Zhu Kangle, Wang Qingqing, Wang Lian
Department of General Surgery, Affiliated Hospital of Nantong University, Nantong, Jiangsu, China.
Department of Oncology, Xuyi People's Hospital, Huai An, Jiangsu, China.
Evol Bioinform Online. 2022 Jul 20;18:11769343221113286. doi: 10.1177/11769343221113286. eCollection 2022.
To construct a competitive endogenous RNA (ceRNA) regulatory network derived from exosomes of human breast cancer (BC) by using the exoRbase database, to explore the possible pathogenesis of BC, and to develop new targets for future diagnosis and treatment.
The exosomal gene sequencing data of BC patients and normal controls were downloaded from the exoRbase database, and the expression profiles of exosomal mRNA, long non-coding RNA (lncRNA), and circular RNA (circRNA) were analyzed by using R language. Use Targetscan and miRanda database to jointly predict and differentially express miRNA (microRNA), miRNA combined with mRNA. The miRcode database was used to predict the miRNA combined with differentially expressed lncRNA, and the starBase database was used to predict the miRNA combined with circRNA in the difference table. The related mRNA, circRNA, lncRNA, and their corresponding miRNA prediction data were imported into Cytoscape software to visualize the ceRNA network. Enrichment analysis and visualization of KEGG were carried out using KOBAS. Hub gene was determined by Cytohubba plug-in.
Forty-two differentially expressed mRNA, 43 differentially expressed circRNA, and 26 differentially expressed lncRNA were screened out. The ceRNA network was constructed by using Cytoscape software, including 19 mRNA nodes, 2 lncRNA nodes, 8 circRNA nodes, and 41 miRNA nodes. KEGG enrichment analysis showed that differentially expressed mRNA in the regulatory network mainly enriched the p53 signaling pathway. Find the key Hub gene PTEN.
The ceRNA regulatory network in blood exosomes of BC patients has been successfully constructed in this study, which provides an exact target for the diagnosis and treatment of BC.
利用exoRbase数据库构建源自人乳腺癌（BC）外泌体的竞争性内源性RNA（ceRNA）调控网络，探讨BC可能的发病机制，并为未来的诊断和治疗开发新靶点。
从exoRbase数据库下载BC患者和正常对照的外泌体基因测序数据，使用R语言分析外泌体mRNA、长链非编码RNA（lncRNA）和环状RNA（circRNA）的表达谱。利用Targetscan和miRanda数据库联合预测并差异表达miRNA（微小RNA），miRNA与mRNA结合。使用miRcode数据库预测与差异表达lncRNA结合的miRNA，使用starBase数据库预测差异表中与circRNA结合的miRNA。将相关的mRNA、circRNA、lncRNA及其相应的miRNA预测数据导入Cytoscape软件以可视化ceRNA网络。使用KOBAS进行KEGG富集分析和可视化。通过Cytohubba插件确定枢纽基因。
筛选出42个差异表达的mRNA、43个差异表达的circRNA和26个差异表达的lncRNA。使用Cytoscape软件构建ceRNA网络，包括19个mRNA节点、2个lncRNA节点、8个circRNA节点和41个miRNA节点。KEGG富集分析表明，调控网络中差异表达的mRNA主要富集在p53信号通路。找到关键枢纽基因PTEN。
本研究成功构建了BC患者血液外泌体中的ceRNA调控网络，为BC的诊断和治疗提供了确切靶点。
