A signature based on seven disulfidptosis-related long non‑coding RNAs to predict the prognosis in Wilms' tumor

Disulfidptosis has been demonstrated to be associated with prognosis in certain tumors. However, the prognostic significance of disulfidptosis-related long non-coding RNAs (lncRNAs) in Wilms' tumor (WT) remains unclear. Initially, we downloaded the transcriptome and clinical data of WT patients from the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) database. Then, we identified disulfidptosis-related lncRNAs with prognostic significance to construct a risk model through correlation analysis, univariate Cox regression analysis, Lasso regression analysis, and multivariate Cox regression analysis. Furthermore, we validated the accuracy of the model using survival analysis, independent prognostic analysis, C-index analysis, receiver operating characteristic (ROC) curves, and a nomogram. Finally, the analysis of tumor microenvironment and immune function was conducted in samples from both high-risk and low-risk groups. A total of 7 lncRNAs were ultimately identified for the development of a prognostic model. Upon internal validation, this model exhibited remarkable efficacy in accurately discriminating between high-risk and low-risk patients, thereby enabling precise prognosis determination. Furthermore, notable statistical disparities were observed in the tumor microenvironment composition and immune function between the high-risk and low-risk groups' samples. In summary, we have successfully developed a prognostic risk model for lncRNAs associated with disulfidptosis in pediatric patients with Wilms’ tumor (WT). It played an important role in determining prognosis and in investigating new targets for tumor therapy.