ArticleJournal of thoracic disease2025
Exploring diagnostic gene markers and immune infiltration in idiopathic pulmonary fibrosis.
Article in Journal of thoracic disease, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
1 citing paper in PubMed.
- An hiPSC-derived multi-lineage lung model exhibiting proximal-distal epithelial features for modeling pulmonary fibrosis.Frontiers in cell and developmental biology · 2026Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Idiopathic pulmonary fibrosis (IPF) is one of the most severe pulmonary disorders, has poor outcomes, and is difficult to predict. This study sought to identify the critical genes involved in IPF progression, and to explore the relationship between these genes and immunogenic invasion. Methods: The GSE10667 dataset was downloaded from the Gene Expression Omnibus (GEO) database to identify differentially expressed genes (DEGs) between IPF patients and normal participants. IPF-related hub genes were screened using differential gene analysis and weighted gene co-expression network analysis (WGCNA). For evaluating the diagnostic efficacy of these hub genes, a nomogram was constructed, and receiver operating characteristic (ROC) analysis was performed. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were conducted to explore the potential biological functions and pathways of the IPF-related hub genes. To reveal key protein-based genetic networks, protein-protein interaction (PPI) networks were constructed as follows: The key candidate genes associated with IPF, identified through WGCNA and differential gene analysis, were input into the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database, for PPI prediction and visualization. The PPI data derived from STRING were further processed and visualized using Cytoscape software. Additionally, the association between MMP2 and immune infiltration was analyzed. Finally, a Mendelian randomization (MR) analysis was performed using genome-wide association study (GWAS) data to establish the causal relationship between MMP2 and IPF. Results: In total, 486 DEGs in IPF were identified. A genetic co-expression network was established by the WGCNA to select the most relevant genes. The genes were mainly involved in processes such as the extracellular matrix (ECM), cellular aging, endoplasmic reticulum (ER) stress, and metalloproteinase (MT) activation signaling pathways. Crosslinks between the DEG-related modules and WGCNA modules were assessed to identify the key genes. A PPI network was then established that identified Conclusions:
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