生物信息学  2024, Vol. 22 Issue (2): 109-115  DOI: 10.12113/202301010
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引用本文 

张雪雪, 王旭杰, 徐钰莹, 王宗雪, 隗睿, 李秋艳. 结节性甲状腺肿circRNA-miRNA-mRNA调控网络的构建[J]. 生物信息学, 2024, 22(2): 109-115. DOI: 10.12113/202301010.
ZHANG Xuexue, WANG Xujie, XU Yuying, WANG Zongxue, WEI Rui, LI Qiuyan. Construction of circRNA-miRNA-mRNA regulatory network in nodular goiter[J]. Chinese Journal of Bioinformatics, 2024, 22(2): 109-115. DOI: 10.12113/202301010.

通信作者

李秋艳, 女,主任医师,博导,研究方向:内分泌疾病的中医药防治研究. E-mail: liqiuyan0928@163.com

文章历史

收稿日期: 2023-01-30
修回日期: 2023-03-23
结节性甲状腺肿circRNA-miRNA-mRNA调控网络的构建
张雪雪 , 王旭杰 , 徐钰莹 , 王宗雪 , 隗睿 , 李秋艳     
中国中医科学院西苑医院 综合内科, 北京 100091
摘要: 基于生物信息分析筛选结节性甲状腺肿中差异表达的环状RNA(circRNA),并揭示circRNA-miRNA-mRNA调控网络在结节性甲状腺肿中的作用。从GEO数据库中检索结节性甲状腺肿组织基因芯片数据,利用R软件筛选出差异表达的circRNA。联合多个生物信息数据库预测差异表达circRNA下游的miRNA及mRNA, 并对靶mRNA进行GO及KEGG富集分析。利用STRING在线数据库及Cytoscape软件筛选核心基因。确定了2个circRNA,42个miRNA及546个mRNA。GO及KEGG富集分析表明靶mRNA主要涉及细胞生长及基因表达调控过程。基于Cytoscape软件筛选出了14个核心基因(SP1、IGF1RRPS6KB1、SMAD2、SMAD3、SMAD4、VEGFACCND1、CDK2、HSPA4、HIF1ACREB1, NR3C1和STAT5A)。最终基于2个circRNA、11个miRNA和14个核心mRNA构建了circRNA-miRNA-mRNA调控网络。结节性甲状腺肿组织中异常表达的circRNA及相关的circRNA-miRNA-mRNA调控网络可能成为结节性甲状腺肿诊断与治疗的新靶点。
关键词: 结节性甲状腺肿    环状RNA    竞争性内源RNA    GEO数据库    
Construction of circRNA-miRNA-mRNA regulatory network in nodular goiter
ZHANG Xuexue , WANG Xujie , XU Yuying , WANG Zongxue , WEI Rui , LI Qiuyan     
Department of general internal medicine, Xiyuan Hospital, China Academy of Chinese Medical Sciences, Beijing 100091, China
Abstract: To screen the differentially expressed circular RNA (circRNA) in nodular goiter based on bioinformatics analysis and reveal the role of circRNA-miRNA-mRNA regulatory network in nodular goiter. The microarray data of nodular goiter tissues are retrieved from GEO database, and the differentially expressed circRNA is screened by R software. Multiple bioinformatics databases are used to predict miRNAs and mRNA downstream, and target mRNA is enriched with GO and KEGG. The core genes are selected by STRING online database and Cytoscape software. Two circRNAs, 42 miRNAs and 546 mRNA are identified. GO and KEGG enrichment analysis show that the target mRNA is mainly involved in cell growth and gene expression regulation. 14 core genes (SP1, IGF1R, RPS6KB1, SMAD2, SMAD3, SMAD4, VEGFA, CCND1, CDK2, HSPA4, HIF1A, CREB1, NR3C1 and STAT5A) have been selected by the Cytoscape software. Finally, the circRNA-miRNA-mRNA regulatory network is constructed based on 2 circRNAs, 11 miRNAs and 14 core mRNA. The abnormal expression of circRNA and related circRNA-miRNA-mRNA regulatory network in nodular goiter may become a new target for diagnosis and treatment of nodular goiter.
Key Words: Nodular goiter    CircRNA    CeRNA    GEO database    

