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Bioinformatics analysis of constructing a HCV-related hepatocellular carcinoma miRNA–mRNA regulation network

Hepatocellular carcinoma (HCC) is one of the tumors with a higher mortality rate globally, which significantly threatens people's health. Hepatitis C virus (HCV) infection is a major driving factor of HCC. This study aims to determine the key microRNA (miRNA), hub genes, and related pathways, c...

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Autores principales: Hao, Rui, Lu, He, Guo, Yanan, Liu, Qianqian, Wang, Lu, Wang, Yang, Huang, Ailong, Tu, Zeng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Lippincott Williams & Wilkins 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8376384/
https://www.ncbi.nlm.nih.gov/pubmed/34414965
http://dx.doi.org/10.1097/MD.0000000000026964
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author Hao, Rui
Lu, He
Guo, Yanan
Liu, Qianqian
Wang, Lu
Wang, Yang
Huang, Ailong
Tu, Zeng
author_facet Hao, Rui
Lu, He
Guo, Yanan
Liu, Qianqian
Wang, Lu
Wang, Yang
Huang, Ailong
Tu, Zeng
author_sort Hao, Rui
collection PubMed
description Hepatocellular carcinoma (HCC) is one of the tumors with a higher mortality rate globally, which significantly threatens people's health. Hepatitis C virus (HCV) infection is a major driving factor of HCC. This study aims to determine the key microRNA (miRNA), hub genes, and related pathways, construct potential miRNA–mRNA regulatory networks, and clarify the new molecular mechanism of HCV-related HCC. In this study, 16 differentially expressed miRNAs (DE miRNAs) were identified. The prediction of potential transcription factors and target genes not only found that SP1 and ERG1 may potentially regulate most of the screened DE miRNAs, but it also obtained 2923 and 1782 predicted target genes for the up-regulation and down-regulation of DE miRNAs, respectively. Subsequently, the introduction of differentially expressed genes dataset GSE62232 for target gene verification yielded 98 and 147 potential up-regulation and down-regulation target genes. The gene ontology (GO) and Kyoto encyclopedia of genes and genomes pathway enrichment analysis showed that they were mainly enriched in the cell cycle process, that is, subsequently, 20 hub genes were screened out through the protein–protein interaction network, and related genes were further evaluated using the GEPIA database. Based on the above analysis, the miRNA-hub gene regulatory network was constructed. In short, this research's hub genes and miRNAs closely related to HCV-related HCC were screened and identified through bioinformatics analysis and then built their connection. These results are expected to find potential therapeutic targets for HCV-related HCC.
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spelling pubmed-83763842021-08-21 Bioinformatics analysis of constructing a HCV-related hepatocellular carcinoma miRNA–mRNA regulation network Hao, Rui Lu, He Guo, Yanan Liu, Qianqian Wang, Lu Wang, Yang Huang, Ailong Tu, Zeng Medicine (Baltimore) 4800 Hepatocellular carcinoma (HCC) is one of the tumors with a higher mortality rate globally, which significantly threatens people's health. Hepatitis C virus (HCV) infection is a major driving factor of HCC. This study aims to determine the key microRNA (miRNA), hub genes, and related pathways, construct potential miRNA–mRNA regulatory networks, and clarify the new molecular mechanism of HCV-related HCC. In this study, 16 differentially expressed miRNAs (DE miRNAs) were identified. The prediction of potential transcription factors and target genes not only found that SP1 and ERG1 may potentially regulate most of the screened DE miRNAs, but it also obtained 2923 and 1782 predicted target genes for the up-regulation and down-regulation of DE miRNAs, respectively. Subsequently, the introduction of differentially expressed genes dataset GSE62232 for target gene verification yielded 98 and 147 potential up-regulation and down-regulation target genes. The gene ontology (GO) and Kyoto encyclopedia of genes and genomes pathway enrichment analysis showed that they were mainly enriched in the cell cycle process, that is, subsequently, 20 hub genes were screened out through the protein–protein interaction network, and related genes were further evaluated using the GEPIA database. Based on the above analysis, the miRNA-hub gene regulatory network was constructed. In short, this research's hub genes and miRNAs closely related to HCV-related HCC were screened and identified through bioinformatics analysis and then built their connection. These results are expected to find potential therapeutic targets for HCV-related HCC. Lippincott Williams & Wilkins 2021-08-20 /pmc/articles/PMC8376384/ /pubmed/34414965 http://dx.doi.org/10.1097/MD.0000000000026964 Text en Copyright © 2021 the Author(s). Published by Wolters Kluwer Health, Inc. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution-Non Commercial License 4.0 (CCBY-NC), where it is permissible to download, share, remix, transform, and buildup the work provided it is properly cited. The work cannot be used commercially without permission from the journal. http://creativecommons.org/licenses/by-nc/4.0 (https://creativecommons.org/licenses/by-nc/4.0/)
spellingShingle 4800
Hao, Rui
Lu, He
Guo, Yanan
Liu, Qianqian
Wang, Lu
Wang, Yang
Huang, Ailong
Tu, Zeng
Bioinformatics analysis of constructing a HCV-related hepatocellular carcinoma miRNA–mRNA regulation network
title Bioinformatics analysis of constructing a HCV-related hepatocellular carcinoma miRNA–mRNA regulation network
title_full Bioinformatics analysis of constructing a HCV-related hepatocellular carcinoma miRNA–mRNA regulation network
title_fullStr Bioinformatics analysis of constructing a HCV-related hepatocellular carcinoma miRNA–mRNA regulation network
title_full_unstemmed Bioinformatics analysis of constructing a HCV-related hepatocellular carcinoma miRNA–mRNA regulation network
title_short Bioinformatics analysis of constructing a HCV-related hepatocellular carcinoma miRNA–mRNA regulation network
title_sort bioinformatics analysis of constructing a hcv-related hepatocellular carcinoma mirna–mrna regulation network
topic 4800
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8376384/
https://www.ncbi.nlm.nih.gov/pubmed/34414965
http://dx.doi.org/10.1097/MD.0000000000026964
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