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TTK, CDC25A, and ESPL1 as Prognostic Biomarkers for Endometrial Cancer

OBJECTIVE: Endometrial cancer (EC) is one of the most common malignant gynaecological tumours worldwide. This study was aimed at identifying EC prognostic genes and investigating the molecular mechanisms of these genes in EC. METHODS: Two mRNA datasets of EC were downloaded from the Gene Expression...

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Autores principales: Yang, Qiannan, Yu, Bojun, Sun, Jing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7685798/
https://www.ncbi.nlm.nih.gov/pubmed/33282948
http://dx.doi.org/10.1155/2020/4625123
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author Yang, Qiannan
Yu, Bojun
Sun, Jing
author_facet Yang, Qiannan
Yu, Bojun
Sun, Jing
author_sort Yang, Qiannan
collection PubMed
description OBJECTIVE: Endometrial cancer (EC) is one of the most common malignant gynaecological tumours worldwide. This study was aimed at identifying EC prognostic genes and investigating the molecular mechanisms of these genes in EC. METHODS: Two mRNA datasets of EC were downloaded from the Gene Expression Omnibus (GEO). The GEO2R tool and Draw Venn Diagram were used to identify differentially expressed genes (DEGs) between normal endometrial tissues and EC tissues. Then, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed using the Database for Annotation, Visualization and Integrated Discovery (DAVID). Next, the protein-protein interactions (PPIs) of these DEGs were determined by the Search Tool for the Retrieval of Interacting Genes (STRING) tool and Cytoscape with Molecular Complex Detection (MCODE). Furthermore, Kaplan-Meier survival analysis was performed by UALCAN to verify genes associated with significantly poor prognosis. Next, Gene Expression Profiling Interactive Analysis (GEPIA) was used to verify the expression levels of these selected genes. Additionally, a reanalysis of the KEGG pathways was performed to understand the potential biological functions of selected genes. Finally, the associations between these genes and clinical features were analysed based on TCGA cancer genomic datasets for EC. RESULTS: In EC tissues, compared with normal endometrial tissues, 147 of 249 DEGs were upregulated and 102 were downregulated. A total of 64 upregulated genes were assembled into a PPI network. Next, 14 genes were found to be both associated with significantly poor prognosis and highly expressed in EC tissues. Reanalysis of the KEGG pathways found that three of these genes were enriched in the cell cycle pathway. TTK, CDC25A, and ESPL1 showed higher expression in cancers with late stage and higher tumour grade. CONCLUSION: In summary, through integrated bioinformatics approaches, we found three significant prognostic genes of EC, which might be potential therapeutic targets for EC patients.
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spelling pubmed-76857982020-12-04 TTK, CDC25A, and ESPL1 as Prognostic Biomarkers for Endometrial Cancer Yang, Qiannan Yu, Bojun Sun, Jing Biomed Res Int Research Article OBJECTIVE: Endometrial cancer (EC) is one of the most common malignant gynaecological tumours worldwide. This study was aimed at identifying EC prognostic genes and investigating the molecular mechanisms of these genes in EC. METHODS: Two mRNA datasets of EC were downloaded from the Gene Expression Omnibus (GEO). The GEO2R tool and Draw Venn Diagram were used to identify differentially expressed genes (DEGs) between normal endometrial tissues and EC tissues. Then, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed using the Database for Annotation, Visualization and Integrated Discovery (DAVID). Next, the protein-protein interactions (PPIs) of these DEGs were determined by the Search Tool for the Retrieval of Interacting Genes (STRING) tool and Cytoscape with Molecular Complex Detection (MCODE). Furthermore, Kaplan-Meier survival analysis was performed by UALCAN to verify genes associated with significantly poor prognosis. Next, Gene Expression Profiling Interactive Analysis (GEPIA) was used to verify the expression levels of these selected genes. Additionally, a reanalysis of the KEGG pathways was performed to understand the potential biological functions of selected genes. Finally, the associations between these genes and clinical features were analysed based on TCGA cancer genomic datasets for EC. RESULTS: In EC tissues, compared with normal endometrial tissues, 147 of 249 DEGs were upregulated and 102 were downregulated. A total of 64 upregulated genes were assembled into a PPI network. Next, 14 genes were found to be both associated with significantly poor prognosis and highly expressed in EC tissues. Reanalysis of the KEGG pathways found that three of these genes were enriched in the cell cycle pathway. TTK, CDC25A, and ESPL1 showed higher expression in cancers with late stage and higher tumour grade. CONCLUSION: In summary, through integrated bioinformatics approaches, we found three significant prognostic genes of EC, which might be potential therapeutic targets for EC patients. Hindawi 2020-11-17 /pmc/articles/PMC7685798/ /pubmed/33282948 http://dx.doi.org/10.1155/2020/4625123 Text en Copyright © 2020 Qiannan Yang et al. https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Yang, Qiannan
Yu, Bojun
Sun, Jing
TTK, CDC25A, and ESPL1 as Prognostic Biomarkers for Endometrial Cancer
title TTK, CDC25A, and ESPL1 as Prognostic Biomarkers for Endometrial Cancer
title_full TTK, CDC25A, and ESPL1 as Prognostic Biomarkers for Endometrial Cancer
title_fullStr TTK, CDC25A, and ESPL1 as Prognostic Biomarkers for Endometrial Cancer
title_full_unstemmed TTK, CDC25A, and ESPL1 as Prognostic Biomarkers for Endometrial Cancer
title_short TTK, CDC25A, and ESPL1 as Prognostic Biomarkers for Endometrial Cancer
title_sort ttk, cdc25a, and espl1 as prognostic biomarkers for endometrial cancer
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7685798/
https://www.ncbi.nlm.nih.gov/pubmed/33282948
http://dx.doi.org/10.1155/2020/4625123
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