胰腺癌特异性差异表达lncRNA相关的ceRNA调控网络的构建
Construction of pancreatic cancer specific lncRNA-associated ceRNA network

目的:构建胰腺癌特异性长链非编码RNA( lncRNA)相关的竞争性内源性RNA(ceRNA)调控网络。方法:从TCGA数据库下载178个胰腺癌及4个正常胰腺样本的RNA表达谱数据及相应的临床资料,对比分析差异表达的lncRNA、miRNA和mRNA,基于lncRNA-miRNA在线预测工具miRcode数据库以及miRNA靶基因预测数据库(miRDB、 miRTarBase、TargetScan)筛选,构建差异表达 lncRNA相关的ceRNA调控网络。针对网络中的关键lncRNA和相应的靶基因进行生存分析。结果:成功构建了胰腺癌特异性lncRNA 相关的ceRNA调控网络,该网络包括12个lncRNA,5个miRNA,54个mRNA。KEGG信号通路和GO功能分析结果表明,靶基因主要富集在“TNF signaling pathway”“Jak-STAT signaling pathway”“Apoptosis multiple species”“MAPK signaling pathway”等通路,与“cellular process”“biological regulation”“regulation of cellular process”等功能关系密切。生存分析结果表明, lncRNA MIR600HR、C9orf139、RP11-796E2.4、AC104809.2,以及靶基因CDHR1、CYFIP2、IL10RA、MAP3K1、SSH2、TSPAN1、VAMP1,与胰腺癌预后关系密切。结论:成功构建了胰腺癌特异性 lncRNA相关的ceRNA调控网络,为胰腺癌的诊断、治疗和预后评估提供了潜在靶点。
Aim: To construct long non-coding RNA(lncRNA)-associated competing endogenous RNA(ceRNA)regulatory networks for pancreatic cancer.Methods: The lncRNA, miRNA and mRNA expression profiles and corresponding clinical data of 178 cases of pancreatic cancer and 4 cases of non-tumor pancreatic samples from TCGA database were analyzed, the differentially expressed lncRNA, miRNA and mRNA were identified, and then the lncRNA-associated ceRNA regulatory networks for pancreatic cancer were constructed based on bioinformatics analysis generated from lncRNA-miRNA online prediction tool(miRcode)and miRNA target gene prediction database(miRDB, miRTarBase,TargetScan). Survival analysis based on the key lncRNA and corresponding target genes in the network was performed.Results: The lncRNA-associated ceRNA regulatory networks for pancreatic cancer were constructed successfully, which included 12 lncRNAs, 5 miRNAs and 54 mRNAs. The results of KEGG and GO analysis showed that the target genes were mainly enriched in "TNF signaling pathway" "Jak-STAT signaling pathway" "Apoptosis multiple species" and "MAPK signaling pathway", and were closely related to the functions of "cellular process""biological regulation""regulation of cellular process".The results of survival analysis showed that lncRNA MIR600HR, C9orf139, RP11-796E2.4, AC104809.2, and target gene CDHR1, CYFIP2, IL10RA, MAP3K1, SSH2, TSPAN1, VAMP1, were closely related to the prognosis of pancreatic cancer.Conclusion: lncRNA-associated ceRNA regulatory networks for pancreatic cancer have been constructed successfully, which may help to identify the potential biomarkers for the diagnosis,therapy and prognosis of pancreatic cancer