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Comprehensive Bioinformatics Analysis of mRNA Expression Profiles and Identification of a miRNA–mRNA Network Associated with the Pathogenesis of Low-Grade Gliomas

PURPOSE: Low-grade glioma is the most common type of primary intracranial tumour, and the overall survival of patients with low-grade glioma (LGG) has shown no significant improvement over the past few decades. Therefore, it is crucial to understand the precise molecular mechanisms involved in the c...

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Autores principales: Wang, Ming, Cui, Yan, Cai, Yang, Jiang, Yugang, Peng, Yong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8254561/
https://www.ncbi.nlm.nih.gov/pubmed/34234557
http://dx.doi.org/10.2147/CMAR.S314011
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author Wang, Ming
Cui, Yan
Cai, Yang
Jiang, Yugang
Peng, Yong
author_facet Wang, Ming
Cui, Yan
Cai, Yang
Jiang, Yugang
Peng, Yong
author_sort Wang, Ming
collection PubMed
description PURPOSE: Low-grade glioma is the most common type of primary intracranial tumour, and the overall survival of patients with low-grade glioma (LGG) has shown no significant improvement over the past few decades. Therefore, it is crucial to understand the precise molecular mechanisms involved in the carcinogenesis of LGG. METHODS: To investigate the regulatory mechanisms of mRNA–miRNA networks related to LGG, in the present study, a comprehensive analysis of the genomic landscape between low-grade gliomas and normal brain tissues from the GEO and TCGA datasets was first conducted to identify differentially expressed genes (DEGs) and differentially expressed miRNAs in LGG. Following a series of analyses, including WGCNA, GO and KEGG analyses, PPI and key model analyses, and survival analysis of the DEGs with clinical phenotypes, the potential key genes were screened and identified, and the related miRNA–mRNA networks were subsequently constructed through miRWalk 3.0. Finally, the potential miRNA–mRNA networks were further validated in CGGA (Chinese Glioma Genome Atlas) datasets and clinical specimens by qRT-PCR. RESULTS: In our results, six hub genes, MELK, NCAPG, KIF4A, NUSAP1, CEP55, and TOP2A, were ultimately identified. Two regulatory pathways, miR-495-3p-TOP2A and miR-1224-3p-MELK, that regulate the pathogenesis of LGG were ultimately identified. Furthermore, the expression of miR-495-3p-TOP2A and miR-1224-3p-MELK in solid tissues was validated by qRT-PCR. CONCLUSION: Our study identified hub genes and related miRNA–mRNA regulatory pathways that contribute to the carcinogenesis of LGG, which may help us reveal the mechanisms underlying the development of LGG.
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spelling pubmed-82545612021-07-06 Comprehensive Bioinformatics Analysis of mRNA Expression Profiles and Identification of a miRNA–mRNA Network Associated with the Pathogenesis of Low-Grade Gliomas Wang, Ming Cui, Yan Cai, Yang Jiang, Yugang Peng, Yong Cancer Manag Res Original Research PURPOSE: Low-grade glioma is the most common type of primary intracranial tumour, and the overall survival of patients with low-grade glioma (LGG) has shown no significant improvement over the past few decades. Therefore, it is crucial to understand the precise molecular mechanisms involved in the carcinogenesis of LGG. METHODS: To investigate the regulatory mechanisms of mRNA–miRNA networks related to LGG, in the present study, a comprehensive analysis of the genomic landscape between low-grade gliomas and normal brain tissues from the GEO and TCGA datasets was first conducted to identify differentially expressed genes (DEGs) and differentially expressed miRNAs in LGG. Following a series of analyses, including WGCNA, GO and KEGG analyses, PPI and key model analyses, and survival analysis of the DEGs with clinical phenotypes, the potential key genes were screened and identified, and the related miRNA–mRNA networks were subsequently constructed through miRWalk 3.0. Finally, the potential miRNA–mRNA networks were further validated in CGGA (Chinese Glioma Genome Atlas) datasets and clinical specimens by qRT-PCR. RESULTS: In our results, six hub genes, MELK, NCAPG, KIF4A, NUSAP1, CEP55, and TOP2A, were ultimately identified. Two regulatory pathways, miR-495-3p-TOP2A and miR-1224-3p-MELK, that regulate the pathogenesis of LGG were ultimately identified. Furthermore, the expression of miR-495-3p-TOP2A and miR-1224-3p-MELK in solid tissues was validated by qRT-PCR. CONCLUSION: Our study identified hub genes and related miRNA–mRNA regulatory pathways that contribute to the carcinogenesis of LGG, which may help us reveal the mechanisms underlying the development of LGG. Dove 2021-06-29 /pmc/articles/PMC8254561/ /pubmed/34234557 http://dx.doi.org/10.2147/CMAR.S314011 Text en © 2021 Wang et al. https://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/ (https://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
Wang, Ming
Cui, Yan
Cai, Yang
Jiang, Yugang
Peng, Yong
Comprehensive Bioinformatics Analysis of mRNA Expression Profiles and Identification of a miRNA–mRNA Network Associated with the Pathogenesis of Low-Grade Gliomas
title Comprehensive Bioinformatics Analysis of mRNA Expression Profiles and Identification of a miRNA–mRNA Network Associated with the Pathogenesis of Low-Grade Gliomas
title_full Comprehensive Bioinformatics Analysis of mRNA Expression Profiles and Identification of a miRNA–mRNA Network Associated with the Pathogenesis of Low-Grade Gliomas
title_fullStr Comprehensive Bioinformatics Analysis of mRNA Expression Profiles and Identification of a miRNA–mRNA Network Associated with the Pathogenesis of Low-Grade Gliomas
title_full_unstemmed Comprehensive Bioinformatics Analysis of mRNA Expression Profiles and Identification of a miRNA–mRNA Network Associated with the Pathogenesis of Low-Grade Gliomas
title_short Comprehensive Bioinformatics Analysis of mRNA Expression Profiles and Identification of a miRNA–mRNA Network Associated with the Pathogenesis of Low-Grade Gliomas
title_sort comprehensive bioinformatics analysis of mrna expression profiles and identification of a mirna–mrna network associated with the pathogenesis of low-grade gliomas
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8254561/
https://www.ncbi.nlm.nih.gov/pubmed/34234557
http://dx.doi.org/10.2147/CMAR.S314011
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