ArticleFrontiers in cell and developmental biology2022
Type 1 T Helper Cell-Based Molecular Subtypes and Signature Are Associated with Clinical Outcome in Pancreatic Ductal Adenocarcinoma.
Article in Frontiers in cell and developmental biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed, 6 citations in OpenAlex.
- The interplay between p21-activated kinases and tumour-infiltrating dendritic cells and T cells and its implication in pancreatic cancer immunotherapy.Cell communication and signaling : CCS · 2026Review
- Glycolysis and T cell-associated gene signature predicts prognosis and therapeutic responses in pancreatic cancer.Frontiers in immunology · 2026Article
- Analysis of PD-L1 promoter methylation combined with immunogenic context in pancreatic ductal adenocarcinoma.Cancer immunology, immunotherapy : CII · 2024Article
- Current and future immunotherapeutic approaches in pancreatic cancer treatment.Journal of hematology & oncology · 2024Review
- Open-source curation of a pancreatic ductal adenocarcinoma gene expression analysis platform (pdacR) supports a two-subtype model.Communications biology · 2023Article
- An integrated overview of the immunosuppression features in the tumor microenvironment of pancreatic cancer.Frontiers in immunology · 2023Review
Corrections and comments
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Authors and funding
6 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Lymph node metastasis in pancreatic ductal adenocarcinoma (PDAC) is shown to be related with poor prognosis. To construct an immune-related gene prognostic risk model for PDAC and clarify the molecular and immune characteristics and the benefit of immune checkpoint inhibitor (ICI) therapy in prognostic risk model-defined subgroups of PDAC, we analyze the association between the density of immune cell infiltration and lymph node metastatic status and further study the potential role of immune cells, immune cell-related genes, and immunotherapy outcomes in PDAC patients using bioinformatics models and machine learning methods. Based on The Cancer Genome Atlas (TCGA), PACA-AU and PACA-CA data sets, 62 immune-related hub genes were identified by weighted gene co-expression network analysis (WGCNA). Four genes were selected to construct a molecular subtype identification based on the type 1 T helper cell-related hub genes by using the Cox regression method. We found that lower type 1 T helper cell abundance was correlated with prolonged survival in PDAC patients. Further, prognostic risk score model constructed with the type 1 T helper cell-related signature showed high accuracy in predicting overall survival and response to immunotherapy. This study might improve the understanding of the role of type 1 T helper cells in PDAC patients and aid in the development of immunotherapy and personalized treatments for these patients.
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Registered trials
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