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首页> 外文期刊>Journal of Thoracic Disease >The construction and analysis of the aberrant lncRNA-miRNA-mRNA network in non-small cell lung cancer
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The construction and analysis of the aberrant lncRNA-miRNA-mRNA network in non-small cell lung cancer

机译：非小细胞肺癌lncRNA-miRNA-mRNA异常网络的构建与分析

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Background: Non-small cell lung cancer (NSCLC) is the most common cancer and the pathogenesis remain unclear. According to the competing endogenous RNA (ceRNA) theory, long noncoding RNA (lncRNA) have a competition with mRNAs for the connecting with miRNAs that affecting the level of mRNA. In this work, the ceRNA network and the important genes to predict the survival prognosis were explored. Methods: In the study, we recognized differently expressed genes (mRNAs, lncRNAs and miRNAs) between NSCLC and normal tissues from The Cancer Genome Atlas database (fold change 2, P0.01) using edgeR. Then, the interaction between lncRNA and miRNA or mRNA and miRNA was explored by miRcode, miRDB, TargetScan, and miRanda. Furthermore, the functions and KEGG pathway were analyzed with DAVID and KOBAS. The connections of these mRNAs were explored by STRING online database. The relation between genes in the network and survival time were further explored by survival package in R. Results: By bioinformatics tools, we explored 155 lncRNAs, 30 miRNAs and 68 mRNAs and constructed ceRNA network. The functions and KEGG pathway of 68 mRNAs were further analyzed. AQP2, EGF, SLC12A1, TRPV5 and AVPR2 was in the center of network and may play key roles in the development of NSCLC. And mRNA (CCNB1, COL1A1, E2F7, EGLN3, FOXG1 and PFKP), miRNA (miR-31, miR-144 and miR-192) and lncRNA (AC080129.1, AC100791.1, AL163952.1, AP000525.1, AP003064.2, C2orf48, C10orf91, FGF12-AS2, HOTAIR, LINC00518, LNX1-AS1, MED4-AS1, MIG31HG, MUC2, TTTY16 and UCA1) were closely related with overall survival (OS). Conclusions: In summary, the present study provides a deeper understanding of the lncRNA-related ceRNA network in NSCLC and some genes may be new target to treat for NSCLC patients.
机译：背景：非小细胞肺癌（NSCLC）是最常见的癌症，其发病机制仍不清楚。根据竞争性内源RNA（ceRNA）理论，长非编码RNA（lncRNA）与mRNA竞争与影响mRNA水平的miRNA连接。在这项工作中，探索了ceRNA网络和预测生存预后的重要基因。方法：在这项研究中，我们使用edgeR从Cancer Genome Atlas数据库中识别了NSCLC与正常组织之间差异表达的基因（mRNA，lncRNA和miRNA）（倍数变化> 2，P <0.01）。然后，通过miRcode，miRDB，TargetScan和miRanda探索了lncRNA与miRNA或mRNA与miRNA之间的相互作用。此外，用DAVID和KOBAS分析了功能和KEGG途径。这些mRNA的联系已通过STRING在线数据库进行了探索。结果：通过生物信息学工具，我们探索了155个lncRNA，30个miRNA和68个mRNA，并构建了ceRNA网络。进一步分析了68个mRNA的功能和KEGG途径。 AQP2，EGF，SLC12A1，TRPV5和AVPR2处于网络的中心，并可能在NSCLC的发展中发挥关键作用。和mRNA（CCNB1，COL1A1，E2F7，EGLN3，FOXG1和PFKP），miRNA（miR-31，miR-144和miR-192）和lncRNA（AC080129.1，AC100791.1，AL163952.1，AP000525.1，AP003064 .2，C2orf48，C10orf91，FGF12-AS2，HOTAIR，LINC00518，LNX1-AS1，MED4-AS1，MIG31HG，MUC2，TTTY16和UCA1与总体生存率（OS）密切相关。结论：总而言之，本研究对NSCLC中与lncRNA相关的ceRNA网络提供了更深入的了解，并且某些基因可能成为NSCLC患者治疗的新靶标。

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