目的 整合生物信息学挖掘并分析与基底型乳腺癌(basal-like breast cancer,BLBC)的预后相关的核心基因.方法 首先,从GEO数据库中遴选与乳腺癌分子分型相关的数据集,数据处理后利用WGCNA筛选与BLBC相关的模块.然后,借助蛋白-蛋白互作(protein-protein interaction,PPI)网络和cytohubba筛选出模块中差异最大的前10％基因作为候选基因,对候选基因进行生存分析和表达分析得到核心基因.最后,利用TIMER、TISIDB等生信工具探索核心基因表达和肿瘤免疫浸润、趋化因子及免疫调节剂的相关性并构建核心基因转录调控网络.结果 利用WGCNA筛选出与BLBC相关的黑色模块中共891个基因,从差异性最大的80个候选基因中分析获得ESPL1和CCNB2两个核心基因.结果 显示,两个核心基因与BLBC免疫细胞浸润有关,主要包括Th2细胞、CD8+T细胞、内皮细胞和肿瘤相关成纤维细胞.而且,核心基因表达水平与趋化因子、免疫刺激因子、免疫抑制因子及MHC分子相关.核心基因上游转录调控网络表明22种转录因子同时调控两个核心基因.结论 ES-PL1和CCNB2是BLBC的预后标志物且与肿瘤免疫相关.
Identification and Analysis of Hub Genes of Basal-like Breast Cancer by Integrated Bioinformatics Methods
Objective To mine and analyse the hub genes associated with the prognosis of basal-like breast cancer(BLBC)by bioinformatic methods.Methods We searched the GEO database to obtain an appropriate microarray dataset related to molecular subtyp-ing of breast cancer,and identified modules associated with BLBC by WGCNA.Then,the top 10％differential expressed genes in the module were screened as candidate genes using PPI and cytohubba.The candidate genes were subjected to survival analysis and expression analysis to obtain hub genes.Finally,we explored the correlation between the expressive level of hub genes and immune cell infiltration,chemokines,and immunomodulators by TIMER and TISIDB database.Furthermore,transcription factors(TFs)-hub gene network was constructed.Results A total of 891 genes in black modules related to BLBC were analyzed,and two hub genes,ESPL1 and CCNB2,were identified from the 80differential expressed genes.Two hub genes are associated with BLBC immune cell infiltration,mainly inclu-ding Th2 cells,CD8+T cells,endothelial cells,and tumor-associated fibroblasts.They were also related to chemokines,immunostimu-lators,immunosuppressive factors,and MHC molecules.The upstream transcriptional regulatory network of hub genes showed that 22 transcription factors simultaneously regulate two hub genes.Conclusion ESPL1 and CCNB2 are prognostic markers of BLBC and related to breast tumor immunity.
Basal-like breast cancerWeighted gene co-expression network analysisImmune infiltrationTranscription factors
万方数据
维普
