Construction of a prognostic model for pancreatic adenocarcinoma based on palmitoylation-related lncRNAs

ABSTRACT: Objective: In recent years, it has been found that palmitoylation of many proteins is closely related to the occurrence and development of tumors. The objective of this study is to construct a prognostic risk model for pancreatic adenocarcinoma based on screening palmitoylation-related long non-coding RNAs (lncRNAs) from The Cancer Genome Atlas (TCGA) database to predict the prognosis of pancreatic adenocarcinoma patients. Methods: A prognostic model was constructed using Pearson correlation analysis, univariate Cox regression analysis, least absolute shrinkage and selection operator (LASSO) regression analysis, and multivariate Cox regression analysis. The model's validity was then validated. Functional enrichment analysis, tumor immune infiltration analysis, tumor mutation analysis, and drug sensitivity analysis were performed on the high-risk and low-risk groups differentiated by the model. Results: In this study, a prognostic risk model containing AC005332.6, AC007728.2, AC011498.6, AC025165.1, LINC00857, LINC02245, and PTPRN2-AS1 was constructed. It was found that the prognosis of patients in the high-risk group was poorer than that of those in the low-risk group (P<0.05). The tumor mutation burden (TMB) in the high-risk group was higher than that in the low-risk group (P<0.05), and the survival prognosis of the high TMB group was poorer. Furthermore, it was found that patients in the low-risk group may exhibit superior efficacy in response to immunotherapy. In the low-risk group, a variety of drugs, such as Cediranib and Foretinib, showed lower half-maximal inhibitory concentrations. Conclusion: The risk model based on palmitoylation-related lncRNAs expression can predict the prognosis of patients with pancreatic adenocarcinoma, and may provide reference for clinical treatment.