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Construction of Potential miRNA–mRNA Regulatory Network in COPD Plasma by Bioinformatics Analysis
BACKGROUND: 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 ne...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Dove
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7490070/ https://www.ncbi.nlm.nih.gov/pubmed/32982206 http://dx.doi.org/10.2147/COPD.S255262 |
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author | Zhu, Mengchan Ye, Maosong Wang, Jian Ye, Ling Jin, Meiling |
author_facet | Zhu, Mengchan Ye, Maosong Wang, Jian Ye, Ling Jin, Meiling |
author_sort | Zhu, Mengchan |
collection | PubMed |
description | BACKGROUND: 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. |
format | Online Article Text |
id | pubmed-7490070 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Dove |
record_format | MEDLINE/PubMed |
spelling | pubmed-74900702020-09-24 Construction of Potential miRNA–mRNA Regulatory Network in COPD Plasma by Bioinformatics Analysis Zhu, Mengchan Ye, Maosong Wang, Jian Ye, Ling Jin, Meiling Int J Chron Obstruct Pulmon Dis Original Research BACKGROUND: 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. Dove 2020-09-10 /pmc/articles/PMC7490070/ /pubmed/32982206 http://dx.doi.org/10.2147/COPD.S255262 Text en © 2020 Zhu et al. http://creativecommons.org/licenses/by-nc/3.0/ This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms (https://www.dovepress.com/terms.php). |
spellingShingle | Original Research Zhu, Mengchan Ye, Maosong Wang, Jian Ye, Ling Jin, Meiling Construction of Potential miRNA–mRNA Regulatory Network in COPD Plasma by Bioinformatics Analysis |
title | 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_short | 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 |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7490070/ https://www.ncbi.nlm.nih.gov/pubmed/32982206 http://dx.doi.org/10.2147/COPD.S255262 |
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