Zhao Xin, Ren Yiming, Cui Naiqiang, Wang Ximo, Cui Yunfeng
Tianjin Medical University, Tianjin.
Department of Surgery, Tianjin Nankai Hospital, Nankai Clinical School, Tianjin Medical University.
Medicine (Baltimore). 2018 Sep;97(39):e12632. doi: 10.1097/MD.0000000000012632.
Pancreatic cancer (PC) is one of the most lethal tumors, due to late diagnosis and limited surgical strategies. It has been reported that serum exosomal microRNAs (S-Exo-miRNAs) play a pivotal role as signaling molecules and serve as noninvasive diagnosis methods for PC. The combination of S-Exo-miRNAs with the corresponding target also plays an important role in the tumor microenvironment.Here we investigated S-Exo-miRNAs involved in PC. The gene expression profile was downloaded from the Gene Expression Omnibus (GEO) database. The analysis was carried out using GEO2R. The targets of differentially expressed serum exosomal miRNAs (DE-S-Exo-miRNAs) were predicted by 4 bioinformatic algorithms (miRanda, miRDB, miRWalk, and Targetscan). Further analysis with gene ontology (GO) and Kyoto Encyclopedia of Genomes pathway (KEGG) enrichment analyses were performed with Cytoscape software version 3.4.0. Subsequently, the interaction regulatory network of target genes was performed with the Search Tool for the Retrieval of Interacting Genes (STRING) database (http://www.string-db.org/) and visualized using Cytoscape software.We downloaded the gene expression profile GSE50632, which was based on an Agilent microarray GPL17660 platform containing 4 eligible samples. In total 467 DE-S-Exo-miRNAs were obtained, including 7 overexpressed miRNAs (1.50%), and 460 remaining underexpressed miRNAs (98.50%). The databases miRWalk, miRDB, miRanda, and TargetScan were used to predict their potential targets, which were subsequently submitted to Cytoscape software version 3.4.0 (www.cytoscape.org). Next the functional and pathway enrichment analysis were used for the KEGG pathway and GO categories analysis. The enrichment analysis identified the genes involved in such processes as developmental and negative regulation of multicellular organismal processes, regulation of anatomical structure morphogenesis, regulation of cell death, apoptotic processes and mitogen-activated protein kinase (MAPK) signaling pathway, transforming growth factor - beta (TGF -β) signaling pathway, cyclic adenosine monophosphate (cAMP) signaling pathway, and the phosphatidylinositol-3 kinases/Akt (PI3K-Akt) signaling pathway. Subsequently according to the protein-protein interaction (PPI) network, the top 10 genes were obtained. The enrichment analyses of the genes involved in a significant module revealed that these genes were related to the TGF-β signaling pathway. After reviewing the literature, we identified the apoptosis genes, and their corresponding miRNAs that have a relationship with apoptosis of the tumor.This analysis provides a comprehensive understanding of the roles of S-Exo-miRNAs and the related targets in the development of PC. Additionally, the present study provides promising candidate targets for early diagnosis and therapeutic intervention. However, these predictions require further experimental validation in future studies.
胰腺癌(PC)是最致命的肿瘤之一,原因是诊断较晚且手术策略有限。据报道,血清外泌体微小RNA(S-Exo-miRNAs)作为信号分子发挥关键作用,并可作为PC的非侵入性诊断方法。S-Exo-miRNAs与相应靶点的结合在肿瘤微环境中也起着重要作用。在此,我们研究了参与PC的S-Exo-miRNAs。基因表达谱从基因表达综合数据库(GEO)下载。使用GEO2R进行分析。通过4种生物信息学算法(miRanda、miRDB、miRWalk和Targetscan)预测差异表达的血清外泌体miRNA(DE-S-Exo-miRNAs)的靶点。使用Cytoscape软件3.4.0版本进行基因本体(GO)和京都基因与基因组百科全书通路(KEGG)富集分析。随后,使用相互作用基因检索工具(STRING)数据库(http://www.string-db.org/)构建靶基因的相互作用调控网络,并使用Cytoscape软件进行可视化。我们下载了基于安捷伦微阵列GPL17660平台的基因表达谱GSE50632,该平台包含4个合格样本。共获得467个DE-S-Exo-miRNAs,包括7个过表达的miRNA(1.50%)和460个其余低表达的miRNA(98.50%)。使用miRWalk、miRDB、miRanda和TargetScan数据库预测其潜在靶点,随后将这些靶点提交至Cytoscape软件3.4.0版本(www.cytoscape.org)。接下来,使用功能和通路富集分析对KEGG通路和GO类别进行分析。富集分析确定了参与多细胞生物体发育和负调控、解剖结构形态发生调控、细胞死亡调控、凋亡过程以及丝裂原活化蛋白激酶(MAPK)信号通路、转化生长因子-β(TGF-β)信号通路、环磷酸腺苷(cAMP)信号通路和磷脂酰肌醇-3激酶/蛋白激酶B(PI3K-Akt)信号通路等过程的基因群。随后根据蛋白质-蛋白质相互作用(PPI)网络,获得了前10个基因。对参与一个重要模块的基因进行富集分析表明,这些基因与TGF-β信号通路相关。查阅文献后,我们确定了凋亡基因及其与肿瘤凋亡相关的相应miRNA。该分析全面了解了S-Exo-miRNAs及其相关靶点在PC发生发展中的作用。此外,本研究为早期诊断和治疗干预提供了有前景的候选靶点。然而,这些预测在未来研究中需要进一步的实验验证。