基于铜死亡相关lncRNAs的胰腺癌预后模型构建与验证OACSTPCD

Objective To explore the prognostic value of cuproptosis-associated lncRNAs in pancreatic cancer patients and develop a prognostic prediction model.Methods Transcriptome sequencing data and corresponding clinical information of pancreatic cancer patients were obtained from the TCGA database.Prognosis-associated cuproptosis-associated lncRNAs were identified through Pearson correlation analysis.A prognostic model was then constructed using univariate Cox regression and Lasso regression analysis.Patients were divided into high and low-risk groups based on the median risk score from the model.The prognostic predictive value of the model was evaluated using Kaplan-Meier survival analysis,subgroup analysis,ROC curve analysis,and concordance index analysis.The model's independence of was confirmed through univariate and multivariate regression analysis.Differential genes expression between high and low-risk groups was analyzed using GO and KEGG functional enrichment analyses.Furthermore,tumor mutation burden(TMB)analysis,immune therapy response prediction,and drug sensitivity analysis were performed for patients in both risk groups.Results Through Pearson correlation analysis,127 cuproptosis-associated lncRNAs were identified.Subsequently,a prognostic prediction model based on six cuproptosis-associated lncRNAs was constructed using univariate Cox regression analysis and Lasso regression analysis.Stratification of PAAD patients into high-risk and low-risk groups was performed based on the model's calculations.Kaplan-Meier survival analysis indicated that patients in the low-risk group had significantly longer survival time compared to those in the high-risk group(P<0.05).ROC curve analysis showed good predictive performance of the model for pancreatic cancer patient prognosis,with AUCs of 0.687(1 year),0.753(3 years),and 0.771(5 years),respectively.Gene function enrichment analysis revealed that differentially expressed genes between the high and low-risk groups were mainly enriched in immune-related pathways.Moreover,patients in the high-risk group exhibited significantly higher TMB values but lower TIDE scores compared to those in the low-risk group.Furthermore,drug sensitivity analysis revealed significant differences in the sensitivity of pancreatic cancer patients to specific drugs among the different risk groups,providing valuable guidance for clinical treatment decisions.Conclusion This study successfully constructed a prognostic signature for pancreatic cancer patients based on cuproptosis-associated lncRNAs,providing accurate prognosis predicitions and personalized guidance for clinical drug treatment selection.