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Anthracyclines induce global changes in chromatin accessibility in cardiomyocytes that overlap with cardiovascular disease loci [ATAC-seq]

GSE291260 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 48 samples Submitted 2025/06/17 Platform GPL30173
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 48 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
48 samples: 48 samples, each with a distinct title — no replicated groupsGroups 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)
Breast cancer drugs including anthracyclines (ACs) and Trastuzumab increase the risk for cardiovascular diseases (CVDs) such as atrial fibrillation (AF) and heart failure (HF) that ultimately affect the heart muscle. These CVDs are associated with hundreds of genetic variants in non-coding regions of the genome. However, how these drugs affect the regulatory potential of the non-coding genome of the heart and CVD risk loci is unknown.
Read the full summary ↓
We therefore measured global chromatin accessibility across iPSC-derived cardiomyocytes derived from four healthy individuals that we treated with topoisomerase II (TOP2) inhibiting ACs, Doxorubicin, Epirubicin, and Daunorubicin, and the anthracenedione, Mitoxantrone as well as the TOP2-independent monoclonal antibody Trastuzumab, for three and 24 hours. We identified tens of thousands of open chromatin regions that are differentially accessible in response to TOP2 inhibitor treatments over time, and no changes in response to Trastuzumab. Early AC-responsive regions are promoter-proximal and are enriched for regions bound by TOP2 beta. Late AC-responsive regions are enriched for AC response genes particularly those associated with mismatch repair. AC-response regions near AC response genes are enriched for FOS:JUNB transcription factor motifs. Three AC-induced cardiotoxicity-, 28 AF- and 14 HF-associated SNPs directly overlap late AC-responsive regions. Early AC-responsive regions are enriched for AF SNPs including rs3176326, which is also associated with HF, and is an eQTL for CDKN1A in heart tissue. This SNP associates with increased chromatin accessibility at a TOP2 beta-bound region, increased histone acetylation, and increased CDKN1A expression in response to all ACs. Our results demonstrate large-scale changes in chromatin accessibility in cardiomyocytes treated with ACs, which correspond to several regions harboring AF and HF risk loci. The identified drug-responsive chromatin regions can be used to annotate variants in cancer patient populations to contribute to risk estimation for CVD.
This dataset
Open GSE291260 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 GSE291260_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 PRJNA1232673 and SRA study SRP568374. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
48 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 48 sample titles: 48 distinct titles with little repetition. 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

+ 8 more — browse all 48 samples with per-sample file links →

Datasets on a similar topic

Search all human ChIP / ATAC / CUT&Tag datasets in GEO →

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