Transcriptomic Analysis of mRNA-lncRNA-miRNA Interactions in Hepatocellular Carcinoma
Transcriptomic Analysis of mRNA-lncRNA-miRNA Interactions in Hepatocellular Carcinoma
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肝细胞癌中 mRNA-lncRNA-miRNA 相互作用的转录组分析
DOI：
10.1038/s41598-019-52559-x
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发表时间：
2019-11-06
影响因子：
4.6
通讯作者：
Ding, Keyue
中科院分区：
文献类型：
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作者：
Tang, Xia;Feng, Delong;Ding, Keyue
充分阐明非编码RNA（ncRNA），包括微小RNA（miRNAs）和长链非编码RNA（lncRNA）的分子机制是具有挑战性的。我们对9例肝细胞癌（HCC）患者的ncRNA表达谱进行了表征，并构建了基于转录组测序（RNA-seq）的调控mRNA-lncRNA-miRNA（MLMI）网络。在鉴定的miRNAs（n = 203）和lncRNAs（n = 1，090）中，我们发现了16个显著差异表达（DE）miRNAs和3个DE lncRNAs。DE RNA在21个与HCC有关的功能通路中高度富集（p < 0.05），包括p53、MAPK和NAFLD信号传导。使用计算机模拟预测和实验验证的证据充分表征了DE ncRNA和mRNA之间的潜在成对相互作用。我们首次构建了肝癌中16种miRNAs、3种lncRNAs和253种mRNAs相互作用的MLMI网络。MEG 3在MLMI网络中的主导作用通过其体外过表达得到验证，即MEG 3靶向的miRNA和mRNA的表达水平的比例发生了显著变化。我们的研究结果表明，全面的MLMI网络协同调制的致癌作用，网络的串扰提供了一个新的途径，以准确地描述肝癌发生的分子机制。
Fully elucidating the molecular mechanisms of non-coding RNAs (ncRNAs), including micro RNAs (miRNAs) and long non-coding RNAs (lncRNAs), underlying hepatocarcinogenesis is challenging. We characterized the expression profiles of ncRNAs and constructed a regulatory mRNA-lncRNA-miRNA (MLMI) network based on transcriptome sequencing (RNA-seq) of hepatocellular carcinoma (HCC, n = 9) patients. Of the identified miRNAs (n = 203) and lncRNAs (n = 1,090), we found 16 significantly differentially expressed (DE) miRNAs and three DE lncRNAs. The DE RNAs were highly enriched in 21 functional pathways implicated in HCC (p < 0.05), including p53, MAPK, and NAFLD signaling. Potential pairwise interactions between DE ncRNAs and mRNAs were fully characterized using in silico prediction and experimentally-validated evidence. We for the first time constructed a MLMI network of reciprocal interactions for 16 miRNAs, three lncRNAs, and 253 mRNAs in HCC. The predominant role of MEG3 in the MLMI network was validated by its overexpression in vitro that the expression levels of a proportion of MEG3-targeted miRNAs and mRNAs was changed significantly. Our results suggested that the comprehensive MLMI network synergistically modulated carcinogenesis, and the crosstalk of the network provides a new avenue to accurately describe the molecular mechanisms of hepatocarcinogenesis.