Based on transcriptome analysis of novel prognosis and targeted therapy-related genes with ferroptosis in cervical cancer: A TCGA database research

Background: Ferroptosis is a newly discovered form of cell death in recent years, mainly due to the accumulation of reactive oxygen species, a metabolite of intracellular lipid. This study mainly focused on the finding of the ferroptosis-related genes associated with cervical cancer. Materials and Methods: The transcriptome sequencing data of cervical cancer patients in the Cancer Genome Atlas (TCGA) database and the ferroptosis driver factors in FerrDb were firstly downloaded. Then using univariate Cox, multi-Cox, and Lasso regression analysis to find prognostic ferroptosis-related genes. Subsequently, the ROC curve, survival analysis, PCA, T-SNE, and risk curve were further constructed to verify the accuracy of the model. Finally, GO and KEGG analysis was used to identify the gene ontology and signaling pathways involved in ferroptosis driver factors genes. Results: By using univariate Cox, lasso, and multivariate Cox proportional risk regression analysis, we constructed a prognosis risk model: Risk score = ETFRC × 0.008151625 + EALOX12B × (-0.091561269) + EATG3 × (-0.065389691) + EATG4D × (-0.074492225) + EWIPI2 × 0.088486467 + EIFNG × (-0.174707719) + ETNFAIP3 × 0.024081289 + EEGLN2 × (-0.15986193). The prognosis model showed that the prognosis of patients in the high-risk group was poor (P=2.568e-05). Besides the ROC curve, the area under the curve (AUC) reached 0.756 in one year, 0.756 in three years, 0.766 in five years, and 0.698 in ten years. GO analyses show that these genes are mainly enriched in the biological processes related to apoptosis and autophagy. KEGG results show that these genes are enriched in hsa04066: HIF-1 signaling pathway (P=0.003), and hsa04140: Regulation of autophagy (P=0.022). Among these 8 ferroptosis-related gene signatures, only ATG4D and ATG3 have no gene expression change in TCGA. Conclusion: In conclusion, this study provides a prognostic risk model based on ferroptosis-related genes, offering a valuable tool for predicting the prognosis of cervical cancer patients. The identified genes and their associated pathways may serve as potential therapeutic targets for improving the treatment outcomes of cervical cancer. Keywords: Cervical cancer, Gene signature, Prognostic, TCGA, Ferroptosis, Overall survival