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首页> 外文期刊>Frontiers in Cell and Developmental Biology >Exploring the Effect of Differentially Expressed Long Non-coding RNAs Driven by Copy Number Variation on Competing Endogenous RNA Network by Mining Lung Adenocarcinoma Data
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Exploring the Effect of Differentially Expressed Long Non-coding RNAs Driven by Copy Number Variation on Competing Endogenous RNA Network by Mining Lung Adenocarcinoma Data

机译：通过采矿肺腺癌数据探索常规表达长期非编码RNA对竞争内源性RNA网络的拷贝数变异的影响

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Lung cancer is the first cause of cancer death, and gene copy number variation (CNV) is a vital cause of lung cancer progression. Prognosis prediction of patients and medication guidance by detecting CNV of lung cancer are promising precision treatments in the future. In this paper, the differences in CNV, long non-coding RNA (lncRNA) expression, mRNA expression, and microRNA (miRNA) expression between cancer tissue and normal tissue of lung adenocarcinoma (LUAD) from TCGA-LUAD data set were analyzed, and greater differences were observed. Furthermore, CNV-driven differentially expressed lncRNAs (DElncRNAs) were screened out based on CNV of DElncRNA coding genes, and the competing endogenous RNA (ceRNA) regulatory network related to gene CNV was explored. It was found that the network contained 9 lncRNAs, 7 miRNAs and 178 downstream mRNAs. After obtaining the ceRNA regulatory network, pathway enrichment analyses were performed to find that downstream mRNAs were mainly enriched in biological pathways related to cell division, DNA repair and so on, which mainly affected the replication and growth of tumor cells. Besides, the relationship between lncRNAs and drug effects was explored based on previous studies, and it was found that LINC00511 and LINC00942 in the CNV-associated ceRNA network could be used to determine tumor response to drug treatment. The drugs affected by these two lncRNAs mainly focused on metabolism, TOR signaling pathway, PI3K signaling pathway, EGFR signaling pathway and cell cycle. In summary, research was conducted on the CNV, lncRNAs, mRNAs and miRNAs of lung cancer and 9 lncRNAs that could affect the ceRNA network were discovered. There were two lncRNAs in the CNV-associated ceRNA network that could be used to determine drug response.
机译：肺癌是癌症死亡的第一个原因，基因拷贝数变异（CNV）是肺癌进展的重要原因。通过检测肺癌CNV患者和药物指导的预后预测是未来有前途的精确治疗。在本文中，分析了TCGA-LUAD数据集的CNV，长期非编码RNA（LNCRNA）表达，mRNA表达和MICRRNA（miRNA）的癌组织和正常组织之间的差异，并进行了来自TCGA-LUAD数据集的癌组织和正常组织的表达观察到更大的差异。此外，基于DelncrNa编码基因的CNV筛选CNV驱动的差异表达的LNCRNA（DelncrNA），探讨了与基因CNV相关的竞争内源性RNA（Cerna）调节网络。发现该网络包含9个LNCRNA，7个miRNA和178个下游MRNA。在获得Cerna调节网络后，进行途径富集分析以发现下游MRNAS主要富集在与细胞分裂，DNA修复等相关的生物途径中，这主要影响了肿瘤细胞的复制和生长。此外，基于先前的研究探讨了LNCRNA和药物效应之间的关系，发现CNV相关的Cerna网络中的LINC00511和LINC00942可用于确定对药物治疗的肿瘤反应。受这两个LNCRNA影响的药物主要集中在代谢上，托信号通路，PI3K信号通路，EGFR信号通路和细胞周期。总之，在CNV，LNCRNA，MRNA和MIRNA的肺癌和9个可能影响CERNA网络的LNCRNA进行研究。 CNV相关的Cerna网络中有两个LNCRNA可用于确定药物反应。

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