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Potential targets and molecular mechanism of miR-331-3p in hepatocellular carcinoma identified by weighted gene coexpression network analysis

Hepatocellular carcinoma (HCC) is one of the most common malignant tumor. miR-331-3p has been reported relevant to the progression of HCC, but the molecular mechanism of its regulation is still unclear. In the study, we comprehensively studied the role of miR-331-3p in HCC through weighted gene coex...

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Autores principales: Chi, Qingjia, Geng, Xinge, Xu, Kang, Wang, Chunli, Zhao, Han
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Portland Press Ltd. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7317601/
https://www.ncbi.nlm.nih.gov/pubmed/32537629
http://dx.doi.org/10.1042/BSR20200124
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author Chi, Qingjia
Geng, Xinge
Xu, Kang
Wang, Chunli
Zhao, Han
author_facet Chi, Qingjia
Geng, Xinge
Xu, Kang
Wang, Chunli
Zhao, Han
author_sort Chi, Qingjia
collection PubMed
description Hepatocellular carcinoma (HCC) is one of the most common malignant tumor. miR-331-3p has been reported relevant to the progression of HCC, but the molecular mechanism of its regulation is still unclear. In the study, we comprehensively studied the role of miR-331-3p in HCC through weighted gene coexpression network analysis (WGCNA) based on The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO) and Oncomine. WGCNA was applied to build gene co-expression networks to examine the correlation between gene sets and clinical characteristics, and to identify potential biomarkers. Five hundred one target genes of miR-331-3p were obtained by overlapping differentially expressed genes (DEGs) from the TCGA database and target genes predicted by miRWalk. The critical turquoise module and its eight key genes were screened by WGCNA. Enrichment analysis was implemented based on the genes in the turquoise module. Moreover, 48 genes with a high degree of connectivity were obtained by protein–protein interaction (PPI) analysis of the genes in the turquoise module. From overlapping genes analyzed by WGCNA and PPI, two hub genes were obtained, namely coatomer protein complex subunit zeta 1 (COPZ1) and elongation factor Tu GTP binding domain containing 2 (EFTUD2). In addition, the expression of both hub genes was also significantly higher in tumor tissues compared with normal tissues, as confirmed by analysis based on TCGA and Oncomine. Both hub genes were correlated with poor prognosis based on TCGA data. Receiver operating characteristic (ROC) curve validated that both hub genes exhibited excellent diagnostic efficiency for normal and tumor tissues.
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spelling pubmed-73176012020-06-30 Potential targets and molecular mechanism of miR-331-3p in hepatocellular carcinoma identified by weighted gene coexpression network analysis Chi, Qingjia Geng, Xinge Xu, Kang Wang, Chunli Zhao, Han Biosci Rep Bioinformatics Hepatocellular carcinoma (HCC) is one of the most common malignant tumor. miR-331-3p has been reported relevant to the progression of HCC, but the molecular mechanism of its regulation is still unclear. In the study, we comprehensively studied the role of miR-331-3p in HCC through weighted gene coexpression network analysis (WGCNA) based on The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO) and Oncomine. WGCNA was applied to build gene co-expression networks to examine the correlation between gene sets and clinical characteristics, and to identify potential biomarkers. Five hundred one target genes of miR-331-3p were obtained by overlapping differentially expressed genes (DEGs) from the TCGA database and target genes predicted by miRWalk. The critical turquoise module and its eight key genes were screened by WGCNA. Enrichment analysis was implemented based on the genes in the turquoise module. Moreover, 48 genes with a high degree of connectivity were obtained by protein–protein interaction (PPI) analysis of the genes in the turquoise module. From overlapping genes analyzed by WGCNA and PPI, two hub genes were obtained, namely coatomer protein complex subunit zeta 1 (COPZ1) and elongation factor Tu GTP binding domain containing 2 (EFTUD2). In addition, the expression of both hub genes was also significantly higher in tumor tissues compared with normal tissues, as confirmed by analysis based on TCGA and Oncomine. Both hub genes were correlated with poor prognosis based on TCGA data. Receiver operating characteristic (ROC) curve validated that both hub genes exhibited excellent diagnostic efficiency for normal and tumor tissues. Portland Press Ltd. 2020-06-25 /pmc/articles/PMC7317601/ /pubmed/32537629 http://dx.doi.org/10.1042/BSR20200124 Text en © 2020 The Author(s). https://creativecommons.org/licenses/by/4.0/ This is an open access article published by Portland Press Limited on behalf of the Biochemical Society and distributed under the Creative Commons Attribution License 4.0 (CC BY).
spellingShingle Bioinformatics
Chi, Qingjia
Geng, Xinge
Xu, Kang
Wang, Chunli
Zhao, Han
Potential targets and molecular mechanism of miR-331-3p in hepatocellular carcinoma identified by weighted gene coexpression network analysis
title Potential targets and molecular mechanism of miR-331-3p in hepatocellular carcinoma identified by weighted gene coexpression network analysis
title_full Potential targets and molecular mechanism of miR-331-3p in hepatocellular carcinoma identified by weighted gene coexpression network analysis
title_fullStr Potential targets and molecular mechanism of miR-331-3p in hepatocellular carcinoma identified by weighted gene coexpression network analysis
title_full_unstemmed Potential targets and molecular mechanism of miR-331-3p in hepatocellular carcinoma identified by weighted gene coexpression network analysis
title_short Potential targets and molecular mechanism of miR-331-3p in hepatocellular carcinoma identified by weighted gene coexpression network analysis
title_sort potential targets and molecular mechanism of mir-331-3p in hepatocellular carcinoma identified by weighted gene coexpression network analysis
topic Bioinformatics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7317601/
https://www.ncbi.nlm.nih.gov/pubmed/32537629
http://dx.doi.org/10.1042/BSR20200124
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