bioRxivCancer BiologyPreprint
Chromatin landscape and epigenetic heterogeneity of acute myeloid leukemia
Yotaro OchiiD, Markus Liew-LittoriniD, Yasuhito NannyaiD, Sofia Bengtzén, Bénédicte Piauger, Stefan DenebergiD, Martin JädersteniD, Vladimir LazarevićiD, Jörg CammengaiD, Anna RobeliusiD, Lovisa Wennström, Emma Ölander, Senji KasaharaiD, Nobuhiro HiramotoiD, Nobuhiro KanemuraiD, Nobuo SezakiiD, Maki Sakurada, Makoto IwasakiiD, Junya KandaiD, Yasunori UedaiD, Satoshi YoshiharaiD, Tom ErkersiD, Nona StruyfiD, Yu Watanabe, Masanori Motomura, , Seishi OgawaiD
Abstract
Acute myeloid leukemia (AML) is an aggressive hematologic cancer characterized by proliferation of immature myeloblasts. It shows profound molecular heterogeneity, which has been primarily studied through genetic abnormalities, providing the basis for disease classification, prognostication, and therapeutic choice. However, genetic factors alone may not fully explain AML pathogenesis and diversity, while leaving the role of abnormal epigenome, particularly chromatin state, largely unexplored in a large cohort of patients. Here we show that AML is classified into 16 subgroups with distinct chromatin accessibility profiles based on ATAC-seq in 1,563 AML cases, including novel AML subgroups not previously recognized in conventional genomic classifications. By integrating multi-omics analyses of genome, transcriptome, and major histone marks, we show that these epigenetic subgroups exhibit unique features in clinical presentation, gene mutations, differentiation states, gene expression, and super-enhancer profiles, which are validated across independent cohorts. Single-cell sequencing demonstrates the presence of subgroup-specific ATAC signatures that are shared by all leukemic cells, confirming the definitive role of the epigenome in the ATAC-based classification. Mechanistically, each subgroup is associated with a distinct gene regulatory network centered on key transcription factors, where subgroup-specific super-enhancers play a pivotal role. These ATAC subgroups also have prognostic significance independent of genomic classification, and help reveal unexpected drug sensitivities. In summary, ATAC-based chromatin profiling in this large sample set, combined with multi-omics data, provides new insights into AML pathogenesis beyond genomic profiling and also serves as an invaluable resource for AML research.
- organism: human
- assay: scATAC-seq
- assay: bulk RNA-seq
- assay: ATAC-seq
- research focus: clustering
- research focus: gene regulatory network inference
- research focus: differential expression
- research focus: protein folding & dynamics
- approach: statistical model
- approach: machine learning (classical)
- Citations
- 0
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- AttentionAML: An Attention-based Deep Learning Framework for Accurate Molecular Categorization of Acute Myeloid Leukemia
Lusheng Li, Joseph David Khoury, … Shibiao Wan·bioRxiv·May 20, 2025
- DNA methylation stochasticity is linked to transcriptional variability and identifies convergent epigenetic disruption across genetically-defined subtypes of AML
Eleanor Hilgart, Weiqiang Zhou, … Andrew P. Feinberg·Cancer ResearchPeer-reviewed·Mar 16, 2026
- Computational modeling of methylation impact of AML drivers reveals new pathways and refines AML risk-stratification
B. Gurun, J. W. Tyner, … P. T. Spellman·bioRxiv·May 17, 2023
- Epigenomic mapping in B-cell acute lymphoblastic leukemia identifies transcriptional regulators and noncoding variants promoting distinct chromatin architectures
Kelly R. Barnett, Robert J. Mobley, … Daniel Savic·Cell GenomicsPeer-reviewed·Nov 20, 2023
- Acute myeloid/T-lymphoblastic leukemia (AMTL): A distinct category of acute leukemias with common pathogenesis in need of improved therapy
A. Gutierrez, A. Kentsis·bioRxiv·Nov 21, 2017
- Network-based clustering unveils interconnected landscapes of genomic and clinical features across myeloid malignancies
F. Bayer, M. Roncador, … J. Kuipers·bioRxiv·Oct 25, 2023