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Bioinformatics prediction and analysis of hub genes and pathways of three types of gynecological cancer

Cervical, endometrial and vulvar cancer are three common types of gynecological tumor that threaten the health of females worldwide. Since their underlying mechanisms and associations remain unclear, a comprehensive and systematic bioinformatics analysis is required. The present study downloaded GSE...

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Autores principales: Liu, Yanyan, Yi, Yuexiong, Wu, Wanrong, Wu, Kejia, Zhang, Wei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: D.A. Spandidos 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6539991/
https://www.ncbi.nlm.nih.gov/pubmed/31289534
http://dx.doi.org/10.3892/ol.2019.10371
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author Liu, Yanyan
Yi, Yuexiong
Wu, Wanrong
Wu, Kejia
Zhang, Wei
author_facet Liu, Yanyan
Yi, Yuexiong
Wu, Wanrong
Wu, Kejia
Zhang, Wei
author_sort Liu, Yanyan
collection PubMed
description Cervical, endometrial and vulvar cancer are three common types of gynecological tumor that threaten the health of females worldwide. Since their underlying mechanisms and associations remain unclear, a comprehensive and systematic bioinformatics analysis is required. The present study downloaded GSE63678 from the GEO database and then performed functional enrichment analyses, including gene ontology and pathway analysis. To further investigate the molecular mechanisms underlying the three types of gynecological cancer, protein-protein interaction (PPI) analysis was performed. A biological network was generated with the guidance of the Kyoto Encyclopedia of Genes and Genomes database and was presented in Cytoscape. A total of 1,219 DEGs were identified for the three types of cancer, and 25 hub genes were revealed. Pathway analysis and the PPI network indicated that four main types of pathway participate in the mechanism of gynecological cancer, including viral infections and cancer formation, tumorigenesis and development, signal transduction, and endocrinology and metabolism. A preliminary gynecological cancer biological network was constructed. Notably, following all analysis, the phosphoinositide 3-kinase (PI3K)/Akt pathway was identified as a potential biomarker pathway. Seven pivotal hub genes (CCNA2, CDK1, CCND1, FGF2, IGF1, BCL2 and VEGFA) of the three gynecological cancer types were proposed. The seven hub genes may serve as targets in gynecological cancer for prevention and early intervention. The PI3K/Akt pathway was identified as a critical biomarker of the three types of gynecological cancer, which may serve a role in the pathogenesis. In summary, the present study provided evidence that could support the treatment of gynecologic tumors in the future.
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spelling pubmed-65399912019-07-09 Bioinformatics prediction and analysis of hub genes and pathways of three types of gynecological cancer Liu, Yanyan Yi, Yuexiong Wu, Wanrong Wu, Kejia Zhang, Wei Oncol Lett Articles Cervical, endometrial and vulvar cancer are three common types of gynecological tumor that threaten the health of females worldwide. Since their underlying mechanisms and associations remain unclear, a comprehensive and systematic bioinformatics analysis is required. The present study downloaded GSE63678 from the GEO database and then performed functional enrichment analyses, including gene ontology and pathway analysis. To further investigate the molecular mechanisms underlying the three types of gynecological cancer, protein-protein interaction (PPI) analysis was performed. A biological network was generated with the guidance of the Kyoto Encyclopedia of Genes and Genomes database and was presented in Cytoscape. A total of 1,219 DEGs were identified for the three types of cancer, and 25 hub genes were revealed. Pathway analysis and the PPI network indicated that four main types of pathway participate in the mechanism of gynecological cancer, including viral infections and cancer formation, tumorigenesis and development, signal transduction, and endocrinology and metabolism. A preliminary gynecological cancer biological network was constructed. Notably, following all analysis, the phosphoinositide 3-kinase (PI3K)/Akt pathway was identified as a potential biomarker pathway. Seven pivotal hub genes (CCNA2, CDK1, CCND1, FGF2, IGF1, BCL2 and VEGFA) of the three gynecological cancer types were proposed. The seven hub genes may serve as targets in gynecological cancer for prevention and early intervention. The PI3K/Akt pathway was identified as a critical biomarker of the three types of gynecological cancer, which may serve a role in the pathogenesis. In summary, the present study provided evidence that could support the treatment of gynecologic tumors in the future. D.A. Spandidos 2019-07 2019-05-17 /pmc/articles/PMC6539991/ /pubmed/31289534 http://dx.doi.org/10.3892/ol.2019.10371 Text en Copyright: © Liu 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
Liu, Yanyan
Yi, Yuexiong
Wu, Wanrong
Wu, Kejia
Zhang, Wei
Bioinformatics prediction and analysis of hub genes and pathways of three types of gynecological cancer
title Bioinformatics prediction and analysis of hub genes and pathways of three types of gynecological cancer
title_full Bioinformatics prediction and analysis of hub genes and pathways of three types of gynecological cancer
title_fullStr Bioinformatics prediction and analysis of hub genes and pathways of three types of gynecological cancer
title_full_unstemmed Bioinformatics prediction and analysis of hub genes and pathways of three types of gynecological cancer
title_short Bioinformatics prediction and analysis of hub genes and pathways of three types of gynecological cancer
title_sort bioinformatics prediction and analysis of hub genes and pathways of three types of gynecological cancer
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6539991/
https://www.ncbi.nlm.nih.gov/pubmed/31289534
http://dx.doi.org/10.3892/ol.2019.10371
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