Identification of key candidate genes and pathways in multiple myeloma by integrated bioinformatics analysis
Identification of key candidate genes and pathways in multiple myeloma by integrated bioinformatics analysis
复制标题
通过综合生物信息学分析鉴定多发性骨髓瘤的关键候选基因和通路。
DOI：
10.1002/jcp.28947
复制
发表时间：
2019-12-01
影响因子：
5.6
通讯作者：
Cai, Zhen
中科院分区：
文献类型：
--
作者：
Yan, Haimeng;Zheng, Gaofeng;Cai, Zhen
Multiple myeloma (MM) is a common hematologic malignancy for which the underlying molecular mechanisms remain largely unclear. This study aimed to elucidate key candidate genes and pathways in MM by integrated bioinformatics analysis. Expression profiles GSE6477 and GSE47552 were obtained from the Gene Expression Omnibus database, and differentially expressed genes (DEGs) with p1 were identified. Functional enrichment, protein-protein interaction network construction and survival analyses were then performed. First, 51 upregulated and 78 downregulated DEGs shared between the two GSE datasets were identified. Second, functional enrichment analysis showed that these DEGs are mainly involved in the B cell receptor signaling pathway, hematopoietic cell lineage, and NF-kappa B pathway. Moreover, interrelation analysis of immune system processes showed enrichment of the downregulated DEGs mainly in B cell differentiation, positive regulation of monocyte chemotaxis and positive regulation of T cell proliferation. Finally, the correlation between DEG expression and survival in MM was evaluated using the PrognoScan database. In conclusion, we identified key candidate genes that affect the outcomes of patients with MM, and these genes might serve as potential therapeutic targets.
