{"title":"Identification of Ferroptosis-Inflammation Related Hub Genes and the Disease Subtypes in Idiopathic Pulmonary Fibrosis via System Biology Approaches.","authors":"Chongyang Niu, Xiaoyu Meng, Tan Wang","doi":"10.1007/s12033-024-01158-x","DOIUrl":null,"url":null,"abstract":"<p><p>We aim to screen and analyze the ferroptosis inflammation-related hub genes associated with idiopathic pulmonary fibrosis (IPF). The GSE52463 and GSE110147 datasets were obtained from the GEO database and merged. The DEGs were selected by differential analysis and intersected with inflammation-related genes and ferroptosis-related genes to acquire the ferroptosis-related differentially expressed genes (FRDEGs). GO, KEGG, GSEA, and GSVA were performed to investigate the features of FRDEGs. The key module genes were selected by WGCNA and employed to generate the PPI network using Cytoscape. Subsequently, the hub genes were identified using cytoHubba and validated by ROC curves generated by survivalROC. Finally, the correlations of hub genes were analyzed through Spearman and the subtypes of IPF were constructed using ConsensusClusterPlus. A total of 1814 DEGs were screened out and 18 FRDEGs were acquired from the intersection of DEGs, ferroptosis-related genes, and inflammation-related genes. GO and KEGG analysis revealed that FRDEGs were primarily involved in bacterial-origin molecular, response infectious disease, and iron ion transport. GSEA results suggested a predominant association with autoimmune diseases and GSVA identified ten different pathways between PF and control. Through WGCNA, three highly correlated modules were identified and ten key module genes were obtained by intersecting genes in the three modules with FRDEGs. Finally, employing three algorithms within the cytoHubba led to the identification of eight hub genes: CCND1, TP53, STAT3, CTNNB1 CDH1, ESR1, HSP90AA1, and EP300. Eventually, two distinct subtypes of IPF were identified. The present research successfully identified the hub genes associated with ferroptosis and inflammation and their biological effects on IPF. Furthermore, two disease subtypes of IPF were constructed.</p>","PeriodicalId":18865,"journal":{"name":"Molecular Biotechnology","volume":" ","pages":"1720-1733"},"PeriodicalIF":2.4000,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Molecular Biotechnology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1007/s12033-024-01158-x","RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/5/11 0:00:00","PubModel":"Epub","JCR":"Q3","JCRName":"BIOCHEMISTRY & MOLECULAR BIOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
We aim to screen and analyze the ferroptosis inflammation-related hub genes associated with idiopathic pulmonary fibrosis (IPF). The GSE52463 and GSE110147 datasets were obtained from the GEO database and merged. The DEGs were selected by differential analysis and intersected with inflammation-related genes and ferroptosis-related genes to acquire the ferroptosis-related differentially expressed genes (FRDEGs). GO, KEGG, GSEA, and GSVA were performed to investigate the features of FRDEGs. The key module genes were selected by WGCNA and employed to generate the PPI network using Cytoscape. Subsequently, the hub genes were identified using cytoHubba and validated by ROC curves generated by survivalROC. Finally, the correlations of hub genes were analyzed through Spearman and the subtypes of IPF were constructed using ConsensusClusterPlus. A total of 1814 DEGs were screened out and 18 FRDEGs were acquired from the intersection of DEGs, ferroptosis-related genes, and inflammation-related genes. GO and KEGG analysis revealed that FRDEGs were primarily involved in bacterial-origin molecular, response infectious disease, and iron ion transport. GSEA results suggested a predominant association with autoimmune diseases and GSVA identified ten different pathways between PF and control. Through WGCNA, three highly correlated modules were identified and ten key module genes were obtained by intersecting genes in the three modules with FRDEGs. Finally, employing three algorithms within the cytoHubba led to the identification of eight hub genes: CCND1, TP53, STAT3, CTNNB1 CDH1, ESR1, HSP90AA1, and EP300. Eventually, two distinct subtypes of IPF were identified. The present research successfully identified the hub genes associated with ferroptosis and inflammation and their biological effects on IPF. Furthermore, two disease subtypes of IPF were constructed.
期刊介绍:
Molecular Biotechnology publishes original research papers on the application of molecular biology to both basic and applied research in the field of biotechnology. Particular areas of interest include the following: stability and expression of cloned gene products, cell transformation, gene cloning systems and the production of recombinant proteins, protein purification and analysis, transgenic species, developmental biology, mutation analysis, the applications of DNA fingerprinting, RNA interference, and PCR technology, microarray technology, proteomics, mass spectrometry, bioinformatics, plant molecular biology, microbial genetics, gene probes and the diagnosis of disease, pharmaceutical and health care products, therapeutic agents, vaccines, gene targeting, gene therapy, stem cell technology and tissue engineering, antisense technology, protein engineering and enzyme technology, monoclonal antibodies, glycobiology and glycomics, and agricultural biotechnology.