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Identification of Differentially Expressed Genes (DEGs) Relevant to Prognosis of Ovarian Cancer by Use of Integrated Bioinformatics Analysis and Validation by Immunohistochemistry Assay

BACKGROUND: The aim of this study was to investigate the differentially expressed genes (DEGs) relevant to prognosis of ovarian cancer by use of integrated bioinformatics analysis. MATERIAL/METHODS: The DEGs between normal ovariy tissue and ovarian cancer tissue were screened in GSE54388, GSE14407,...

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Autores principales: Zhang, Limin, Sun, Lijun, Zhang, Bin, Chen, Lihong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: International Scientific Literature, Inc. 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6941780/
https://www.ncbi.nlm.nih.gov/pubmed/31871312
http://dx.doi.org/10.12659/MSM.921661
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author Zhang, Limin
Sun, Lijun
Zhang, Bin
Chen, Lihong
author_facet Zhang, Limin
Sun, Lijun
Zhang, Bin
Chen, Lihong
author_sort Zhang, Limin
collection PubMed
description BACKGROUND: The aim of this study was to investigate the differentially expressed genes (DEGs) relevant to prognosis of ovarian cancer by use of integrated bioinformatics analysis. MATERIAL/METHODS: The DEGs between normal ovariy tissue and ovarian cancer tissue were screened in GSE54388, GSE14407, and GSE18520 datasets and the overlapping DEGs were then indentified. GO and KEEG enrichment were performed to analyze the biological functions and pathways of the DEGs. A protein–protein interaction (PPI) network of the identified DEGs was constructed using the STRING database. Differences in prognosis between low and high expression of the hub DEGs were also evaluated using the Kaplan-Meier Plotter database. Protein expression of 2 hub genes – BUB1B and KIF201A – was assessed by immunohistochemistry assay and evaluated with the patient’s clinical pathology characteristics. RESULTS: We identified 361 DEGs, mainly involving oncogene-induced cell senescence, cyclin B1-CDK1 complex, protein kinase A catalytic subunit binding, cell cycle, and p53 signaling pathway. Ten hub genes were identified from among the 361 DEGs. The overall survival (OS) and progression-free survival (PFS) of these 10 hub genes were evaluated in the Kaplan-Meier-plotter database. Three (BUB1B, KIF11, and KIF20A) of the 10 hub genes were found to be correlated with ovarian cancer OS and PFS. BUB1B expression level was correlated with ovarian FIGO stage (p<0.05) and tumor differentiation (p<0.05). For KIF20A, the expression level was correlated with FIGO stage (p<0.05) and intraperitoneal metastasis (p<0.05). CONCLUSIONS: DEGs can participate in ovarian cancer development and can be used as biomarkers for prognosis. Patients with upregulated BUB1B, KIF11, and KIF20A tend to have worse overall survival and disease-free survival compared with patients who have low expression.
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spelling pubmed-69417802020-01-10 Identification of Differentially Expressed Genes (DEGs) Relevant to Prognosis of Ovarian Cancer by Use of Integrated Bioinformatics Analysis and Validation by Immunohistochemistry Assay Zhang, Limin Sun, Lijun Zhang, Bin Chen, Lihong Med Sci Monit Clinical Research BACKGROUND: The aim of this study was to investigate the differentially expressed genes (DEGs) relevant to prognosis of ovarian cancer by use of integrated bioinformatics analysis. MATERIAL/METHODS: The DEGs between normal ovariy tissue and ovarian cancer tissue were screened in GSE54388, GSE14407, and GSE18520 datasets and the overlapping DEGs were then indentified. GO and KEEG enrichment were performed to analyze the biological functions and pathways of the DEGs. A protein–protein interaction (PPI) network of the identified DEGs was constructed using the STRING database. Differences in prognosis between low and high expression of the hub DEGs were also evaluated using the Kaplan-Meier Plotter database. Protein expression of 2 hub genes – BUB1B and KIF201A – was assessed by immunohistochemistry assay and evaluated with the patient’s clinical pathology characteristics. RESULTS: We identified 361 DEGs, mainly involving oncogene-induced cell senescence, cyclin B1-CDK1 complex, protein kinase A catalytic subunit binding, cell cycle, and p53 signaling pathway. Ten hub genes were identified from among the 361 DEGs. The overall survival (OS) and progression-free survival (PFS) of these 10 hub genes were evaluated in the Kaplan-Meier-plotter database. Three (BUB1B, KIF11, and KIF20A) of the 10 hub genes were found to be correlated with ovarian cancer OS and PFS. BUB1B expression level was correlated with ovarian FIGO stage (p<0.05) and tumor differentiation (p<0.05). For KIF20A, the expression level was correlated with FIGO stage (p<0.05) and intraperitoneal metastasis (p<0.05). CONCLUSIONS: DEGs can participate in ovarian cancer development and can be used as biomarkers for prognosis. Patients with upregulated BUB1B, KIF11, and KIF20A tend to have worse overall survival and disease-free survival compared with patients who have low expression. International Scientific Literature, Inc. 2019-12-24 /pmc/articles/PMC6941780/ /pubmed/31871312 http://dx.doi.org/10.12659/MSM.921661 Text en © Med Sci Monit, 2019 This work is licensed under Creative Common Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0 (https://creativecommons.org/licenses/by-nc-nd/4.0/) )
spellingShingle Clinical Research
Zhang, Limin
Sun, Lijun
Zhang, Bin
Chen, Lihong
Identification of Differentially Expressed Genes (DEGs) Relevant to Prognosis of Ovarian Cancer by Use of Integrated Bioinformatics Analysis and Validation by Immunohistochemistry Assay
title Identification of Differentially Expressed Genes (DEGs) Relevant to Prognosis of Ovarian Cancer by Use of Integrated Bioinformatics Analysis and Validation by Immunohistochemistry Assay
title_full Identification of Differentially Expressed Genes (DEGs) Relevant to Prognosis of Ovarian Cancer by Use of Integrated Bioinformatics Analysis and Validation by Immunohistochemistry Assay
title_fullStr Identification of Differentially Expressed Genes (DEGs) Relevant to Prognosis of Ovarian Cancer by Use of Integrated Bioinformatics Analysis and Validation by Immunohistochemistry Assay
title_full_unstemmed Identification of Differentially Expressed Genes (DEGs) Relevant to Prognosis of Ovarian Cancer by Use of Integrated Bioinformatics Analysis and Validation by Immunohistochemistry Assay
title_short Identification of Differentially Expressed Genes (DEGs) Relevant to Prognosis of Ovarian Cancer by Use of Integrated Bioinformatics Analysis and Validation by Immunohistochemistry Assay
title_sort identification of differentially expressed genes (degs) relevant to prognosis of ovarian cancer by use of integrated bioinformatics analysis and validation by immunohistochemistry assay
topic Clinical Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6941780/
https://www.ncbi.nlm.nih.gov/pubmed/31871312
http://dx.doi.org/10.12659/MSM.921661
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