Chi Jiadong, Zheng Xiangqian, Gao Ming, Zhao Jingzhu, Li Dapeng, Li Jiansen, Dong Li, Ruan Xianhui
Department of Thyroid and Neck Tumors, Tianjin Medical University Cancer Institute and Hospital, Oncology Key Laboratory of Cancer Prevention and Therapy, National Clinical Research Center of Cancer, Tianjin 300060, P.R. China.
Department of Graduate College, Tianjin Medical University, Tianjin 300070, P.R. China.
Oncol Lett. 2017 Dec;14(6):7153-7160. doi: 10.3892/ol.2017.7146. Epub 2017 Oct 6.
MicroRNAs (miRNAs/miRs) are small non-coding RNAs identified in plants, animals and certain viruses; they function in RNA silencing and post-transcriptional regulation of gene expression. miRNAs also serve an important role in the pathogenesis, diagnosis and treatment of tumors. However, few studies have investigated the role of miRNAs in thyroid tumors. In the present study, the expression of miRNA and mRNA was compared between follicular thyroid carcinoma (FTC) and follicular thyroid adenoma (FA) samples, and then miRNA-mRNA regulatory network analysis was performed. Microarray datasets (GSE29315 and GSE62054) were downloaded from the Gene Expression Omnibus, and profiling data were processed with R software. Differentially expressed miRNAs (DEMs) and differentially expressed genes (DEGs) were determined, and Gene Ontology enrichment analysis was subsequently performed for DEGs using the Database for Annotation, Visualization and Integrated Discovery. The target genes of the DEMs were identified with miRWalk, miRecords and TarMir databases. Network analysis of the DEMs and DEMs-targeted DEGs was performed using Cytoscape software. In GSE62054, 23 downregulated and 9 upregulated miRNAs were identified. In GSE29315, 42 downregulated and 44 upregulated mRNAs were identified. A total of 36 miRNA-gene pairs were also identified. Network analysis indicated a co-regulatory association between miR-296-5p, miR-10a, miR-139-5p, miR-452, miR-493, miR-7, miR-137, miR-144, miR-145 and corresponding targeted mRNAs, including TNF receptor superfamily member 11b, benzodiazepine receptor (peripheral) -associated protein 1, and transforming growth factor β receptor 2. These results suggest that miRNA-mRNAs networks serve an important role in the pathogenesis, diagnosis and treatment of FTC and FA.
微小RNA（miRNA/miR）是在植物、动物和某些病毒中发现的小非编码RNA；它们在RNA沉默和基因表达的转录后调控中发挥作用。miRNA在肿瘤的发病机制、诊断和治疗中也起着重要作用。然而，很少有研究调查miRNA在甲状腺肿瘤中的作用。在本研究中，比较了滤泡性甲状腺癌（FTC）和滤泡性甲状腺腺瘤（FA）样本中miRNA和mRNA的表达，然后进行了miRNA-mRNA调控网络分析。从基因表达综合数据库下载微阵列数据集（GSE29315和GSE62054），并用R软件处理分析数据。确定了差异表达的miRNA（DEM）和差异表达的基因（DEG），随后使用注释、可视化和综合发现数据库对DEG进行基因本体富集分析。通过miRWalk、miRecords和TarMir数据库鉴定DEM的靶基因。使用Cytoscape软件对DEM和以DEM为靶点的DEG进行网络分析。在GSE62054中，鉴定出23个下调的miRNA和9个上调的miRNA。在GSE29315中，鉴定出42个下调的mRNA和44个上调的mRNA。还总共鉴定出36对miRNA-基因对。网络分析表明，miR-296-5p、miR-10a、miR-139-5p、miR-452、miR-493、miR-7、miR-137、miR-144、miR-145与相应的靶mRNA之间存在共调控关联，这些靶mRNA包括肿瘤坏死因子受体超家族成员11b、苯二氮䓬受体（外周）相关蛋白1和转化生长因子β受体2。这些结果表明，miRNA-mRNA网络在FTC和FA的发病机制、诊断和治疗中起重要作用。