结节性甲状腺肿(Nodular goiter,NG)是由于甲状腺内多个区域结构和功能的改变导致滤泡上皮细胞局灶性增生,随后在甲状腺内形成结节[1]。尽管在全民实施食盐加碘后,结节性甲状腺肿的发病率有所下降,但其仍是临床上最常见的甲状腺疾病之一[2]。据报道,结节性甲状腺肿在人群中的发病率约为7%,其癌变率为7%~14%[3]。多数结节性甲状腺肿患者无明显症状,常通过超声或体格检查发现结节,但结节大于3 cm时易产生压迫症状,如呼吸困难、吞咽困难等[4],且患者易合并焦虑、抑郁情绪,治疗意愿较强[5]。目前,西医对于此病尚无特效疗法,指南推荐以临床随访为主[6]。因此,亟需找到结节性甲状腺肿治疗的潜在靶点。

circRNA属于非编码RNA的一种,可作为miRNA海绵或竞争性内源ceRNA,与其它RNA竞争miRNA[7]。而miRNA可通过调节目标mRNA的翻译或稳定性(如细胞增殖、凋亡、分化、免疫等)来发挥细胞功能[8-9]。与其它RNA相比,circRNA因其具有高度保守性及组织器官特异性赋予其具有诊断标志物和治疗靶点的巨大潜力[10]。目前,大量研究发现circRNA可调控不同细胞的增殖与凋亡,如甲状腺细胞、肝细胞、肺癌细胞、血管平滑肌细胞等[11-14]。而甲状腺细胞增殖与凋亡失衡是结节性甲状腺肿发病的主要原因[15]。本研究基于GEO数据库中结节性甲状腺肿组织基因芯片筛选出差异表达circRNA分子,并联合多个生物信息学数据库预测下游miRNA及mRNA,构建circRNA-miRNA-mRNA调控网络,以揭示其发病的分子机制,并为临床诊断和治疗提供参考。

1 资料与方法 1.1 资料来源

以“Nodular goiter”, “circRNA”为关键词检索GEO数据库(http://www.ncbi.nlm.nih.gov/geo),筛选出GSE93522数据集。该数据集使用基因芯片技术检测了3例结节性甲状腺肿组织和6例正常组织中circRNA的表达量。

1.2 研究方法 1.2.1 差异表达circRNA的筛选

利用R 4.0.2软件Limma包寻找结节性甲状腺肿组织和正常组织中差异表达的circRNA,筛选条件为结节性甲状腺肿组织相对正常组织circRNA表达量变化|logFC|≥1,且校正后P值(采用Benjamini-Hochberg方法对P值进行校正)小于0.05。

1.2.2 差异表达circRNA结合的miRNA预测

同时采用4个生物信息数据库对差异表达circRNA潜在结合的miRNA进行预测, 数据库包括circbank(http://www.circbank.cn/searchMiRNA.html)、circinteractome(https://circinteractome.irp.nia.nih.gov/)、miRDB (http://mirdb.org/cgi-bin/custom.cgi)及circatlas (http://circatlas.biols.ac.cn/),同时满足在3个或3个以上数据库中能预测到的视为候选miRNA。

1.2.3 miRNA下游靶基因预测

利用TargetScan (http://www.targetscan.org/vert_72/), miRDB (http://mirdb.org/cgi-bin/custom.cgi), miRwalk (http://mirwalk.umm.uni-heidelberg.de/), miRTarBase (https://mirtarbase.cuhk.edu.cn/~miRTarBase/miRTarBase_2022/php/index.php), TargetMiner (http://www.isical.ac.in/~bioinfo_miu/targetminer20.htm), RNA22 (https://cm.jefferson.edu/rna22/), RNAInter (http://rnainter.org/) 等7大数据库预测miRNA-mRNA之间可能的靶向关系,至少在上述5个或5个以上数据库能预测到的视为候选miRNA下游mRNA。

