Bioinformatics analysis of gene expression profile of central nervous system primitive neuroectodermal tumors / 西安交通大学学报(医学版)

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.