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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...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
SAGE Publications
2020
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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. |
format | Online Article Text |
id | pubmed-7137642 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | SAGE Publications |
record_format | MEDLINE/PubMed |
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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