1.2.4 靶mRNA GO和KEGG富集分析

将预测到的靶mRNA输入在线分析工具(https://cloud.oebiotech.cn)进行基因本体论(Gene ontology,GO)和京都基因与基因组百科全书数据库(Kyoto encyclopedia of genes and genomes,KEGG)富集分析,筛选条件为P < 0.01。

1.2.5 靶mRNA蛋白互作(Protein-protein interaction,PPI)网络及核心基因筛选

利用STRING(https://string-db.org/)在线数据库获得预测的靶mRNA蛋白互作网络(截断值为信度评分>0.9),导入Cytoscape 3.9.1软件进一步绘图[16]。分别采用Cytoscape软件的Cytohubba及MOCODE插件(参数设置如下:degree cutoff=2,k-core=2,node score cutoff=0.2,maximum depth=100)[17]及根据Degree值中位数2倍及以上的方法筛选核心基因[18],以上2种方法获得的基因取交集视为最终筛选出的核心基因。

1.2.6 circRNA-miRNA-mRNA调控网络的建立

将筛选出的核心基因与miRNA预测靶基因取交集,得到miRNA-核心mRNA靶向关系,构建circRNA-miRNA-核心mRNA调控网络,基于Cytoscape 3.9.1软件进行网络调控的可视化分析。

2 结果 2.1 结节性甲状腺肿组织差异表达circRNA

GSE93522数据集共筛选到2个符合条件的差异表达circRNA,2个circRNA均表达上调,分别为hsa_circ_0100181和hsa_circ_0104916,详见表 1。对差异表达circRNA进行后续分析。

表 1 差异表达circRNA基本信息 Table 1 Basic information on differentially expressed circRNA
2.2 预测差异表达circRNA-miRNA和miRNA-mRNA靶向关系

通过circbank、circinteractome、miRDB及circatlas 4个生物信息数据库预测差异表达circRNA结合的miRNA共42个。基于TargetScan, miRDB, miRwalk, miRTarBase, TargetMiner, RNA22, RNAInter 7大数据库预测靶miRNA下游mRNA,共获得611对miRNA-mRNA,546个下游靶mRNA,详见表 2

表 2 circRNA-miRNA及miRNA-mRNA靶向关系预测结果 Table 2 Predicted results of circRNA-miRNA and miRNA-mRNA
2.3 miRNA下游靶基因GO和KEGG富集分析

将预测到的546个靶基因导入在线分析工具进行GO和KEGG富集分析,结果见图 1图 2。GO富集分析显示,细胞成分注释方面,靶基因最常见的细胞定位是核质,其次为基底膜等;生物过程注释方面,靶基因主要参与RNA聚合酶Ⅱ启动子转录调控、模板DNA转录、细胞增殖调控、器官生长等;分子功能方面,靶基因主要参与肌动蛋白、离子通道、β连环蛋白、蛋白磷酸酶2A的结合等。KEGG富集结果表明,上述靶基因主要富集于癌症相关信号通路、AGE-RAGE in diabetic complications信号通路、Endocytosis, PI3K-Akt信号通路, MicroRNAs in cancer, TGF-beta信号通路等。

图 1 靶基因GO分析 Figure 1 GO analyses of target gene
图 2 靶基因KEGG富集分析 Figure 2 KEGG analyses of target gene
2.4 PPI网络分析及核心基因筛选

通过STRING在线工具获得靶基因蛋白互作网络图,进一步导入Cytoscape软件绘图,见图 3。基于Cytoscape软件筛选出14个核心基因,分别是SP1, IGF1R, RPS6KB1, SMAD2, SMAD3, SMAD4, VEGFA, CCND1, CDK2, HSPA4, HIF1A, CREB1, NR3C1和STAT5A

图 3 靶基因PPI网络 Figure 3 PPI network of target gene
2.5 circRNA-miRNA-mRNA/核心基因调控网络的构建

