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Identification of hub genes with prognostic values in multiple myeloma by bioinformatics analysis

机译:生物信息学分析鉴定多发性骨髓瘤预后值的枢纽基因

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Purpose Multiple myeloma (MM) is a malignant disease with abnormal proliferation of clonal plasma cells. Hypoxia is an important factor in the pathogenesis and development of MM. However, the underlying mechanisms are not fully understood. Material & Methods To determine hub genes related to hypoxia in MM, this study took integrated bioinformatics analysis with two expression datasets (GSE80140 and GSE80545) downloaded from Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were filtrated under the condition of both p -value??1. Then, gene ontology (GO) and Kyoto encyclopedia of genes and genomes enrichment (KEGG) analysis, and protein–protein interaction (PPI) network construction were utilized to further explore these DEGs. PrognoScan evaluated all the candidate hub genes for survival analysis. Results In total, three hub genes, including FH, TSTA3, and POLR3G, were screened out to be related to hypoxia in MM. Patients with the lower expression level of FH, TSTA3, and POLR3G have statistically significantly longer disease- specific survival (Cox p ?0.05). Conclusion We identified FH, TSTA3, and POLR3G as hub genes which can affect MM patients’outcome and new biomarkers for diagnosis and prognosis of MM. Further functional and mechanistic studies are need to develop in order to make them as potential target for clinical treatment.
机译:目的多发性骨髓瘤(mm)是一种恶性疾病,具有克隆血浆细胞异常增殖。缺氧是发病机制和发育的重要因素。然而,潜在机制尚未完全理解。本研究用来自基因表达综合(GEOM)数据库下载的两种表达数据集(GSE80140和GSE80545)进行了与MM相关的缺氧相关的集线基因的材料和方法。在P-value的条件下过滤差异表达基因(DEG)。然后,利用基因本体(GO)和京都基因组富集(KEGG)分析和蛋白质 - 蛋白质相互作用(PPI)网络建设进行进一步探索这些次数。预测评估所有候选中心基因用于存活分析。结果总共三个集线基因,包括FH,TSTA3和POLR3G,筛选出与MM的缺氧有关。 FH,TSTA3和POLR3G表达水平较低的患者具有统计学上显着的致病特异性存活率(COX P& 0.05)。结论我们将FH,TSTA3和POLR3G识别为枢纽基因,可影响MM患者的诊断和新生物标志物,用于诊断和预后MM。需要开发进一步的功能和机械研究,以使它们成为临床治疗的潜在目标。

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