Objective: Currently, the mechanism of ferroptosis in the progression of kidney renal clear cell carcinoma (KIRC) is still unclear. This paper aims to explore the potential mechanism of ferroptosis-related genes in KIRC.Methods: Using KIRC chip data in Gene Expression Synthesis (GEO) database, the differentially expressed genes (DEGs) between normal and tumor group were screened in GSE168845, GSE105261 and GSE11151 by limma package. Ferroptosis-related DEGs were gained by the intersection of DEGs and ferroptosis-related genes, which from the FerrDb database. Gene ontology (GO) enrichment analysis of ferroptosis-related DEGs was carried out by gene set enrichment analysis (GSEA). Univariate and multivariate Cox risk regression model was used to screen and establish gene prognosis risk prediction model. For ferroptosis-related DEGs, targeted small molecules are predicted for the treatment of KIRC.Results: In GSE168845, GSE105261 and GSE11151, 2532 DEGs were screened from normal group and tumor group. And 149 ferroptosis-related genes were obtained from the FerrDb database. Through the intersection of DEGs and ferroptosis-related genes, 17 ferroptosis-related DEGs were obtained. GO enrichment analysis indicated that primary biological processes of 17 ferroptosis-related DEGs enrichment had iron ion binding, microvillus membrane and regulation of transcription from RNA polymerase II promoter in response to stress. Based on univariate and multivariate Cox regression analysis, the multivariate prognostic risk prediction model composed of three ferroptosis DEGs including MT1G, LAMP2 and MIOX was constructed. The results of patient risk score indicated that the prognosis with high score was worse than those with low score. Meanwhile, we found that the exprssion of MT1G, LAMP2 and MIOX were related with methylation and immune infiltration in KIRC. Terroptosis-gene interaction and terroptosis-miRNA coregulatory network of MT1G, LAMP2 and MIOX were collected by Network Analyst. Then, the ferroptosis-related prognosis nomogram, including age, gender, grade, TNM and risk score, was found to predict the overall survival (OS) of KIRC patients. Finally, according to ferroptosis related DEGs, the potential therapeutic effects of emetine, cephaeline,scoulerline, sanguinarine, cicloheximide, tolfenamic acid, phenoxybenzamine and calmidazolium were predicted in KIRC.Conclusion: The risk prediction models of MT1G, LAMP2 and MIOX can effectively predict the prognosis of patients with KIRC. And MT1G, LAMP2 and MIOX are related to methylation and immune infiltration in KIRC, which is expected to play a guiding role in the clinical treatment of KIRC. Targeted these three genes, potential therapeutic drugs of emetine, cephaeline,scoulerline, sanguinarine, cicloheximide, tolfenamic acid, phenoxybenzamine and calmidazolium were also predicted in KIRC.