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Integrated Analysis To Identify Molecular Biomarkers Of High-Grade Serous Ovarian Cancer.
Onco Targets Ther 2019; 12:10057-10075OT

Abstract

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.

Authors+Show Affiliations

Department of Obstetrics and Gynecology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, People's Republic of China.Department of Obstetrics and Gynecology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, People's Republic of China.Department of General Surgery, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, People's Republic of China.Department of Vascular Surgery, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, People's Republic of China.Department of Obstetrics and Gynecology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, People's Republic of China.Department of Obstetrics and Gynecology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, People's Republic of China.Department of Obstetrics and Gynecology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, People's Republic of China.

Pub Type(s)

Journal Article

Language

eng

PubMed ID

31819501

Citation

Si, Manfei, et al. "Integrated Analysis to Identify Molecular Biomarkers of High-Grade Serous Ovarian Cancer." OncoTargets and Therapy, vol. 12, 2019, pp. 10057-10075.
Si M, Zhang J, Cao J, et al. Integrated Analysis To Identify Molecular Biomarkers Of High-Grade Serous Ovarian Cancer. Onco Targets Ther. 2019;12:10057-10075.
Si, M., Zhang, J., Cao, J., Xie, Z., Shu, S., Zhu, Y., & Lang, J. (2019). Integrated Analysis To Identify Molecular Biomarkers Of High-Grade Serous Ovarian Cancer. OncoTargets and Therapy, 12, pp. 10057-10075. doi:10.2147/OTT.S228678.
Si M, et al. Integrated Analysis to Identify Molecular Biomarkers of High-Grade Serous Ovarian Cancer. Onco Targets Ther. 2019;12:10057-10075. PubMed PMID: 31819501.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Integrated Analysis To Identify Molecular Biomarkers Of High-Grade Serous Ovarian Cancer. AU - Si,Manfei, AU - Zhang,Junji, AU - Cao,Jianzhong, AU - Xie,Zhibo, AU - Shu,Shan, AU - Zhu,Yapei, AU - Lang,Jinghe, Y1 - 2019/11/21/ PY - 2019/08/26/received PY - 2019/10/30/accepted PY - 2019/12/11/entrez PY - 2019/12/11/pubmed PY - 2019/12/11/medline KW - bioinformatic analysis KW - biomarker KW - differentially expressed genes KW - high-grade serous ovarian cancer KW - integrated analysis KW - survival SP - 10057 EP - 10075 JF - OncoTargets and therapy JO - Onco Targets Ther VL - 12 N2 - 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. SN - 1178-6930 UR - https://www.unboundmedicine.com/medline/citation/31819501/Integrated_Analysis_To_Identify_Molecular_Biomarkers_Of_High_Grade_Serous_Ovarian_Cancer_ L2 - https://dx.doi.org/10.2147/OTT.S228678 DB - PRIME DP - Unbound Medicine ER -