Identification of biomarkers for esophageal squamous cell carcinoma based on bioinformatics
10.19485/j.cnki.issn2096-5087.2022.09.009
- Author:
Yujun ZHANG
;
Yan WANG
;
Wusimanjiang Diliyaer
;
Guangchao LIU
;
Yanwu NIE
;
Lin ZHU
- Publication Type:Journal Article
- Keywords:
esophageal squamous cell carcinoma;
bioinformaticr;
biomarker;
differentially expressed gene
- From:
Journal of Preventive Medicine
2022;34(9):906-913
- CountryChina
- Language:Chinese
-
Abstract:
Objective :To identify biomarkers for esophageal squamous cell carcinoma (ESCC) using bioinformatics tools, so as to provide insights into diagnosis and targeted therapy of ESCC.
Methods:The gene expression datasets GSE23400, GSE45670, GSE20347 and GSE17351 were screened and downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) of ESCC were screened using the online tool GEO2R, and the common DEGs among the four datasets were determined using Venn diagram. Gene Ontology (GO) annotations and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed using the DAVID database, and protein-protein interaction (PPI) analysis was performed using the STRING database. The key modules were identified using molecular complex detection (MCODE) plugin in the Cytoscape software, and hub genes with the highest connectivity degree were identified using the CytoHubba plugin, and the gene expression was validated on the UALCAN platform. Survival analysis of hub genes was performed using the Kaplan-Meier plotter database.
Results:Totally 146 common DEGs were screened, including 102 up-regulated genes and 44 down-regulated genes. GO annotation analysis showed that the common DEGs were mainly enriched in biological processes of cell cycle, sister chromatid separation in the late mitotic phase and cell cycle regulation, enriched in cellular components of spindle and centrosome, and molecular functions of enzyme binding and ATP binding. KEGG pathway analysis showed that DEGs was significantly enriched in cell cycle, extracellular matrix (ECM)-receptor interactions and oocyte meiosis. A total of 10 hub genes were screened, and gene expression validation and survival analysis identified 7 genes associated with prognosis of ESCC, including CCNB1, CDK1, BUB1B, ZWINT, AURKA, MAD2L1 and MCM4, which were all highly expressed in ESCC specimens.
Conclusion:Seven hub genes of ESCC are identified based on bioinformatics, which may serve as biomarkers and therapeutic targets for ESCC.
- Full text:应用生物信息学方法鉴定食管鳞状细胞癌生物标志物.pdf
