Cargando…
Identification of driver genes associated with chemotherapy resistance of Ewing’s sarcoma
BACKGROUND: The aim of this study was to identify the driver genes associated with chemotherapy resistance of Ewing’s sarcoma and potential targets for Ewing’s sarcoma treatment. METHODS: Two mRNA microarray datasets, GSE12102 and GSE17679, were downloaded from the Gene Expression Omnibus database,...
Autores principales: | , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Dove Medical Press
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6199211/ https://www.ncbi.nlm.nih.gov/pubmed/30410352 http://dx.doi.org/10.2147/OTT.S172190 |
_version_ | 1783365094071074816 |
---|---|
author | Liao, Hongyi Xie, Xianbiao Xu, Yuanyuan Huang, Gang |
author_facet | Liao, Hongyi Xie, Xianbiao Xu, Yuanyuan Huang, Gang |
author_sort | Liao, Hongyi |
collection | PubMed |
description | BACKGROUND: The aim of this study was to identify the driver genes associated with chemotherapy resistance of Ewing’s sarcoma and potential targets for Ewing’s sarcoma treatment. METHODS: Two mRNA microarray datasets, GSE12102 and GSE17679, were downloaded from the Gene Expression Omnibus database, which contain 94 human Ewing’s sarcoma samples, including 65 from those who experienced a relapse and 29 from those with no evidence of disease. The differen tially expressed genes (DEGs) were identified using LIMMA package R. Subsequently, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were performed for DEGs using Database for Annotation, Visualization and Integrated Analysis. The protein–protein interaction network was constructed using Cytoscape software, and module analysis was performed using Molecular Complex Detection. RESULTS: A total of 206 upregulated DEGs and 141 downregulated DEGs were identified. Upregulated DEGs were primarily enriched in DNA replication, nucleoplasm and protein kinase binding for biological processes, cellular component and molecular functions, respectively. Downregulated DEGs were predominantly involved in receptor clustering, membrane raft, and ligand-dependent nuclear receptor binding. The protein–protein interaction network of DEGs consisted of 150 nodes and 304 interactions. Thirteen hub genes were identified, and biological analysis revealed that these genes were primarily enriched in cell division, cell cycle, and mitosis. Furthermore, based on closeness centrality, betweenness centrality, and degree centrality, the three most significant genes were identified as GAPDH, AURKA, and EHMT2. Furthermore, the significant network module was composed of nine genes. These genes were primarily enriched in mitotic nuclear division, mitotic chromosome condensation, and nucleoplasm. CONCLUSION: These hub genes, especially GAPDH, AURKA, and EHMT2, may be closely associated with the progression of Ewing’s sarcoma chemotherapy resistance, and further experiments are needed for confirmation. |
format | Online Article Text |
id | pubmed-6199211 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Dove Medical Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-61992112018-11-08 Identification of driver genes associated with chemotherapy resistance of Ewing’s sarcoma Liao, Hongyi Xie, Xianbiao Xu, Yuanyuan Huang, Gang Onco Targets Ther Original Research BACKGROUND: The aim of this study was to identify the driver genes associated with chemotherapy resistance of Ewing’s sarcoma and potential targets for Ewing’s sarcoma treatment. METHODS: Two mRNA microarray datasets, GSE12102 and GSE17679, were downloaded from the Gene Expression Omnibus database, which contain 94 human Ewing’s sarcoma samples, including 65 from those who experienced a relapse and 29 from those with no evidence of disease. The differen tially expressed genes (DEGs) were identified using LIMMA package R. Subsequently, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were performed for DEGs using Database for Annotation, Visualization and Integrated Analysis. The protein–protein interaction network was constructed using Cytoscape software, and module analysis was performed using Molecular Complex Detection. RESULTS: A total of 206 upregulated DEGs and 141 downregulated DEGs were identified. Upregulated DEGs were primarily enriched in DNA replication, nucleoplasm and protein kinase binding for biological processes, cellular component and molecular functions, respectively. Downregulated DEGs were predominantly involved in receptor clustering, membrane raft, and ligand-dependent nuclear receptor binding. The protein–protein interaction network of DEGs consisted of 150 nodes and 304 interactions. Thirteen hub genes were identified, and biological analysis revealed that these genes were primarily enriched in cell division, cell cycle, and mitosis. Furthermore, based on closeness centrality, betweenness centrality, and degree centrality, the three most significant genes were identified as GAPDH, AURKA, and EHMT2. Furthermore, the significant network module was composed of nine genes. These genes were primarily enriched in mitotic nuclear division, mitotic chromosome condensation, and nucleoplasm. CONCLUSION: These hub genes, especially GAPDH, AURKA, and EHMT2, may be closely associated with the progression of Ewing’s sarcoma chemotherapy resistance, and further experiments are needed for confirmation. Dove Medical Press 2018-10-15 /pmc/articles/PMC6199211/ /pubmed/30410352 http://dx.doi.org/10.2147/OTT.S172190 Text en © 2018 Liao et al. 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/). 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. |
spellingShingle | Original Research Liao, Hongyi Xie, Xianbiao Xu, Yuanyuan Huang, Gang Identification of driver genes associated with chemotherapy resistance of Ewing’s sarcoma |
title | Identification of driver genes associated with chemotherapy resistance of Ewing’s sarcoma |
title_full | Identification of driver genes associated with chemotherapy resistance of Ewing’s sarcoma |
title_fullStr | Identification of driver genes associated with chemotherapy resistance of Ewing’s sarcoma |
title_full_unstemmed | Identification of driver genes associated with chemotherapy resistance of Ewing’s sarcoma |
title_short | Identification of driver genes associated with chemotherapy resistance of Ewing’s sarcoma |
title_sort | identification of driver genes associated with chemotherapy resistance of ewing’s sarcoma |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6199211/ https://www.ncbi.nlm.nih.gov/pubmed/30410352 http://dx.doi.org/10.2147/OTT.S172190 |
work_keys_str_mv | AT liaohongyi identificationofdrivergenesassociatedwithchemotherapyresistanceofewingssarcoma AT xiexianbiao identificationofdrivergenesassociatedwithchemotherapyresistanceofewingssarcoma AT xuyuanyuan identificationofdrivergenesassociatedwithchemotherapyresistanceofewingssarcoma AT huanggang identificationofdrivergenesassociatedwithchemotherapyresistanceofewingssarcoma |