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Background Cuproptosis is a novel method of modulating cell death that regulates tumorigenesis and progression processes. Cuproptosis-associated lncRNAs (CALs) are not clearly understood in colon cancer (CC). Furthermore, it is currently unknown how CALs affect prognosis and how they relate to the immune microenvironment of CC. Our study investigated the potential prognostic value of CALs and their association with immune microenvironments in CC patients.Methods The RNA of CC patients was sequenced, and medical data were retrieved from The Cancer Genome Atlas (TCGA) portal. A total of 446 participants were randomly assigned to the training and testing cohorts. The Pearson correlation analysis was used to recognize CALs. To choose significant markers in the training cohort, we used univariate regression with the LASSO method, followed by multivariate Cox regression analysis to develop the final prediction model. Therefore, we developed a predictive model based on the cuproptosis signature. The performance of the proposed model was assessed using the receiving operating characteristic (ROC) analysis. We also investigated the relationship between this signature and medication susceptibility, somatic mutations, and immunological infiltration.Results CC patients were divided into two risk cohorts using a 5-CAL signature; the patients in the elevated-risk cohort exhibited a poorer prognosis. The ROC analysis revealed the predictive accuracy of the developed risk model. We also detected variations in immune cell infiltration between the two cohorts, such as CD8 + T cells, regulatory T cells, and M0 and M1 macrophages. The high-risk cohort also exhibited lower IC50 values for several chemotherapy drugs.Conclusion We recognized a novel CAL signature that accurately predicts the prognosis of CC patients. CALs may be therapeutic targets for CC and may have a function in the antitumor immune system. |