基于生物信息学揭示ceRNA调控网络在结直肠癌中的作用

Role of ceRNA Regulatory Network in Colorectal Cancer Basedon Bioinformatics

为探索结直肠癌(CRC)相关的竞争性内源RNA(ceRNA)网络调控机制,寻找治疗CRC的潜在靶点,本研究从基因表达综合(GEO)数据库中下载CRC相关环状RNA(circRNA)数据集,应用稳健排序整合(RRA)算法、加权基因共表达网络分析(WGCNA)筛选差异表达circRNA,采用实时荧光定量PCR(RT-qPCR)验证了筛选的circRNA(hsa_circRNA_057090、hsa_circRNA_092566)呈环状,且在CRC组织、CRC细胞系中均高表达。在circBank及CircInteractome数据库中预测与circRNA相结合的微RNA(miRNA),在TargetScan、miRDB数据库中预测miRNA的靶基因,从癌症基因组图谱(TCGA)数据库中筛选CRC差异表达mRNA,两者取交集后得到差异表达靶基因,构建出ceRNA调控网络。应用DAVID软件、String数据库、Cytoscape软件及基因表达谱互动分析(GEPIA)数据库对靶基因进行基因本体(GO)富集分析、京都基因和基因百科全书(KEGG)富集分析、蛋白质-蛋白质相互作用网络(PPI)构建及生存分析。从PPI网络中筛选出10个核心基因,最终构建出circRNA-miRNA-核心基因网络。GO富集分析和KEGG富集分析显示,核心基因主要参与化学突触传递、配体门控离子通道活性等过程,且在cAMP等多个信号通路中显著富集。生存分析显示,2个核心基因SNAP25、ATP2B2的表达水平与CRC患者预后显著相关。本研究鉴定的hsa_circRNA_057090、hsa_circRNA_092566及构建的ceRNA调控网络可能为CRC提供新的生物标志物或潜在的治疗靶点。

To explore the regulatory mechanisms of the competing endogenous RNA(ceRNA)network associated with colorectal cancer(CRC)and to find potential targets for CRC treatment,The CRC-related circRNA datasets were downloaded from the Gene Expression Omnibus(GEO)database,differentially expressed circRNAs were screened using the robust rank aggregation(RRA)algorithm and weighted gene co-expression network analysis(WGCNA)analysis.Real-time fluorogenic quantitative PCR(RT-qPCR)was used to verify that screened circRNAs(hsa_circRNA_057090,hsa_circRNA_092566)were circular and both highly expressed in CRC tissues and CRC cell lines.And miRNAs bound to circRNAs were predicted on the circBank and CircInteractome databases.Target genes of miRNAs were predicted on the TargetScan and miRDB databases,differentially expressed mRNAs in CRC were screened on The Cancer Genome Atlas(TCGA)databases,after intersection,differentially expressed target genes were recognized.Then,the ceRNA regulatory network was constructed.Gene ontology(GO)enrichment analysis and Kyoto encyclopedia of genes and genomes(KEGG)enrichment analysis,protein interaction network construction, and survival analysis were performed on target genes using DAVID software, String database, Cytoscape software,and Gene Expression Profiling Interactive Analysis (GEPIA) database, respectively. Ten core genes were identified fromPPI network containing 427 mRNAs. Finally, the circRNA-miRNA-coregene network was constructed. GO enrichment analysisand KEGG enrichment analysis showed that core genes were mainly involved in chemical synaptic transmission, ion transmembranetransport and were significantly enriched in several signaling pathways, such as cAMP. Survival analysis showed that theexpression levels of two core genes SNAP25, ATP2B2 were significantly correlated with the prognosis of CRC patients. Thehsa_circRNA_057090, hsa_circRNA_092566 identified and ceRNA network constructed might provide novel biomarkers orpotential therapeutic targets for CRC.