RESUMEN
Objective To develop a new risk scoring model based on cuproptosis-related lncRNAs (CRLs) to predict the prognosis of lung squamous cell carcinoma (LUSC). Methods Data were obtained mainly from TCGA and GTEx databases. Univariate Cox, Lasso, and multivariate Cox regression analyses were conducted to determine CRLs that affect the prognosis of LUSC and establish a risk scoring model. The ability of risk score characteristics to independently predict LUSC survival was compared with that of clinical characteristics by calculating the area under the ROC curve (AUC). Immune-related functions and immune checkpoint differences were compared between high- and low-risk groups. Results Nine CRLs were selected as independent prognostic lncRNAs for LUSC, and a risk scoring model was developed. Risk score was the influence factor for the prognosis of LUSC. The AUC values predicted by the risk score model for 1-, 3-, and 5-year survival rates of patients with LUSC were 0.710, 0.718, and 0.743, respectively. The high- and low-risk groups were partly statistically different in terms of immune-related functional assays and immune checkpoint assays (P < 0.05). Conclusion The risk scoring model developed based on nine CRLs could predict the prognosis and immune therapy response of patients with LUSC in clinical practice.