基于GEO数据库筛查急性淋巴细胞白血病糖皮质激素耐药相关基因

目的: 基于全基因组表达芯片筛查急性淋巴细胞白血病糖皮质激素耐药相关的基因，分析其可能参与的信号传导通路。方法: 从GEO数据库中下载表达谱数据集，应用R软件分析急性淋巴细胞白血病糖皮质激素敏感组与耐药组差异表达基因（DEGs），并对差异基因进行基因功能（GO）分析和信号通路富集分析，构建基因间相互作用网络，筛选出关键基因。结果: 共筛选出差异基因109个，其中表达上调基因86个，下调基因23个。GO富集分析得到DEGs主要涉及免疫应答，凝血调节，细胞增殖和凋亡、细胞迁移等生物过程；pathway分析发现DEGs主要富集参与MAPK信号通路、Toll样受体信号通路、NF-κB-MAP通路、细胞凋亡等；互作网络分析挖掘出的关键基因FOS、NFKB1、MAP2K1、IRS1、CASP3。结论: 糖皮质激素耐药的急性淋巴细胞白血病存在基因差异表达，筛选出耐药相关的重要作用基因及信号通路。

Gene microarray Analysis of Glucocorticoid resistance-related genes in Acute Lymphoblastic Leukemia based on GEO

AIM: To detect the differentially expressed genes associated with glucocoticoid resistance by microarray and to analyze the signal transduction pathways in acute lymphoblastic leukemia. METHODS: Downloading the gene chip data from the gene expression omnibus (GEO), R software was used to analyze the differentially expressed genes between glucocorticoid resistance samples and sensitive samples. The function of differential genes was determined by gene ontology (GO) and pathway analysis. Intergene interaction network were constructed to screen key genes. RESULTS: In total, 109 differential genes were screened out, of which 86 genes were up-regulated and 23 genes were down-regulated. GO enrichment analysis revealed that DEGs were mainly involved in biological processes of immune response, blood coagulation, regulation of cell proliferation and apoptosis, cell migration. Pathway analysis showed that DEGs were mostly enriched in Toll like receptor cascade, MAPK pathway, NF-κB-MAP pathway and cell apoptosis. The network analyses identified the hub genes such as FOS, NFKB1, MAP2K1, IRS1, CASP3. CONCLUSION: The glucocrticoid resistance-related ALL shows differentially expressed genes, we screen out the hub genes and signal pathways of glucocrticoid resistance.