DNA methylation for subtype classification and prediction of treatment outcome in patients with childhood acute lymphoblastic leukemia

Abstract

Abstract Despite improvements in the prognosis of childhood acute lymphoblastic leukemia (ALL), subgroups of patients would benefit from alternative treatment approaches. Our aim was to identify genes with DNA methylation profiles that could identify such groups. We determined the methylation levels of 1320 CpG sites in regulatory regions of 416 genes in cells from 401 children diagnosed with ALL. Hierarchical clustering of 300 CpG sites distinguished between T-lineage ALL and B-cell precursor (BCP) ALL and between the main cytogenetic subtypes of BCP ALL. It also stratified patients with high hyperdiploidy and t(12;21) ALL into 2 subgroups with different probability of relapse. By using supervised learning, we constructed multivariate classifiers by external cross-validation procedures. We identified 40 genes that consistently contributed to accurate discrimination between the main subtypes of BCP ALL and gene sets that discriminated between subtypes of ALL and between ALL and controls in pairwise classification analyses. We also identified 20 individual genes with DNA methylation levels that predicted relapse of leukemia. Thus, methylation analysis should be explored as a method to improve stratification of ALL patients. The genes highlighted in our study are not enriched to specific pathways, but the gene expression levels are inversely correlated to the methylation levels.