Construction of a prognostic model for pancreatic ductal adenocarcinoma based on m6A- and m5C-related lncRNAs and its relationship with the immune microenvironment
Author:
Affiliation:

1.Department of Gastroenterology Xiangya Hospital, Central South University, Changsha 410008, China;2.Department of Cardiology Xiangya Hospital, Central South University, Changsha 410008, China;3.Department of Hematology Xiangya Hospital, Central South University, Changsha 410008, China;4.Department of Obstetrics and Gynecology Xiangya Hospital, Central South University, Changsha 410008, China

Clc Number:

R735.9

Fund Project:

  • Article
  • |
  • Figures
  • |
  • Metrics
  • |
  • Reference
  • |
  • Related
  • |
  • Cited by
  • |
  • Materials
  • |
  • Comments
    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.

    Reference
    Related
    Cited by
Get Citation

WANG Jie, LIAO Junxi, QIU Yi, JIANG Yuanna, SHI Yuxin, PENG Jie. Construction of a prognostic model for pancreatic ductal adenocarcinoma based on m6A- and m5C-related lncRNAs and its relationship with the immune microenvironment[J]. Chin J Gen Surg,2025,34(3):475-484.
DOI:10.7659/j. issn.1005-6947.240563

Copy
Share
Article Metrics
  • Abstract:
  • PDF:
  • HTML:
  • Cited by:
History
  • Received:November 06,2024
  • Revised:March 21,2025
  • Adopted:
  • Online: April 14,2025
  • Published: