Abstract:

Objective To analyze the relationship between Differentially Expressed Genes（DEGs）and prognosis in Esophageal Squamous Cell Carcinoma（ESCC），explore the key pathways affecting the development of ESCC. Methods The R language′ s limma program was used to screen DEGs from ESCC transcriptomics data downloaded from the Gene Expression Omnibus（GEO）and The Cancer Genome Atlas（TCGA）databases. The Cox regression models were used to screen for independent prognostic genes in ESCC. The TIMER database was used to investigate the relationship between independent prognostic genes and immune infiltrating cells. To predict the regulatory network of DEGs in ESCC，Gene Set Enrichment Analysis（GSEA）and Gene Set Variation Analysis （GSVA）were used. Results The GSE17351，GSE20347，GSE100942 and TCGA datasets yielded a total of 55 common DEGs，with 40 up⁃regulated and 15 down⁃regulated genes. Univariate Cox regression analysis of 55 com⁃ mon DEGs indicated the 7 DEGs，including TTK，CHEK1，FEN1，KIF14，NUP155，KIF23 and CENPE，were related to the overall survival time of ESCC patients. Multivariate Cox regression analysis showed only TTK could be used as an independent prognostic factor for ESCC. TTK may influence the development of ESCC by regulating cell cycle,DNA damage repair，and other cell proliferation⁃related pathways，according to GSEA and GSVA results. Conclusion The up⁃regulation of TTK could be used as a potential poor prognostic marker in ESCC. 

Key words: TCGA database,  , GEO database,  , esophageal squamous cell carcinoma,  , differentially expressed genes,  , prognosis