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Identification of key candidate genes and pathways in endometrial cancer: Evidence from bioinformatics analysis

Endometrial cancer (EC) is the fourth most common cancer in women worldwide. Although researchers are exploring the biological processes of tumorigenesis and development of EC, the gene interactions and biological pathways of EC are not accurately verified. In the present study, bioinformatics metho...

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Autores principales: Lv, Sha, Xu, Xiaoxiao, Wu, Zhangying
Formato: Online Artículo Texto
Lenguaje:English
Publicado: D.A. Spandidos 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6876294/
https://www.ncbi.nlm.nih.gov/pubmed/31807178
http://dx.doi.org/10.3892/ol.2019.11040
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author Lv, Sha
Xu, Xiaoxiao
Wu, Zhangying
author_facet Lv, Sha
Xu, Xiaoxiao
Wu, Zhangying
author_sort Lv, Sha
collection PubMed
description Endometrial cancer (EC) is the fourth most common cancer in women worldwide. Although researchers are exploring the biological processes of tumorigenesis and development of EC, the gene interactions and biological pathways of EC are not accurately verified. In the present study, bioinformatics methods were used to screen for key candidate genes and pathways that were associated with EC and to reveal the possible mechanisms at molecular level. Microarray datasets (GSE63678, GSE17025 and GSE3013) from the Gene Expression Omnibus database were downloaded and 118 differentially expressed genes (DEGs) were selected using a Venn diagram. Functional enrichment analyses were performed on the DEGs. A protein-protein interaction network was constructed, including the module analysis. A total of 11 hub genes were identified from the DEGs, and functional enrichment analyses were performed to clarify their possible biological processes. A total of 118 DEGs were selected from three mRNA datasets. Functional enrichment demonstrated 27 downregulated genes that were primarily involved in the positive regulation of transcription from RNA polymerase II promoter, protein binding and the nucleus. A total of 91 upregulated DEGs were mainly associated with cell division, protein binding and the nucleus. Pathway analysis indicated that the downregulated DEGs were mainly enriched in pathways associated with cancer, and the upregulated DEGs were mainly enriched in the cell cycle. The 11 hub genes were primarily enriched in the cell cycle, oocyte meiosis, progesterone-mediated oocyte maturation, the p53 signaling pathway and viral carcinogenesis. The integrated analysis showed that cyclin B1, ubiquitin conjugating enzyme E2 C and cell division cycle 20 may participate in the tumorigenesis, development and invasion of EC. In conclusion, the hub genes and pathways identified in the present study contributed to the understanding of carcinogenesis and progression of EC at the mechanistic and molecular-biological level. As candidate targets for the diagnosis and treatment of EC, these genes deserve further investigation.
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spelling pubmed-68762942019-12-05 Identification of key candidate genes and pathways in endometrial cancer: Evidence from bioinformatics analysis Lv, Sha Xu, Xiaoxiao Wu, Zhangying Oncol Lett Articles Endometrial cancer (EC) is the fourth most common cancer in women worldwide. Although researchers are exploring the biological processes of tumorigenesis and development of EC, the gene interactions and biological pathways of EC are not accurately verified. In the present study, bioinformatics methods were used to screen for key candidate genes and pathways that were associated with EC and to reveal the possible mechanisms at molecular level. Microarray datasets (GSE63678, GSE17025 and GSE3013) from the Gene Expression Omnibus database were downloaded and 118 differentially expressed genes (DEGs) were selected using a Venn diagram. Functional enrichment analyses were performed on the DEGs. A protein-protein interaction network was constructed, including the module analysis. A total of 11 hub genes were identified from the DEGs, and functional enrichment analyses were performed to clarify their possible biological processes. A total of 118 DEGs were selected from three mRNA datasets. Functional enrichment demonstrated 27 downregulated genes that were primarily involved in the positive regulation of transcription from RNA polymerase II promoter, protein binding and the nucleus. A total of 91 upregulated DEGs were mainly associated with cell division, protein binding and the nucleus. Pathway analysis indicated that the downregulated DEGs were mainly enriched in pathways associated with cancer, and the upregulated DEGs were mainly enriched in the cell cycle. The 11 hub genes were primarily enriched in the cell cycle, oocyte meiosis, progesterone-mediated oocyte maturation, the p53 signaling pathway and viral carcinogenesis. The integrated analysis showed that cyclin B1, ubiquitin conjugating enzyme E2 C and cell division cycle 20 may participate in the tumorigenesis, development and invasion of EC. In conclusion, the hub genes and pathways identified in the present study contributed to the understanding of carcinogenesis and progression of EC at the mechanistic and molecular-biological level. As candidate targets for the diagnosis and treatment of EC, these genes deserve further investigation. D.A. Spandidos 2019-12 2019-11-01 /pmc/articles/PMC6876294/ /pubmed/31807178 http://dx.doi.org/10.3892/ol.2019.11040 Text en Copyright: © Lv 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
Lv, Sha
Xu, Xiaoxiao
Wu, Zhangying
Identification of key candidate genes and pathways in endometrial cancer: Evidence from bioinformatics analysis
title Identification of key candidate genes and pathways in endometrial cancer: Evidence from bioinformatics analysis
title_full Identification of key candidate genes and pathways in endometrial cancer: Evidence from bioinformatics analysis
title_fullStr Identification of key candidate genes and pathways in endometrial cancer: Evidence from bioinformatics analysis
title_full_unstemmed Identification of key candidate genes and pathways in endometrial cancer: Evidence from bioinformatics analysis
title_short Identification of key candidate genes and pathways in endometrial cancer: Evidence from bioinformatics analysis
title_sort identification of key candidate genes and pathways in endometrial cancer: evidence from bioinformatics analysis
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6876294/
https://www.ncbi.nlm.nih.gov/pubmed/31807178
http://dx.doi.org/10.3892/ol.2019.11040
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