Bioinformatics analysis of key biomarkers and pathways in KSHV infected endothelial cells

Kaposi sarcoma (KS) is an endothelial tumor etiologically related to Kaposi sarcoma herpesvirus (KSHV) infection. The aim of our study was to screen out candidate genes of KSHV infected endothelial cells and to elucidate the underlying molecular mechanisms by bioinformatics methods. Microarray datas...

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Autores principales: Gong, Hai-Bo, Wu, Xiu-Juan, Pu, Xiong-Ming, Kang, Xiao-Jing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Wolters Kluwer Health 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6635252/
https://www.ncbi.nlm.nih.gov/pubmed/31277155
http://dx.doi.org/10.1097/MD.0000000000016277
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author Gong, Hai-Bo
Wu, Xiu-Juan
Pu, Xiong-Ming
Kang, Xiao-Jing
author_facet Gong, Hai-Bo
Wu, Xiu-Juan
Pu, Xiong-Ming
Kang, Xiao-Jing
author_sort Gong, Hai-Bo
collection PubMed
description Kaposi sarcoma (KS) is an endothelial tumor etiologically related to Kaposi sarcoma herpesvirus (KSHV) infection. The aim of our study was to screen out candidate genes of KSHV infected endothelial cells and to elucidate the underlying molecular mechanisms by bioinformatics methods. Microarray datasets GSE16354 and GSE22522 were downloaded from Gene Expression Omnibus (GEO) database. the differentially expressed genes (DEGs) between endothelial cells and KSHV infected endothelial cells were identified. And then, functional enrichment analyses of gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) pathway analysis were performed. After that, Search Tool for the Retrieval of Interacting Genes (STRING) was used to investigate the potential protein–protein interaction (PPI) network between DEGs, Cytoscape software was used to visualize the interaction network of DEGs and to screen out the hub genes. A total of 113 DEGs and 11 hub genes were identified from the 2 datasets. GO enrichment analysis revealed that most of the DEGs were enrichen in regulation of cell proliferation, extracellular region part and sequence-specific DNA binding; KEGG pathway enrichments analysis displayed that DEGs were mostly enrichen in cell cycle, Jak-STAT signaling pathway, pathways in cancer, and Insulin signaling pathway. In conclusion, the present study identified a host of DEGs and hub genes in KSHV infected endothelial cells which may serve as potential key biomarkers and therapeutic targets, helping us to have a better understanding of the molecular mechanism of KS.
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spelling pubmed-66352522019-08-01 Bioinformatics analysis of key biomarkers and pathways in KSHV infected endothelial cells Gong, Hai-Bo Wu, Xiu-Juan Pu, Xiong-Ming Kang, Xiao-Jing Medicine (Baltimore) Research Article Kaposi sarcoma (KS) is an endothelial tumor etiologically related to Kaposi sarcoma herpesvirus (KSHV) infection. The aim of our study was to screen out candidate genes of KSHV infected endothelial cells and to elucidate the underlying molecular mechanisms by bioinformatics methods. Microarray datasets GSE16354 and GSE22522 were downloaded from Gene Expression Omnibus (GEO) database. the differentially expressed genes (DEGs) between endothelial cells and KSHV infected endothelial cells were identified. And then, functional enrichment analyses of gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) pathway analysis were performed. After that, Search Tool for the Retrieval of Interacting Genes (STRING) was used to investigate the potential protein–protein interaction (PPI) network between DEGs, Cytoscape software was used to visualize the interaction network of DEGs and to screen out the hub genes. A total of 113 DEGs and 11 hub genes were identified from the 2 datasets. GO enrichment analysis revealed that most of the DEGs were enrichen in regulation of cell proliferation, extracellular region part and sequence-specific DNA binding; KEGG pathway enrichments analysis displayed that DEGs were mostly enrichen in cell cycle, Jak-STAT signaling pathway, pathways in cancer, and Insulin signaling pathway. In conclusion, the present study identified a host of DEGs and hub genes in KSHV infected endothelial cells which may serve as potential key biomarkers and therapeutic targets, helping us to have a better understanding of the molecular mechanism of KS. Wolters Kluwer Health 2019-07-05 /pmc/articles/PMC6635252/ /pubmed/31277155 http://dx.doi.org/10.1097/MD.0000000000016277 Text en Copyright © 2019 the Author(s). Published by Wolters Kluwer Health, Inc. http://creativecommons.org/licenses/by-nc-nd/4.0 This is an open access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND), where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal. http://creativecommons.org/licenses/by-nc-nd/4.0
spellingShingle Research Article
Gong, Hai-Bo
Wu, Xiu-Juan
Pu, Xiong-Ming
Kang, Xiao-Jing
Bioinformatics analysis of key biomarkers and pathways in KSHV infected endothelial cells
title Bioinformatics analysis of key biomarkers and pathways in KSHV infected endothelial cells
title_full Bioinformatics analysis of key biomarkers and pathways in KSHV infected endothelial cells
title_fullStr Bioinformatics analysis of key biomarkers and pathways in KSHV infected endothelial cells
title_full_unstemmed Bioinformatics analysis of key biomarkers and pathways in KSHV infected endothelial cells
title_short Bioinformatics analysis of key biomarkers and pathways in KSHV infected endothelial cells
title_sort bioinformatics analysis of key biomarkers and pathways in kshv infected endothelial cells
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6635252/
https://www.ncbi.nlm.nih.gov/pubmed/31277155
http://dx.doi.org/10.1097/MD.0000000000016277
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