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Identification of key candidate genes and pathways in multiple myeloma by integrated bioinformatics analysis

机译: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途径

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摘要

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 and were obtained from the Gene Expression Omnibus database, and differentially expressed genes (DEGs) with p < .05 and [logFC] > 1 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.
机译:多发性骨髓瘤(MM)是一种常见的血液系统恶性肿瘤,其潜在的分子机制仍不清楚。这项研究旨在通过综合的生物信息学分析阐明MM中的关键候选基因和途径。表达谱和从基因表达综合数据库获得,并鉴定了具有p <0.05和[logFC]> 1的差异表达基因(DEG)。然后进行功能富集,蛋白质-蛋白质相互作用网络的构建和生存分析。首先,确定了两个GSE数据集之间共享的51个上调的DEG和78个下调的DEG。其次,功能富集分析表明,这些DEG主要参与B细胞受体信号传导途径,造血细胞谱系和NF-κB途径。此外,免疫系统过程的相互关系分析显示,下调的DEG的富集主要集中在B细胞分化,单核细胞趋化性的正调控和T细胞增殖的正调控。最后,使用PrognoScan数据库评估了DEG表达与MM生存之间的相关性。总之,我们确定了影响MM患者预后的关键候选基因,这些基因可能作为潜在的治疗靶标。

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