Construction of a Cuproptosis-Related lncRNA Signature for Predicting Prognosis and Immune Response in Cervical Cancer

Abstract

Background:Cuproptosis is a novel form of cell death, which is triggered by targeted mitochondria that bind the acylated lipid components of the tricarboxylic acid (TCA) cycle. Recent studies have suggested that targeting cuproptosis may be a new treatment strategy for cancer, but its association with cervcal cancer (CC) has not been elucidated. Methods: Data were downloaded from the TCGA-CESC. The cuproptosis-related lncRNAs were identified and prognostic risk models were constructed. Kaplan-Meier survival analysis, ROC curve, PCA and stratified analysis were used to validate the predictive ability of the model. A nomogram for predicting CC prognosis was established. The biological mechanisms associated with cuproptosis were investigated by GO and KEGG enrichment analysis. The CIBERSORT algorithm, immunoassay and TIDE score were used to measure different immune responses. Finally, we screened for sensitive drugs based on cuproptosis correlation. Results: We constructed a cuproptosis-related lncRNAs signature as a risk prognostic prediction model. The risk score was proved and the risk model had higher diagnostic efficiency than other features. The Kaplan-Meier curve indicated that lower risk score was significantly associated with better OS rate in training (P<0.001), testing group (P=0.004), and all groups (P<0.001). The time-dependent ROC curves showed the AUC reached 0.738 at 1 year, 0.698 at 3 years, and 0.699 at 5 years. GO and KEGG enrichment analysis found that the DEGs of low- and high-risk groups may be related to immune regulation. Further study of immune cell infiltration demonstrated that cuproptosis-related lncRNAs signature was significantly associated with the immune response of CC. A total of 23 drugs showed significant differences in the semi-inhibitory concentration (IC50) value, suggesting the signature may participate in the influence on drug efficacy. Conclusions: Our study reveals that assessing cuproptosis patterns in individual tumors will help improve our understanding of the immune mechanisms and prognosis of cervical cancer and thus guide immunotherapy more effectively. Establishing an independent prognostic model based on cuproptosis-associated lncRNAs could serve as a predictor of overall survival and also as a predictor of immunotherapy. The model may help provide personalized medical therapy and new insights into cancer treatment.