Cuproptosis‑related lncRNAs predict the prognosis and immune landscape in esophageal carcinoma

Background: Used cuproptosis-related lncRNA (CUPlncRNA) to construct an overall survival (OS) model of the esophageal carcinoma (ESCC) and predict potentially effective chemotherapeutic agents. Methods: Gain RNA-seq and clinical date of ESCC patients from The Cancer Genome Atlas (TCGA) database, extract cuproptosis-related lncRNAs (CUPlncRNAs) by co-expression analysis with cuproptosis-related genes (CRGs). Cox regression analysis and the least absolute shrinkage and selection operator analysis were used to construct the prognostic model. Kaplan-Meier survival curves, receiver operating characteristic (ROC) analysis, and C-index was used to further test the model. Tumor mutation burden (TMB) analysis was performed. Finally, TMER and single-sample gene set enrichment analysis (GESA) were applied to find out whether CUPlncRNA influenced the tumor immune microenvironment and to predict potentially effective chemotherapeutic agents for ESCC. Results: Five CUPlncRNAs were used to construct prognostic model. The model showed power in survival prediction between the high- and low-risk groups both before and after binding to TMB. The high-risk group had increased immune checkpoint and HLA mutations, means immune evasion happens more easily. Finally, 15 chemotherapeutic agents were screened for differences in efficacy between groups. Conclusions: This study has prognostic prediction and immune evaluation, provide theoretical basis for the role of cuproptosis in ESCC.