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Identification of potential micro-messenger RNAs (miRNA–mRNA) interaction network of osteosarcoma

Osteosarcoma (OS) is the most common primary malignant tumor in children and adolescents. Numerous studies have reported the importance of miRNA in OS. The purpose of this study is to predict potential biomarkers and new therapeutic targets for OS diagnosis and prognosis by analyzing miRNAs of OS pl...

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Autores principales: Xu, Keteng, Zhang, Pei, Zhang, Jiale, Quan, Huahong, Wang, Jingcheng, Liang, Yuan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Taylor & Francis 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8806609/
https://www.ncbi.nlm.nih.gov/pubmed/34252359
http://dx.doi.org/10.1080/21655979.2021.1947065
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author Xu, Keteng
Zhang, Pei
Zhang, Jiale
Quan, Huahong
Wang, Jingcheng
Liang, Yuan
author_facet Xu, Keteng
Zhang, Pei
Zhang, Jiale
Quan, Huahong
Wang, Jingcheng
Liang, Yuan
author_sort Xu, Keteng
collection PubMed
description Osteosarcoma (OS) is the most common primary malignant tumor in children and adolescents. Numerous studies have reported the importance of miRNA in OS. The purpose of this study is to predict potential biomarkers and new therapeutic targets for OS diagnosis and prognosis by analyzing miRNAs of OS plasma samples from the Gene Expression Omnibus (GEO) database. Data-sets were downloaded from the GEO and analyzed using R software. Different expressions of miRNAs (DE-miRNAs) in plasma and mRNAs (DE-mRNAs) in OS patients were identified. Funrich was used to predict the transcription factors and target genes of miRNAs. By comparing the target mRNAs and DE-mRNAs, the intersection mRNAs were identified. The intersection mRNAs were imported to perform Gene Ontology (GO) functional annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. MiRNA-mRNA regulatory network and a protein-protein interaction (PPI) network were constructed by using Cytoscape. Finally, a total of 164 DE-miRNAs, 256 DE-mRNAs, and 76 intersection mRNAs were identified. The top 10 TF of up- and down-regulated DE-miRNAs were also predicted. In addition, GO and KEGG analyses further revealed the intersection mRNAs. By constructing the miRNA–mRNA networks, we found miR-30d-5p, miR-17-5p, miR-98-5p, miR-301a-3p, and miR-30e-5p were the central hubs. COL1A1, COL1A2, MMP2, CDH11, COL4A1 etc. were predicted to be the key mRNA by constructing the PPI networks. Through a comprehensive bioinformatics analysis of miRNAs and mRNAs in OS, we explored the potential effective biomarkers and novel therapeutic targets for the diagnosis and prognosis of OS.
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spelling pubmed-88066092022-02-02 Identification of potential micro-messenger RNAs (miRNA–mRNA) interaction network of osteosarcoma Xu, Keteng Zhang, Pei Zhang, Jiale Quan, Huahong Wang, Jingcheng Liang, Yuan Bioengineered Research Paper Osteosarcoma (OS) is the most common primary malignant tumor in children and adolescents. Numerous studies have reported the importance of miRNA in OS. The purpose of this study is to predict potential biomarkers and new therapeutic targets for OS diagnosis and prognosis by analyzing miRNAs of OS plasma samples from the Gene Expression Omnibus (GEO) database. Data-sets were downloaded from the GEO and analyzed using R software. Different expressions of miRNAs (DE-miRNAs) in plasma and mRNAs (DE-mRNAs) in OS patients were identified. Funrich was used to predict the transcription factors and target genes of miRNAs. By comparing the target mRNAs and DE-mRNAs, the intersection mRNAs were identified. The intersection mRNAs were imported to perform Gene Ontology (GO) functional annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. MiRNA-mRNA regulatory network and a protein-protein interaction (PPI) network were constructed by using Cytoscape. Finally, a total of 164 DE-miRNAs, 256 DE-mRNAs, and 76 intersection mRNAs were identified. The top 10 TF of up- and down-regulated DE-miRNAs were also predicted. In addition, GO and KEGG analyses further revealed the intersection mRNAs. By constructing the miRNA–mRNA networks, we found miR-30d-5p, miR-17-5p, miR-98-5p, miR-301a-3p, and miR-30e-5p were the central hubs. COL1A1, COL1A2, MMP2, CDH11, COL4A1 etc. were predicted to be the key mRNA by constructing the PPI networks. Through a comprehensive bioinformatics analysis of miRNAs and mRNAs in OS, we explored the potential effective biomarkers and novel therapeutic targets for the diagnosis and prognosis of OS. Taylor & Francis 2021-07-12 /pmc/articles/PMC8806609/ /pubmed/34252359 http://dx.doi.org/10.1080/21655979.2021.1947065 Text en © 2021 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Paper
Xu, Keteng
Zhang, Pei
Zhang, Jiale
Quan, Huahong
Wang, Jingcheng
Liang, Yuan
Identification of potential micro-messenger RNAs (miRNA–mRNA) interaction network of osteosarcoma
title Identification of potential micro-messenger RNAs (miRNA–mRNA) interaction network of osteosarcoma
title_full Identification of potential micro-messenger RNAs (miRNA–mRNA) interaction network of osteosarcoma
title_fullStr Identification of potential micro-messenger RNAs (miRNA–mRNA) interaction network of osteosarcoma
title_full_unstemmed Identification of potential micro-messenger RNAs (miRNA–mRNA) interaction network of osteosarcoma
title_short Identification of potential micro-messenger RNAs (miRNA–mRNA) interaction network of osteosarcoma
title_sort identification of potential micro-messenger rnas (mirna–mrna) interaction network of osteosarcoma
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8806609/
https://www.ncbi.nlm.nih.gov/pubmed/34252359
http://dx.doi.org/10.1080/21655979.2021.1947065
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