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Screening of disorders associated with osteosarcoma by integrated network analysis

Osteosarcoma is a common malignant bone tumor in children and adolescents under the age of 20. However, research on the pathogenesis and treatment of osteosarcoma is still insufficient. In the present study, based on gene-phenotype correlation network, an analysis was performed to screen disorders r...

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Autores principales: Dou, Yongfeng, Zhu, Kai, Sun, Zhaozhong, Geng, Xiaopeng, Fang, Qingmin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Portland Press Ltd. 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6527930/
https://www.ncbi.nlm.nih.gov/pubmed/30936265
http://dx.doi.org/10.1042/BSR20190235
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author Dou, Yongfeng
Zhu, Kai
Sun, Zhaozhong
Geng, Xiaopeng
Fang, Qingmin
author_facet Dou, Yongfeng
Zhu, Kai
Sun, Zhaozhong
Geng, Xiaopeng
Fang, Qingmin
author_sort Dou, Yongfeng
collection PubMed
description Osteosarcoma is a common malignant bone tumor in children and adolescents under the age of 20. However, research on the pathogenesis and treatment of osteosarcoma is still insufficient. In the present study, based on gene-phenotype correlation network, an analysis was performed to screen disorders related to osteosarcoma. First, we analyzed the differential expression of osteosarcoma in two groups according to different types of osteosarcoma and screened the differentially expressed genes (DEGs) related to osteosarcoma. Further, these DEG coexpression modules were obtained. Finally, we identified a series of regulatory factors, such as endogenous genes, transcription factors (TFs), and ncRNAs, which have potential regulatory effects on osteosarcoma, based on the prediction analysis of related network of gene phenotypes. A total of 3767 DEGs of osteosarcoma were identified and clustered them into 20 osteosarcoma-related dysfunction modules. And there were 38 endogenous genes (including ARF1, HSP90AB1, and TUBA1B), 53 TFs (including E2F1, NFKB1, and EGR1), and 858 ncRNAs (including MALAT1, miR-590-3p, and TUG1) were considered as key regulators of osteosarcoma through a series of function enrichment analysis and network analysis. Based on the results of the present study, we can show a new way for biologists and pharmacists to reveal the potential molecular mechanism of osteosarcoma typing, and provide valuable reference for different follow-up treatment options.
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spelling pubmed-65279302019-05-30 Screening of disorders associated with osteosarcoma by integrated network analysis Dou, Yongfeng Zhu, Kai Sun, Zhaozhong Geng, Xiaopeng Fang, Qingmin Biosci Rep Research Articles Osteosarcoma is a common malignant bone tumor in children and adolescents under the age of 20. However, research on the pathogenesis and treatment of osteosarcoma is still insufficient. In the present study, based on gene-phenotype correlation network, an analysis was performed to screen disorders related to osteosarcoma. First, we analyzed the differential expression of osteosarcoma in two groups according to different types of osteosarcoma and screened the differentially expressed genes (DEGs) related to osteosarcoma. Further, these DEG coexpression modules were obtained. Finally, we identified a series of regulatory factors, such as endogenous genes, transcription factors (TFs), and ncRNAs, which have potential regulatory effects on osteosarcoma, based on the prediction analysis of related network of gene phenotypes. A total of 3767 DEGs of osteosarcoma were identified and clustered them into 20 osteosarcoma-related dysfunction modules. And there were 38 endogenous genes (including ARF1, HSP90AB1, and TUBA1B), 53 TFs (including E2F1, NFKB1, and EGR1), and 858 ncRNAs (including MALAT1, miR-590-3p, and TUG1) were considered as key regulators of osteosarcoma through a series of function enrichment analysis and network analysis. Based on the results of the present study, we can show a new way for biologists and pharmacists to reveal the potential molecular mechanism of osteosarcoma typing, and provide valuable reference for different follow-up treatment options. Portland Press Ltd. 2019-05-21 /pmc/articles/PMC6527930/ /pubmed/30936265 http://dx.doi.org/10.1042/BSR20190235 Text en © 2019 The Author(s). http://creativecommons.org/licenses/by/4.0/This is an open access article published by Portland Press Limited on behalf of the Biochemical Society and distributed under the Creative Commons Attribution License 4.0 (CC BY) (http://creativecommons.org/licenses/by/4.0/) .
spellingShingle Research Articles
Dou, Yongfeng
Zhu, Kai
Sun, Zhaozhong
Geng, Xiaopeng
Fang, Qingmin
Screening of disorders associated with osteosarcoma by integrated network analysis
title Screening of disorders associated with osteosarcoma by integrated network analysis
title_full Screening of disorders associated with osteosarcoma by integrated network analysis
title_fullStr Screening of disorders associated with osteosarcoma by integrated network analysis
title_full_unstemmed Screening of disorders associated with osteosarcoma by integrated network analysis
title_short Screening of disorders associated with osteosarcoma by integrated network analysis
title_sort screening of disorders associated with osteosarcoma by integrated network analysis
topic Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6527930/
https://www.ncbi.nlm.nih.gov/pubmed/30936265
http://dx.doi.org/10.1042/BSR20190235
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