DOI: 10.57760/sciencedb.j00217.00914
title: Identification of the core genes to endoplasmic reticulum stress in chronic obstructive pulmonary disease based on multi-chip integrated analysis of GEO database and experimental validation.
title: 基于GEO数据库多芯片集成分析和实验验证的慢性阻塞性肺疾病内质网应激核心基因鉴定

description: Objective Bioinformatics and experimental validation reveal the core genes of endoplasmic reticulum stress(ERS) in chronic obstructive pulmonary disease.Methods The microarray datasets GSE5058、GSE8545andGSE19407were downloaded from the Gene Expression Omnibus (GEO) database to identify differentially expressed genes (DEGs) between COPD smokers and non-smokers airway epithelial，and the common differentially expressed genes were obtained after overlapping with endoplasmic reticulum stress-related genes and enriched for analysis.Three machine learning algorithms, LASSO, SVM-RFE, and RF, were used to screen the characteristic genes of endoplasmic reticulum stress, and their diagnostic performance was verified and evaluated in the GSE10006, next, CIBERSORT algorithm was used to analyze immune cell infiltration.Finally the mRNA-miRNA network was constructed and the mRNA expression level of lung tissue in mouse emphysema model were verified.Results A total of 153 common DEGs were acquired. GO analysis showed that they were involved in endoplasmic reticulum stress response、protein folding、ubiquitin-like protease and other processes, KEGG analysis mainly involved protein processing、lipid and atherosclerosis、P53 signaling pathway、PI3K-Akt signaling pathway etc ,and DO analysis was mainly enriched in pulmonary vascular occlusive disease and chronic obstructive pulmonary disease.Immune infiltration analysis showed that COPD samples contained significantly more M0 macrophages、resting dendritic cells and eosinophils, while regulatory T cells and M2 macrophages were significantly less.A total of four key endoplasmic reticulum stress genes (including THBS1, BCL2, USP13 and RNFT2) were identified by machine learning algorithms, and they showed good diagnostic performance in both the training and validation sets. At the same time, co-expressed mRNA and miRNA were selected to construct the mRNA-miRNA interaction network.Compared with the air-exposed mice, the mRNA expression levels of THBS1 and RNFT2 in the lung tissues of emphysema mice induced by cigarette smoke exposure were statistically significant, and the mRNA expression levels of BCL2 and USP13 decreased (P&lt;0.05).Conclusion THBS1、BCL2、USP13 and RNFT2 may be the core genes formed by endoplasmic reticulum stress during the pathogenesis of chronic obstructive pulmonary disease, which are expected to be the targets of immunotherapy for chronic obstructive pulmonary disease.
description: Objective Bioinformatics and experimental validation reveal the core genes of endoplasmic reticulum stress(ERS) in chronic obstructive pulmonary disease.Methods The microarray datasets GSE5058、GSE8545andGSE19407were downloaded from the Gene Expression Omnibus (GEO) database to identify differentially expressed genes (DEGs) between COPD smokers and non-smokers airway epithelial，and the common differentially expressed genes were obtained after overlapping with endoplasmic reticulum stress-related genes and enriched for analysis.Three machine learning algorithms, LASSO, SVM-RFE, and RF, were used to screen the characteristic genes of endoplasmic reticulum stress, and their diagnostic performance was verified and evaluated in the GSE10006, next, CIBERSORT algorithm was used to analyze immune cell infiltration.Finally the mRNA-miRNA network was constructed and the mRNA expression level of lung tissue in mouse emphysema model were verified.Results A total of 153 common DEGs were acquired. GO analysis showed that they were involved in endoplasmic reticulum stress response、protein folding、ubiquitin-like protease and other processes, KEGG analysis mainly involved protein processing、lipid and atherosclerosis、P53 signaling pathway、PI3K-Akt signaling pathway etc ,and DO analysis was mainly enriched in pulmonary vascular occlusive disease and chronic obstructive pulmonary disease.Immune infiltration analysis showed that COPD samples contained significantly more M0 macrophages、resting dendritic cells and eosinophils, while regulatory T cells and M2 macrophages were significantly less.A total of four key endoplasmic reticulum stress genes (including THBS1, BCL2, USP13 and RNFT2) were identified by machine learning algorithms, and they showed good diagnostic performance in both the training and validation sets. At the same time, co-expressed mRNA and miRNA were selected to construct the mRNA-miRNA interaction network.Compared with the air-exposed mice, the mRNA expression levels of THBS1 and RNFT2 in the lung tissues of emphysema mice induced by cigarette smoke exposure were statistically significant, and the mRNA expression levels of BCL2 and USP13 decreased (P&lt;0.05).Conclusion THBS1、BCL2、USP13 and RNFT2 may be the core genes formed by endoplasmic reticulum stress during the pathogenesis of chronic obstructive pulmonary disease, which are expected to be the targets of immunotherapy for chronic obstructive pulmonary disease.