Wang Xiaoyuan, Yin Hang, Zhang Luquan, Zheng Dayong, Yang Yingnan, Zhang Jinfeng, Jiang Hao, Ling Xiaodong, Xin Yanzhong, Liang Hao, Fang Chengyuan, Ma Jianqun, Zhu Jinhong
Department of Thoracic Surgery, Molecular Epidemiology Laboratory, Harbin Medical University Cancer Hospital, Harbin 150040, China.
Department of Radiotherapy Oncology, Molecular Epidemiology Laboratory, Harbin Medical University Cancer Hospital, Harbin 150040, China.
J Thorac Dis. 2019 May;11(5):1772-1778. doi: 10.21037/jtd.2019.05.69.
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.
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, P<0.01) 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.
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).
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.
非小细胞肺癌（NSCLC）是最常见的癌症，其发病机制仍不清楚。根据竞争性内源性RNA（ceRNA）理论，长链非编码RNA（lncRNA）与mRNA竞争结合微小RNA（miRNA），从而影响mRNA水平。在本研究中，我们探索了ceRNA网络以及预测生存预后的重要基因。
在本研究中，我们使用edgeR从癌症基因组图谱数据库中识别出NSCLC组织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lncRNA与miRNA或mRNA与miRNA之间的相互作用。此外，使用DAVID和KEGG分析其功能和KEGG通路。通过STRING在线数据库探索这些mRNA之间的联系。利用R语言中的生存包进一步探索网络中基因与生存时间的关系。
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。对68个mRNA的功能和KEGG通路进行了进一步分析。水通道蛋白2（AQP2）、表皮生长因子（EGF）、溶质载体家族12成员1（SLC12A1）、瞬时受体电位香草酸亚型5（TRPV5）和血管加压素受体2（AVPR2）处于网络中心，可能在NSCLC的发生发展中起关键作用。并且mRNA（细胞周期蛋白B1（CCNB1）、Ⅰ型胶原蛋白α1链（COL1A1）、E2F转录因子7（E2F7）、脯氨酰羟化酶结构域蛋白3（EGLN3）、叉头框蛋白G1（FOXG1）和磷酸果糖激酶（PFKP））、miRNA（miR-31、miR-144和miR-192）以及lncRNA（AC假基因80129.1、AC假基因100791.1、AL163952.1、AP000525.1、AP003064.2、2号染色体开放阅读框48（C2orf48）、10号染色体开放阅读框91（C10orf91）、成纤维细胞生长因子12反义RNA2（FGF12-AS2）、HOX转录反义RNA（HOTAIR）、长链非编码RNA 00518（LINC