根据上述结果最终确定了2个circRNA, 11个miRNA和14个核心mRNA,建立了circRNA-miRNA-mRNA调控网络,展示ceRNA在结节性甲状腺肿中可能的调控机制,见图 4

图 4 circRNA-miRNA-mRNA调控网络 Figure 4 circRNA-miRNA-mRNA regulatory network 注:菱形代表circRNA, 三角形代表miRNA, 圆形代表mRNA/核心基因.
3 讨论

大多数非蛋白质编码RNA被认为具有参与细胞稳态的多样化功能。circRNA作为一种非编码RNA,除了直接影响mRNA转录外,还可以通过miRNA海绵或RNA结合蛋白来调控靶基因的表达,对许多生理和病理状态的启动和发展起着关键作用[19]。近年来,大量研究揭示了circRNA-miRNA-mRNA轴在细胞增殖[11-12]、细胞凋亡[13]、胰岛素抵抗[19]、血管生成[20]等中的作用机制。相似的是,这些病理过程同时促进了结节的发生和发展[15, 21]

目前关于circRNA在结节性甲状腺肿中的作用鲜有报道。本研究基于GEO数据库发现,与正常组织相比,结节性甲状腺肿组织中hsa_circ_0100181和hsa_circ_0104916表达上调,基于生物信息学分析确定了匹配度最高的circRNA-miRNA及miRNA-mRNA。对靶基因进行KEGG富集分析发现它们在PI3K-Akt信号通路富集明显,这与文献报道结果一致[22]。hsa_circ_0100181在人类和小鼠的肠道干细胞中高度表达,并且以肽非依赖性方式调节肠道干细胞的自我更新[23]。而在甲状腺结节患者中发现肠道微生物种类和基因家族数量的减少[24],这提示hsa_circ_0100181可能通过调节肠道功能影响甲状腺代谢。前期研究发现has-miR-1294可直接靶向抑制IGF1R的表达[25]。而在甲状腺中,IGF-1由甲状腺滤泡上皮细胞合成,可通过自分泌及旁分泌的方式调节甲状腺细胞增殖[26],因此hsa_circ_0100181/has-miR-1294/IGF1R调控通路也可能成为治疗结节性甲状腺肿的潜在通路。VEGF能促进血管内皮细胞增殖,改变毛细血管通透性,并通过旁分泌的方式作用于VEGFR从而促进甲状腺内血管生成[27]。VEGF在正常甲状腺组织中呈阴性表达,而在结节性甲状腺肿患者中表达升高[28],本研究结果发现hsa_circ_0104916可通过hsa-miR-3126-5p影响VEGFR表达,这可能促进了结节性甲状腺肿的发生与发展。CREB是一类转录因子,能特异性结合基因启动上游cAMP反应元件[29]。结节性甲状腺肿多由于缺碘引起甲状腺激素合成减少,促甲状腺激素反馈性升高,而促甲状腺激素可通过TSHR-cAMP-PKA途径磷酸化CREB,从而调节NIS和TPO,促进甲状腺组织增生[21]。因此hsa_circ_0104916/has-miR-6834-5p/CREB1调控轴可能是结节性甲状腺肿发病的重要机制。TGF-β1/SMADS信号通路可调控细胞的增殖、凋亡、分化等生物过程[30],而has-miR145-5p负反馈调控TGF-β1/SMADS通路[31],这与本研究的结果吻合,提示hsa_circ_0104916/ has-miR145-5p/SMADS可能在结节性甲状腺肿发生发展中发挥一定的作用。此外,前期研究发现has-miR-605-3p, hsa-miR-1200在细胞增殖及凋亡中发挥重要作用[32-33],但其在甲状腺细胞中的作用尚未被揭示。未来可进一步深入研究上述miRNA对甲状腺细胞的作用。

综上所述,本研究确定了16个circRNA-miRNA-mRNA相关信号轴,这些调控轴可能在结节性甲状腺肿的发生发展中占据着重要的位置。由于该结果仅基于生物信息学分析,未来还需要细胞和动物实验进一步验证。

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