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Analyzing the disease module associated with osteosarcoma via a network- and pathway-based approach
Osteosarcoma is the most common type of primary malignant bone tumor observed in children and adolescents. The aim of the present study was to identify an osteosarcoma-related gene module (OSM) by looking for a dense module following the integration of signals from genome-wide association studies (G...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
D.A. Spandidos
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6122582/ https://www.ncbi.nlm.nih.gov/pubmed/30210606 http://dx.doi.org/10.3892/etm.2018.6506 |
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author | Zhang, Yi Yang, Fei |
author_facet | Zhang, Yi Yang, Fei |
author_sort | Zhang, Yi |
collection | PubMed |
description | Osteosarcoma is the most common type of primary malignant bone tumor observed in children and adolescents. The aim of the present study was to identify an osteosarcoma-related gene module (OSM) by looking for a dense module following the integration of signals from genome-wide association studies (GWAS) into the human protein-protein interaction (PPI) network. A dataset of somatic mutations in osteosarcoma was obtained from the dbGaP database and their testing P-values were incorporated into the PPI network from a recent study using the dmGWAS bioconductor package. An OSM containing 201 genes (OS genes) and 268 interactions, which were closely associated with immune response, intracellular signal transduction and cell activity was identified. Topological analysis of the OSM identified 11 genes, including APP, APPBP2, ATXN1, HSP90B1, IKZF1, KRTAP10-1, PAK1, PDPK1, SMAD4, SUZ12 and TP53 as potential diagnostic biomarkers for osteosarcoma. The overall survival analysis of osteosarcoma for those 11 genes based on a dataset from the Cancer Genome Atlas, identified APP, HSP90B1, SUZ12 and IKZF1 as osteosarcoma survival-related genes. The results of the present study should be helpful in understanding the diagnosis and treatment of osteosarcoma and its underlying mechanisms. In addition, the methodology used in the present study may be suitable for the analysis of other types of disease. |
format | Online Article Text |
id | pubmed-6122582 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | D.A. Spandidos |
record_format | MEDLINE/PubMed |
spelling | pubmed-61225822018-09-12 Analyzing the disease module associated with osteosarcoma via a network- and pathway-based approach Zhang, Yi Yang, Fei Exp Ther Med Articles Osteosarcoma is the most common type of primary malignant bone tumor observed in children and adolescents. The aim of the present study was to identify an osteosarcoma-related gene module (OSM) by looking for a dense module following the integration of signals from genome-wide association studies (GWAS) into the human protein-protein interaction (PPI) network. A dataset of somatic mutations in osteosarcoma was obtained from the dbGaP database and their testing P-values were incorporated into the PPI network from a recent study using the dmGWAS bioconductor package. An OSM containing 201 genes (OS genes) and 268 interactions, which were closely associated with immune response, intracellular signal transduction and cell activity was identified. Topological analysis of the OSM identified 11 genes, including APP, APPBP2, ATXN1, HSP90B1, IKZF1, KRTAP10-1, PAK1, PDPK1, SMAD4, SUZ12 and TP53 as potential diagnostic biomarkers for osteosarcoma. The overall survival analysis of osteosarcoma for those 11 genes based on a dataset from the Cancer Genome Atlas, identified APP, HSP90B1, SUZ12 and IKZF1 as osteosarcoma survival-related genes. The results of the present study should be helpful in understanding the diagnosis and treatment of osteosarcoma and its underlying mechanisms. In addition, the methodology used in the present study may be suitable for the analysis of other types of disease. D.A. Spandidos 2018-09 2018-07-23 /pmc/articles/PMC6122582/ /pubmed/30210606 http://dx.doi.org/10.3892/etm.2018.6506 Text en Copyright: © Zhang 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 Zhang, Yi Yang, Fei Analyzing the disease module associated with osteosarcoma via a network- and pathway-based approach |
title | Analyzing the disease module associated with osteosarcoma via a network- and pathway-based approach |
title_full | Analyzing the disease module associated with osteosarcoma via a network- and pathway-based approach |
title_fullStr | Analyzing the disease module associated with osteosarcoma via a network- and pathway-based approach |
title_full_unstemmed | Analyzing the disease module associated with osteosarcoma via a network- and pathway-based approach |
title_short | Analyzing the disease module associated with osteosarcoma via a network- and pathway-based approach |
title_sort | analyzing the disease module associated with osteosarcoma via a network- and pathway-based approach |
topic | Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6122582/ https://www.ncbi.nlm.nih.gov/pubmed/30210606 http://dx.doi.org/10.3892/etm.2018.6506 |
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