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August 27, 2026Blood

Epigenetic markers expand genetic risk estimation in acute myeloid leukemia

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Authors

SASalma AbdelbakyBGBrian GiacopelliJKJessica Kohlschmidt

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Overview

Cohort study demonstrates that DNA methylation profiling refines prognostic risk assessment in acute myeloid leukemia, suggesting epitypes capture clinically meaningful genetic phenocopies.

Key Points

  • To determine whether DNA methylation signatures can augment standard genetic and clinical risk stratification to better predict clinical outcomes in acute myeloid leukemia.
  • Classified 1,262 patients with de novo acute myeloid leukemia into 13 unsupervised DNA methylation subtypes (epitypes).
  • Derived a DNA methylation signature marked by hypomethylation of STAT binding sites (SHS) enriched in FLT3-ITD mutations.
  • Developed machine learning models combining DNA methylation profiles with clinical, demographic, and genetic variables to predict remission, relapse, and overall survival.
  • Patients lacking cardinal genetic alterations who displayed alteration-like DNA methylation patterns (e.g., CEBPAbZIP, FLT3-ITD, core-binding factor, and KMT2A-rearrangements) exhibited outcomes comparable to patients with actual mutations.
  • Positivity for the STAT hypomethylation signature (SHS) independently identified patients with inferior outcomes, enhancing the prognostic resolution of FLT3-ITD mutations.
  • Machine learning models integrating DNA methylation signatures significantly outperformed standard genetic, demographic, and clinical markers alone in predicting complete remission, relapse, and overall survival.

Cite This Study

Abdelbaky et al. (2026) studied this question.

synapsesocial.com/papers/6a8fe98110c91c1e926211a9https://doi.org/10.1182/blood.2025031899
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