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Ectopic MYC Expression Reprograms Epigenetic Landscapes and Transcription Factor Networks to Drive Differentiation Block and Malignant Transformation in AML [ATAC-seq]

GSE293201 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 35 samples Submitted 2026/03/26 Platform GPL18573
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 35 samples

What it is
ChIP-seq / ATAC-seq (genome binding and open chromatin)Where proteins bind the genome, or which regions are open and active.
Organism
Homo sapiens (human)
Topic
Acute myeloid leukemiaThis series is part of our curated briefing on it.
Samples
35 samples: 16 conditions, mostly in duplicateGroups are read from the sample names, not from the paper. Check the list below.
Data you can get
A processed table (series matrix) and supplementary files from NCBI; the raw sequencing reads from ENA. Which of these hold counts depends on the study, so check the file list.
Paper
Sustained MYC overexpression drives myeloid differentiation block and acquisition of leukemic phenotypesExperimental hematology · 2026
Summary (written by the submitters)
Overexpression of MYC is a common convergent consequence of genetic driver mutations in acute myeloid leukemia (AML). However, despite extensive research, the mechanisms by which this proto-oncogene promotes leukemogenesis remain incompletely understood. Here, we developed models of deregulated MYC expression in human pluripotent stem cell (hPSC)-derived myelopoiesis.
Read the full summary ↓
We show that MYC overexpression from the endogenous locus maintaining physiological regulation is insufficient for leukemogenesis. Rather, constitutive MYC overexpression from ectopic alleles is necessary for driving and sustaining leukemia-associated phenotypes. These phenotypes depend on the widespread disruption of epigenetic landscapes imposed by MYC overexpression, which in turn underlies a differentiation arrest and dysregulation of the BACH1 transcription factor network, identified here as a mediator of these changes. Our findings shed new light into the mechanisms underlying MYC-induced malignant transformation and leukemogenesis, suggesting novel therapeutic targets for AML.
Published in
Sustained MYC overexpression drives myeloid differentiation block and acquisition of leukemic phenotypes
Stokes N, Carcamo S, Demircioglu D et al. · Experimental hematology 2026 · PMID 41796634 · doi:10.1016/j.exphem.2026.105403
This dataset
Open GSE293201 in finder → Find more human ChIP / ATAC / CUT&Tag datasets → Acute myeloid leukemia landscape →
Download · which file do I need?

Direct links to NCBI and ENA, no account and no request form. Pick by what you want to do: take the small processed table to look, the supplementary files to re-analyse, or the original raw data to start over.

1 · Just have a look

Processed table

The series matrix: one table of values per sample as the submitters processed it. The smallest download, and it opens in Excel or R. Start here to see what the data look like.

Series matrix ↓
2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE293201_RAW.tar (it can run to tens of gigabytes).

All supplementary files ↗ Whole study · RAW.tar ↓
3 · Start from the raw reads

Raw sequencing reads

The original FASTQ files, straight from the sequencer, held at ENA. Large, and you align them yourself, so only choose this if you need to re-process the study from scratch.

Raw reads on ENA ↗

What the files usually look like: Look for peak files (.bed, .narrowPeak) and signal tracks (.bigWig) among the supplementary files; the raw reads are on ENA.

Also filed as BioProject PRJNA1243339 and SRA study SRP574031. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41796634) ↗
Study design
16 conditions, mostly in duplicate
doxee17_dox_d12 ×3 doxee17_ut_d12 ×2 doxee17_ut_d14 ×2 doxee17_ut_d16 ×2 doxee17_ut_d18 ×2 doxee17_ut_d20 ×2 doxee17_dox_d14 ×2 doxee17_dox_d16 ×2 +10 more

Supports a between-group comparison across 33 samples.

How we read this: 16 replicated groups read from 35 sample titles; they account for 33 of them. These groups are guessed from the sample names, not taken from the paper, so check them against the sample list below before relying on them.

Samples in this study
More Acute myeloid leukemia datasets

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