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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...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
AME Publishing Company
2021
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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. |
format | Online Article Text |
id | pubmed-8798886 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | AME Publishing Company |
record_format | MEDLINE/PubMed |
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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