Bioinformatics analysis of gene expression profile of central nervous system primitive neuroectodermal tumors

Wenhui Zhao; Dongxiang XU; Lei Zhong; Wanwen Feng

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Bioinformatics analysis of gene expression profile of central nervous system primitive neuroectodermal tumors

VernacularTitle:中枢神经系统性原始神经外胚层瘤基因表达谱芯片的生物信息学分析
Author: Wenhui ZHAO ¹ ; Dongxiang XU ¹ ; Lei ZHONG ¹ ; Wanwen FENG ²
Author Information

1. Department of Clinical Laboratory, Lianyungang Oriental Hospital Affiliated to Xuzhou Medical University, Lianyungang 222042, China
2. The Center for Clinical Research and Translational Medicine, Lianyungang Oriental Hospital Affiliated to Xuzhou Medical University, Lianyungang 222042, China
Publication Type:Journal Article
Keywords: primitive neuroectodermal tumor; central nervous system; gene chip; differentially expressed gene; bioinformatics
From: Journal of Xi'an Jiaotong University(Medical Sciences) 2022;43(2):220-227
CountryChina
Language:Chinese
Abstract: 【Objective】 To analyze the gene expression profile of central nervous system primitive neuroectodermal tumors （CNS-PNETs） by bioinformatics methods so as to explore the possible pathogenesis of CNS-PNETs at the molecular level. 【Methods】 The gene expression profile of CNS-PNETs was downloaded from the GEO database， GSE35493 and GSE74195. The differentially expressed genes （DEGs） were screened by the online analysis tool of GEO2R and Venn software， DEGs were analyzed by using the online analysis tools of David database， such as Gene Ontology （GO） and pathway enrichment （KEGG）. The protein interaction network analysis （PPI） of CNS-PNETs was made by using STRING online analysis tool， Cytoscape software and its plug-in cytohubba to find the key genes. 【Results】 We obtained 262 DEGs， including 49 upregulated genes and 213 downregulated genes. The analysis of GO function and KEGG signal pathway enrichment showed that DEG was involved in DNA transcription and mitosis， cell division， synaptic signal transmission and other biological processes， and associated with cell cycle， tumor-related pathway， p53 signal pathway， synapsis-related signal pathway， cAMP signal pathway and calcium ion signal pathway. Ten key genes， namely， CDK1， CDC20， MAD2L1， KIF11， ASPM， TOP2A， TTK， NDC80， NUSAP1 and DLGAP5 were screened out by STRING analysis. 【Conclusion】 Ten key genes including CDK1 may play an important role in the initiation and progression of CNS-PNETs， providing new clues for exploring the pathogenesis of CNS-PNETs.