To construct a prognostic model for pancreatic cancer based on disulfidptosis-related lncRNA and to analyze its clinical value in pancreatic cancer patients.

Initially, transcriptome data and clinical information pertaining to pancreatic cancer were retrieved from the Cancer Genome Atlas. By analyzing genes related to disulfidptosis, lncRNAs related to disulfidptosis were identified. Through univariate Cox analysis, LASSO analysis, and multivariate Cox analysis, lncRNAs closely related to disulfidptosis were screened and a prognostic model was constructed. Subsequently, univariate and multivariate Cox regression analysis was employed to conduct an independent prognostic analysis of the model, verifying whether its risk score functioned as an independent prognostic factor, regardless of other clinical features. Secondly, the accuracy of the prognostic model was verified using ROC curves, C-index, survival curves, nomogram, and principal component analysis. Additionally, gene enrichment analysis, immune-related functional analysis, tumor mutation burden analysis, immune-related analysis, tumor immune dysfunction analysis, and exclusion analysis were also performed.

The analysis identified and screened disulfidptosis-related lncRNAs. A prognostic model was then constructed, comprising 5 disulfidptosis-related lncRNAs: EMSLR, AC068580.2, AC096733.2, AC087501.4, and AC069360.1. Based on the survival analysis of this model, the areas under the ROC curves for predicting 1-, 3-, and 5-year overall survival were 0.675, 0.771, and 0.773, respectively, indicating the reliable predictive capability of this prognostic model for patient survival. Secondly, the model was verified through univariate and multivariate independent prognostic analysis to serve as an independent prognostic factor for predicting the prognosis of pancreatic cancer patients. Notably, significant differences in immune cell populations, immune function, tumor mutation burden, as well as tumor immune dysfunction and exclusion were observed between the high-risk and low-risk groups based on the analysis of this model.

In this study, a prognostic model for pancreatic cancer is successfully constructed based on 5 disulfidptosis-related lncRNAs. As an independent prognostic factor, this model exhibits strong predictive power for the prognosis of pancreatic cancer. These findings enhance our understanding of pancreatic cancer and potentially have positive impacts on personalized treatment strategies and risk assessment for the disease.