Identification of circRNA-miRNA-mRNA networks contributes to explore underlying pathogenesis and therapy strategy of gastric cancer.
Identification of circRNA-miRNA-mRNA networks contributes to explore underlying pathogenesis and therapy strategy of gastric cancer.
复制标题
DOI：
10.1186/s12967-021-02903-5
复制
发表时间：
2021-05-28
影响因子：
7.4
通讯作者：
Yao W
中科院分区：
文献类型：
--
作者：
Dong Z;Liu Z;Liang M;Pan J;Lin M;Lin H;Luo Y;Zhou X;Yao W
环状RNAs(CircRNAs)是一类新的非编码RNA，在人类肿瘤研究中受到越来越多的关注。然而，在胃癌(GC)的背景下，CircRNAs的识别和功能在很大程度上是未知的。本研究旨在发现新的CircRNAs，并确定其在GC中的作用网络。采用数据挖掘、逆转录定量聚合酶链式反应(RT-qPCR)和计算生物学的综合策略，发现新的CircRNAs，并探讨其在GC中的作用机制。通过连通图(Cmap)分析确定了治疗GC的有前途的药物。从选定的基因芯片和GC的RNA-Seq数据集中筛选出6个重叠的差异表达CircRNAs(DECs)，并通过Sanger测序和RNase R处理对这6个DECs进行验证。进一步的RT-qPCR分析证实，6个DECs(hSA_CIRC_0000390、hSA_CIRC_0000615、hSA_CIRC_0001438、hSA_CIRC_0002190、hSA_CIRC_0002449和hSA_CIRC_0003120)的表达降低，它们都优先聚集在细胞质中。利用在线数据库预测了6个CircRNAs的miRNA结合位点和AGO2占有率，并确定了6个CircRNAs和33个miRNAs的CircRNA-miRNA相互作用。然后，从肿瘤基因组图谱(TCGA)数据库中鉴定了上述33个miRNAs中的5320个靶基因和1492个差异表达基因(Deg)。将miRNA靶基因与889个下调的目的基因交叉后，获得320个重叠的靶基因。京都百科全书的基因和基因组浓缩分析表明，这些靶基因与两条关键的肿瘤相关信号通路有关。利用STRING构建了一个包含320个目的基因的蛋白质-蛋白质相互作用网络，共鉴定出15个基因(ATF3、BTG2、DUSP1、Egr1、FGF2、FosB、GNAO1、GNAI1、GNAZ、GNG7、ITPR1、ITPKB、Jund、NR4A3、PRKCB)。最后，通过Cmap分析，确定了基于15个中心基因的生物活性化合物(包括伏立诺定、曲古菌素A和阿司咪唑)为治疗GC的药物。本研究为从CircRNA-miRNA-mRNA网络角度进一步探讨胃癌的发病机制和治疗提供了新的视角。网上版载有补充材料，可在10.1186/s12967-021-02903-5查阅。
Circular RNAs (circRNAs) are a new class of noncoding RNAs that have gained increased attention in human tumor research. However, the identification and function of circRNAs are largely unknown in the context of gastric cancer (GC). This study aims to identify novel circRNAs and determine their action networks in GC. A comprehensive strategy of data mining, reverse transcription-quantitative polymerase chain reaction (RT-qPCR) and computational biology were conducted to discover novel circRNAs and to explore their potential mechanisms in GC. Promising therapeutic drugs for GC were determined by connectivity map (CMap) analysis. Six overlapped differentially expressed circRNAs (DECs) were screened from selected microarray and RNA-Seq datasets of GC, and the six DECs were then validated by sanger sequencing and RNase R treatment. Subsequent RT-qPCR analysis of GC samples confirmed decreased expressions of the six DECs (hsa_circ_0000390, hsa_circ_0000615, hsa_circ_0001438, hsa_circ_0002190, hsa_circ_0002449 and hsa_circ_0003120), all of which accumulated preferentially in the cytoplasm. MiRNA binding sites and AGO2 occupation of the six circRNAs were predicted using online databases, and circRNA–miRNA interactions including the six circRNAs and 33 miRNAs were determined. Then, 5320 target genes of the above 33 miRNAs and 1492 differently expressed genes (DEGs) from The Cancer Genome Atlas (TCGA) database were identified. After intersecting the miRNA target genes and the 889 downregulated DEGs, 320 overlapped target genes were acquired. The Kyoto Encyclopedia of Genes and Genomes enrichment analysis indicated that these target genes were related to two critical tumor-associated signaling pathways. A protein–protein interaction network with the 320 target genes was constructed using STRING, and fifteen hubgenes (ATF3, BTG2, DUSP1, EGR1, FGF2, FOSB, GNAO1, GNAI1, GNAZ, GNG7, ITPR1, ITPKB, JUND, NR4A3, PRKCB) in the network were identified. Finally, bioactive chemicals (including vorinostat, trichostatin A and astemizole) based on the fifteen hubgenes were identifed as therapeutic agents for GC through the CMap analysis. This study provides a novel insight for further exploration of the pathogenesis and therapy of GC from the circRNA-miRNA-mRNA network perspective. The online version contains supplementary material available at 10.1186/s12967-021-02903-5.
登录
查看更多内容
影响因子：
4.1
作者：
Dudekulay, Dawood B.;Panda, Amaresh C.;Gorospe, Myriam
通讯作者：
Gorospe, Myriam
影响因子：
11.2
作者：
Diaz, Lorenza;Ceja-Ochoa, Irais;Camacho, Javier
通讯作者：
Camacho, Javier
HDAC 对于 IFN-γ 诱导的胃癌中 B7-H1 表达是不可或缺的
影响因子：
5.7
作者：
Deng, Rui;Zhang, Peng;Tao, Kaixiong
通讯作者：
Tao, Kaixiong
影响因子：
12.3
作者：
Enright AJ;John B;Gaul U;Tuschl T;Sander C;Marks DS
通讯作者：
Marks DS
影响因子：
3.4
作者：
Ding, Xiang-wu;Luo, He-Sheng;Ai, Yao-Wei
通讯作者：
Ai, Yao-Wei