Prognostic Value of Ferroptosis-Immunity-Related Signature Genes in Cervical Cancer Radiotherapy Resistance and Risk Modeling.

INTRODUCTION

The aim of this study was to clarify the genome of ferroptosis in the genes involved in radiotherapy resistance and regulation of tumor immune microenvironment by multigene analysis of cervical cancer (CC) patients.

METHODS

Different radiation sensitivity samples from CC patients were collected for RNA sequencing. Differentially expressed genes (DEGs) between the RNA dataset and the GSE9750 dataset were considered as radiotherapy-DEGs. The intersection genes of radiotherapy-DEGs with ferroptosis-related genes (FRGs) and the intersection genes of radiotherapy-DEGs with immune-related genes (IRGs) were labeled as FRGs-IRGs-DEGs (FIGs). A risk model was established by prognostic genes selected from FIGs by univariate Cox analysis and least absolute shrinkage and selection operator (LASSO) analysis. The results were further validated using samples from CC tissue samples.

RESULTS

The 329 DEGs related to CC radiotherapy were identified. LSAAO analysis was utilized to identify five prognostic genes (, and ) from six candidate prognosis genes and construct a risk model. The risk model demonstrated favorable effectiveness in predicting outcomes at 1, 3, and 5 years, as evidenced by ROC curves. Univariate and multivariate Cox regression analysis demonstrated that , and were independent prognostic factors. The results of functional similarity analysis showed that and had high average functional similarity. The results of PCR and IHC showed the same trend with the results above.

DISCUSSION

A novel prognostic model related to ferroptosis and immune microenvironment in CC radiotherapy was developed and validated, providing valuable guidance for personalized anti-cancer therapy.