Epigenomic Analysis Uncovers New AML Subgroups and Drug Sensitivities
As one of the most aggressive blood cancers, the way acute myeloid leukemia (AML) is classified continues to shape every major clinical decision—from risk stratification to the choice of targeted therapies. For decades, that classification has rested almost entirely on the gene mutations found in leukemic cells. But mutations alone have never fully explained why AML behaves so differently from patient to patient. A new study published in Nature now provides the missing layer: the epigenome.
In the largest chromatin‑profiling effort ever conducted for any cancer, a research team led by Seishi Ogawa, MD, PhD, and Yotaro Ochi, MD, PhD, of Kyoto University, together with Sören Lehmann, MD, PhD, of the Karolinska Institute, mapped the chromatin accessibility landscape of 1,563 AML patient samples. Their analysis—built on ATAC‑seq, RNA‑seq, DNA methylation, ChIP‑seq, whole‑genome sequencing, and single‑cell multiomics—reveals that AML can be classified into 16 distinct epigenomic subgroups, each defined by a characteristic chromatin state and its own regulatory wiring.
As the authors wrote, “ATAC-seq…show[s] that AML can be classified into 16 subgroups on the basis of chromatin accessibility profiles.” This chromatin‑based structure was remarkably stable: single‑cell ATAC‑seq across more than 280,000 cells confirmed that each patient’s leukemic population shares a conserved accessibility fingerprint.
Each subgroup carries a unique combination of driver mutations, differentiation states, transcription‑factor networks, DNA methylation patterns, and super‑enhancer architecture. Many do not align cleanly with existing genomic classifications such as WHO or ICC, according to the researchers. In fact, the team found that even exhaustive decision‑tree analyses of known driver mutations could not explain most subgroup identities. As the paper noted, “Evidence suggests that genetic alterations do not fully explain AML pathophysiology and heterogeneity.”
Clinically, chromatin information sharpened prognostic assessment in both Swedish and Japanese cohorts. Several subgroups also showed unexpected drug sensitivities. Three subgroups responded to MEK inhibitors despite lacking RAS‑pathway mutations. Another subgroup, enriched for RUNX1 mutations and marked by a chromatin profile resembling early B‑cell precursors, proved highly sensitive to ABL inhibitors.
The study, “Chromatin landscape and epigenetic heterogeneity of acute myeloid leukemia,” positions chromatin architecture as a foundational dimension of AML biology. It also provides a practical path toward clinical adoption: the team distilled a 30‑gene expression signature capable of identifying high‑risk chromatin subgroups using standard sequencing workflows.
Looking ahead, the group aims to develop lower‑cost diagnostic approaches and refine treatment strategies tailored to each epigenomic subgroup. The newly generated eCHROMA AML atlas is expected to serve as a resource for cancer epigenomics broadly, enabling discovery of new therapeutic targets and mechanistic insights.
