Bioinformatics analysis of gene expression profiles in childhood B-precursor acute lymphoblastic leukemia

Abstract

Objectives

To explore the underlying molecular mechanisms of childhood B-precursor acute lymphoblastic leukemia (ALL) by bioinformatics analysis and find potential targets for childhood ALL diagnosis and treatment.

Methods

Gene expression profile GSE28460 was downloaded from the Gene Expression Omnibus, including 49 diagnostic and relapse bone marrow samples with childhood B-precursor ALL. The differentially expressed genes (DEGs) were identified by paired t-test. Pathway enrichment analysis of DEGs and transcription factors (TFs) enrichment analysis were performed, followed by construction of co-expressed, DEGs, and susceptibility gene protein–protein interaction (PPI) network. Based on these three networks, relevant regulatory network modules and the important DEGs in the modules were identified.

Results

Total of 947 DEGs were identified. Up-regulated DEGs enriched 20 pathways including cell cycle, and down-regulated DEGs significantly enriched Jak-STAT signaling pathways. CDK1 and BRCA1 were found to have more hubs in both co-expressed network and PPI network. Besides, total of five modules in INTS10, MCM, BRCA1, GYPA, and VCAN1 families were identified and a pathway of INTS10-INTS6-POLR2A-MAGI2 was selected.

Conclusion

Cell cycle and Jak-STAT signaling pathway were closely associated with relapse of childhood B-precursor ALL. The DEGs, such as PTTG1, PIK3CA, CDK1, and BRCA1 may be the potential targets for childhood ALL diagnosis and treatment.