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基于生物信息学分析的 miRNA 芯片鉴定神经母细胞瘤中枢纽 miRNA 并构建 miRNA-mRNA 网络

Integrated Microarray to Identify the Hub miRNAs and Constructed miRNA-mRNA Network in Neuroblastoma Via Bioinformatics Analysis.

机构信息

Department of Pediatrics, Shengjing Hospital of China Medical University, Shenyang, China.

Medical Research Center, Liaoning Key Laboratory of Research and Application of Animal Models for Environmental and Metabolic Diseases, Shengjing Hospital of China Medical University, #36 Sanhao Street, Heping District, Shenyang, 110004, China.

出版信息

Neurochem Res. 2021 Feb;46(2):197-212. doi: 10.1007/s11064-020-03155-3. Epub 2020 Oct 26.

Abstract

Neuroblastomas (NB) are childhood malignant tumors originating in the sympathetic nervous system. MicroRNAs (miRNAs) play an essential regulatory role in tumorigenesis and development. In this study, NB miRNA and mRNA expression profile data in the Gene Expression Omnibus database were used to screen for differentially expressed miRNAs (DEMs) and genes (DEGs). We used the miRTarBase and miRSystem databases to predict the target genes of the DEMs, and we selected target genes that overlapped with the DEGs as candidate genes for further study. Annotations, visualization, and the DAVID database were used to perform Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis on the candidate genes. Additionally, the protein-protein interaction (PPI) network and miRNA-mRNA regulatory network were constructed and visualized using the STRING database and Cytoscape, and the hub modules were analyzed for function and pathway enrichment using the DAVID database and BiNGO plug-in. 107 DEMs and 1139 DEGs were identified from the miRNA and mRNA chips, respectively. 4390 overlapping target genes were identified using the two databases, and 405 candidate genes which intersected with the DEGs were selected. These candidate genes were enriched in 363 GO terms and 24 KEGG pathways. By constructing a PPI network and a miRNA-mRNA regulatory network, three hub miRNAs (hsa-miR-30e-5p, hsa-miR-15a, and hsa-miR-16) were identified. The target genes of the hub miRNAs were significantly enriched in the following pathways: microRNAs in cancer, the PI3K-Akt signaling pathway, pathways in cancer, the p53 signaling pathway, and the cell cycle. In summary, our results have identified candidate genes and pathways related to the underlying molecular mechanism of NB. These findings provide a new perspective for NB research and treatment.

摘要

神经母细胞瘤(NB)是起源于交感神经系统的儿童期恶性肿瘤。microRNAs(miRNAs)在肿瘤发生和发展中发挥着重要的调节作用。本研究利用基因表达综合数据库(GEO)中 NB 的 miRNA 和 mRNA 表达谱数据,筛选差异表达的 miRNAs(DEMs)和基因(DEGs)。我们使用 miRTarBase 和 miRSystem 数据库预测 DEMs 的靶基因,并选择与 DEGs 重叠的靶基因作为进一步研究的候选基因。使用注释、可视化和 DAVID 数据库对候选基因进行基因本体论(GO)和京都基因与基因组百科全书(KEGG)富集分析。此外,使用 STRING 数据库和 Cytoscape 构建和可视化蛋白质-蛋白质相互作用(PPI)网络和 miRNA-mRNA 调控网络,并使用 DAVID 数据库和 BiNGO 插件分析功能和途径富集。从 miRNA 和 mRNA 芯片中分别鉴定出 107 个 DEMs 和 1139 个 DEGs。使用两个数据库鉴定出 4390 个重叠的靶基因,并选择与 DEGs 相交的 405 个候选基因。这些候选基因富集在 363 个 GO 术语和 24 个 KEGG 途径中。通过构建 PPI 网络和 miRNA-mRNA 调控网络,鉴定出三个 hub miRNAs(hsa-miR-30e-5p、hsa-miR-15a 和 hsa-miR-16)。hub miRNAs 的靶基因在以下途径中显著富集:癌症中的 microRNAs、PI3K-Akt 信号通路、癌症途径、p53 信号通路和细胞周期。总之,本研究结果鉴定出与 NB 潜在分子机制相关的候选基因和途径。这些发现为 NB 的研究和治疗提供了新的视角。

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