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Identification and interaction analysis of key genes and microRNAs in hepatocellular carcinoma by bioinformatics analysis

BACKGROUND: Hepatocellular carcinoma (HCC) is the most common liver malignancy worldwide. However, present studies of its multiple gene interaction and cellular pathways still could not explain the initiation and development of HCC perfectly. To find the key genes and miRNAs as well as their potenti...

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Autores principales: Mou, Tong, Zhu, Di, Wei, Xufu, Li, Tingting, Zheng, Daofeng, Pu, Junliang, Guo, Zhen, Wu, Zhongjun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5356276/
https://www.ncbi.nlm.nih.gov/pubmed/28302149
http://dx.doi.org/10.1186/s12957-017-1127-2
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author Mou, Tong
Zhu, Di
Wei, Xufu
Li, Tingting
Zheng, Daofeng
Pu, Junliang
Guo, Zhen
Wu, Zhongjun
author_facet Mou, Tong
Zhu, Di
Wei, Xufu
Li, Tingting
Zheng, Daofeng
Pu, Junliang
Guo, Zhen
Wu, Zhongjun
author_sort Mou, Tong
collection PubMed
description BACKGROUND: Hepatocellular carcinoma (HCC) is the most common liver malignancy worldwide. However, present studies of its multiple gene interaction and cellular pathways still could not explain the initiation and development of HCC perfectly. To find the key genes and miRNAs as well as their potential molecular mechanisms in HCC, microarray data GSE22058, GSE25097, and GSE57958 were analyzed. METHODS: The microarray datasets GSE22058, GSE25097, and GSE57958, including mRNA and miRNA profiles, were downloaded from the GEO database and were analyzed using GEO2R. Functional and pathway enrichment analyses were performed using the DAVID database, and the protein–protein interaction (PPI) network was constructed using the Cytoscape software. Finally, miRDB was applied to predict the targets of the differentially expressed miRNAs (DEMs). RESULTS: A total of 115 differentially expressed genes (DEGs) were found in HCC, including 52 up-regulated genes and 63 down-regulated genes. The gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses from DAVID showed that up-regulated genes were significantly enriched in chromosome segregation and cell division, while the down-regulated genes were mainly involved in complement activation, protein activation cascades, carboxylic acid metabolic processes, oxoacid metabolic processes, and the immune response. From the PPI network, the 18 nodes with the highest degree were screened as hub genes. Among them, ESR1 was found to have close interactions with FOXO1, CXCL12, and GNAO1. In addition, a total of 64 DEMs were identified, which included 58 up-regulated miRNAs and 6 down-regulated miRNAs. ESR1 was potentially targeted by five miRNAs, including hsa-mir-18a and hsa-mir-221. CONCLUSIONS: The roles of DEMs like hsa-mir-221 in HCC through interactions with DEGs such as ESR1 and CXCL12 may provide new clues for the diagnosis and treatment of HCC patients. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12957-017-1127-2) contains supplementary material, which is available to authorized users.
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spelling pubmed-53562762017-03-22 Identification and interaction analysis of key genes and microRNAs in hepatocellular carcinoma by bioinformatics analysis Mou, Tong Zhu, Di Wei, Xufu Li, Tingting Zheng, Daofeng Pu, Junliang Guo, Zhen Wu, Zhongjun World J Surg Oncol Research BACKGROUND: Hepatocellular carcinoma (HCC) is the most common liver malignancy worldwide. However, present studies of its multiple gene interaction and cellular pathways still could not explain the initiation and development of HCC perfectly. To find the key genes and miRNAs as well as their potential molecular mechanisms in HCC, microarray data GSE22058, GSE25097, and GSE57958 were analyzed. METHODS: The microarray datasets GSE22058, GSE25097, and GSE57958, including mRNA and miRNA profiles, were downloaded from the GEO database and were analyzed using GEO2R. Functional and pathway enrichment analyses were performed using the DAVID database, and the protein–protein interaction (PPI) network was constructed using the Cytoscape software. Finally, miRDB was applied to predict the targets of the differentially expressed miRNAs (DEMs). RESULTS: A total of 115 differentially expressed genes (DEGs) were found in HCC, including 52 up-regulated genes and 63 down-regulated genes. The gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses from DAVID showed that up-regulated genes were significantly enriched in chromosome segregation and cell division, while the down-regulated genes were mainly involved in complement activation, protein activation cascades, carboxylic acid metabolic processes, oxoacid metabolic processes, and the immune response. From the PPI network, the 18 nodes with the highest degree were screened as hub genes. Among them, ESR1 was found to have close interactions with FOXO1, CXCL12, and GNAO1. In addition, a total of 64 DEMs were identified, which included 58 up-regulated miRNAs and 6 down-regulated miRNAs. ESR1 was potentially targeted by five miRNAs, including hsa-mir-18a and hsa-mir-221. CONCLUSIONS: The roles of DEMs like hsa-mir-221 in HCC through interactions with DEGs such as ESR1 and CXCL12 may provide new clues for the diagnosis and treatment of HCC patients. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12957-017-1127-2) contains supplementary material, which is available to authorized users. BioMed Central 2017-03-16 /pmc/articles/PMC5356276/ /pubmed/28302149 http://dx.doi.org/10.1186/s12957-017-1127-2 Text en © The Author(s). 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Mou, Tong
Zhu, Di
Wei, Xufu
Li, Tingting
Zheng, Daofeng
Pu, Junliang
Guo, Zhen
Wu, Zhongjun
Identification and interaction analysis of key genes and microRNAs in hepatocellular carcinoma by bioinformatics analysis
title Identification and interaction analysis of key genes and microRNAs in hepatocellular carcinoma by bioinformatics analysis
title_full Identification and interaction analysis of key genes and microRNAs in hepatocellular carcinoma by bioinformatics analysis
title_fullStr Identification and interaction analysis of key genes and microRNAs in hepatocellular carcinoma by bioinformatics analysis
title_full_unstemmed Identification and interaction analysis of key genes and microRNAs in hepatocellular carcinoma by bioinformatics analysis
title_short Identification and interaction analysis of key genes and microRNAs in hepatocellular carcinoma by bioinformatics analysis
title_sort identification and interaction analysis of key genes and micrornas in hepatocellular carcinoma by bioinformatics analysis
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5356276/
https://www.ncbi.nlm.nih.gov/pubmed/28302149
http://dx.doi.org/10.1186/s12957-017-1127-2
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