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Comprehensive analysis of an endoplasmic reticulum stress-related gene prediction model and immune infiltration in idiopathic pulmonary fibrosis

Authors :
Honglan Zhu
Aiming Zhou
Menglin Zhang
Lin Pan
Xiao Wu
Chenkun Fu
Ling Gong
Wenting Yang
Daishun Liu
Yiju Cheng
Source :
Frontiers in Immunology, Vol 14 (2024)
Publication Year :
2024
Publisher :
Frontiers Media S.A., 2024.

Abstract

BackgroundIdiopathic pulmonary fibrosis (IPF) is a chronic progressive interstitial lung disease. This study aimed to investigate the involvement of endoplasmic reticulum stress (ERS) in IPF and explore its correlation with immune infiltration.MethodsERS-related differentially expressed genes (ERSRDEGs) were identified by intersecting differentially expressed genes (DEGs) from three Gene Expression Omnibus datasets with ERS-related gene sets. Gene Set Variation Analysis and Gene Ontology were used to explore the potential biological mechanisms underlying ERS. A nomogram was developed using the risk signature derived from the ERSRDEGs to perform risk assessment. The diagnostic value of the risk signature was evaluated using receiver operating characteristics, calibration, and decision curve analyses. The ERS score of patients with IPF was measured using a single-sample Gene Set Enrichment Analysis (ssGSEA) algorithm. Subsequently, a prognostic model based on the ERS scores was established. The proportion of immune cell infiltration was assessed using the ssGSEA and CIBERSORT algorithms. Finally, the expression of ERSRDEGs was validated in vivo and in vitro via RT-qPCR.ResultsThis study developed an 8-ERSRDEGs signature. Based on the expression of these genes, we constructed a diagnostic nomogram model in which agouti-related neuropeptide had a significantly greater impact on the model. The area under the curve values for the predictive value of the ERSRDEGs signature were 0.975 and 1.000 for GSE70866 and GSE110147, respectively. We developed a prognostic model based on the ERS scores of patients with IPF. Furthermore, we classified patients with IPF into two subtypes based on their signatures. The RT-qPCR validation results supported the reliability of most of our conclusions.ConclusionWe developed and verified a risk model using eight ERSRDEGs. These eight genes can potentially affect the progression of IPF by regulating ERS and immune responses.

Details

Language :
English
ISSN :
16643224
Volume :
14
Database :
Directory of Open Access Journals
Journal :
Frontiers in Immunology
Publication Type :
Academic Journal
Accession number :
edsdoj.7aa1ae498c9430597fcec20bb4e12d6
Document Type :
article
Full Text :
https://doi.org/10.3389/fimmu.2023.1305025