Abstract:

Objective To analyze the differential expression genes between children with acute lymphoblastic leukemia（ALL） and healthy children by bioinformatics,and to find new molecular markers for the auxiliary diagnosis of ALL in children. Methods The gene chips of newly diagnosed children with ALL and healthy children was downloaded from the Gene Expression Omnibus（GEO）,and the differential expression genes were screened by R language. The Database for Annotation,Visualization and Integrated Discovery（DIVID） was employed for Gene Ontology（GO） and Kyoto Encyclopedia of Genes and Genomes（KEGG） pathway enrichment analysis. The protein interaction network of differential expression genes was constructed on STRING database,the results were visualized by Cytoscape software,and the hub genes were screened by CytoHubba plug-in. Results A total of 2 platforms' gene chips of newly diagnosed ALL children and healthy children were included,and 245 common differential expression genes were selected,which included 88 up-regulated genes and 157 down-regulated genes. Enrichment analysis showed that the common differential expression genes were mainly concentrated in the immune response（biological process）,integrating in the extracellular space（cell composition）,participating protein binding（molecular function）,and enriching hematopoietic cell lineage and cell cycle signal pathways（KEGG pathway analysis）. Totally,10 hub genes were screened out,namely CDK1,TOP2A,TYMS,MCM2,MCM4,TTK,CCNB2,BUB1B,KIF4A and MAD2L1. Conclusions The bioinformatics analysis of children with ALL reveals that 10 hub genes may be new markers for assisting the diagnosis of children with ALL.

Key words: Acute lymphoblastic leukemia, Differential expression gene, Hub gene, Bioinformatics