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Construction of a Potential Breast Cancer-Related miRNA-mRNA Regulatory Network
BACKGROUND: Breast cancer is a malignant tumor that occurs in the epithelial tissue of the breast gland and has become the most common malignancy in women. The regulation of the expression of related genes by microRNA (miRNA) plays an important role in breast cancer. We constructed a comprehensive b...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7657683/ https://www.ncbi.nlm.nih.gov/pubmed/33204705 http://dx.doi.org/10.1155/2020/6149174 |
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author | Liu, Xinhong Chen, Feng Tan, Fang Li, Fang Yi, Ruokun Yang, Dingyi Zhao, Xin |
author_facet | Liu, Xinhong Chen, Feng Tan, Fang Li, Fang Yi, Ruokun Yang, Dingyi Zhao, Xin |
author_sort | Liu, Xinhong |
collection | PubMed |
description | BACKGROUND: Breast cancer is a malignant tumor that occurs in the epithelial tissue of the breast gland and has become the most common malignancy in women. The regulation of the expression of related genes by microRNA (miRNA) plays an important role in breast cancer. We constructed a comprehensive breast cancer-miRNA-gene interaction map. METHODS: Three miRNA microarray datasets (GSE26659, GSE45666, and GSE58210) were obtained from the GEO database. Then, the R software “LIMMA” package was used to identify differential expression analysis. Potential transcription factors and target genes of screened differentially expressed miRNAs (DE-miRNAs) were predicted. The BRCA GE-mRNA datasets (GSE109169 and GSE139038) were downloaded from the GEO database for identifying differentially expressed genes (DE-genes). Next, GO annotation and KEGG pathway enrichment analysis were conducted. A PPI network was then established, and hub genes were identified via Cytoscape software. The expression and prognostic roles of hub genes were further evaluated. RESULTS: We found 6 upregulated differentially expressed- (DE-) miRNAs and 18 downregulated DE-miRNAs by analyzing 3 Gene Expression Omnibus databases, and we predicted the upstream transcription factors and downstream target genes for these DE-miRNAs. Then, we used the GEO database to perform differential analysis on breast cancer mRNA and obtained differentially expressed mRNA. We found 10 hub genes of upregulated DE-miRNAs and 10 hub genes of downregulated DE-miRNAs through interaction analysis. CONCLUSIONS: In this study, we have performed an integrated bioinformatics analysis to construct a more comprehensive BRCA-miRNA-gene network and provide new targets and research directions for the treatment and prognosis of BRCA. |
format | Online Article Text |
id | pubmed-7657683 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-76576832020-11-16 Construction of a Potential Breast Cancer-Related miRNA-mRNA Regulatory Network Liu, Xinhong Chen, Feng Tan, Fang Li, Fang Yi, Ruokun Yang, Dingyi Zhao, Xin Biomed Res Int Research Article BACKGROUND: Breast cancer is a malignant tumor that occurs in the epithelial tissue of the breast gland and has become the most common malignancy in women. The regulation of the expression of related genes by microRNA (miRNA) plays an important role in breast cancer. We constructed a comprehensive breast cancer-miRNA-gene interaction map. METHODS: Three miRNA microarray datasets (GSE26659, GSE45666, and GSE58210) were obtained from the GEO database. Then, the R software “LIMMA” package was used to identify differential expression analysis. Potential transcription factors and target genes of screened differentially expressed miRNAs (DE-miRNAs) were predicted. The BRCA GE-mRNA datasets (GSE109169 and GSE139038) were downloaded from the GEO database for identifying differentially expressed genes (DE-genes). Next, GO annotation and KEGG pathway enrichment analysis were conducted. A PPI network was then established, and hub genes were identified via Cytoscape software. The expression and prognostic roles of hub genes were further evaluated. RESULTS: We found 6 upregulated differentially expressed- (DE-) miRNAs and 18 downregulated DE-miRNAs by analyzing 3 Gene Expression Omnibus databases, and we predicted the upstream transcription factors and downstream target genes for these DE-miRNAs. Then, we used the GEO database to perform differential analysis on breast cancer mRNA and obtained differentially expressed mRNA. We found 10 hub genes of upregulated DE-miRNAs and 10 hub genes of downregulated DE-miRNAs through interaction analysis. CONCLUSIONS: In this study, we have performed an integrated bioinformatics analysis to construct a more comprehensive BRCA-miRNA-gene network and provide new targets and research directions for the treatment and prognosis of BRCA. Hindawi 2020-11-04 /pmc/articles/PMC7657683/ /pubmed/33204705 http://dx.doi.org/10.1155/2020/6149174 Text en Copyright © 2020 Xinhong Liu et al. https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Liu, Xinhong Chen, Feng Tan, Fang Li, Fang Yi, Ruokun Yang, Dingyi Zhao, Xin Construction of a Potential Breast Cancer-Related miRNA-mRNA Regulatory Network |
title | Construction of a Potential Breast Cancer-Related miRNA-mRNA Regulatory Network |
title_full | Construction of a Potential Breast Cancer-Related miRNA-mRNA Regulatory Network |
title_fullStr | Construction of a Potential Breast Cancer-Related miRNA-mRNA Regulatory Network |
title_full_unstemmed | Construction of a Potential Breast Cancer-Related miRNA-mRNA Regulatory Network |
title_short | Construction of a Potential Breast Cancer-Related miRNA-mRNA Regulatory Network |
title_sort | construction of a potential breast cancer-related mirna-mrna regulatory network |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7657683/ https://www.ncbi.nlm.nih.gov/pubmed/33204705 http://dx.doi.org/10.1155/2020/6149174 |
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