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Identification of a five-gene signature for predicting the progression and prognosis of stage I endometrial carcinoma

Uterine corpus endometrial carcinoma (UCEC) is often diagnosed at an early clinical stage based on abnormal vaginal bleeding. However, the prognosis of UCEC is poor. The present study was conducted to identify novel tumor grade-related genes with the potential to predict the prognosis and progressio...

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Autores principales: Bian, Jia, Xu, Yuzi, Wu, Fei, Pan, Qiangwei, Liu, Yunlong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: D.A. Spandidos 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7400971/
https://www.ncbi.nlm.nih.gov/pubmed/32782557
http://dx.doi.org/10.3892/ol.2020.11798
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author Bian, Jia
Xu, Yuzi
Wu, Fei
Pan, Qiangwei
Liu, Yunlong
author_facet Bian, Jia
Xu, Yuzi
Wu, Fei
Pan, Qiangwei
Liu, Yunlong
author_sort Bian, Jia
collection PubMed
description Uterine corpus endometrial carcinoma (UCEC) is often diagnosed at an early clinical stage based on abnormal vaginal bleeding. However, the prognosis of UCEC is poor. The present study was conducted to identify novel tumor grade-related genes with the potential to predict the prognosis and progression of UCEC. A total of three gene expression microarray datasets were downloaded from the Gene Expression Omnibus database, and one RNA-sequencing dataset with corresponding clinical information of patients with UCEC was obtained from The Cancer Genome Atlas database. In summary, 1,447 differentially expressed genes (DEGs) were identified between endometrial cancerous tissues and normal endometrial tissues. Weighted gene co-expression network analysis was performed to assess the associations between DEGs and clinical traits. In total, five genes were found to be highly associated with the tumorigenesis and prognosis of UCEC. Among them, BUB1 mitotic checkpoint serine/threonine kinase B, cyclin B1, cell-division cycle protein 20 and non-SMC condensing I complex subunit G were involved in cell cycle regulation pathways, and DLG-associated protein 5 was involved in the Notch receptor 3 signaling pathway based on functional enrichment analyses. Of the five genes, four were highly expressed in endometrial cancerous tissues compared with normal endometrial tissues at the protein level. In addition, the higher expression of these genes predicted a higher tumor grade and worse overall survival. In conclusion, the present study revealed a 5-gene signature that can be used to predict the progression of UCEC.
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spelling pubmed-74009712020-08-10 Identification of a five-gene signature for predicting the progression and prognosis of stage I endometrial carcinoma Bian, Jia Xu, Yuzi Wu, Fei Pan, Qiangwei Liu, Yunlong Oncol Lett Articles Uterine corpus endometrial carcinoma (UCEC) is often diagnosed at an early clinical stage based on abnormal vaginal bleeding. However, the prognosis of UCEC is poor. The present study was conducted to identify novel tumor grade-related genes with the potential to predict the prognosis and progression of UCEC. A total of three gene expression microarray datasets were downloaded from the Gene Expression Omnibus database, and one RNA-sequencing dataset with corresponding clinical information of patients with UCEC was obtained from The Cancer Genome Atlas database. In summary, 1,447 differentially expressed genes (DEGs) were identified between endometrial cancerous tissues and normal endometrial tissues. Weighted gene co-expression network analysis was performed to assess the associations between DEGs and clinical traits. In total, five genes were found to be highly associated with the tumorigenesis and prognosis of UCEC. Among them, BUB1 mitotic checkpoint serine/threonine kinase B, cyclin B1, cell-division cycle protein 20 and non-SMC condensing I complex subunit G were involved in cell cycle regulation pathways, and DLG-associated protein 5 was involved in the Notch receptor 3 signaling pathway based on functional enrichment analyses. Of the five genes, four were highly expressed in endometrial cancerous tissues compared with normal endometrial tissues at the protein level. In addition, the higher expression of these genes predicted a higher tumor grade and worse overall survival. In conclusion, the present study revealed a 5-gene signature that can be used to predict the progression of UCEC. D.A. Spandidos 2020-09 2020-07-01 /pmc/articles/PMC7400971/ /pubmed/32782557 http://dx.doi.org/10.3892/ol.2020.11798 Text en Copyright: © Bian 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
Bian, Jia
Xu, Yuzi
Wu, Fei
Pan, Qiangwei
Liu, Yunlong
Identification of a five-gene signature for predicting the progression and prognosis of stage I endometrial carcinoma
title Identification of a five-gene signature for predicting the progression and prognosis of stage I endometrial carcinoma
title_full Identification of a five-gene signature for predicting the progression and prognosis of stage I endometrial carcinoma
title_fullStr Identification of a five-gene signature for predicting the progression and prognosis of stage I endometrial carcinoma
title_full_unstemmed Identification of a five-gene signature for predicting the progression and prognosis of stage I endometrial carcinoma
title_short Identification of a five-gene signature for predicting the progression and prognosis of stage I endometrial carcinoma
title_sort identification of a five-gene signature for predicting the progression and prognosis of stage i endometrial carcinoma
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7400971/
https://www.ncbi.nlm.nih.gov/pubmed/32782557
http://dx.doi.org/10.3892/ol.2020.11798
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