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DNA methylation and hydroxymethylation patterns in acute myeloid leukemia patients with mutations in DNMT3A and IDH1/2 and their combinations
Autoři | |
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Rok publikování | 2019 |
Druh | Článek v odborném periodiku |
Časopis / Zdroj | Cancer Biomarkers |
Fakulta / Pracoviště MU | |
Citace | |
www | http://dx.doi.org/10.3233/CBM-182176 |
Doi | http://dx.doi.org/10.3233/CBM-182176 |
Klíčová slova | AML; DNMT3A and IDH1/2 mutations; methylation; hydroxymethylation; GZMB; CHFR |
Popis | BACKGROUND: Aberrant epigenetic patterns are a hallmark of acute myeloid leukemia (AML). Mutations in profound epigenetic regulators DNMT3A and IDH1/2 often occur concurrently in AML. OBJECTIVES: The aim was to analyze DNA methylation, hydroxymethylation and mRNA expression profiles in AML with mutations in DNMT3A and IDH1/2 (individually and in combinations). METHODS: Infinium MethylationEPIC BeadChip (Illumina) covering 850,000 CpGs was utilized. The validation of hydroxy-/methylation data was done by pyrosequencing. HumanHT-12 v4 Expression BeadChip (Illumina) was used for expression examination. RESULTS: Hierarchical clustering analysis of DNA hydroxy-/methylation data revealed clusters corresponding to DNMT3A and IDH1/2 mutations and CD34+ healthy controls. Samples with concurrent presence of DNMT3A and IDH1/2 mutations displayed mixed DNA hydroxy-/methylation profile with preferential clustering to healthy controls. Numbers and levels of DNA hydroxymethylation were low. Uniformly hypermethylated loci in AML patients with IDH1/2 mutations were enriched for immune response and apoptosis related genes, among which hypermethylation of granzyme B (GZMB) was found to be associated with inferior overall survival of AML patients (P = 0.035). CONCLUSIONS: Distinct molecular background results in specific DNA hydroxy-/methylation profiles in AML. Site-specific DNA hydroxymethylation changes are much less frequent in AML pathogenesis compared to DNA methylation. Methylation levels of enhancer located upstream GZMB gene might contribute to AML prognostication models. |
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