Comprehensive Methylation Analysis in Pediatric Patients with Acute Myeloid Leukemia —the JCCG Study, JPLSG AML-05-

Introduction

The genetic heterogeneity of acute myeloid leukemia (AML) makes it difficult to predict an appropriate prognosis of patients with AML. Currently, several gene mutations associated with the pathogenesis of AML have been identified owing to recent advances in massively parallel sequencing technologies. However, despite incorporating these molecular markers, the prognosis of many patients remains uncertain. Aberrant DNA methylation has frequently been observed in myeloid cells of patients with AML. Reportedly, DNA methylation patterns are associated with molecular features. Furthermore, a previous report has demonstrated that the methylation levels of polycomb target genes are associated with the outcome, implying that the definition of DNA methylation patterns of AML is expected to reveal clinical and molecular features and survival in patients with AML. However, there are few reports of DNA methylation in pediatric patients with AML. Thus, we analyzed genome-wide DNA methylation in pediatric patients with AML to reveal its association with clinical features, genetic alterations, and prognostic impact. Besides, our previous study revealed that the high expression of MECOM (also known as EVI1 ) or PRDM16 (also known as MEL1 ) was associated with inferior outcomes in patients with AML. We also investigated the correlation between DNA methylation and gene expression in pediatric patients with AML.

Methods

Between 2006 and 2010, 443 pediatric patients with de novo AML (0-17 years) participated in the Japanese AML-05 trial conducted by the Japanese Pediatric Leukemia/Lymphoma Study Group. Of these, 369 samples were available, and 64 patients were enrolled in this study. The cytogenetic features of 64 patients were as follows: normal karyotype, 33; RUNX1-RUNX1T1 , 8; KMT2A rearrangement, 10; complex karyotype, 6; and other cytogenetics, 7. This cohort included 15 patients with FLT3 -internal tandem duplication (ITD), 8 with CEBPA biallelic mutations, 10 with high MECOM expression, and 30 with high PRDM16 expression. We performed comprehensive DNA methylation analysis using Infinium MethylationEPIC BeadChip (Illumina, Inc., San Diego, CA, USA) in 64 pediatric patients with AML to reveal the correlations among DNA methylation patterns, clinical features, genetic alterations, and prognostic impact in pediatric AML.

Results and Discussion

Unsupervised hierarchical clustering based on methylation values of the 567 CpG sites, which showed most variable methylation values between 64 individuals, generated four clusters (clusters 1-4). The number of patients in clusters 1, 2, 3, and 4 was 23, 12, 13, and 16, respectively. Interestingly, these four clusters harbored their molecular features. Cluster 1 included patients with RUNX1/RUNX1T1 , normal karyotype with low PRDM16 expression, or KMT2A rearrangement with low MECOM expression. Cluster 2 included patients with FLT3 -ITD and/or normal karyotype with high PRDM16 expression. Cluster 3 included patients with normal karyotype with CEBPA biallelic mutations and cluster 4 patients with FLT3 -ITD, normal karyotype with high PRDM 16 expression, or KMT2A rearrangement with high MECOM expression. Differences in frequencies of common molecular aberrations among clusters were assessed with the Fisher-Freeman-Halton test. There was an unequal distribution of FLT3 -ITD and high PRDM16 expression ( P = 0.003 for both), with concordantly high frequencies in clusters 2 and 4 and low in clusters 1 and 3. Clusters 2 and 4 tended to be correlated with older age, higher white blood cell counts at diagnosis, high relapse rate, and high mortality. These results suggest that DNA methylation can stratify the risk in pediatric AML. Conversely, no independent methylation marker was present to predict the adverse outcome, thereby indicating that an assortment of several methylation sites may be a useful marker for risk stratification.

Conclusion

We investigated DNA methylation patterns in pediatric patients with AML and found four distinct clusters. Furthermore, our findings indicated that quantitative determination of DNA methylation percentage at specific CpG sites may be useful for risk stratification in pediatric AML. Considering the need of further analyses to reveal the significance of DNA methylation, we are analyzing the results currently and would like to discuss these data at the annual meeting.