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Identification of Key Genes and Pathways for Enchondromas by Bioinformatics Analysis

BACKGROUND: The risk of malignant transformation of enchondromas (EC) toward central chondrosarcoma is increased up to 35%, while the exact etiology of EC is unknown. The purpose of this research was to authenticate gene signatures during EC and reveal their potential mechanisms in occurrence and de...

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Autores principales: Wu, Tianlong, Cao, Honghai, Liu, Lei, Peng, Kan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7137642/
https://www.ncbi.nlm.nih.gov/pubmed/32284694
http://dx.doi.org/10.1177/1559325820907536
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author Wu, Tianlong
Cao, Honghai
Liu, Lei
Peng, Kan
author_facet Wu, Tianlong
Cao, Honghai
Liu, Lei
Peng, Kan
author_sort Wu, Tianlong
collection PubMed
description BACKGROUND: The risk of malignant transformation of enchondromas (EC) toward central chondrosarcoma is increased up to 35%, while the exact etiology of EC is unknown. The purpose of this research was to authenticate gene signatures during EC and reveal their potential mechanisms in occurrence and development of EC. METHODS: The gene expression profiles was acquired from Gene Expression Omnibus database (no. GSE22855). The gene ontology (GO), protein–protein interaction (PPI) network and Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) enrichment analyses were utilized to identify differentially expressed genes (DEGs). RESULTS: Finally, 242 DEGs were appraisal, containing 200 overregulated genes and 42 downregulated genes. The outcomes of GO analysis indicated that upregulated DEGs were mainly enriched in several biological processes containing response to hypoxia, calcium ion, and negative regulation extrinsic apoptotic signaling pathway. Furthermore, the upregulated DEGs were enriched in extracellular matrix (ECM)–receptor interaction, protein processing in endoplasmic reticulum and ribosome, which was analyzed by KEGG pathway. From the PPI network, the top 10 hub genes were identified, which were related to significant pathways containing ribosome, protein processing in endoplasmic reticulum, and ECM-receptor interaction. CONCLUSION: In conclusion, the present study may be helpful for understanding the diagnostic biomarkers of EC.
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spelling pubmed-71376422020-04-13 Identification of Key Genes and Pathways for Enchondromas by Bioinformatics Analysis Wu, Tianlong Cao, Honghai Liu, Lei Peng, Kan Dose Response Original Article BACKGROUND: The risk of malignant transformation of enchondromas (EC) toward central chondrosarcoma is increased up to 35%, while the exact etiology of EC is unknown. The purpose of this research was to authenticate gene signatures during EC and reveal their potential mechanisms in occurrence and development of EC. METHODS: The gene expression profiles was acquired from Gene Expression Omnibus database (no. GSE22855). The gene ontology (GO), protein–protein interaction (PPI) network and Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) enrichment analyses were utilized to identify differentially expressed genes (DEGs). RESULTS: Finally, 242 DEGs were appraisal, containing 200 overregulated genes and 42 downregulated genes. The outcomes of GO analysis indicated that upregulated DEGs were mainly enriched in several biological processes containing response to hypoxia, calcium ion, and negative regulation extrinsic apoptotic signaling pathway. Furthermore, the upregulated DEGs were enriched in extracellular matrix (ECM)–receptor interaction, protein processing in endoplasmic reticulum and ribosome, which was analyzed by KEGG pathway. From the PPI network, the top 10 hub genes were identified, which were related to significant pathways containing ribosome, protein processing in endoplasmic reticulum, and ECM-receptor interaction. CONCLUSION: In conclusion, the present study may be helpful for understanding the diagnostic biomarkers of EC. SAGE Publications 2020-03-30 /pmc/articles/PMC7137642/ /pubmed/32284694 http://dx.doi.org/10.1177/1559325820907536 Text en © The Author(s) 2020 https://creativecommons.org/licenses/by/4.0/ This article is distributed under the terms of the Creative Commons Attribution 4.0 License (https://creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage).
spellingShingle Original Article
Wu, Tianlong
Cao, Honghai
Liu, Lei
Peng, Kan
Identification of Key Genes and Pathways for Enchondromas by Bioinformatics Analysis
title Identification of Key Genes and Pathways for Enchondromas by Bioinformatics Analysis
title_full Identification of Key Genes and Pathways for Enchondromas by Bioinformatics Analysis
title_fullStr Identification of Key Genes and Pathways for Enchondromas by Bioinformatics Analysis
title_full_unstemmed Identification of Key Genes and Pathways for Enchondromas by Bioinformatics Analysis
title_short Identification of Key Genes and Pathways for Enchondromas by Bioinformatics Analysis
title_sort identification of key genes and pathways for enchondromas by bioinformatics analysis
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7137642/
https://www.ncbi.nlm.nih.gov/pubmed/32284694
http://dx.doi.org/10.1177/1559325820907536
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