Identification of Hub Genes Correlated With Poor Prognosis for Patients With Uterine Corpus Endometrial Carcinoma by Integrated Bioinformatics Analysis and Experimental Validation

Uterine Corpus Endometrial Carcinoma (UCEC) is one of the most common malignancies of the female genital tract and there remains a major public health problem. Although significant progress has been made in explaining the progression of UCEC, it is still warranted that molecular mechanisms underlyin...

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Autores principales:	Yi Yuan, Zhengzheng Chen, Xushan Cai, Shengxiang He, Dong Li, Weidong Zhao
Formato:	article
Lenguaje:	EN
Publicado:	Frontiers Media S.A. 2021
Materias:	uterine corpus endometrial carcinoma weighted gene co-expression network analysis protein-protein interaction network hub gene tumor differentiation Neoplasms. Tumors. Oncology. Including cancer and carcinogens RC254-282
Acceso en línea:	https://doaj.org/article/b01612e0835c4607a25cfb83fac2a172
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spelling	oai:doaj.org-article:b01612e0835c4607a25cfb83fac2a1722021-11-19T05:09:44ZIdentification of Hub Genes Correlated With Poor Prognosis for Patients With Uterine Corpus Endometrial Carcinoma by Integrated Bioinformatics Analysis and Experimental Validation2234-943X10.3389/fonc.2021.766947https://doaj.org/article/b01612e0835c4607a25cfb83fac2a1722021-11-01T00:00:00Zhttps://www.frontiersin.org/articles/10.3389/fonc.2021.766947/fullhttps://doaj.org/toc/2234-943XUterine Corpus Endometrial Carcinoma (UCEC) is one of the most common malignancies of the female genital tract and there remains a major public health problem. Although significant progress has been made in explaining the progression of UCEC, it is still warranted that molecular mechanisms underlying the tumorigenesis of UCEC are to be elucidated. The aim of the current study was to investigate key modules and hub genes related to UCEC pathogenesis, and to explore potential biomarkers and therapeutic targets for UCEC. The RNA-seq dataset and corresponding clinical information for UCEC patients were obtained from the Cancer Genome Atlas (TCGA) database. Differentially expressed genes (DEGs) were screened between 23 paired UCEC tissues and adjacent non-cancerous tissues. Subsequently, the co-expression network of DEGs was determined via weighted gene co-expression network analysis (WGCNA). The Blue and Brown modules were identified to be significantly positively associated with neoplasm histologic grade. The highly connected genes of the two modules were then investigated as potential key factors related to tumor differentiation. Additionally, a protein-protein interaction (PPI) network for all genes in the two modules was constructed to obtain key modules and nodes. 10 genes were identified by both WGCNA and PPI analyses, and it was shown by Kaplan-Meier curve analysis that 6 out of the 10 genes were significantly negatively related to the 5-year overall survival (OS) in patients (AURKA, BUB1, CDCA8, DLGAP5, KIF2C, TPX2). Besides, according to the DEGs from the two modules, lncRNA-miRNA-mRNA and lncRNA-TF-mRNA networks were constructed to explore the molecular mechanism of UCEC-related lncRNAs. 3 lncRNAs were identified as being significantly negatively related to the 5-year OS (AC015849.16, DUXAP8 and DGCR5), with higher expression in UCEC tissues compared to non-tumor tissues. Finally, quantitative Real-time PCR was applied to validate the expression patterns of hub genes. Cell proliferation and colony formation assays, as well as cell cycle distribution and apoptosis analysis, were performed to test the effects of representative hub genes. Altogether, this study not only promotes our understanding of the molecular mechanisms for the pathogenesis of UCEC but also identifies several promising biomarkers in UCEC development, providing potential therapeutic targets for UCEC.Yi YuanZhengzheng ChenXushan CaiXushan CaiShengxiang HeDong LiWeidong ZhaoFrontiers Media S.A.articleuterine corpus endometrial carcinomaweighted gene co-expression network analysisprotein-protein interaction networkhub genetumor differentiationNeoplasms. Tumors. Oncology. Including cancer and carcinogensRC254-282ENFrontiers in Oncology, Vol 11 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	uterine corpus endometrial carcinoma weighted gene co-expression network analysis protein-protein interaction network hub gene tumor differentiation Neoplasms. Tumors. Oncology. Including cancer and carcinogens RC254-282
