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Data from DNA Methylation Stochasticity Is Linked to Transcriptional Variability and Convergent Epigenetic Disruption across Genetic Subtypes of Acute Myeloid Leukemia

Year: 2026
Type: other
Abstract: Disruption of the epigenetic landscape is of particular interest in acute myeloid leukemia (AML) due to its relatively low mutational burden and frequent occurrence of mutations in epigenetic regulators. In this study, we applied an information-theoretic analysis of methylation potential energy landscapes, capturing changes in mean methylation level and methylation entropy, to comprehensively analyze DNA methylation stochasticity in subtypes of AML defined by mutually exclusive genetic mutations. AML subtypes with CEBPA double mutation and those with IDH mutations were identified as distinctly high-entropy subtypes, marked by methylation disruption over a convergent set of genes. The analysis revealed a core program of epigenetic landscape disruption across all AML subtypes; discordant methylation stochasticity, transcriptional dysregulation, and altered chromatin accessibility converged on functionally important leukemic signatures. Demonstration of a relationship between methylation entropy and gene expression variability connected the disruption of the epigenetic landscape to transcription in AML. Finally, the hypomethylating drug decitabine led to reduction of DNA methylation entropy specifically in IDH2-mutant AML cells. Overall, this approach identified a convergent program of epigenetic dysregulation in leukemia, clarifying the contribution of specific genetic mutations to stochastic disruption of the epigenetic and transcriptional landscapes of AML. Significance: DNA methylation stochasticity, variable gene expression, and altered chromatin accessibility converge on key leukemic regulators across AML subtypes, suggesting a genotype-independent role of stochastic disruption of the epigenetic landscape in mediating leukemogenesis.
Language: English
Subfield: Hematology
Field: Medicine
Open Access status: gold
OpenAlex ID: W7167092432
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