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Integrated bioinformatics analysis to identify key genes related to the prognosis of esophageal squamous cell carcinoma

BACKGROUND: Esophageal squamous cell carcinoma (ESCC) is a serious threat to human health and life. The National Center for Biotechnology Information Gene Expression Omnibus (NCBI-GEO) database provides valuable information on genes related to the pathogenesis and prognosis of ESCC, which helps us t...

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Autores principales: Yang, Ying, Sun, Zhiwei, Shi, Youwu, Sun, Jing, Zhang, Xiaodong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AME Publishing Company 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8798886/
https://www.ncbi.nlm.nih.gov/pubmed/35116493
http://dx.doi.org/10.21037/tcr-20-3220
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author Yang, Ying
Sun, Zhiwei
Shi, Youwu
Sun, Jing
Zhang, Xiaodong
author_facet Yang, Ying
Sun, Zhiwei
Shi, Youwu
Sun, Jing
Zhang, Xiaodong
author_sort Yang, Ying
collection PubMed
description BACKGROUND: Esophageal squamous cell carcinoma (ESCC) is a serious threat to human health and life. The National Center for Biotechnology Information Gene Expression Omnibus (NCBI-GEO) database provides valuable information on genes related to the pathogenesis and prognosis of ESCC, which helps us to make in-depth understanding about the disease and improve its prognosis. METHODS: Four microarray profiles [GSE77861 (African Americans), GSE26886 (Germans), GSE17351 (Americans), and GSE45670 (Chinese)] from the NCBI-GEO including 49 ESCC tissues and 41 corresponding normal tissues were collected. Integrated bioinformatics methods, including protein-protein interaction (PPI) network analysis, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses, and Kaplan-Meier plotter were applied to determine the differentially expressed genes (DEGs) in ESCC together with their core functions and relationship with survival. RESULTS: A total of 220 upregulated and 112 downregulated genes were identified as DEGs in ESCC, of which, 40 upregulated genes were core function genes. The DEGs were mostly involved in DNA replication and cell cycle pathways. Survival analysis and Bonferroni adjustment showed kinesin family member 18A (KIF18A) and TTK protein kinase (TTK) to be related to prognosis in ESCC. CONCLUSIONS: The findings of the present study verified the previously proposed association between TTK and patient survival in ESCC, and identified KIF18A as ESCC prognosis-related gene markers for the first time. The underlying mechanism needs to be further investigated using larger sample size studies and biological experiments in future.
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spelling pubmed-87988862022-02-02 Integrated bioinformatics analysis to identify key genes related to the prognosis of esophageal squamous cell carcinoma Yang, Ying Sun, Zhiwei Shi, Youwu Sun, Jing Zhang, Xiaodong Transl Cancer Res Original Article BACKGROUND: Esophageal squamous cell carcinoma (ESCC) is a serious threat to human health and life. The National Center for Biotechnology Information Gene Expression Omnibus (NCBI-GEO) database provides valuable information on genes related to the pathogenesis and prognosis of ESCC, which helps us to make in-depth understanding about the disease and improve its prognosis. METHODS: Four microarray profiles [GSE77861 (African Americans), GSE26886 (Germans), GSE17351 (Americans), and GSE45670 (Chinese)] from the NCBI-GEO including 49 ESCC tissues and 41 corresponding normal tissues were collected. Integrated bioinformatics methods, including protein-protein interaction (PPI) network analysis, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses, and Kaplan-Meier plotter were applied to determine the differentially expressed genes (DEGs) in ESCC together with their core functions and relationship with survival. RESULTS: A total of 220 upregulated and 112 downregulated genes were identified as DEGs in ESCC, of which, 40 upregulated genes were core function genes. The DEGs were mostly involved in DNA replication and cell cycle pathways. Survival analysis and Bonferroni adjustment showed kinesin family member 18A (KIF18A) and TTK protein kinase (TTK) to be related to prognosis in ESCC. CONCLUSIONS: The findings of the present study verified the previously proposed association between TTK and patient survival in ESCC, and identified KIF18A as ESCC prognosis-related gene markers for the first time. The underlying mechanism needs to be further investigated using larger sample size studies and biological experiments in future. AME Publishing Company 2021-04 /pmc/articles/PMC8798886/ /pubmed/35116493 http://dx.doi.org/10.21037/tcr-20-3220 Text en 2021 Translational Cancer Research. All rights reserved. https://creativecommons.org/licenses/by-nc-nd/4.0/Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.
spellingShingle Original Article
Yang, Ying
Sun, Zhiwei
Shi, Youwu
Sun, Jing
Zhang, Xiaodong
Integrated bioinformatics analysis to identify key genes related to the prognosis of esophageal squamous cell carcinoma
title Integrated bioinformatics analysis to identify key genes related to the prognosis of esophageal squamous cell carcinoma
title_full Integrated bioinformatics analysis to identify key genes related to the prognosis of esophageal squamous cell carcinoma
title_fullStr Integrated bioinformatics analysis to identify key genes related to the prognosis of esophageal squamous cell carcinoma
title_full_unstemmed Integrated bioinformatics analysis to identify key genes related to the prognosis of esophageal squamous cell carcinoma
title_short Integrated bioinformatics analysis to identify key genes related to the prognosis of esophageal squamous cell carcinoma
title_sort integrated bioinformatics analysis to identify key genes related to the prognosis of esophageal squamous cell carcinoma
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8798886/
https://www.ncbi.nlm.nih.gov/pubmed/35116493
http://dx.doi.org/10.21037/tcr-20-3220
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