Abstract
Abstract 3568
Acute lymphoblastic Leukemia (ALL) is the most common malignancy in children. Risk stratification at initial diagnosis is essential for an intensity adapted therapy.
During the last years epigenetic processes such as DNA methylation have been discovered to play an important role in the pathogenesis of leukemia. Nevertheless up to now there is only little information whether deregulation of DNA methylation has a prognostic impact and can be associated with the response to therapy and outcome of patients. However, identification of such prognostic methylation markers might improve risk prediction and individualized therapy approaches.
In order to identify ALL-specific DNA methylation pattern as well as risk-associated aberrant DNA methylation we analyzed a cohort of 100 ALL samples (79 B-ALL, 21 T-ALL) of the ALL-BFM 2000 study including 36 matched remissions. Classification into risk groups was based on prednisone response and positivity for BCR/ABL or MLL/AF4 fusion transcripts as well as minimal residual disease. For whole genome DNA methylation analysis we used the newly developed Infinium HumanMethylation450 BeadChip covering 482,421 CpG dinucleotides of the human Genome.
Unsupervised hierarchical clustering showed that the ALL samples, independent of immunphenotype or risk group, clustered separately from the remission samples. A total of 18,326 promoter CpGs referring to 3491 genes were differentially methylated in ALL compared with remission controls. About 95% of these genes were hypermethylated by more than 2-fold (p<0.001). Genes predominantly affected by differential methylation were associated with Cellular and Tissue Development and Cell Signaling. Notably, several genes of the PAX- and SIX-families, comprising transcription factors that regulate proliferation and development, were hypermethylated in the ALL samples. A correlation with microarray-RNA-expression data comparing ALL vs. healthy (www.leukemia-gene-atlas.org) showed an inverse correlation between DNA methylation and mRNA levels for about half of the top 50 hypermethylated genes and of 70% of the top 50 hypomethylated genes.
Interestingly, hierarchical clustering revealed that patients grouped into high risk and intermediate risk clustered apart from patients of the standard risk group. Comparing high risk (HR) and standard risk (SR) groups, 860 differentially methylated genes could be detected and the majority (approximately 80%) was hypermethylated in the HR group. Hypermethylated genes predominantly functioned in gene expression- (e.g. HDAC9, HDAC4 and DNMT3A), cell death- as well as hematological development-pathways. Hypomethylated genes mainly belonged to cellular growth and proliferation- as well as signaling pathways. Interestingly, the ABC transporter ABCC4 that confers drug resistance in solid tumors was also hypomethylated in the HR group. Prednisone response was also associated with DNA methylation differences: A total of 325 genes were differentially methylated between good and poor prednisone responders. Again, ABCC4 was hypomethylated in the poor-response group potentially indicating increased drug resistance. Correlation of differentially methylated genes in the HR- and poor-prognostic groups showed an overlap in 293 genes, probably representing the gene set whose aberrant methylation might be associated with therapy failure.
Taken together, genome spanning methylation analyses can identify prognosis and therapy response associated markers. Some of these methylation changes might also be functionally associated with therapy resistance.
Disclosures:
No relevant conflicts of interest to declare.
Identification of adult Philadelphia-like acute lymphoblastic leukemia using a FISH‐based algorithm distinguishes prognostic groups and outcomes