ArticleFrontiers in molecular biosciences2021
Identification of Hub Genes and Pathways Associated With Idiopathic Pulmonary Fibrosis
Article in Frontiers in molecular biosciences, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed.
- A generative AI-discovered TNIK inhibitor for idiopathic pulmonary fibrosis: a randomized phase 2a trial.Nature medicine · 2025Trial
- Fibronectin's tensional state as a mechanical signature of fibrotic extracellular matrix in idiopathic pulmonary fibrosis models.Matrix biology plus · 2026Article
- Myeloperoxidase promotes fibrosis by inhibiting cathepsin K to bias the lung toward ECM accumulation.bioRxiv : the preprint server for biology · 2026Article
- Relationship between cathepsin K and extracellular matrix dynamics: a comprehensive review.Frontiers in oncology · 2026Review
- A deep generative model for deciphering cellular dynamics and in silico drug discovery in complex diseases.Nature biomedical engineering · 2025Article
- The role of age-related genes in idiopathic pulmonary fibrosis and molecular docking analysis of their drug targets.Frontiers in immunology · 2025Article
- Identification of Hub Genes and Prediction of Targeted Drugs for Rheumatoid Arthritis and Idiopathic Pulmonary Fibrosis.Biochemical genetics · 2024Article
- Construction of an artificial neural network diagnostic model and investigation of immune cell infiltration characteristics for idiopathic pulmonary fibrosis.BMC pulmonary medicine · 2024Article
- Development of a Novel Biomarker for the Progression of Idiopathic Pulmonary Fibrosis.International journal of molecular sciences · 2024Article
- Identifying health risk determinants and molecular targets in patients with idiopathic pulmonary fibrosis via combined differential and weighted gene co-expression analysis.Frontiers in genetics · 2024Article
- Multi-omics integration reveals a nonlinear signature that precedes progression of lung fibrosis.Clinical & translational immunology · 2024Article
- iDESC: identifying differential expression in single-cell RNA sequencing data with multiple subjects.BMC bioinformatics · 2023Article
- Identification of diagnostic hub genes related to neutrophils and infiltrating immune cell alterations in idiopathic pulmonary fibrosis.Frontiers in immunology · 2023Article
- An explainable machine learning-driven proposal of pulmonary fibrosis biomarkers.Computational and structural biotechnology journal · 2023Article
- Machine learning-based prediction of candidate gene biomarkers correlated with immune infiltration in patients with idiopathic pulmonary fibrosis.Frontiers in medicine · 2023Article
- Maximizing Small Biopsy Patient Samples: Unified RNA-Seq Platform Assessment of over 120,000 Patient Biopsies.Journal of personalized medicine · 2022Article
- Identification of Critical Genes and Pathways for Influenza A Virus Infections via Bioinformatics Analysis.Viruses · 2022Article
- Matrix Metalloproteinases and Their Inhibitors in Pulmonary Fibrosis: EMMPRIN/CD147 Comes into Play.International journal of molecular sciences · 2022Review
- Co-expression of fibrotic genes in inflammatory bowel disease; A localized event?Frontiers in immunology · 2022Article
Corrections and comments
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Authors and funding
12 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Idiopathic pulmonary fibrosis (IPF) is a progressive disease whose etiology remains unknown. The purpose of this study was to explore hub genes and pathways related to IPF development and prognosis. Multiple gene expression datasets were downloaded from the Gene Expression Omnibus database. Weighted correlation network analysis (WGCNA) was performed and differentially expressed genes (DEGs) identified to investigate Hub modules and genes correlated with IPF. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, and protein-protein interaction (PPI) network analysis were performed on selected key genes. In the PPI network and cytoHubba plugin, 11 hub genes were identified, including ASPN, CDH2, COL1A1, COL1A2, COL3A1, COL14A1, CTSK, MMP1, MMP7, POSTN, and SPP1. Correlation between hub genes was displayed and validated. Expression levels of hub genes were verified using quantitative real-time PCR (qRT-PCR). Dysregulated expression of these genes and their crosstalk might impact the development of IPF through modulating IPF-related biological processes and signaling pathways. Among these genes, expression levels of COL1A1, COL3A1, CTSK, MMP1, MMP7, POSTN, and SPP1 were positively correlated with IPF prognosis. The present study provides further insights into individualized treatment and prognosis for IPF.
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