Construction and Validation of a Novel Cuproptosis-Related Seven-lncRNA Signature to Predict the Outcomes, Immunotherapeutic Responses, and Targeted Therapy in Patients with Clear Cell Renal Cell Carcinoma

Abstract

Background. Cuproptosis was recently recognized as a novel form of cell death, linked closely to the occurrence and progression of cancer. We aimed to identify prognostic cuproptosis-related long noncoding RNAs (lncRNAs) and build a risk signature to predict the prognosis and treatment responses of clear cell renal cell carcinoma (ccRCC) in this work. Methods. LASSO–Cox regression was conducted to construct the signature based on prognostic cuproptosis-related lncRNAs (CR-lncRNAs). The signature’s reliability and sensitivity were assessed by the Kaplan-Meier survival analysis and receiver operating characteristic analysis. External validation was performed via data from the International Cancer Genome Consortium database. On the basis of CR-lncRNAs, an lncRNA-microRNA-mRNA regulatory network was created, and functional enrichment analysis was used to investigate the underlying biological roles of these genes. In addition, the relationship between the risk signature and immunotherapy and targeted therapy responses was examined. Finally, the expression levels of seven candidate lncRNAs between tumor and normal cells were compared in vitro using quantitative real-time PCR. Results. A seven-CR-lncRNA risk signature was constructed, which showed a stronger potential for survival prediction than standard clinicopathological features in patients with kidney cancer. Functional enrichment analysis showed that the CR-lncRNA risk signature was enriched in ion transport-related molecular functions as well as various immune-related biological processes. Furthermore, we discovered that individuals in the high-risk group were more likely than those in the low-risk group to respond to immunotherapy and targeted therapies with medications like sunitinib and pazopanib. Finally, quantitative real-time PCR revealed that the expression levels of seven candidate lncRNAs differed significantly between RCC and healthy kidney cells. Conclusion. In summary, we generated a CR-lncRNA risk signature that may be utilized to predict outcomes in patients with ccRCC and responsiveness to immunotherapy and targeted treatment, potentially serving as a reference for clinical personalized medicine.