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SWI/SNF is a gatekeeper of chromatin access at enhancer networks controlling triple-negative breast cancer progression [ChIP-Seq]

GSE261988 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 79 samples Submitted 2025/08/27 Platform GPL24676
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 79 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
79 samples: 28 conditions, mostly in triplicateGroups 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)
Triple-negative breast cancer (TNBC) is a particularly aggressive subtype of breast cancer with high metastatic potential, limited treatment options, and low patient survival rates. By combining proteomics and genomics approaches, we identify an oncogenic transcriptional network in TNBC involving the glucocorticoid receptor (GR), GATA6, the key oncoprotein MYC, and AP-1 transcription factors.
Read the full summary ↓
Although these transcription factors share cis-regulatory regions, they control largely distinct oncogenic pathways. We demonstrate that SWI/SNF chromatin remodeling complex is a common gatekeeper of chromatin access for these transcription factors, and that inhibition of SWI/SNF-mediated chromatin remodeling decommissions the distinct enhancer repertoires and target gene programs controlled by these transcription factors. Consistently, SWI/SNF inhibition blocks cancer cell proliferation, chemoresistance, and invasion both in vitro and in vivo. Thus, we propose that several key oncogenic pathways in TNBC depend on SWI/SNF-mediated chromatin remodeling, making this disease vulnerable to SWI/SNF inhibitors.
This dataset
Open GSE261988 in finder → Find more human ChIP / ATAC / CUT&Tag datasets → Breast cancer 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 GSE261988_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 PRJNA1089994 and SRA study SRP496610. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
28 conditions, mostly in triplicate
GATA6 ChIP, Veh, BT549 cells, ×3 GATA6 ChIP, +DEX, BT549 cells, ×3 MED1 ChIP, siCtl, +DEX, BT549, ×3 GR ChIP, siCtl, +DEX, BT549, ×3 MED1 ChIP, siGATA6, Veh, BT549, ×3 MED1 ChIP, siGATA6, +DEX, BT549, ×3 GR ChIP, siGATA6, +DEX, BT549, ×3 GR ChIP, +DEX, BT549 cells, ×3 +28 more

Supports a between-group comparison across 71 samples.

How we read this: 28 replicated groups read from 79 sample titles; they account for 71 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

+ 39 more — browse all 79 samples with per-sample file links →

More Breast cancer datasets

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

Share this dataset

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.