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Protein-protein interaction analysis to identify biomarker networks for endometriosis
The identification of biomarkers and their interaction network involved in the processes of endometriosis is a critical step in understanding the underlying mechanisms of the disease. The aim of the present study was to construct biomarker networks of endometriosis that integrated human protein-prot...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
D.A. Spandidos
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5704338/ https://www.ncbi.nlm.nih.gov/pubmed/29201163 http://dx.doi.org/10.3892/etm.2017.5185 |
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author | Xiao, Hong Yang, Lihua Liu, Jianjun Jiao, Yang Lu, Lin Zhao, Hongbo |
author_facet | Xiao, Hong Yang, Lihua Liu, Jianjun Jiao, Yang Lu, Lin Zhao, Hongbo |
author_sort | Xiao, Hong |
collection | PubMed |
description | The identification of biomarkers and their interaction network involved in the processes of endometriosis is a critical step in understanding the underlying mechanisms of the disease. The aim of the present study was to construct biomarker networks of endometriosis that integrated human protein-protein interactions and known disease-causing genes. Endometriosis-associated genes were extracted from Genotator and DisGeNet and biomarker network and pathway analyses were constructed using atBioNet. Of 100 input genes, 96 were strongly mapped to six major modules. The majority of the pathways in the first module were associated with the proliferation of cancer cells, the enriched pathways in module B were associated with the immune system and infectious diseases, module C included pathways related to immune and metastasis, the enriched pathways in module D were associated with inflammatory processes, and the majority of the pathways in module E were related to replication and repair. The present approach identified known and potential biomarkers in endometriosis. The identified biomarker networks are highly enriched in biological pathways associated with endometriosis, which may provide further insight into the molecular mechanisms underlying endometriosis. |
format | Online Article Text |
id | pubmed-5704338 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | D.A. Spandidos |
record_format | MEDLINE/PubMed |
spelling | pubmed-57043382017-11-30 Protein-protein interaction analysis to identify biomarker networks for endometriosis Xiao, Hong Yang, Lihua Liu, Jianjun Jiao, Yang Lu, Lin Zhao, Hongbo Exp Ther Med Articles The identification of biomarkers and their interaction network involved in the processes of endometriosis is a critical step in understanding the underlying mechanisms of the disease. The aim of the present study was to construct biomarker networks of endometriosis that integrated human protein-protein interactions and known disease-causing genes. Endometriosis-associated genes were extracted from Genotator and DisGeNet and biomarker network and pathway analyses were constructed using atBioNet. Of 100 input genes, 96 were strongly mapped to six major modules. The majority of the pathways in the first module were associated with the proliferation of cancer cells, the enriched pathways in module B were associated with the immune system and infectious diseases, module C included pathways related to immune and metastasis, the enriched pathways in module D were associated with inflammatory processes, and the majority of the pathways in module E were related to replication and repair. The present approach identified known and potential biomarkers in endometriosis. The identified biomarker networks are highly enriched in biological pathways associated with endometriosis, which may provide further insight into the molecular mechanisms underlying endometriosis. D.A. Spandidos 2017-11 2017-09-22 /pmc/articles/PMC5704338/ /pubmed/29201163 http://dx.doi.org/10.3892/etm.2017.5185 Text en Copyright: © Xiao 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 Xiao, Hong Yang, Lihua Liu, Jianjun Jiao, Yang Lu, Lin Zhao, Hongbo Protein-protein interaction analysis to identify biomarker networks for endometriosis |
title | Protein-protein interaction analysis to identify biomarker networks for endometriosis |
title_full | Protein-protein interaction analysis to identify biomarker networks for endometriosis |
title_fullStr | Protein-protein interaction analysis to identify biomarker networks for endometriosis |
title_full_unstemmed | Protein-protein interaction analysis to identify biomarker networks for endometriosis |
title_short | Protein-protein interaction analysis to identify biomarker networks for endometriosis |
title_sort | protein-protein interaction analysis to identify biomarker networks for endometriosis |
topic | Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5704338/ https://www.ncbi.nlm.nih.gov/pubmed/29201163 http://dx.doi.org/10.3892/etm.2017.5185 |
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