食管鳞状细胞癌中驱动基因的多组学关联分析

Integrated Analysis of Multi-omics Data in Driver Genes of Esophageal Squamous Cell Carcinoma

目的探讨食管鳞癌驱动基因的体细胞突变、拷贝数改变、基因表达和DNA甲基化等多个分子层面的改变及其交互影响。方法从肿瘤基因组图谱计划(TCGA)下载95例食管鳞癌多组学数据,结合实验室前期91例患者测序结果进行分析;根据驱动基因突变将患者分组,对两组患者的基因表达水平进行非配对t检验;通过Spearman秩相关进行拷贝数改变、DNA甲基化与驱动基因表达水平的关联分析;通过Log-Rank检验对突变组和非突变组患者生存曲线进行比较。结果多维度数据关联分析结果显示,驱动基因TP53、RB1、ZNF750和PTCH1的表达水平在突变组与非突变组间比较,差异有统计学意义(P=0.011,FC=1.43;P=0.045,FC=0.44;P=0.012,FC=2.20;P=0.011,FC=2.62);驱动基因CUL3、PIK3CA、RBPJ、FBXW7、CDKN2A、PTEN、RB1和CERBBP的表达水平与其拷贝数改变呈显著正相关;多个驱动基因表达受启动子和基因体甲基化的共同调控,并且在两部分数据中存在差异;驱动基因CREBBP(P=0.000)和FAT1(P=0.002)的突变与患者预后相关,可作为食管鳞癌潜在的预后标志物。结论通过对食管鳞癌多组学数据的整合分析,阐述了食管鳞癌中体细胞突变、拷贝数改变、DNA甲基化与20个驱动基因表达水平的关联,并发现CREBBP和FAT1的突变可能成为食管鳞癌患者潜在的预后标志物。这些结果为进一步探究驱动基因在食管鳞癌中的功能机制奠定了一定基础。

Objective Multi-omics integration analysis was carried out on somatic mutation,copy number alteration,gene expression and DNA methylation of 20 driver genes in esophageal squamous cell carcinoma(ESCC),in order to fully elucidate the role and interaction of each alteration.Methods Multigroup data of 95 cases of ESCC were downloaded from the cancer genome atlas(TCGA)and analyzed in combination with the existing 91 patients in our study.Patients were grouped according to the mutation of driver gene and the gene expression levels of groups were then compared with Student′s t-test.Spearman′s rank correlation was used to drive association analysis of copy number alteration,DNA methylation and gene expression.Kaplan-Meier survival curves of groups with or without driver gene mutation were compared by Log-Rank test.Results Multi-omics integration analysis revealed that,TP53,RB1,ZNF750 and PTCH1 showed significant difference between two groups(P=0.011,FC=1.43;P=0.045,FC=0.44;P=0.012,FC=2.20;P=0.011,FC=2.62).The expression levels of CUL3,PIK3CA,RBPJ,FBXW7,CDKN2A,PTEN,RB1 and CERBBP were significantly correlated with copy number alteration.The expression levels of several driver genes were regulated by DNA methylation of promoter and gene body regions,and they were different between two datasets.The mutations of CREBBP(P=0.000)and FAT1(P=0.002)was associated with ESCC prognosis and can serve as potential prognostic markers.Conclusion Through the integration analysis of multi-omics data in ESCC,we discussed the correlations between somatic mutation,copy number alteration,DNA methylation and gene expression of 20 driver genes,as well as identified successfully two prognostic markers for ESCC.It also laid a foundation for further exploration of underlying mechanism of driver genes in ESCC.