Abstract【Objective】 To screen and identify the key pivotal genes of ESCC by bioinformatics methods based on transcriptome data of ESCC from geo and TCGA databases.【Methods】 GSE17351 dataset and RNA-seq data of ESCC were downloaded from GEO and TCGA databases. Then Limma package of R software was applied to screen differentially expressed genes; ClusterProfiler package was used to perform GO analysis and KEGG Pathway enrichment; STRING tool was used to analyze the interaction network among proteins encoded by differential genes and the interactome was visualized by Cytoscape software; Cytoscape's Cytohubba plug-in was subjected to analyze key hub genes among interactome; The prognostic values of hub genes were analyzed by K-M plotter. 【Results】 A total of 167 differentially expressed genes were screened by GEO and TCGA; The differentially expressed genes were mainly related to GO processes such as mitosis, ATPase activity and DNA helicase activity, and were significantly enriched in DNA cell cycle, DNA replication, mismatch repair, oocyte meiosis, ECM receptor interaction, p53 and Wnt signaling pathways; A total of 10 key genes were screened, including BUB1,MAD2L1,NUF2,KIF18A,CENPK,CENPN,CENPQ and SPC25,which were negatively correlated with the prognosis of patients with ESCC.【Conclusion】 Ten key pivotal genes of ESCC were screened, and eight of them were related to prognosis, which provided potential targets for molecular mechanism research and prognosis judgment of ESCC.
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2021, Vol. 38 
