Table 1.
The characteristics of patients.
Fig 1.
PCA based on 118,871 sites differentially methylated between BCP ALL and control samples.
Fig 2.
Genomic distribution of CpGs with significant differences in methylation level between BCP ALL and control in gene context.
Fig 3.
Distribution of hyper- and hypomethylated sites differentially methylated between leukemic and control samples.
Table 2.
Genomic distribution of probes differentially methylated between leukemic and control samples with respect to CpG island and gene context.
Fig 4.
Unsupervised hierarchical clustering of promoter regions-associated methylation profiles in leukemic and control samples.
Fig 5.
Unsupervised hierarchical clustering of methylation profiles with probes selected to minimize variation among leukemic samples.
Fig 6.
PCA based on filtered probes set minimizing the variation of methylation profiles in leukemic samples.
Fig 7.
Results of Ridge Regression of a high risk of a patient in the analyzed data set.
Each curve corresponds to a variable. It shows how much this variable contributes to the prediction of high risk of patient (a), hyperdiploidy (b) and t(12;21) ETV6-RUNX1 (c) aberrations in analyzed data set. Numbers on the left are coefficients and numbers on top are total count of variables selected for an L1 Norm (statistical parameter) shown on the bottom.
Fig 8.
Multidimensional scaling analysis based on 1000 the most variable sites with respect to: A—gender, B—age.
Table 3.
Statistic of sites differentially methylated between specific genetic subtypes of leukemia and remaining BCP ALL patients with known cytogenetic status.
Table 4.
Top ten KEGG pathways connected with genes containing sites differentially methylated between specific genetic subtype and remaining BCP ALL patients.
Fig 9.
The unsupervised hierarchical clustering of the methylation level of a panel of 500 probes with the largest differences in methylation level between different leukemia genetic subtypes.
Fig 10.
Principal component analysis 3D plot based on 500 probes with the highest differences in methylation level among genetic subtypes and remaining pre-B ALL patients.
The plot is presented in three different layouts to enable visualization of separate clusters.
Fig 11.
Methylation profile of ETV6 and RUNX1 genes in ETV6-RUNX1 subtype patients, remaining pre-B ALL cases and control individuals.
Red square marks the CpG fragments with large differences in methylation level between pre-B ALL and control samples.
Fig 12.
Methylation profile of TCF3 and PBX1 genes in TCF3-PBX1 subtype patients, remaining pre-B ALL cases and control individuals.
Red square marks the CpG fragments with large differences in methylation level between pre-B ALL and control samples.
Table 5.
The most important DM sites in patients from particular BCP ALL subgroups extracted using the lasso penalized logistic regression analysis.
Table 6.
Selected disease phenotypes enriched by genes associated with uniform leukemia methylation pattern.