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目的筛选多发性骨髓瘤(MM)患者与正常人群之间的差异表达基因(DEGs),探究MM的发病机制,为MM的基因诊断和治疗提供导向。方法从GEO数据库中检索获取MM患者的芯片数据,通过Morpheus在线工具进行芯片数据质量控制和DEGs的筛选,运用DAVID数据库对筛选获得的DEGs行基因富集和通路分析,通过STRING数据库构建蛋白相互作用网络,并采用Cytoscape软件行模块分析。结果共获得16 211个DEGs,包括7 586个上调基因和8 625个下调基因(P<0.05)。基因本体(GO)分析结果表明,生物学过程中上调DEGs主要涉及鞘糖脂代谢等30个功能簇,下调DEGs涉及细胞分裂等163个功能簇;分子功能中上调DEGs主要涉及蛋白质结合等29个功能簇,下调DEGs主要涉及组蛋白结合等59个功能簇;细胞成分中上调DEGs主要集中在细胞溶质等27个功能簇中,而下调DEGs主要集中在核质等78个功能簇中。京都基因与基因组百科全书(KEGG)分析结果表明,上调DEGs主要涉及溶酶体相关通路等26条通路,下调DEGs主要涉及DNA复制等27条通路。蛋白互作网络分析示CDK1、TOP2A、AURKB、BRCA1、CHEK1、PTEN、RAD51、GMPS、CDC45和CDKN2A 10个基因为富集程度最高的核心DEGs,模块分析显示得分最高的3个基因模块主要与核分裂、DNA复制和核酸代谢过程相关。结论通过多种生物信息学方法筛选获得了MM患者和健康对照组的DEGs,并从不同角度阐释了MM发病机制的相关基因及其表达特征,为MM特异性诊断标志和靶向治疗等提供了依据。
Objective To screen differentially expressed genes (DEGs) between patients with multiple myeloma (MM) and normal subjects, to explore the pathogenesis of MM and to provide guidance for the gene diagnosis and treatment of MM. METHODS: Chips from patients with MM were retrieved from the GEO database. Chip data quality control and DEGs screening were performed using the Morpheus online tool. Genes enrichment and pathway analysis of DEGs were screened using the DAVID database. Protein interactions were constructed using the STRING database Network, and use Cytoscape software line module analysis. Results A total of 16 211 DEGs were obtained, including 7 586 up-regulated genes and 8 625 down-regulated genes (P <0.05). The results of GO analysis showed that up-regulation of DEGs in biological processes mainly involved 30 functional clusters such as glycosphingolipid metabolism and down-regulation of 163 functional clusters such as cell division. Up-regulation of DEGs in molecular functions mainly involved 29 protein-binding There were 59 functional clusters in which DEGs were down-regulated, such as histone binding. DEGs in cellular components were mainly concentrated in 27 functional clusters such as cytosol, while down-regulation of DEGs mainly concentrated in 78 functional clusters such as nuclear. The Kyoto Encyclopedia of Gene and Genome (KEGG) analysis showed that up-regulation of DEGs mainly involved 26 pathways such as lysosome-related pathways, and down-regulation of DEGs mainly involved 27 pathways such as DNA replication. The protein interaction network analysis showed that 10 genes of CDK1, TOP2A, AURKB, BRCA1, CHEK1, PTEN, RAD51, GMPS, CDC45 and CDKN2A were the most abundant DEGs. DNA replication and nucleic acid metabolism. Conclusion DEGs of MM patients and healthy controls were screened by a variety of bioinformatics methods, and the genes involved in the pathogenesis of MM and their expression characteristics were elucidated from different perspectives, which provided evidence for MM-specific diagnostic markers and targeted therapy in accordance with.