ArticleJournal of thoracic disease2023
Exploration of the shared genes and signaling pathways between lung adenocarcinoma and idiopathic pulmonary fibrosis.
Article in Journal of thoracic disease, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.
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Who cites it
8 citing papers in PubMed, 1 synthesis or guideline pooled it, 13 citations in OpenAlex.
- Advances and frontiers in pulmonary fibrosis and lung cancer research (2000-2024): a bibliometric analysis.Frontiers in medicine · 2025Pooled it
- Exploring the mechanism of Shengmai San in treating lung adenocarcinoma based on bioinformatics and molecular dynamics simulation.Medicine · 2026Article
- CXCL14 in prostate cancer: complex interactions in the tumor microenvironment and future prospects.Journal of translational medicine · 2025Review
- Identification of potential biomarkers for lung cancer using integrated bioinformatics and machine learning approaches.PloS one · 2025Article
- Shapley additive explanations based feature selection reveals CXCL14 as a key immune-related gene in predicting idiopathic pulmonary fibrosis.Frontiers in medicine · 2025Article
- Article
- Expression of HOXB7 in the Lung of Patients with Idiopathic Pulmonary Fibrosis: A Proof-of-Concept Study.Biomedicines · 2024Article
- [Identification of SULF1 as a Shared Gene in Idiopathic Pulmonary Fibrosis and Lung Adenocarcinoma].Zhongguo fei ai za zhi = Chinese journal of lung cancer · 2023Article
Corrections and comments
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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: Idiopathic pulmonary fibrosis (IPF), a type of interstitial lung disease (ILD), is a chronic disease with an unknown etiology. The occurrence of lung cancer (LC) is one of the main causes of death in patients with IPF. However, the pathogenesis driving these malignant transformations remains unclear; therefore, this study aimed to identify the shared genes and functional pathways associated with both disease conditions. Methods: Data were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. To identify overlapping genes in both diseases, the "limma" package in R software and weighted gene coexpression network analysis (WGCNA) were used. Venn diagrams were used to obtain the shared genes. The diagnostic value of the shared genes was assessed using receiver operating characteristic (ROC) curve analysis. Gene Ontology (GO) term enrichment was performed on the shared genes between lung adenocarcinoma (LUAD) and IPF, and the genes were also functionally enriched using Metascape. A protein-protein interaction (PPI) network was created using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database. Finally, the link between shared genes and common antineoplastic medicines was investigated using the CellMiner database. Results: The coexpression modules associated with LUAD and IPF were discovered using WGCNA, and 148 genes were found to overlap. In addition, 74 upregulated and 130 downregulated overlapping genes were obtained via differential gene analysis. Functional analysis of the genes revealed that these genes are primarily engaged in extracellular matrix (ECM) pathways. Furthermore, Conclusions: ECM-related mechanisms may be the underlying link between LC and IPF. A total of 7 shared genes were identified as potential diagnostic markers and therapeutic targets for LUAD and IPF.
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