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Inhibition of p300/CREBBP catalytic activity drives context-dependent transcriptional activation in AML. [ChIP-seq]

GSE304612 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 95 samples Submitted 2026/02/27 Platform GPL34284Platform GPL24676
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 95 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
95 samples: 47 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.
Summary (written by the submitters)
The lysine acetyltransferase (KAT) activity of p300/CREBBP has traditionally been linked to transcriptional activation. This has been attributed largely to acetylation of histone residues such as H3K27ac, a defining hallmark of active regulatory elements. Here we show that, in acute myeloid leukemia (AML), inhibition of p300/CREBBP catalysis can paradoxically increase transcription.
Read the full summary ↓
We combined time-resolved dynamics of nascent and total transcription with chromatin binding dynamics of p300/CREBBP and their associated TFs/co-regulators (inferred from chromatin pull-down proteomics, acetyl-proteomics and motif enrichment) to uncover mechanisms of transcriptional rewiring after p300/CREBBP catalytic inhibition. In parallel, we dissected the functional contribution of individual p300/CREBBP acetyl-interactome members to KAT inhibition using genome-wide CRISPR-Cas9 dropout and focused Perturb-seq screens. Together, these approaches revealed that KAT inhibition paradoxically retains p300/CREBBP and promotes cooperative TF assembly and increased H3K27 acetylation at a subset of regulatory elements. The effect was most pronounced at IRF motif-enriched loci, including interferon-stimulated genes (ISGs), where KAT inhibition triggered p300/CREBBP accumulation and enhanced combinatorial TF binding, enabling recruitment of the ISG activator STAT1. Consequently, ISG loci were converted into transcriptionally active states that induced cell-cycle arrest, differentiation and apoptosis. Therapeutically, combining KAT inhibition with interferon-alpha augmented ISG expression, synergistically drove AML cell death in vitro and significantly extended survival in both AML xenografts and murine models. These findings refine our understanding of p300/CREBBP KAT activity, demonstrating that cooperative TF assembly can reconfigure p300/CREBBP-containing complexes under catalytic inhibition to induce transcription, with translational implications for reprogramming interferon-driven programs through catalytic inhibition in AML and beyond.
This dataset
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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 GSE304612_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 PRJNA1301922 and SRA study SRP607196. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
47 conditions, mostly in duplicate
MOLM13, DMSO control, P300, ×2 MOLM13, 1 µM A485, P300, ×2 MOLM13, DMSO control, CREBBP, ×2 MOLM13, 1 µM A485, CREBBP, ×2 MOLM13, DMSO control, IRF2BP2, ×2 MOLM13, 1 µM A485, IRF2BP2, ×2 MOLM13, DMSO control, CEBPA, ×2 MOLM13, 1 µM A485, CEBPA, ×2 +40 more

Supports a between-group comparison across 94 samples.

How we read this: 47 replicated groups read from 95 sample titles; they account for 94 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

+ 55 more — browse all 95 samples with per-sample file links →

Datasets on a similar topic

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