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Integrated Analysis To Identify Molecular Biomarkers Of High-Grade Serous Ovarian Cancer
PURPOSE: Ovarian cancer is the leading cause of gynecologic cancer-related death worldwide. Early diagnosis of ovarian cancer can significantly improve patient prognosis. Hence, there is an urgent need to identify key diagnostic and prognostic biomarkers specific for ovarian cancer. Because high-gra...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Dove
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6877452/ https://www.ncbi.nlm.nih.gov/pubmed/31819501 http://dx.doi.org/10.2147/OTT.S228678 |
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author | Si, Manfei Zhang, Junji Cao, Jianzhong Xie, Zhibo Shu, Shan Zhu, Yapei Lang, Jinghe |
author_facet | Si, Manfei Zhang, Junji Cao, Jianzhong Xie, Zhibo Shu, Shan Zhu, Yapei Lang, Jinghe |
author_sort | Si, Manfei |
collection | PubMed |
description | PURPOSE: Ovarian cancer is the leading cause of gynecologic cancer-related death worldwide. Early diagnosis of ovarian cancer can significantly improve patient prognosis. Hence, there is an urgent need to identify key diagnostic and prognostic biomarkers specific for ovarian cancer. Because high-grade serous ovarian cancer (HGSOC) is the most common type of ovarian cancer and accounts for the majority of deaths, we identified potential biomarkers for the early diagnosis and prognosis of HGSOC. METHODS: Six datasets (GSE14001, GSE18520, GSE26712, GSE27651, GSE40595, and GSE54388) were downloaded from the Gene Expression Omnibus database for analysis. Differentially expressed genes (DEGs) between HGSOC and normal ovarian surface epithelium samples were screened via integrated analysis. Hub genes were identified by analyzing protein–protein interaction (PPI) network data. The online Kaplan-Meier plotter was utilized to evaluate the prognostic roles of these hub genes. The expression of these hub genes was confirmed with Oncomine datasets and validated by quantitative real-time PCR and Western blotting. RESULTS: A total of 103 DEGs in patients with HGSOC—28 upregulated genes and 75 downregulated genes—were successfully screened. Enrichment analyses revealed that the upregulated genes were enriched in cell division and cell proliferation and that the downregulated genes mainly participated in the Wnt signaling pathway and various metabolic processes. Ten hub genes were associated with HGSOC pathogenesis. Seven overexpressed hub genes were partitioned into module 1 of the PPI network, which was enriched in the cell cycle and DNA replication pathways. Survival analysis revealed that MELK, CEP55 and KDR expression levels were significantly correlated with the overall survival of HGSOC patients (P < 0.05). The RNA and protein expression levels of these hub genes were validated experimentally. CONCLUSION: Based on an integrated analysis, we propose the further investigation of MELK, CEP55 and KDR as promising diagnostic and prognostic biomarkers of HGSOC. |
format | Online Article Text |
id | pubmed-6877452 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Dove |
record_format | MEDLINE/PubMed |
spelling | pubmed-68774522019-12-09 Integrated Analysis To Identify Molecular Biomarkers Of High-Grade Serous Ovarian Cancer Si, Manfei Zhang, Junji Cao, Jianzhong Xie, Zhibo Shu, Shan Zhu, Yapei Lang, Jinghe Onco Targets Ther Original Research PURPOSE: Ovarian cancer is the leading cause of gynecologic cancer-related death worldwide. Early diagnosis of ovarian cancer can significantly improve patient prognosis. Hence, there is an urgent need to identify key diagnostic and prognostic biomarkers specific for ovarian cancer. Because high-grade serous ovarian cancer (HGSOC) is the most common type of ovarian cancer and accounts for the majority of deaths, we identified potential biomarkers for the early diagnosis and prognosis of HGSOC. METHODS: Six datasets (GSE14001, GSE18520, GSE26712, GSE27651, GSE40595, and GSE54388) were downloaded from the Gene Expression Omnibus database for analysis. Differentially expressed genes (DEGs) between HGSOC and normal ovarian surface epithelium samples were screened via integrated analysis. Hub genes were identified by analyzing protein–protein interaction (PPI) network data. The online Kaplan-Meier plotter was utilized to evaluate the prognostic roles of these hub genes. The expression of these hub genes was confirmed with Oncomine datasets and validated by quantitative real-time PCR and Western blotting. RESULTS: A total of 103 DEGs in patients with HGSOC—28 upregulated genes and 75 downregulated genes—were successfully screened. Enrichment analyses revealed that the upregulated genes were enriched in cell division and cell proliferation and that the downregulated genes mainly participated in the Wnt signaling pathway and various metabolic processes. Ten hub genes were associated with HGSOC pathogenesis. Seven overexpressed hub genes were partitioned into module 1 of the PPI network, which was enriched in the cell cycle and DNA replication pathways. Survival analysis revealed that MELK, CEP55 and KDR expression levels were significantly correlated with the overall survival of HGSOC patients (P < 0.05). The RNA and protein expression levels of these hub genes were validated experimentally. CONCLUSION: Based on an integrated analysis, we propose the further investigation of MELK, CEP55 and KDR as promising diagnostic and prognostic biomarkers of HGSOC. Dove 2019-11-21 /pmc/articles/PMC6877452/ /pubmed/31819501 http://dx.doi.org/10.2147/OTT.S228678 Text en © 2019 Si et al. http://creativecommons.org/licenses/by-nc/3.0/ This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms (https://www.dovepress.com/terms.php). |
spellingShingle | Original Research Si, Manfei Zhang, Junji Cao, Jianzhong Xie, Zhibo Shu, Shan Zhu, Yapei Lang, Jinghe Integrated Analysis To Identify Molecular Biomarkers Of High-Grade Serous Ovarian Cancer |
title | Integrated Analysis To Identify Molecular Biomarkers Of High-Grade Serous Ovarian Cancer |
title_full | Integrated Analysis To Identify Molecular Biomarkers Of High-Grade Serous Ovarian Cancer |
title_fullStr | Integrated Analysis To Identify Molecular Biomarkers Of High-Grade Serous Ovarian Cancer |
title_full_unstemmed | Integrated Analysis To Identify Molecular Biomarkers Of High-Grade Serous Ovarian Cancer |
title_short | Integrated Analysis To Identify Molecular Biomarkers Of High-Grade Serous Ovarian Cancer |
title_sort | integrated analysis to identify molecular biomarkers of high-grade serous ovarian cancer |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6877452/ https://www.ncbi.nlm.nih.gov/pubmed/31819501 http://dx.doi.org/10.2147/OTT.S228678 |
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