中国癌症杂志 ›› 2022, Vol. 32 ›› Issue (1): 13-23.doi: 10.19401/j.cnki.1007-3639.2022.01.002

• 论著 • 上一篇    下一篇

胶质母细胞瘤复发相关基因的筛选、表达和临床预后分析

林艺, 王策, 康勋, 康庄, 陈峰, 江波, 李文斌()   

  1. 首都医科大学附属北京天坛医院肿瘤综合治疗中心,北京 100070
  • 收稿日期:2021-07-05 修回日期:2021-12-09 出版日期:2022-01-30 发布日期:2022-01-25
  • 通信作者: 李文斌 E-mail:liwenbin@ccmu.edu.cn
  • 基金资助:
    国家自然科学基金(81972338);首都医科大学校自然基金(14JL55)

Screening recurrent glioblastoma-related genes and analyzing their gene expressions in association with clinicopathological parameters and prognosis

LIN Yi, WANG Ce, KANG Xun, KANG Zhuang, CHEN Feng, JIANG Bo, LI Wenbin()   

  1. Department of Neuro-oncology, Cancer Center, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China
  • Received:2021-07-05 Revised:2021-12-09 Published:2022-01-30 Online:2022-01-25
  • Contact: LI Wenbin E-mail:liwenbin@ccmu.edu.cn

摘要:

背景与目的:脑胶质瘤是常见的中枢神经系统原发性恶性脑肿瘤之一,胶质母细胞瘤恶性程度高、侵袭性强、容易复发,复发后患者的预后极差。筛选胶质母细胞瘤复发相关的基因,并分析其在胶质瘤中的表达、临床病理学参数和预后的关系。方法:通过对GEO数据库中胶质母细胞瘤相关数据集进行挖掘,筛选包含胶质母细胞瘤原发和复发病例的相关数据集,并分析胶质母细胞瘤原发病例和复发病例样本间的差异表达基因(differentially expressed gene,DEG)。对DEG进行基因本体功能和信号富集分析,构架蛋白质相互作用(protein-protein interaction,PPI)网络,筛选Hub基因。通过PPI网络和Venn图筛选关键基因,而后研究使用基因表达谱数据动态分析(Gene Expression Profiling Interactive Analysis,GEPIA)和中国脑胶质瘤基因组图谱(Chinese Glioma Genome Atlas,CGGA)数据库进行关键基因的生存分析和表达分析,分析其表达与胶质瘤临床病理学参数的关系。结果:GSE62153数据集筛选到40个DEG,上调基因34个,下调基因6个。GSE58399数据集筛选到19个DEG,上调基因16个,下调基因3个。GO功能分析结果提示GSE62153的DEG主要参与中枢神经系统发育、髓鞘、肌动蛋白结合及中枢神经系统髓鞘形成等11个生理过程。而GSE58399的DEG主要参与上皮细胞迁移的正调控。京都基因和基因组百科全书(Kyoto Encyclopedia of Genes and Genomes,KEGG)通路富集分析结果显示,GSE62153和GSE58399的DEG存在共同富集—组氨酸代谢。通过STRING数据库,将20个蛋白分子构建成为核心PPI,Hub基因共筛选出10个,分别为MOBPOPALINERMNPLP1、MOGCLDN11、ASPATMEM125、KLK6和NKX6-2基因。胶质母细胞瘤复发关键基因筛选结果显示,共有3个基因:ERMNMOGMOBP基因。基于癌症基因组图谱(The Cancer Genome Atlas,TCGA)和CGGA数据库胶质瘤数据分析,ERMNMOGMOBP基因高表达者预后均优于低表达组,ERMNMOGMOBP基因在胶质母细胞瘤组织内表达水平低于对照组织(P<0.001)。ERMNMOGMOBP基因在不同世界卫生组织(World Health Organization,WHO)分级(WHOⅡ、Ⅲ和Ⅳ级)组织内表达差异有统计学意义(P<0.001),且随着胶质母细胞瘤的级别升高,ERMNMOGMOBP基因的表达逐渐降低。ERMNMOGMOBP基因表达与WHO分级、异柠檬酸脱氢酶(isocitrate dehydrogenase,IDH)状态及临床病理学参数相关(P<0.001)。而MOBP基因表达与患者年龄(P<0.001)及MGMT甲基化状态(P=0.022)相关。结论:ERMNMOGMOBP基因可能发挥抑癌基因作用参与胶质瘤复发过程,组氨酸代谢途径可能与甲氨蝶呤治疗敏感性相关。

关键词: 胶质瘤, 生物信息, 生存预后, 复发, 组氨酸代谢

Abstract:

Background and purpose: Glioma is the most common and malignant primary brain tumor in the central nervous system (CNS). Glioblastoma is highly malignant and aggressive, and the prognosis of patients with recurrent glioblastoma is very poor. This study aimed to screen the genes related to the recurrent glioblastoma, and analyze the relationship between their expressions, clinicopathological parameters and prognosis in glioma. Methods: By mining the relevant datasets of the primary and recurrent cases of glioblastoma in the GEO database, the differentially expressed gene (DEG) in the samples of primary and recurrent glioblastomas were screened and analyzed. All DEGs analyses were carried out in ontology function and pathway enrichment. Protein-protein interaction (PPI) network was constructed and used for screening Hub gene. Key genes were intersected by PPI network and Venn diagram, and the Gene Expression Profiling Interactive Analysis (GEPIA) and Chinese Glioma Genome Atlas (CGGA) database were analyzed for association of key gene expressions and survival status. Key genes were furtherly analyzed to determine the relationship between their expressions and clinicopathological parameters of glioma. Results: There were 40 DEG screened in the dataset GSE62153, including 34 up-regulated genes and 6 down-regulated genes. There were 19 DEG screened in the dataset GSE58399, including 16 up-regulated genes and 3 down-regulated genes. Go functional analyses showed that the DEG of GSE62153 were mainly involved in 11 physiological processes, such as central nervous system development, myelin sheath, actin binding, central nervous system myelination. The DEG of GSE58399 were mainly enriched in the positive regulation of epithelial cell migration. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment showed that the datasets GSE62153 and GSE58399 were both enriched in histidine metabolism. By using the STRING database, the core of PPI network was constructed with 20 protein molecules. A total of 10 hub genes were screened, including MOBP, OPALIN, ERMN, PLP1, MOG, CLDN11, ASPA, TMEM125, KLK6 and NKX6-2 gene. The key genes for recurrent glioblastoma were ERMN, MOG and MOBP gene. Based on analyses using The Cancer Genome Atlas (TCGA) and CGGA databases, the prognosis of patients with high expressions of ERMN, MOG and MOBP was favorable compared with the low expression group. The expression levels of key genes in glioblastoma were lower compared with the control tissues (P<0.001). There were significant differences in the expressions of ERMN, MOG and MOBP gene among different World Health Organization (WHO) grades (WHO Ⅱ, Ⅲ and Ⅳ) (P<0.001). As the grade of glioblastoma increased, the expressions of ERMN, MOG and MOBP were decreased gradually. The expressions of ERMN, MOG and MOBP gene were correlated with WHO classification, isocitrate dehydrogenase (IDH) status and clinicopathological characteristics (P<0.001). The expression of MOBP gene was correlated with age (P<0.001) and MGMT methylation status (P=0.022). Conclusion: ERMN, MOG and MOBP gene may function as tumor suppressor genes and participate in the recurrence of glioblastoma. The histidine metabolism pathway may be related to the sensitivity of methotrexate treatment.

Key words: Glioma, Bioinformatics, Survival, Recurrence, Histidine metabolism

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