A circRNA-miRNA-mRNA network identification for exploring underlying pathogenesis and therapy strategy of hepatocellular carcinoma.
A circRNA-miRNA-mRNA network identification for exploring underlying pathogenesis and therapy strategy of hepatocellular carcinoma.
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circRNA-miRNA-mRNA网络鉴定，探索肝细胞癌的潜在发病机制和治疗策略
DOI：
10.1186/s12967-018-1593-5
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发表时间：
2018-08-09
影响因子：
7.4
通讯作者：
Chen G
中科院分区：
文献类型：
--
作者：
Xiong DD;Dang YW;Lin P;Wen DY;He RQ;Luo DZ;Feng ZB;Chen G
环状RNA（CircRNA）在人类肿瘤研究中受到越来越多的关注。然而，仍有大量未知的circRNA需要破译。本研究的目的是挖掘新型circRNA及其在肝细胞癌（HCC）中的作用机制。采用大数据挖掘、逆转录-定量聚合酶链反应（RT-qPCR）和计算生物学相结合的策略，挖掘HCC相关的circRNA，并探讨其潜在的作用机制。进行连接图（CMap）分析以鉴定HCC的潜在治疗剂。使用RobustRankAggreg方法从三个基因表达Omnibus微阵列数据集（GSE 78520、GSE 94508和GSE 97332）获得六种不同表达的circRNA。在RT-qPCR确证后，选择三种circRNA（hsa_circRNA_102166、hsa_circRNA_100291和hsa_circRNA_104515）用于进一步分析。预测了三种circRNA的miRNA响应元件。鉴定了五种circRNA-miRNA相互作用，包括两种circRNA（hsa_circRNA_104515和hsa_circRNA_100291）和五种miRNA（hsa-miR-1303、hsa-miR-142- 5 p、hsa-miR-877- 5 p、hsa-miR-583和hsa-miR-1276）。收集上述5种miRNAs的1424个靶基因和3278个肝癌差异表达基因（DEG）。将miRNA靶基因与DEG交叉，共获得172个重叠基因。构建了基于172个基因的蛋白质相互作用网络，并从中确定了JUN、MYCN、AR、ESR 1、FOXO 1、IGF 1和CD 34 7个中心基因。基因肿瘤学、京都基因与基因组百科全书和Reactome富集分析显示，这7个hubgenes与一些癌症相关的生物学功能和途径有关。此外，通过CMap分析，基于七个hubgenes的三种生物活性化学品（地西他滨，BW-B70 C和吉非替尼）被确定为HCC的治疗选择。我们的研究从circRNA-miRNA-mRNA网络的角度为HCC的发病机制和治疗提供了新的见解。
Circular RNAs (circRNAs) have received increasing attention in human tumor research. However, there are still a large number of unknown circRNAs that need to be deciphered. The aim of this study is to unearth novel circRNAs as well as their action mechanisms in hepatocellular carcinoma (HCC). A combinative strategy of big data mining, reverse transcription-quantitative polymerase chain reaction (RT-qPCR) and computational biology was employed to dig HCC-related circRNAs and to explore their potential action mechanisms. A connectivity map (CMap) analysis was conducted to identify potential therapeutic agents for HCC. Six differently expressed circRNAs were obtained from three Gene Expression Omnibus microarray datasets (GSE78520, GSE94508 and GSE97332) using the RobustRankAggreg method. Following the RT-qPCR corroboration, three circRNAs (hsa_circRNA_102166, hsa_circRNA_100291 and hsa_circRNA_104515) were selected for further analysis. miRNA response elements of the three circRNAs were predicted. Five circRNA–miRNA interactions including two circRNAs (hsa_circRNA_104515 and hsa_circRNA_100291) and five miRNAs (hsa-miR-1303, hsa-miR-142-5p, hsa-miR-877-5p, hsa-miR-583 and hsa-miR-1276) were identified. Then, 1424 target genes of the above five miRNAs and 3278 differently expressed genes (DEGs) on HCC were collected. By intersecting the miRNA target genes and the DEGs, we acquired 172 overlapped genes. A protein–protein interaction network based on the 172 genes was established, with seven hubgenes (JUN, MYCN, AR, ESR1, FOXO1, IGF1 and CD34) determined from the network. The Gene Oncology, Kyoto Encyclopedia of Genes and Genomes and Reactome enrichment analyses revealed that the seven hubgenes were linked with some cancer-related biological functions and pathways. Additionally, three bioactive chemicals (decitabine, BW-B70C and gefitinib) based on the seven hubgenes were identified as therapeutic options for HCC by the CMap analysis. Our study provides a novel insight into the pathogenesis and therapy of HCC from the circRNA–miRNA–mRNA network view.
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circRNA生物合成的调控
影响因子：
4.1
作者：
Chen, Ling-Ling;Yang, Li
通讯作者：
Yang, Li
影响因子：
4.1
作者：
Dudekulay, Dawood B.;Panda, Amaresh C.;Gorospe, Myriam
通讯作者：
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影响因子：
9.7
作者：
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通讯作者：
Chang, Chawnshang
影响因子：
5.2
作者：
Hishida, Mitsuhiro;Nomoto, Shuji;Kodera, Yasuhiro
通讯作者：
Kodera, Yasuhiro
影响因子：
3
作者：
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通讯作者：
Hogue, CW