ArticleFrontiers in immunology2022
Construction of prediction model of inflammation related genes in idiopathic pulmonary fibrosis and its correlation with immune microenvironment.
Article in Frontiers in immunology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 8 citations in OpenAlex.
- Antifibrotic Strategies Targeting Phosphodiesterase-4 in Idiopathic Pulmonary Fibrosis: Molecular Mechanisms and Clinical Translation.Clinical pharmacology : advances and applications · 2026Review
- Unraveling the pleiotropic effects of CCR2-dependent signal transduction in fibrosis development.Theranostics · 2026Review
- The role of oxidative stress-related genes in idiopathic pulmonary fibrosis.Scientific reports · 2025Article
- Role of inflammation-related genes as prognostic biomarkers and mechanistic implications in idiopathic pulmonary fibrosis.Frontiers in genetics · 2025Article
- Identification of PANoptosis-related genes for idiopathic pulmonary fibrosis by machine learning and molecular subtype analysis.Scientific reports · 2024Article
- Updates on the controversial roles of regulatory lymphoid cells in idiopathic pulmonary fibrosis.Frontiers in immunology · 2024Review
- The role and therapeutic targeting of the CCL2/CCR2 signaling axis in inflammatory and fibrotic diseases.Frontiers in immunology · 2024Review
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Authors and funding
9 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: The role of inflammation in the formation of idiopathic pulmonary fibrosis (IPF) has gained a lot of attention recently. However, the involvement of genes related to inflammation and immune exchange environment status in the prognosis of IPF remains to be further clarified. The objective of this research is to establish a new model for the prediction of the overall survival (OS) rate of inflammation-related IPF. Methods: Gene Expression Omnibus (GEO) was employed to obtain the three expression microarrays of IPF, including two from alveolar lavage fluid cells and one from peripheral blood mononuclear cells. To construct the risk assessment model of inflammation-linked genes, least absolute shrinkage and selection operator (lasso), univariate cox and multivariate stepwise regression, and random forest method were used. The proportion of immune cell infiltration was evaluated by single sample Gene Set Enrichment Analysis (ssGSEA) algorithm. Results: The value of genes linked with inflammation in the prognosis of IPF was analyzed, and a four-genes risk model was constructed, including tpbg, Myc, ffar2, and CCL2. It was highlighted by Kaplan Meier (K-M) survival analysis that patients with high-risk scores had worse overall survival time in all training and validation sets, and univariate and multivariate analysis highlighted that it has the potential to act as an independent risk indicator for poor prognosis. ROC analysis showed that the prediction efficiency of 1-, 3-, and 5-year OS time in the training set reached 0.784, 0.835, and 0.921, respectively. Immune infiltration analysis showed that Myeloid-Derived Suppressor Cells (MDSC), macrophages, regulatory T cells, cd4+ t cells, neutrophils, and dendritic cells were more infiltrated in the high-risk group than in the low-risk group. Conclusion: Inflammation-related genes can be well used to evaluate the IPF prognosis and impart a new idea for the treatment and follow-up management of IPF patients.
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