ArticleFrontiers in immunology2023
Revealing the role of regulatory T cells in the tumor microenvironment of lung adenocarcinoma: a novel prognostic and immunotherapeutic signature.
Article in Frontiers in immunology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers.
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Who cites it
31 citing papers in PubMed, 62 citations in OpenAlex.
- Myeloid-derived MIF is a central regulator of MDSC-driven T-cell dysfunction in head and neck squamous cell carcinoma.Oncoimmunology · 2026Article
- CCT7 Expression Affects the Prognosis of Lung Adenocarcinoma.Cancer reports (Hoboken, N.J.) · 2026Article
- Single-cell analysis identifies a stemness-associated tumor cell subpopulation and develops a prognostic scoring model in esophageal squamous cell carcinoma.Translational oncology · 2026Article
- Identification and validation of prognostic genes for lung adenocarcinoma prognosis based on PANoptosis-related genes.Discover oncology · 2025Article
- Integrative Single-Cell and Machine Learning Analysis Reveals Immune Microenvironment Remodelling in Lymph Node Metastasis of Lung Adenocarcinoma.Journal of cellular and molecular medicine · 2025Article
- Identification of a deubiquitinating gene-related signature in ovarian cancer using integrated transcriptomic analysis and machine learning framework.Discover oncology · 2025Article
- Integrative analysis of genetic variability and functional traits in lung adenocarcinoma epithelial cells via single-cell RNA sequencing, GWAS, bayesian deconvolution, and machine learning.Genes & genomics · 2025Article
- Machine Learning-Based Glycolipid Metabolism Gene Signature Predicts Prognosis and Immune Landscape in Oesophageal Squamous Cell Carcinoma.Journal of cellular and molecular medicine · 2025Article
- Development of a novel prognostic signature based on cytotoxic T lymphocyte-evasion genes for hepatocellular carcinoma patient management.Discover oncology · 2025Article
- Unveiling the Role of Sialylation-Related LncRNAs in Lung Adenocarcinoma: A New Prognostic Model.Current genomics · 2025Article
- Article
- PANoptosis-Related Optimal Model (PROM): A Novel Prognostic Tool Unveiling Immune Dynamics in Lung Adenocarcinoma.International journal of genomics · 2025Article
- Multi-cohort validation based on a novel prognostic signature of anoikis for predicting prognosis and immunotherapy response of esophageal squamous cell carcinoma.Frontiers in oncology · 2025Article
- Harnessing single-cell and multi-omics insights: STING pathway-based predictive signature for immunotherapy response in lung adenocarcinoma.Frontiers in immunology · 2025Article
- Malignant epithelial cell marker-driven risk signature enables precise stratification in esophageal cancer.Frontiers in immunology · 2025Article
- Development of a machine learning-derived dendritic cell signature for prognostic stratification in lung adenocarcinoma.Frontiers in immunology · 2025Article
- Identification of novel molecular subtypes and construction of a prognostic signature via multi-omics analysis and machine learning in lung adenocarcinoma.Frontiers in oncology · 2025Article
- Single-cell and multi-omics analysis reveals the role of stem cells in prognosis and immunotherapy of lung adenocarcinoma patients.Frontiers in immunology · 2025Article
- Tumor associated neutrophils promote prostate cancer progression by mediating neutrophil trap secretion through PSMA1- NF-κB-HIF-1α signaling axis.Frontiers in immunology · 2025Article
- Multi-cohort validation based on coagulation-related genes for predicting prognosis of esophageal squamous cell carcinoma.Frontiers in immunology · 2025Article
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Authors and funding
6 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Regulatory T cells (Tregs), are a key class of cell types in the immune system. In the tumor microenvironment (TME), the presence of Tregs has important implications for immune response and tumor development. Relatively little is known about the role of Tregs in lung adenocarcinoma (LUAD). Methods: Tregs were identified using but single-cell RNA sequencing (scRNA-seq) analysis and interactions between Tregs and other cells in the TME were investigated. Next, we used multiple bulk RNA-seq datasets to construct risk models based on marker genes of Tregs and explored differences in prognosis, mutational landscape, immune cell infiltration and immunotherapy between high- and low-risk groups, and finally, qRT-PCR and cell function experiments were performed to validate the model genes. Results: The cellchat analysis showed that MIF-(CD74+CXCR4) pairs play a key role in the interaction of Tregs with other cell subpopulations, and the Tregs-associated signatures (TRAS) could well classify multiple LUAD cohorts into high- and low-risk groups. Immunotherapy may offer greater potential benefits to the low-risk group, as indicated by their superior survival, increased infiltration of immune cells, and heightened expression of immune checkpoints. Finally, the experiment verified that the model genes LTB and PTTG1 were relatively highly expressed in cancer tissues, while PTPRC was relatively highly expressed in paracancerous tissues. Colony Formation assay confirmed that knockdown of PTTG1 reduced the proliferation ability of LUAD cells. Conclusion: TRAS were constructed using scRNA-seq and bulk RNA-seq to distinguish patient risk subgroups, which may provide assistance in the clinical management of LUAD patients.
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