A predictive model of circRNA⁃miRNA regulation in thyroid carcinoma based on integrated microarray analysis
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摘要:
目的：通过微阵列分析寻找更多甲状腺癌中差异表达的环状RNA（circRNA）并探讨其作用机制。方法：使用R软件分析来自基因表达图谱（gene expression omnibus，GEO）数据库中下载的基因芯片数据集GSE93522得到差异表达的circRNA。使用miRDB、miRTarBase和TargetScan数据库预测相关微小RNA（miRNA）和信使RNA（mRNA），结合来自肿瘤基因组图谱（The Cancer Genome Atlas，TCGA）数据库的513个甲状腺癌组织样本和59个癌旁组织样本中差异表达的miRNA和mRNA，利用Cytoscpe软件构建circRNA-miRNA-mRNA调控网络。通过基因本体论（gene ontology，GO）分析、京都基因与基因组百科全书数据库（Kyoto encyclopedia of genes and genomes，KEGG）分析以及生存曲线分析等，筛选其中重要的circRNA-miRNA-mRNA调控网络。进一步结合基因芯片数据集GSE40807、GSE3467和GSE33630以及TCGA库中数据及临床资料验证得到的调控网络。结果：构建的circRNA-miRNA-mRNA调控网络包括18个circRNA、8个miRNA和26个mRNA。GO分析显示，其中一些mRNA参与细胞代谢、迁移等，并参与细胞周期蛋白依赖性蛋白激酶复合物的组成。KEGG分析显示，一些mRNA与PI3K-AKT通路、MAPK通路和P53信号通路等相关。结合circRNA评分构建由21对circRNA-miRNA关系对和16对miRNA-mRNA关系对组成的重要circRNA-miRNA-mRNA调控网络，其中包括6个circRNA、8个miRNA和16个mRNA。根据TCGA数据库中表达验证及临床资料分析，得到hsa_circ_0001658-hsa-mir-183-AKAP12调控网络与甲状腺癌发生发展关系最为密切。结论：多条circRNA-miRNA-mRNA网络与甲状腺癌的发生发展有关，其中hsa_circ_0001658-hsa-mir-183-AKAP12调控网络最为重要，这可能有助于寻找更多的甲状腺癌诊断与预后标志物和治疗靶点。
Abstract:
Objective：To find more differentially expressed circRNAs in thyroid cancer and explore their mechanisms through microarray analysis. Methods：R software was used to obtain differential expressed circRNAs from the microarray datasets GSE93522. CircRNA-miRNA-mRNA regulatory networks were constructed by Cytoscape software according to the relevant miRNAs and mRNAs predicted by miRDB，miRTarBase and TargetScan，combining with differential expressed miRNAs and mRNAs from The Cancer Genome Atlas（TCGA）. The important circRNA-miRNA-mRNA networks were obtained by using gene ontology（GO）analysis，Kyoto encyclopedia of genes and genomes（KEGG）analysis，survival curve analysis and so on. Furthermore，the vital regulatory networks were verified by GSE40807，GSE3467，GSE33630 and clinical data from TCGA. Results：The circRNA-miRNA-mRNA regulatory networks included 18 circRNAs，8 miRNAs and 26 mRNAs. GO analysis showed that some of the mRNAs were involved in cell metabolism，migration，and other functions，as well as the composition of cyclin-dependent protein kinase complex. KEGG analysis showed that some mRNAs were correlated with the PI3K-AKT pathway，MAPK pathway，and P53 signaling pathway. Important circRNA-miRNA-mRNA regulatory networks were constructed according to the circRNA score and function analysis，which based on 6 circRNAs，8 miRNAs and 16 mRNAs. Hsa_circ_0001658-hsa-mir-183-AKAP12 was considered to the vital regulatory network according to the expression verification and clinical data analysis from TCGA. Conclusion：Many circRNA-miRNA-mRNA networks are related to the development of thyroid cancer. Hsa_circ_0001658-hsa-mir-183-AKAP12 is considered to a vital regulatory network. These findings may be helpful to find more diagnostic or prognostic markers and therapeutic targets of thyroid cancer.
