Identification of Ferroptosis-Inflammation Related Hub Genes and the Disease Subtypes in Idiopathic Pulmonary Fibrosis via System Biology Approaches

Chongyang Niu; Xiaoyu Meng; Tan Wang

doi:10.1007/s12033-024-01158-x

Identification of Ferroptosis-Inflammation Related Hub Genes and the Disease Subtypes in Idiopathic Pulmonary Fibrosis via System Biology Approaches

Mol Biotechnol. 2024 May 11. doi: 10.1007/s12033-024-01158-x. Online ahead of print.

Authors

Chongyang Niu^{1

2}, Xiaoyu Meng³, Tan Wang⁴

Affiliations

¹ Changchun University of Chinese Medicine, No. 1035 Boshuo Road, Jingyue Economic Development district, Changchun, Jilin Province, 130000, China.
² Lung Disease Center, The Affiliated Hospital of Changchun University of Chinese Medicine, No. 1478 Gongnong Road, Chaoyang District, Changchun, Jilin Province, 130000, China.
³ Pediatric Center, The third affiliated hospital of Changchun university Chinese medicine, No. 1643 Jingyue Street, Nanguan District, Changchun, Jilin Province, 130000, China.
⁴ Lung Disease Center, The Affiliated Hospital of Changchun University of Chinese Medicine, No. 1478 Gongnong Road, Chaoyang District, Changchun, Jilin Province, 130000, China. wangtan215@sina.com.

PMID: 38734841
DOI: 10.1007/s12033-024-01158-x

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.

Keywords: Disease subtype; Ferroptosis; Inflammation; Pulmonary fibrosis; System biology.