食管鳞癌预后生物标志物的挖掘及其通路分析

Analysis of prognostic biomarkers and pathways in esophageal squamous cell carcinoma

目的分析食管鳞癌(ESCC)组织中的差异表达基因(DEGs)与预后的关系,并探索影响食管鳞癌发生的关键通路。方法R语言limma程序对基因表达数据库(GEO)与癌症基因图谱(TCGA)数据库的食管鳞癌转录组数据进行差异表达基因进行分析。Cox回归模型筛选食管鳞癌独立预后基因。TIMER数据库进行独立预后基因与免疫浸润细胞之间的相关性分析。基因集富集分析(GSEA)和基因集变异分析(GSVA)预测差异基因的调控网络。结果分析三个GEO数据集(GSE17351、GSE20347和GSE100942)和TCGA的差异表达基因结果,得到55个共同差异表达基因(40个上调和15个下调基因)。对55个基因进行单因素Cox回归分析,发现TTK、CHEK1、FEN1、KIF14、NUP155、KIF23和CENPE与食管鳞癌患者总体生存时间相关。对7个预后相关基因进行多因素Cox回归分析,发现TTK可作为食管鳞癌的独立预后因素。GSEA和GSVA结果显示TTK可能通过调节细胞周期、DNA损伤修复等通路影响食管鳞癌的发生发展。结论TTK高表达是一种预后不良因素,可能作为食管鳞癌的潜在预后标志物。

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 common 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.