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探讨肝癌中 miRNA 和 mRNA 共表达网络及其预后价值。

Investigation of the miRNA and mRNA Coexpression Network and Their Prognostic Value in Hepatocellular Carcinoma.

机构信息

Department of Hepatobiliary and Pancreatic Surgery, Zhongnan Hospital of Wuhan University, Donghu Road 169# Wuhan 430071, China.

出版信息

Biomed Res Int. 2020 Nov 12;2020:8726567. doi: 10.1155/2020/8726567. eCollection 2020.

Abstract

PURPOSE

To identify pivotal differentially expressed miRNAs and genes and construct their regulatory network in hepatocellular carcinoma.

METHODS

mRNA (GSE101728) and microRNA (GSE108724) microarray datasets were obtained from the NCBI Gene Expression Omnibus (GEO) database. Then, we identified the differentially expressed miRNAs and mRNAs. Sequentially, transcription factor enrichment and gene ontology (GO) enrichment analysis for miRNA were performed. Target genes of these differential miRNAs were obtained using packages in language ( package ). After that, downregulated miRNAs were matched with target mRNAs which were upregulated, while upregulated miRNAs were paired with downregulated target mRNA using scripts written in Perl. An miRNA-mRNA network was constructed and visualized in Cytoscape software. For miRNAs in the network, survival analysis was performed. And for genes in the network, we did gene ontology (GO) and KEGG pathway enrichment analysis.

RESULTS

A total of 35 miRNAs and 295 mRNAs were involved in the network. These differential genes were enriched in positive regulation of cell-cell adhesion, positive regulation of leukocyte cell-cell adhesion, and so on. Eight differentially expressed miRNAs were found to be associated with the OS of patients with HCC. Among which, miR-425 and miR-324 were upregulated while the other six, including miR-99a, miR-100, miR-125b, miR-145, miR-150, and miR-338, were downregulated.

CONCLUSION

In conclusion, these results can provide a potential research direction for further studies about the mechanisms of how miRNA affects malignant behavior in hepatocellular carcinoma.

摘要

目的

鉴定肝癌中关键差异表达的 miRNA 和基因,并构建它们的调控网络。

方法

从 NCBI 基因表达综合数据库(GEO)中获取 mRNA(GSE101728)和 microRNA(GSE108724)微阵列数据集。然后,我们鉴定了差异表达的 miRNA 和 mRNAs。接着,对 miRNA 进行转录因子富集和基因本体(GO)富集分析。使用 R 语言中的 packages 获得这些差异 miRNA 的靶基因。然后,使用 Perl 编写的脚本将下调的 miRNA 与上调的靶 mRNA 进行匹配,将上调的 miRNA 与下调的靶 mRNA 进行配对。在 Cytoscape 软件中构建并可视化 miRNA-mRNA 网络。对网络中的 miRNA 进行生存分析,对网络中的基因进行基因本体(GO)和 KEGG 通路富集分析。

结果

该网络共包含 35 个 miRNA 和 295 个 mRNAs。这些差异基因富集于细胞-细胞间黏附的正调控、白细胞细胞-细胞间黏附的正调控等。发现 8 个差异表达的 miRNA 与 HCC 患者的 OS 相关。其中,miR-425 和 miR-324 上调,而其余 6 个 miRNA,包括 miR-99a、miR-100、miR-125b、miR-145、miR-150 和 miR-338,下调。

结论

综上所述,这些结果可为进一步研究 miRNA 影响肝癌恶性行为的机制提供潜在的研究方向。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bef2/7676931/a7f01da5f1b5/BMRI2020-8726567.001.jpg

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