共表达网络鉴定食管鳞癌中抗肿瘤细胞毒性分子

Identification of Cytolytic Activity Related Molecules in Esophageal Squamous Cell Carcinoma by Co-expression Network

目的鉴定新的抗食管鳞癌(ESCC)免疫细胞毒性相关分子。方法基于ESCC转录组表达谱数据,利用CIBERSORT反卷积算法计算ESCC样本中免疫细胞构成比;通过加权基因共表达网络分析(WGCNA)构建基因模块;计算免疫细胞构成比与细胞毒性基因、共表达网络模块的相关性,确定关键模块。通过基因的模块隶属度、基因显著性和预后相关性,鉴定关键基因。结果WGCNA方法共构建30个基因模块,其中white模块包含了本研究纳入的所有细胞毒性相关基因(GZMA、PRF1、GZMB和IFNG),将其作为关键模块。关键模块共包含18个关键hub基因,其中8个基因表达异常与ESCC患者预后相关。结论通过基因共表达网络方法,鉴定到8个ESCC细胞毒性相关基因。

Objective To identify novel molecules related to cytolytic activity in esophageal squamous cell carcinoma(ESCC).Methods CIBERSORT was used to enumerate the composition ratio of immune cells in ESCC samples based on transcriptome data.Gene modules were constructed by the weighted gene co-expression network analysis(WGCNA).Correlations between composition ratio of immune cells and cytolytic activity genes,composition ratio of immune cells and modules were calculated to determine key modules.Key genes were identified by module membership,gene significance,and prognostic relevance.The key genes were identified by the module membership,gene significance and prognostic correlation of genes.Results A total of 30 modules were constructed by WGCNA,among which the white module contained all the cytolytic activity genes(GZMA,PRF1,GZMB and IFNG),which was used as key modules.The key module contains a total of 18 hub genes,of which 8 genes have prognostic relevance.Conclusion In this study,several cytolytic activity-related genes were identified by gene co-expression network method.