Methylome profiling enhances risk stratification and reveals context-dependent chemo-resistance mechanisms in acute myeloid leukemia

While current risk stratification systems, such as European LeukemiaNet (ELN), use cytogenetic and molecular markers to guide treatment decisions, their predictive accuracy remains suboptimal, particularly in forecasting treatment response. In this study, we performed integrated methylome and transcriptome analysis of diagnostic samples from 145 AML patients, including methylome data on 25 patients, to investigate the molecular basis underlying the discrepancy between predicted and actual treatment outcomes.

Unsupervised analysis revealed that while genomic backgrounds strongly influence molecular profiles, treatment response patterns frequently diverge from predictions based on cytogenetic and mutational risk classifications. We identified PTX4 as a novel tumor suppressor gene (TSG) silenced by DNA hypermethylation in patients with adverse-risk AML. Within individual AML subtypes, comparison of refractory/relapsed (RR) cases versus those achieving complete remission (CR) uncovered distinct resistance mechanisms.