急性早期前体T淋巴细胞白血病核心基因的筛选及其调控网络分析

Identification of Differentially Expressed Gene Core Genes in Early T-Cell Precursor Acute Lymphoblastic Leukemia and Its Regulatory Network Analysis

目的:筛选急性早期前体T淋巴细胞白血病(ETP ALL)核心基因并分析其与上游互作miRNA、lncRNA和参与通路的相互作用,探讨ETP ALL发生发展过程中的调控机制并寻找可用于临床诊疗的分子靶点。方法:利用基因表达公共数据库(Gene Expression Omnibus,GEO)和癌症基因组图谱(The Cancer Genome Atlas,TCGA)数据库的2者交集,筛选ETP ALL差异表达基因集(differentially expressed genes,DEG)分别进行功能富集和相互作用的分析;再利用网络模块划分方法筛选DEG核心基因,并利用mirDIP、star Base在线工具对核心基因上游miRNA、lncRNA进行预测。结果:获得高可信度的差异表达基因424个,基因本体(gene ontology,GO)功能富集于转录调控、信号通路及蛋白功能活化等生物学活性,KEGG通路富集于造血、缺氧应激反应、转录失调、免疫等功能;通过两者相互关联分析。获得7个核心基因,并先后预测到7个miRNA和19个lncRNA符合筛选标准,最后构建出1个lncRNA-miRNA-mRNA-pathway调控网络。结论:基于数据挖掘方法筛选获得ETP ALL中的差异表达基因集,通过共表达分析寻找到其中的核心基因,并对核心基因上游miRNA,lncRNA进行预测,为ETP ALL的早期诊断和合理治疗提供了理论依据,有助于寻找新的区别于经典T-ALL的ETP ALL肿瘤标志物。

Objective:To identify the differentially expressed gene(DEG)core genes in early T-cell precursor acute lymphoblastic leukemia(ETP ALL)and to analyze their interactions with upstream miRN As,lncRNAs and involved pathways;to clarify the regulatory mechanism of ETP ALL development;and to explore the molecular targets for clinical diagnosis and treatment.Methods:The DEG of ETP ALL were screened based on the intersection of GEO database and TCGA database.The functional enrichment analysis and interaction analysis were carried out for DEG.Next,MCODE algorithm was used to screen core genes of DEG,and the mirDIP online tool and starBase online tool were utilized to predict upstream miRNA and lncRNA of the core genes.Results:A total of 424 DEG with a high credibility were identified,which were mainly enriched in the biological activity,such as transcriptional regulation,signaling pathway and protein function activation according to GO function,and the KEGG pathway was enriched in hematopoiesis,anoxic stress response,transcriptional misregulation,immunity and other functions,which interrelated each other 7 core genes were identified.Subsequently,7 miRNAs and 19 lncRNAs were predicted to meet screening criteria.Finally,a lncRNAmiRNA-mRNA-pathway regulatory network was constructed.Conclusion:The DEG in ETP ALL has been identified based on data mining methods;the core genes have been gained by co-expression analysis,and their upstream miRNA and lncRNA can be predicted for the early diagnosis of ETP ALL,thus providing a theoretical basis for the early diagnosis and reasonable treatment of ETP ALL,and helping to look for new tumor biomarkers of ETP ALL different from classical TALL.