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Investigating age-induced differentially expressed genes and potential molecular mechanisms in osteosarcoma based on integrated bioinformatics analysis

Osteosarcoma (OS) is the most common primary bone malignancy. It predominantly occurs in adolescents, but can develop at any age. The age at diagnosis is a prognostic factor of OS, but the molecular basis of this remains unknown. The current study aimed to identify age-induced differentially express...

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Autores principales: Wang, Jian-Sheng, Duan, Ming-Yue, Zhong, Yong-Sheng, Li, Xue-Dong, Du, Shi-Xin, Xie, Peng, Zheng, Gui-Zhou, Han, Jing-Ming
Formato: Online Artículo Texto
Lenguaje:English
Publicado: D.A. Spandidos 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6423644/
https://www.ncbi.nlm.nih.gov/pubmed/30720085
http://dx.doi.org/10.3892/mmr.2019.9912
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author Wang, Jian-Sheng
Duan, Ming-Yue
Zhong, Yong-Sheng
Li, Xue-Dong
Du, Shi-Xin
Xie, Peng
Zheng, Gui-Zhou
Han, Jing-Ming
author_facet Wang, Jian-Sheng
Duan, Ming-Yue
Zhong, Yong-Sheng
Li, Xue-Dong
Du, Shi-Xin
Xie, Peng
Zheng, Gui-Zhou
Han, Jing-Ming
author_sort Wang, Jian-Sheng
collection PubMed
description Osteosarcoma (OS) is the most common primary bone malignancy. It predominantly occurs in adolescents, but can develop at any age. The age at diagnosis is a prognostic factor of OS, but the molecular basis of this remains unknown. The current study aimed to identify age-induced differentially expressed genes (DEGs) and potential molecular mechanisms that contribute to the different outcomes of patients with OS. Microarray data (GSE39058 and GSE39040) obtained from the Gene Expression Omnibus database and used to analyze age-induced DEGs to reveal molecular mechanism of OS among different age groups (<20 and >20 years old). Differentially expressed mRNAs (DEMs) were divided into up and downregulated DEMs (according to the expression fold change), then Gene Ontology function enrichment and Kyoto Encyclopedia of Genes and Genomes pathway analysis were performed. Furthermore, the interactions among proteins encoded by DEMs were integrated with prediction for microRNA-mRNA interactions to construct a regulatory network. The key subnetwork was extracted and Kaplan-Meier survival analysis for a key microRNA was performed. DEMs within the subnetwork were predominantly involved in ‘ubiquitin protein ligase binding’, ‘response to growth factor’, ‘regulation of type I interferon production’, ‘response to decreased oxygen levels’, ‘voltage-gated potassium channel complex’, ‘synapse part’, ‘regulation of stem cell proliferation’. In summary, integrated bioinformatics was applied to analyze the potential molecular mechanisms leading to different outcomes of patients with OS among different age groups. The hub genes within the key subnetwork may have crucial roles in the different outcomes associated with age and require further analysis.
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spelling pubmed-64236442019-03-22 Investigating age-induced differentially expressed genes and potential molecular mechanisms in osteosarcoma based on integrated bioinformatics analysis Wang, Jian-Sheng Duan, Ming-Yue Zhong, Yong-Sheng Li, Xue-Dong Du, Shi-Xin Xie, Peng Zheng, Gui-Zhou Han, Jing-Ming Mol Med Rep Articles Osteosarcoma (OS) is the most common primary bone malignancy. It predominantly occurs in adolescents, but can develop at any age. The age at diagnosis is a prognostic factor of OS, but the molecular basis of this remains unknown. The current study aimed to identify age-induced differentially expressed genes (DEGs) and potential molecular mechanisms that contribute to the different outcomes of patients with OS. Microarray data (GSE39058 and GSE39040) obtained from the Gene Expression Omnibus database and used to analyze age-induced DEGs to reveal molecular mechanism of OS among different age groups (<20 and >20 years old). Differentially expressed mRNAs (DEMs) were divided into up and downregulated DEMs (according to the expression fold change), then Gene Ontology function enrichment and Kyoto Encyclopedia of Genes and Genomes pathway analysis were performed. Furthermore, the interactions among proteins encoded by DEMs were integrated with prediction for microRNA-mRNA interactions to construct a regulatory network. The key subnetwork was extracted and Kaplan-Meier survival analysis for a key microRNA was performed. DEMs within the subnetwork were predominantly involved in ‘ubiquitin protein ligase binding’, ‘response to growth factor’, ‘regulation of type I interferon production’, ‘response to decreased oxygen levels’, ‘voltage-gated potassium channel complex’, ‘synapse part’, ‘regulation of stem cell proliferation’. In summary, integrated bioinformatics was applied to analyze the potential molecular mechanisms leading to different outcomes of patients with OS among different age groups. The hub genes within the key subnetwork may have crucial roles in the different outcomes associated with age and require further analysis. D.A. Spandidos 2019-04 2019-01-30 /pmc/articles/PMC6423644/ /pubmed/30720085 http://dx.doi.org/10.3892/mmr.2019.9912 Text en Copyright: © Wang et al. This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License (https://creativecommons.org/licenses/by-nc-nd/4.0/) , which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.
spellingShingle Articles
Wang, Jian-Sheng
Duan, Ming-Yue
Zhong, Yong-Sheng
Li, Xue-Dong
Du, Shi-Xin
Xie, Peng
Zheng, Gui-Zhou
Han, Jing-Ming
Investigating age-induced differentially expressed genes and potential molecular mechanisms in osteosarcoma based on integrated bioinformatics analysis
title Investigating age-induced differentially expressed genes and potential molecular mechanisms in osteosarcoma based on integrated bioinformatics analysis
title_full Investigating age-induced differentially expressed genes and potential molecular mechanisms in osteosarcoma based on integrated bioinformatics analysis
title_fullStr Investigating age-induced differentially expressed genes and potential molecular mechanisms in osteosarcoma based on integrated bioinformatics analysis
title_full_unstemmed Investigating age-induced differentially expressed genes and potential molecular mechanisms in osteosarcoma based on integrated bioinformatics analysis
title_short Investigating age-induced differentially expressed genes and potential molecular mechanisms in osteosarcoma based on integrated bioinformatics analysis
title_sort investigating age-induced differentially expressed genes and potential molecular mechanisms in osteosarcoma based on integrated bioinformatics analysis
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6423644/
https://www.ncbi.nlm.nih.gov/pubmed/30720085
http://dx.doi.org/10.3892/mmr.2019.9912
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