Children's Hospital of Chongqing Medical University, Chongqing, People's Republic of China.
Invest New Drugs. 2021 Aug;39(4):901-913. doi: 10.1007/s10637-021-01064-y. Epub 2021 Mar 5.
Neuroblastoma (NB) is a common tumor in children, usually in the retroperitoneum. After various treatments, low- and intermediate-risk patients have achieved good results, but the prognosis of high-risk patients is still very poor. Therefore, it is necessary to find new effective targets for the treatment of high-risk patients. In this study, comprehensive bioinformatics analysis was used to identify the differentially expressed genes (DEG and DEM) between high-risk patients and non-high-risk patients, and it was identified that ADRB2 may affect the survival status of high-risk patients due to miR -30a-5p regulation. The GSE49710, GSE73517, and GSE121513 datasets were downloaded from the Gene Expression Synthesis (GEO) database, and DEG and DEM were selected. Then, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were applied to the selected DEGs. The STRING database and Cytoscape software were used to construct protein-protein interaction (PPI) networks and perform modular analysis of the DEGs. The TARGET data set containing information on overall survival days were used for the prognostic analysis of central genes. We identified a total of 255 DEGs from GSE49710 and GSE73517, and 193 DEMs from GSE121513. We identified the 5 most important central genes from the PPI network, performed a prognostic analysis in the target data set, and verified their expression using RT-qPCR to select the most important ADRB2 gene to predict miRNA. Integrating the differential miRNA predicted by miRDB and miRSystem and GSE121513 between the targeted miRNA and the prognosis, miR-30a-5p was finally identified as the targeted miRNA of ADRB2.
神经母细胞瘤(NB)是儿童常见的肿瘤,通常位于腹膜后。经过各种治疗,低危和中危患者已取得良好效果,但高危患者的预后仍很差。因此,有必要寻找新的有效治疗高危患者的靶点。本研究通过综合生物信息学分析,鉴定高危患者与非高危患者之间的差异表达基因(DEG 和 DEM),并发现 ADRB2 可能通过 miR-30a-5p 调控影响高危患者的生存状态。从基因表达综合(GEO)数据库中下载 GSE49710、GSE73517 和 GSE121513 数据集,选择 DEG 和 DEM。然后,对选择的 DEGs 进行基因本体(GO)和京都基因与基因组百科全书(KEGG)分析。应用 STRING 数据库和 Cytoscape 软件构建蛋白-蛋白相互作用(PPI)网络,并对 DEGs 进行模块分析。使用包含总生存天数信息的 TARGET 数据集进行核心基因的预后分析。我们从 GSE49710 和 GSE73517 中总共鉴定出 255 个 DEG,从 GSE121513 中鉴定出 193 个 DEM。我们从 PPI 网络中确定了 5 个最重要的核心基因,在 TARGET 数据集中进行了预后分析,并使用 RT-qPCR 验证了它们的表达,选择了最重要的 ADRB2 基因来预测 miRNA。整合 miRDB 和 miRSystem 预测的差异 miRNA 和 GSE121513 之间靶向 miRNA 与预后的关系,最终确定 miR-30a-5p 为 ADRB2 的靶向 miRNA。