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Identification of core genes in ovarian cancer by an integrative meta-analysis
BACKGROUND: Epithelial ovarian cancer is one of the most severe public health threats in women. Since it is still challenging to screen in early stages, identification of core genes that play an essential role in epithelial ovarian cancer initiation and progression is of vital importance. RESULTS:...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6240943/ https://www.ncbi.nlm.nih.gov/pubmed/30453999 http://dx.doi.org/10.1186/s13048-018-0467-z |
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author | Li, Wenyu Liu, Zheran Liang, Bowen Chen, Siyang Zhang, Xinping Tong, Xiaoqin Lou, Weiming Le, Lulu Tang, Xiaoli Fu, Fen |
author_facet | Li, Wenyu Liu, Zheran Liang, Bowen Chen, Siyang Zhang, Xinping Tong, Xiaoqin Lou, Weiming Le, Lulu Tang, Xiaoli Fu, Fen |
author_sort | Li, Wenyu |
collection | PubMed |
description | BACKGROUND: Epithelial ovarian cancer is one of the most severe public health threats in women. Since it is still challenging to screen in early stages, identification of core genes that play an essential role in epithelial ovarian cancer initiation and progression is of vital importance. RESULTS: Seven gene expression datasets (GSE6008, GSE18520, GSE26712, GSE27651, GSE29450, GSE36668, and GSE52037) containing 396 ovarian cancer samples and 54 healthy control samples were analyzed to identify the significant differentially expressed genes (DEGs). We identified 563 DEGs, including 245 upregulated and 318 downregulated genes. Enrichment analysis based on the gene ontology (GO) functions and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways showed that the upregulated genes were significantly enriched in cell division, cell cycle, tight junction, and oocyte meiosis, while the downregulated genes were associated with response to endogenous stimuli, complement and coagulation cascades, the cGMP-PKG signaling pathway, and serotonergic synapse. Two significant modules were identified from a protein-protein interaction network by using the Molecular Complex Detection (MCODE) software. Moreover, 12 hub genes with degree centrality more than 29 were selected from the protein-protein interaction network, and module analysis illustrated that these 12 hub genes belong to module 1. Furthermore, Kaplan-Meier analysis for overall survival indicated that 9 of these hub genes was correlated with poor prognosis of epithelial ovarian cancer patients. CONCLUSION: The present study systematically validates the results of previous studies and fills the gap regarding a large-scale meta-analysis in the field of epithelial ovarian cancer. Furthermore, hub genes that could be used as a novel biomarkers to facilitate early diagnosis and therapeutic approaches are evaluated, providing compelling evidence for future genomic-based individualized treatment of epithelial ovarian cancer. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13048-018-0467-z) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-6240943 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-62409432018-11-23 Identification of core genes in ovarian cancer by an integrative meta-analysis Li, Wenyu Liu, Zheran Liang, Bowen Chen, Siyang Zhang, Xinping Tong, Xiaoqin Lou, Weiming Le, Lulu Tang, Xiaoli Fu, Fen J Ovarian Res Research BACKGROUND: Epithelial ovarian cancer is one of the most severe public health threats in women. Since it is still challenging to screen in early stages, identification of core genes that play an essential role in epithelial ovarian cancer initiation and progression is of vital importance. RESULTS: Seven gene expression datasets (GSE6008, GSE18520, GSE26712, GSE27651, GSE29450, GSE36668, and GSE52037) containing 396 ovarian cancer samples and 54 healthy control samples were analyzed to identify the significant differentially expressed genes (DEGs). We identified 563 DEGs, including 245 upregulated and 318 downregulated genes. Enrichment analysis based on the gene ontology (GO) functions and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways showed that the upregulated genes were significantly enriched in cell division, cell cycle, tight junction, and oocyte meiosis, while the downregulated genes were associated with response to endogenous stimuli, complement and coagulation cascades, the cGMP-PKG signaling pathway, and serotonergic synapse. Two significant modules were identified from a protein-protein interaction network by using the Molecular Complex Detection (MCODE) software. Moreover, 12 hub genes with degree centrality more than 29 were selected from the protein-protein interaction network, and module analysis illustrated that these 12 hub genes belong to module 1. Furthermore, Kaplan-Meier analysis for overall survival indicated that 9 of these hub genes was correlated with poor prognosis of epithelial ovarian cancer patients. CONCLUSION: The present study systematically validates the results of previous studies and fills the gap regarding a large-scale meta-analysis in the field of epithelial ovarian cancer. Furthermore, hub genes that could be used as a novel biomarkers to facilitate early diagnosis and therapeutic approaches are evaluated, providing compelling evidence for future genomic-based individualized treatment of epithelial ovarian cancer. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13048-018-0467-z) contains supplementary material, which is available to authorized users. BioMed Central 2018-11-19 /pmc/articles/PMC6240943/ /pubmed/30453999 http://dx.doi.org/10.1186/s13048-018-0467-z Text en © The Author(s). 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Li, Wenyu Liu, Zheran Liang, Bowen Chen, Siyang Zhang, Xinping Tong, Xiaoqin Lou, Weiming Le, Lulu Tang, Xiaoli Fu, Fen Identification of core genes in ovarian cancer by an integrative meta-analysis |
title | Identification of core genes in ovarian cancer by an integrative meta-analysis |
title_full | Identification of core genes in ovarian cancer by an integrative meta-analysis |
title_fullStr | Identification of core genes in ovarian cancer by an integrative meta-analysis |
title_full_unstemmed | Identification of core genes in ovarian cancer by an integrative meta-analysis |
title_short | Identification of core genes in ovarian cancer by an integrative meta-analysis |
title_sort | identification of core genes in ovarian cancer by an integrative meta-analysis |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6240943/ https://www.ncbi.nlm.nih.gov/pubmed/30453999 http://dx.doi.org/10.1186/s13048-018-0467-z |
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