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Identification of key genes and pathways between type I and type II endometrial cancer using bioinformatics analysis

Endometrial carcinoma (EC) is a common malignant neoplasm of the female reproductive tract. The malignant degree of type II EC is much greater than that of type I EC, usually presenting with a high recurrence rate and a poor prognosis. Therefore, the present study aimed to examine the principal gene...

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Autores principales: Zhang, Kai, Li, Huiyang, Yan, Ye, Zang, Yuqin, Li, Ke, Wang, Yingmei, Xue, Fengxia
Formato: Online Artículo Texto
Lenguaje:English
Publicado: D.A. Spandidos 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6676660/
https://www.ncbi.nlm.nih.gov/pubmed/31452737
http://dx.doi.org/10.3892/ol.2019.10550
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author Zhang, Kai
Li, Huiyang
Yan, Ye
Zang, Yuqin
Li, Ke
Wang, Yingmei
Xue, Fengxia
author_facet Zhang, Kai
Li, Huiyang
Yan, Ye
Zang, Yuqin
Li, Ke
Wang, Yingmei
Xue, Fengxia
author_sort Zhang, Kai
collection PubMed
description Endometrial carcinoma (EC) is a common malignant neoplasm of the female reproductive tract. The malignant degree of type II EC is much greater than that of type I EC, usually presenting with a high recurrence rate and a poor prognosis. Therefore, the present study aimed to examine the principal genes associated with the degree of differentiation in type I and type II EC and reveal their potential mechanisms. Differentially expressed genes (DEGs) were selected from the gene expression profiles derived from The Cancer Genome Atlas. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were conducted. In the present study, the KEGG pathway enrichment analysis revealed that 5,962 upregulated DEGs were significantly enriched in the ‘p53 signaling pathway’ and involved in ‘lysine degradation’. In addition, 3,709 downregulated DEGs were enriched in ‘pathways in cancer’, as well as ‘tight junction regulation’, the ‘cell cycle’ and the ‘Wnt signaling pathway’. The 13 top hub genes MAPK1, PHLPP1, ESR1, MDM2, CDKN2A, CDKN1A, AURKA, BCL2L1, POLQ, PIK3R3, RHOQ, EIF4E and LATS2 were identified via the protein-protein interaction network. Furthermore, the OncoPrint algorithm from cBioPortal declared that 25% of EC cases carried genetic alterations. The altered DEGs (MAPK1, MDM2, AURKA, EIF4E and LATS2) may be involved in tumor differentiation and may be valuable diagnostic biomarkers. In conclusion, a number of principal genes were identified in the present study that may be determinants of poorly differentiated type II EC carcinogenesis, which may contribute to future research into potential molecular mechanisms. In addition, these genes may help identify candidate biomarkers and novel therapeutic targets for type II EC.
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spelling pubmed-66766602019-08-26 Identification of key genes and pathways between type I and type II endometrial cancer using bioinformatics analysis Zhang, Kai Li, Huiyang Yan, Ye Zang, Yuqin Li, Ke Wang, Yingmei Xue, Fengxia Oncol Lett Articles Endometrial carcinoma (EC) is a common malignant neoplasm of the female reproductive tract. The malignant degree of type II EC is much greater than that of type I EC, usually presenting with a high recurrence rate and a poor prognosis. Therefore, the present study aimed to examine the principal genes associated with the degree of differentiation in type I and type II EC and reveal their potential mechanisms. Differentially expressed genes (DEGs) were selected from the gene expression profiles derived from The Cancer Genome Atlas. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were conducted. In the present study, the KEGG pathway enrichment analysis revealed that 5,962 upregulated DEGs were significantly enriched in the ‘p53 signaling pathway’ and involved in ‘lysine degradation’. In addition, 3,709 downregulated DEGs were enriched in ‘pathways in cancer’, as well as ‘tight junction regulation’, the ‘cell cycle’ and the ‘Wnt signaling pathway’. The 13 top hub genes MAPK1, PHLPP1, ESR1, MDM2, CDKN2A, CDKN1A, AURKA, BCL2L1, POLQ, PIK3R3, RHOQ, EIF4E and LATS2 were identified via the protein-protein interaction network. Furthermore, the OncoPrint algorithm from cBioPortal declared that 25% of EC cases carried genetic alterations. The altered DEGs (MAPK1, MDM2, AURKA, EIF4E and LATS2) may be involved in tumor differentiation and may be valuable diagnostic biomarkers. In conclusion, a number of principal genes were identified in the present study that may be determinants of poorly differentiated type II EC carcinogenesis, which may contribute to future research into potential molecular mechanisms. In addition, these genes may help identify candidate biomarkers and novel therapeutic targets for type II EC. D.A. Spandidos 2019-09 2019-06-28 /pmc/articles/PMC6676660/ /pubmed/31452737 http://dx.doi.org/10.3892/ol.2019.10550 Text en Copyright: © Zhang 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
Zhang, Kai
Li, Huiyang
Yan, Ye
Zang, Yuqin
Li, Ke
Wang, Yingmei
Xue, Fengxia
Identification of key genes and pathways between type I and type II endometrial cancer using bioinformatics analysis
title Identification of key genes and pathways between type I and type II endometrial cancer using bioinformatics analysis
title_full Identification of key genes and pathways between type I and type II endometrial cancer using bioinformatics analysis
title_fullStr Identification of key genes and pathways between type I and type II endometrial cancer using bioinformatics analysis
title_full_unstemmed Identification of key genes and pathways between type I and type II endometrial cancer using bioinformatics analysis
title_short Identification of key genes and pathways between type I and type II endometrial cancer using bioinformatics analysis
title_sort identification of key genes and pathways between type i and type ii endometrial cancer using bioinformatics analysis
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6676660/
https://www.ncbi.nlm.nih.gov/pubmed/31452737
http://dx.doi.org/10.3892/ol.2019.10550
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