Construction of a prognostic model for pancreatic ductal adenocarcinoma based on m6A-and m5C-related lncRNAs and its relationship with the immune microenvironment
10.7659/j.issn.1005-6947.240563
- VernacularTitle:基于m6A和m5C相关lncRNA的胰腺导管腺癌预后模型及其与免疫微环境的关系
- Author:
Jie WANG
1
;
Junxi LIAO
;
Yi QIU
;
Yuanna JIANG
;
Yuxin SHI
;
Jie PENG
Author Information
1. 中南大学湘雅医院消化内科,湖南 长沙 410008
- Publication Type:Journal Article
- Keywords:
Pancreatic Neoplasms;
Methylation;
Tumor Microenvironment;
Prognostic Model
- From:
Chinese Journal of General Surgery
2025;34(3):475-484
- CountryChina
- Language:Chinese
-
Abstract:
Background and Aims:Pancreatic ductal adenocarcinoma(PDAC)is a highly malignant digestive system tumor with an inferior prognosis,and its early diagnosis and treatment remain significant challenges.In recent years,RNA methylation modifications(such as m6A and m5C)have attracted considerable attention for their roles in tumor development;however,their regulatory mechanisms and clinical significance in PDAC remain unclear.This study was conducted to identify prognosis-related long noncoding RNAs(lncRNAs)associated with m6A and m5C in PDAC,construct a reliable prognostic prediction model,and explore their relationship with the tumor immune microenvironment.Methods:Based on RNA-seq data from the TCGA-PDAC cohort,differentially expressed lncRNAs(DElncRNAs)related to m6A and m5C were identified through differential expression analysis and Pearson correlation analysis.The samples were randomly divided into a training set(n=89)and a validation set(n=89).Key DElncRNAs were selected using LASSO-Cox regression to construct a prognostic model,and patients were categorized into high-and low-risk groups based on risk scores.Kaplan-Meier survival analysis,ROC curves,and multivariate Cox regression were used to evaluate the model's predictive performance.Furthermore,CIBERSORT and ESTIMATE scores were used to analyze immune cell infiltration characteristics and tumor microenvironment(TME)differences between the high-and low-risk groups.Results:To construct the prognostic model,four m6A-and m5C-related DElncRNAs(LINC00857,LINC02038,TSPOAP1-AS1,and TRPC7-AS1)were identified.Patients in the high-risk group had significantly lower overall survival than those in the low-risk group(P<0.05),and the risk score was an independent prognostic factor for PDAC(HR=1.551,95%CI=1.297-1.854,P<0.001).ROC curve analysis showed that the risk score model exhibited high predictive efficiency in both the training and validation sets(AUC values for 1,3,and 5 years:0.766,0.875,0.879;0.685,0.711,0.792,respectively).Immune analysis revealed increased infiltration of M0 macrophages with lower TME scores in the high-risk group(all P<0.05),suggesting an immunosuppressive microenvironment.Conclusion:This study successfully established a PDAC prognostic model based on m6A-and m5C-related DElncRNAs and confirmed its independent predictive value.High-risk patients exhibited M0 macrophage enrichment and immunosuppressive microenvironment characteristics,possibly contributing to poor prognosis.