spellingShingle	uterine corpus endometrial carcinoma weighted gene co-expression network analysis protein-protein interaction network hub gene tumor differentiation Neoplasms. Tumors. Oncology. Including cancer and carcinogens RC254-282 Yi Yuan Zhengzheng Chen Xushan Cai Xushan Cai Shengxiang He Dong Li Weidong Zhao Identification of Hub Genes Correlated With Poor Prognosis for Patients With Uterine Corpus Endometrial Carcinoma by Integrated Bioinformatics Analysis and Experimental Validation
description	Uterine Corpus Endometrial Carcinoma (UCEC) is one of the most common malignancies of the female genital tract and there remains a major public health problem. Although significant progress has been made in explaining the progression of UCEC, it is still warranted that molecular mechanisms underlying the tumorigenesis of UCEC are to be elucidated. The aim of the current study was to investigate key modules and hub genes related to UCEC pathogenesis, and to explore potential biomarkers and therapeutic targets for UCEC. The RNA-seq dataset and corresponding clinical information for UCEC patients were obtained from the Cancer Genome Atlas (TCGA) database. Differentially expressed genes (DEGs) were screened between 23 paired UCEC tissues and adjacent non-cancerous tissues. Subsequently, the co-expression network of DEGs was determined via weighted gene co-expression network analysis (WGCNA). The Blue and Brown modules were identified to be significantly positively associated with neoplasm histologic grade. The highly connected genes of the two modules were then investigated as potential key factors related to tumor differentiation. Additionally, a protein-protein interaction (PPI) network for all genes in the two modules was constructed to obtain key modules and nodes. 10 genes were identified by both WGCNA and PPI analyses, and it was shown by Kaplan-Meier curve analysis that 6 out of the 10 genes were significantly negatively related to the 5-year overall survival (OS) in patients (AURKA, BUB1, CDCA8, DLGAP5, KIF2C, TPX2). Besides, according to the DEGs from the two modules, lncRNA-miRNA-mRNA and lncRNA-TF-mRNA networks were constructed to explore the molecular mechanism of UCEC-related lncRNAs. 3 lncRNAs were identified as being significantly negatively related to the 5-year OS (AC015849.16, DUXAP8 and DGCR5), with higher expression in UCEC tissues compared to non-tumor tissues. Finally, quantitative Real-time PCR was applied to validate the expression patterns of hub genes. Cell proliferation and colony formation assays, as well as cell cycle distribution and apoptosis analysis, were performed to test the effects of representative hub genes. Altogether, this study not only promotes our understanding of the molecular mechanisms for the pathogenesis of UCEC but also identifies several promising biomarkers in UCEC development, providing potential therapeutic targets for UCEC.
format	article
author	Yi Yuan Zhengzheng Chen Xushan Cai Xushan Cai Shengxiang He Dong Li Weidong Zhao
author_facet	Yi Yuan Zhengzheng Chen Xushan Cai Xushan Cai Shengxiang He Dong Li Weidong Zhao
author_sort	Yi Yuan
title	Identification of Hub Genes Correlated With Poor Prognosis for Patients With Uterine Corpus Endometrial Carcinoma by Integrated Bioinformatics Analysis and Experimental Validation
title_short	Identification of Hub Genes Correlated With Poor Prognosis for Patients With Uterine Corpus Endometrial Carcinoma by Integrated Bioinformatics Analysis and Experimental Validation
title_full	Identification of Hub Genes Correlated With Poor Prognosis for Patients With Uterine Corpus Endometrial Carcinoma by Integrated Bioinformatics Analysis and Experimental Validation
title_fullStr	Identification of Hub Genes Correlated With Poor Prognosis for Patients With Uterine Corpus Endometrial Carcinoma by Integrated Bioinformatics Analysis and Experimental Validation
title_full_unstemmed	Identification of Hub Genes Correlated With Poor Prognosis for Patients With Uterine Corpus Endometrial Carcinoma by Integrated Bioinformatics Analysis and Experimental Validation
title_sort	identification of hub genes correlated with poor prognosis for patients with uterine corpus endometrial carcinoma by integrated bioinformatics analysis and experimental validation
publisher	Frontiers Media S.A.
publishDate	2021
url	https://doaj.org/article/b01612e0835c4607a25cfb83fac2a172
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Identification of Hub Genes Correlated With Poor Prognosis for Patients With Uterine Corpus Endometrial Carcinoma by Integrated Bioinformatics Analysis and Experimental Validation

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