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Chromatin architecture reprogramming reveals novel epigenetic dependencies in breast cancer [Cut&Run]

GSE296423 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 24 samples Submitted 2026/04/24 Platform GPL24676
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 24 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
Breast cancerThis series is part of our curated briefing on it.
Samples
24 samples: 12 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
Chromatin architecture reprogramming reveals novel epigenetic dependencies in breast cancerGenes & development · 2026
Summary (written by the submitters)
Chromatin architecture plays a key role in development and cancer, yet most studies lack mechanistic depth due to widespread epigenomic remodeling. To address this, we tracked chromatin structure dynamics during the progression of endocrine resistance in ER+ breast cancer using Hi-C, chromatin accessibility, epigenomic, and transcriptomic profiling.
Read the full summary ↓
We uncovered a critical role for H3K9 methylation and the demethylase KDM4C in driving proliferation of cells fated to become resistant through a non-genomic estrogen-mediated mechanism. These findings highlight the mechanistic contribution of chromatin regulation in therapy resistance and offer a blueprint for studying similar processes in cancer, development, and cell fate decisions.
Published in
Chromatin architecture reprogramming reveals novel epigenetic dependencies in breast cancer
Garcia-Martinez L, Zha M, Borges RL et al. · Genes & development 2026 · PMID 41412800 · doi:10.1101/gad.352982.125
This dataset
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.

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 GSE296423_RAW.tar (it can run to tens of gigabytes).

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.

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 PRJNA1259259 and SRA study SRP583373. Searching any of these in the dataset finder brings you back here.

Study design
12 conditions, mostly in duplicate
HD_SiC_H3K9me3 ×2 HD_SiC_H3K27me3 ×2 HD_SiC_IgG ×2 HD_SiKDM4C_H3K9me3 ×2 HD_SiKDM4C_H3K27me3 ×2 HD_SiKDM4C_IgG ×2 E2_SiC_H3K9me3 ×2 E2_SiC_H3K27me3 ×2 +4 more

Supports a between-group comparison across 24 samples.

How we read this: 12 replicated groups read from 24 sample titles; they account for 24 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 Breast cancer datasets

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Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.