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Perturbing LSD1 and WNT rewires transcription to synergistically induce AML differentiation (CUT&RUN)

GSE251857 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 26 samples Submitted 2025/01/09 Platform GPL30173
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 26 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)
Samples
26 samples: 13 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
Perturbing LSD1 and WNT rewires transcription to synergistically induce AML differentiationNature · 2025
Summary (written by the submitters)
Impaired differentiation is a hallmark of myeloid malignancies1,2. Therapies that enable cells to circumvent the differentiation block, such as all-trans retinoic acid (ATRA) and arsenic trioxide (ATO), are by and large curative in acute promyelocytic leukaemia3, but whether 'differentiation therapy' is a generalizable therapeutic approach for acute myeloid leukaemia (AML) and beyond remains incompletely understood.
Read the full summary ↓
Here we demonstrate that simultaneous inhibition of the histone demethylase LSD1 (LSD1i) and the WNT pathway antagonist GSK3 kinase4 (GSK3i) robustly promotes therapeutic differentiation of established AML cell lines and primary human AML cells, as well as reducing tumour burden and significantly extending survival in a patient-derived xenograft mouse model. Mechanistically, this combination promotes differentiation by activating genes in the type I interferon pathway via inducing expression of transcription factors such as IRF7 (LSD1i) and the co-activator β-catenin (GSK3i), and their selective co-occupancy at targets such as STAT1, which is necessary for combination-induced differentiation. Combination treatment also suppresses the canonical, pro-oncogenic WNT pathway and cell cycle genes. Analysis of datasets from patients with AML suggests a correlation between the combination-induced transcription signature and better prognosis, highlighting clinical potential of this strategy. Collectively, this combination strategy rewires transcriptional programs to suppress stemness and to promote differentiation, which may have important therapeutic implications for AML and WNT-driven cancers beyond AML.
Published in
Perturbing LSD1 and WNT rewires transcription to synergistically induce AML differentiation
Hosseini A, Dhall A, Ikonen N et al. · Nature 2025 · PMID 40240608 · doi:10.1038/s41586-025-08915-1
This dataset
Open GSE251857 in finder → Find more human ChIP / ATAC / CUT&Tag datasets →
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 GSE251857_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 PRJNA1055694 and SRA study SRP479739. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40240608) ↗
Study design
13 conditions, mostly in duplicate
THP-1 cells, combo-b-cat, CUT&RUN biol ×2 THP-1 cells, combo-IRF-7, CUT&RUN biol ×2 THP-1 cells, CONTROL, CUT&RUN biol ×2 THP-1 cells, CTRL-b-cat, CUT&RUN biol ×2 THP-1 cells, CTRL-IRF7, CUT&RUN biol ×2 THP-1 cells, GSK-LSD-b-cat, CUT&RUN biol ×2 THP-1 cells, GSK-LSD-IRF7, CUT&RUN biol ×2 THP-1 cells, LY-b-cat, CUT&RUN biol ×2 +5 more

Supports a between-group comparison across 26 samples.

How we read this: 13 replicated groups read from 26 sample titles; they account for 26 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
Datasets on a similar topic

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