Molecular Subtyping and Prognostic Prediction Based on the Ferroptosis-Related Long Non-Coding RNA Signature in Clear Cell Renal Cell Carcinoma

BackgroundRenal cell carcinoma is gradually characteristic of the accumulation of lipid-reactive oxygen species. And, the ferroptosis-related LncRNAs have been reported strongly correlated with tumorigenesis and progression. However, the further functions of ferroptosis-related LncRNAs in clear cell renal cell carcinoma have not been explored. MethodsAfter sample cleaning, data integration, and batch effect removal, we used the Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) public database to screen out the expression and prognostic value of ferroptosis-related LncRNAs and then performed the molecular subtyping. The molecular subtyping was developed using the K-means. Then, the KEGG pathway enrichment and statistical analyses of the immune microenvironment and clusters were carried out. The outcomes indicated significant differences in the immune microenvironment and potential therapeutic targets between the two clusters. Then, LASSO Cox regression was performed to establish the 5-LncRNAs-based prognostic signature. The signature could accurately predict patient prognosis and be used as an independent clinical risk factor. And the 5 LncRNAs were validated in the cell lines and clinical samples. We then combined significant clinical parameters in multivariate Cox regression and prognostic signature to construct a clinical predictive nomogram, which provides appropriate guidance for predicting the overall survival of ccRCC patients.ResultsThe prognostic DEFRLncRNAs were identified, and 5 LncRNAs were finally utilized to establish the prognostic signature in the TCGA cohort, which was subsequently validated in the internal and external cohorts. Moreover, we conducted the molecular subtyping and divided the patients in the TCGA cohort into two clusters, showing the difference in the Hallmark pathways, immune infiltration, expression of the immune target, and drug therapy. Furthermore, the nomogram was established better to predict the clinical outcomes of the ccRCC patients. ConclusionsOur study conducted molecular subtyping and established a novel predictive signature based on the ferroptosis-related LncRNAs, which could accurately predict prognosis and potential therapeutic targets in ccRCC patients.