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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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Detalles Bibliográficos
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
Descripción
Sumario: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.