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Selection of biomarkers for HIV-1 latency by integrated analysis

机译:综合分析选择HIV-1潜伏期的生物标志物

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A major obstacle in the treatment of human immunodeficiency virus type 1 (HIV-1) is its ability to establish latent infection. To find novel biomarkers associated with the mechanism of HIV-1 latent infection, we identified 70 candidate genes in HIV-1 latently infected cells through the integrated analysis in a previous study. It is important to select more effective biomarkers among 70 candidates and to verify the possibility of selected biomarkers for HIV-1 latency. We identified the 24 and 25 genes from 70 candidate genes in significantly enriched categories selected by Database for Annotation, Visualization and Integrated Discovery (DAVID) software and Gene Set Enrichment Analysis (GSEA) software, respectively. Also, we investigated genes regulated in both HIV-1 latently infected cell lines and PBMCs from HIV-1 infected patients and found the genes with a common pattern of expression levels in both cell lines and PBMCs. Consequently, we identified nine genes, APBB2, GMPR, IGF2BP3, LRP1, MAD2L2, MX1, OXR1, PTK2B, and TNFSF13B, via integrated analysis. Especially, APBB2 and MAD2L2 were identified in both DAVID and GSEA software. Our findings suggest that nine genes were identified via integrated analysis as potential biomarkers and in particular, APBB2 and MAD2L2 may be considered as more significant biomarkers for HIV-1 latency.
机译:治疗人免疫缺陷病毒1型(HIV-1)的主要障碍是其建立潜在感染的能力。为了寻找与HIV-1潜入感染机制相关的新生物标志物,通过在先前的研究中通过综合分析确定了HIV-1潜在感染细胞中的70个候选基因。重要的是在70个候选者中选择更有效的生物标志物,并验证选定的生物标志物的HIV-1潜伏期的可能性。我们鉴定了70个候选基因的24和25个基因,以分别由数据库选择的重要浓缩类别,分别用于注释,可视化和集成发现(David)软件和基因集体富集分析(GSEA)软件。此外,我们研究了来自HIV-1潜伏的细胞系和来自HIV-1感染患者的PBMC的基因,并发现了细胞系和PBMC中具有常见表达水平模式的基因。因此,我们通过综合分析确定了九种基因,APBB2,GMPR,IGF2BP3,LRP1,MAD2L2,MX1,OXR1,PTK2B和TNFSF13B。特别是,在David和GSEA软件中识别出APBB2和Mad2L2。我们的研究结果表明,通过综合分析鉴定九种基因作为潜在的生物标志物,特别是APBB2和MAD2L2可被认为是HIV-1潜伏期的更重要的生物标志物。

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