these DEGs were identified. CONCLUSIONS: We constructed a prognostic model with good predictive performance, based on the expression of ferroptosis-related genes. Further research found that the ceRNA pairs of ULBP2/CA9 could regulate cervical cancer through hsa-miR-34a. These results identified the mechanism of ferroptosis in cervical cancer, and might provide novel therapeutics for cervical cancer patients.