Construction of Potential miRNA–mRNA Regulatory Network in COPD Plasma by Bioinformatics Analysis
Mengchan Zhu,* Maosong Ye,* Jian Wang, Ling Ye, Meiling Jin Department of Pulmonary and Critical Care Medicine, Zhongshan Hospital, Fudan University, Shanghai, People’s Republic of China*These authors contributed equally to this workCorrespondence: Meiling Jin; Ling Ye Email jin.meiling@zs...
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doaj-5ee53dea525f48058073d15f6d2cfb5f2020-11-25T03:25:49ZengDove Medical PressInternational Journal of COPD1178-20052020-09-01Volume 152135214556924Construction of Potential miRNA–mRNA Regulatory Network in COPD Plasma by Bioinformatics AnalysisZhu MYe MWang JYe LJin MMengchan Zhu,* Maosong Ye,* Jian Wang, Ling Ye, Meiling Jin Department of Pulmonary and Critical Care Medicine, Zhongshan Hospital, Fudan University, Shanghai, People’s Republic of China*These authors contributed equally to this workCorrespondence: Meiling Jin; Ling Ye Email jin.meiling@zs-hospital.sh.cn; ye.ling@zs-hospital.sh.cnBackground: Chronic obstructive pulmonary disease (COPD) has become a major cause of morbidity and mortality worldwide. Increasing evidence indicates that aberrantly expressed microRNAs (miRNAs) are involved in the pathogenesis of COPD. However, an integrative exploration of miRNA–mRNA regulatory network in COPD plasma remains lacking.Methods: The microarray datasets GSE24709, GSE61741, and GSE31568 were downloaded from the GEO database and analyzed using GEO2R tool to identify differentially expressed miRNAs (DEMs) between COPD and normal plasma. The consistently changing miRNAs in the three datasets were screened out as candidate DEMs. Potential upstream transcription factors and downstream target genes of candidate DEMs were predicted by FunRich and miRNet, respectively. Next, GO annotation and KEGG pathway enrichment analysis for target genes were performed using DAVID. Then, PPI and DEM-hub gene network were constructed using the STRING database and Cytoscape software. Finally, GSE56768 was used to evaluate the hub gene expressions.Results: A total of nine (six upregulated and three downregulated) DEMs were screened out in the above three datasets. SP1 was predicted to potentially regulate most of the downregulated DEMs, while YY1 and E2F1 could regulate both upregulated and downregulated DEMs. 1139 target genes were then predicted, including 596 upregulated DEM target genes and 543 downregulated DEM target genes. Target genes of DEMs were mainly enriched in PI3K/Akt signaling pathway, mTOR signaling pathway, and autophagy. Through the DEM-hub gene network construction, most of the hub genes were found to be potentially modulated by miR-497-5p, miR-130b-5p, and miR-126-5p. Among the top 12 hub genes, MYC and FOXO1 expressions were consistent with that in the GSE56768 dataset.Conclusion: In the study, potential miRNA–mRNA regulatory network was firstly constructed in COPD plasma, which may provide a new insight into the pathogenesis and treatment of COPD.Keywords: microRNAs (miRNAs), chronic obstructive pulmonary disease (COPD), bioinformatics analysis, miRNA–mRNA regulatory networkhttps://www.dovepress.com/construction-of-potential-mirnandashmrna-regulatory-network-in-copd-pl-peer-reviewed-article-COPDmicrornas (mirnas)chronic obstructive pulmonary disease (copd)bioinformatics analysismirna–mrna regulatory network |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Zhu M Ye M Wang J Ye L Jin M |
spellingShingle |
Zhu M Ye M Wang J Ye L Jin M Construction of Potential miRNA–mRNA Regulatory Network in COPD Plasma by Bioinformatics Analysis International Journal of COPD micrornas (mirnas) chronic obstructive pulmonary disease (copd) bioinformatics analysis mirna–mrna regulatory network |
author_facet |
Zhu M Ye M Wang J Ye L Jin M |
author_sort |
Zhu M |
title |
Construction of Potential miRNA–mRNA Regulatory Network in COPD Plasma by Bioinformatics Analysis |
title_short |
Construction of Potential miRNA–mRNA Regulatory Network in COPD Plasma by Bioinformatics Analysis |
title_full |
Construction of Potential miRNA–mRNA Regulatory Network in COPD Plasma by Bioinformatics Analysis |
title_fullStr |
Construction of Potential miRNA–mRNA Regulatory Network in COPD Plasma by Bioinformatics Analysis |
title_full_unstemmed |
Construction of Potential miRNA–mRNA Regulatory Network in COPD Plasma by Bioinformatics Analysis |
title_sort |
construction of potential mirna–mrna regulatory network in copd plasma by bioinformatics analysis |
publisher |
Dove Medical Press |
series |
International Journal of COPD |
issn |
1178-2005 |
publishDate |
2020-09-01 |
description |
Mengchan Zhu,* Maosong Ye,* Jian Wang, Ling Ye, Meiling Jin Department of Pulmonary and Critical Care Medicine, Zhongshan Hospital, Fudan University, Shanghai, People’s Republic of China*These authors contributed equally to this workCorrespondence: Meiling Jin; Ling Ye Email jin.meiling@zs-hospital.sh.cn; ye.ling@zs-hospital.sh.cnBackground: Chronic obstructive pulmonary disease (COPD) has become a major cause of morbidity and mortality worldwide. Increasing evidence indicates that aberrantly expressed microRNAs (miRNAs) are involved in the pathogenesis of COPD. However, an integrative exploration of miRNA–mRNA regulatory network in COPD plasma remains lacking.Methods: The microarray datasets GSE24709, GSE61741, and GSE31568 were downloaded from the GEO database and analyzed using GEO2R tool to identify differentially expressed miRNAs (DEMs) between COPD and normal plasma. The consistently changing miRNAs in the three datasets were screened out as candidate DEMs. Potential upstream transcription factors and downstream target genes of candidate DEMs were predicted by FunRich and miRNet, respectively. Next, GO annotation and KEGG pathway enrichment analysis for target genes were performed using DAVID. Then, PPI and DEM-hub gene network were constructed using the STRING database and Cytoscape software. Finally, GSE56768 was used to evaluate the hub gene expressions.Results: A total of nine (six upregulated and three downregulated) DEMs were screened out in the above three datasets. SP1 was predicted to potentially regulate most of the downregulated DEMs, while YY1 and E2F1 could regulate both upregulated and downregulated DEMs. 1139 target genes were then predicted, including 596 upregulated DEM target genes and 543 downregulated DEM target genes. Target genes of DEMs were mainly enriched in PI3K/Akt signaling pathway, mTOR signaling pathway, and autophagy. Through the DEM-hub gene network construction, most of the hub genes were found to be potentially modulated by miR-497-5p, miR-130b-5p, and miR-126-5p. Among the top 12 hub genes, MYC and FOXO1 expressions were consistent with that in the GSE56768 dataset.Conclusion: In the study, potential miRNA–mRNA regulatory network was firstly constructed in COPD plasma, which may provide a new insight into the pathogenesis and treatment of COPD.Keywords: microRNAs (miRNAs), chronic obstructive pulmonary disease (COPD), bioinformatics analysis, miRNA–mRNA regulatory network |
topic |
micrornas (mirnas) chronic obstructive pulmonary disease (copd) bioinformatics analysis mirna–mrna regulatory network |
url |
https://www.dovepress.com/construction-of-potential-mirnandashmrna-regulatory-network-in-copd-pl-peer-reviewed-article-COPD |
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