Chen Y S, Guo Y, Shen H W, Zhang P, Chen H
Department of Neurosurgery, Henan Provincial People's Hospital, People's Hospital of Zhengzhou University, Medical College of Henan University, Zhengzhou 450000, China.
Zhonghua Yi Xue Za Zhi. 2019 Aug 6;99(29):2311-2314. doi: 10.3760/cma.j.issn.0376-2491.2019.29.013.
To screen the differentially expressed genes, functional enrichment and related signaling pathways in glioma by bioinformatics analysis. Microarray data of glioma related gene expression profiles were selected in GEO database, and differentially expressed genes in glioma patients and normal brain tissues were screened by R statistical software of lima package. Functional enrichment of differentially expressed genes (GO and KEGG) was performed. The protein-protein interaction database (STRING) was used to analyze the interaction between the screened differentially expressed genes and the related signaling pathways. Two gene expression profiles, GSE15824 and GSE66354, were selected for analysis, and 158 genes with differential expression more than 2 times and 0.05 were screened. Molecular function (MF) of 158 differentially expressed genes was integrin binding, cell adhesion molecule binding, calcium binding and AMPA glutamate receptor activity. Cell component localization (CC) was located in cell membrane, neuron cell body, axon of nerve cell and so on, while biological process (BP) was mainly cell adhesion and nervous system. Development, cell proliferation, GTPase activity, apoptosis and angiogenesis; KEGG signaling pathways were mainly cAMP signaling pathway, purine metabolism pathway, MAPK signaling pathway and cGMP-PKG signaling pathway. There were 177 interaction connections in 158 differential expression gene-protein interaction networks, with an average interaction of 2.39 between each node and an aggregation coefficient of 0.37. Cytohubb screened the key genes (hub genes) in the signaling pathway. The results indicated that SLC6A1,SLC1A2,BDNF,GAP43,NRXN1,GAD1,OLIG2, PLP1,S100B and GRIA3 were the key genes in the signaling pathway of the interacting protein network. All the 10 key genes were related to the prognosis of patients (0.05). There are differentially expressed genes profile in glioma tissues and normal tissues. SLC6A1, SLC1A2, BDNF, GAP43, NRXN1, GAD1, OLIG2, PLP1, S100B and GRIA3 are key genes for glioma development and are related to the prognosis of patients.
通过生物信息学分析筛选胶质瘤中差异表达的基因、功能富集及相关信号通路。在GEO数据库中选取胶质瘤相关基因表达谱的微阵列数据，运用limma软件包的R统计软件筛选胶质瘤患者与正常脑组织中的差异表达基因。对差异表达基因进行功能富集分析（GO和KEGG）。利用蛋白质-蛋白质相互作用数据库（STRING）分析筛选出的差异表达基因之间的相互作用及相关信号通路。选取两个基因表达谱GSE15824和GSE66354进行分析，筛选出差异表达倍数大于2且P值小于0.05的158个基因。158个差异表达基因的分子功能（MF）为整合素结合、细胞黏附分子结合、钙结合及AMPA谷氨酸受体活性。细胞成分定位（CC）位于细胞膜、神经元细胞体、神经细胞轴突等，而生物学过程（BP）主要为细胞黏附、神经系统发育、细胞增殖、GTP酶活性、凋亡及血管生成；KEGG信号通路主要为cAMP信号通路、嘌呤代谢通路、MAPK信号通路及cGMP-PKG信号通路。158个差异表达基因-蛋白质相互作用网络中有177个相互作用连接，每个节点间平均相互作用度为2.39，聚集系数为0.37。通过Cytohubb筛选信号通路中的关键基因（枢纽基因）。结果表明，SLC6A1、SLC1A2、BDNF、GAP43、NRXN1、GAD1、OLIG2、PLP1、S100B和GRIA3是相互作用蛋白网络信号通路中的关键基因。所有10个关键基因均与患者预后相关（P<0.05）。胶质瘤组织与正常组织存在差异表达基因谱。SLC6A1、SLC1A2、BDNF、GAP43、NRXN1、GAD1、OLIG2、PLP1、S100B和GRIA3是胶质瘤发生发展的关键基因，且与患者预后相关。
