Shi Yaohong, Sun Yuanyuan, Cheng Hongyan, Wang Chen
Department of Neurology, The First People's Hospital of Lianyungang, The Affiliated Lianyungang Hospital of Xuzhou Medical University, The Affiliated Hospital of Kangda College of Nanjing Medical University, Lianyungang Clinical College of Nanjing Medical University, Lianyungang 222061, China.
Department of Radiation Oncology, The First Affiliated Hospital of Nanjing Medical University, Nanjing 210000, China.
J Oncol. 2021 Nov 16;2021:4701680. doi: 10.1155/2021/4701680. eCollection 2021.
Ephrin B1 (EFNB1), the Eph-associated receptor tyrosine kinase ligand, is suggested to have an important function in neurodevelopment. However, its contribution to glioblastoma multiforme (GBM) remains uncertain. This study aimed to determine the prognostic power and immune implication of EFNB1 in GBM.
We first identified differentially coexpressed genes within GBM relative to noncarcinoma samples from GEO and TCGA databases by WGCNA. The STRING online database and the maximum cluster centrality (MCC) algorithm in Cytoscape software were used to design for predicting protein-protein interactions (PPI) and calculating pivot nodes, respectively. The expression of hub genes in cancer and noncancer tissues was verified by an online tool gene expression profile interactive analysis (GEPIA). Thereafter, the TISIDB online tool with Cox correlation regression method was employed to screen for immunomodulators associated with EFNB1 and to model the risk associated with immunomodulators.
Altogether 201 differentially expressed genes (DEGs) were discovered. After that, 10 hub genes (CALB2, EFNB1, ENO2, EPHB4, NES, OBSCN, RAB9B, RPL23A, STMN2, and THY1) were incorporated to construct the PPI network. As revealed by survival analysis, EFNB1 upregulation predicted poor overall survival (OS) for GBM cases. Furthermore, we developed a prognostic risk signature according to the EFNB1-associated immunomodulators. Kaplan-Meier survival analysis and receiver operating characteristic method were adopted for analysis, which revealed that our signature showed favorable accuracy of prognosis prediction. Finally, EFNB1 inhibition was found to block cell proliferation and migration in GBM cells.
The above results indicate that EFNB1 participates in cancer immunity and progression, which is the candidate biomarker for GBM.
Ephrin B1（EFNB1）是一种与Eph相关的受体酪氨酸激酶配体，被认为在神经发育中具有重要作用。然而，其在多形性胶质母细胞瘤（GBM）中的作用仍不确定。本研究旨在确定EFNB1在GBM中的预后价值及免疫意义。
我们首先通过加权基因共表达网络分析（WGCNA）从基因表达综合数据库（GEO）和癌症基因组图谱（TCGA）数据库中鉴定出与非癌样本相比，GBM中差异共表达的基因。利用STRING在线数据库和Cytoscape软件中的最大聚类中心性（MCC）算法分别预测蛋白质-蛋白质相互作用（PPI）并计算枢纽节点。通过在线工具基因表达谱交互式分析（GEPIA）验证枢纽基因在癌组织和非癌组织中的表达。此后，使用带有Cox相关回归方法的TISIDB在线工具筛选与EFNB1相关的免疫调节因子，并对与免疫调节因子相关的风险进行建模。
共发现201个差异表达基因（DEG）。之后，纳入10个枢纽基因（CALB2、EFNB1、ENO2、EPHB4、NES、OBSCN、RAB9B、RPL23A、STMN2和THY1）构建PPI网络。生存分析显示，EFNB1上调预示GBM患者总体生存期（OS）较差。此外，我们根据与EFNB1相关的免疫调节因子建立了一个预后风险特征。采用Kaplan-Meier生存分析和受试者工作特征方法进行分析，结果显示我们构建的特征具有良好的预后预测准确性。最后，发现抑制EFNB1可阻断GBM细胞的增殖和迁移。
上述结果表明EFNB1参与癌症免疫和进展，是GBM的候选生物标志物。
