Screening of Differentially Expressed Iron Death-Related Genes and the Construction of Prognosis Model in Patients with Renal Clear Cell Carcinoma.

Objective: In this study, we used the TCGA database and ICGC database to establish a prognostic model of iron death associated with renal cell carcinoma, which can provide predictive value for the identification of iron death-related genes and clinical treatment of renal clear cell carcinoma. Methods: The gene expression profiles and clinical data of renal clear cell carcinoma and normal tissues were obtained in the TCGA database and ICGC database, and the differential genes related to iron death were screened out. The differential genes were screened out by single and multifactor Cox risk regression model. R software, "edge" package (version 4.0), was used to identify the DELs of 551 transcriptional gene samples and 522 clinical samples. The risk prediction model with genes was established to analyze the correlation between the genes in the established model and clinical characteristics, Through the final screening of iron death related genes, it can be used to predict the prognosis of renal clear cell carcinoma and provide advice for clinical targeted therapy. Results: Seven iron death differential genes (CLS2, FANCD2, PHKG2, ACSL3, ATP5MC3, CISD1, PEBP1) associated with renal clear cell carcinoma were finally screened and were refer to previous relevant studies. These genes are closely related to iron death and have great value for the prognosis of renal clear cell carcinoma. Conclusion: Seven iron death genes can accurately predict the survival of patients with renal clear cell carcinoma.