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Incorporating histone H2B variants into chromatin modifies chromatin accessibility to induce the epithelial-to-mesenchymal transition in breast cancer [CUT&RUN]

GSE285390 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 32 samples Submitted 2026/02/11 Platform GPL24676
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 32 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
32 samples: 32 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.
Paper
Single amino-acid differences define H2B variants and modify chromatin accessibility to induce EMT in breast cancerOncogene · 2026
Summary (written by the submitters)
Histones scaffold genomic DNA and regulate access to the transcriptional machinery. However, naturally occurring histone variants can alter histone-DNA interactions, DNA and histone modifications, and the chromatin interactome. Hence, alterations in histone variant deposition can disrupt chromatin, and are increasingly recognized as a way to trigger various disease (including cancer).
Read the full summary ↓
While significant attention has been placed on the biochemical and functional roles of H2A and H3 variants, H2B variants remain largely understudied. Here, we show that H2B variants are dysregulated in breast cancer and that certain variants are associated with specific breast cancer subtypes. HIST1H2BO overexpression (in particular) is more common in Asian, African American/Black, and young female populations and is associated with a worse prognosis. In vitro, H2B1O compacts chromatin, and incorporating H2B1O into chromatin activates pro-inflammatory and oncogenic pathways and the epithelial-to-mesenchymal transition (EMT), and generates resistance to first-line chemotherapeutic agents. Thus, H2B1O acts much like an onco-histone, with H2B variant expression being a prognostic biomarker for breast cancer and a potential new target for drug therapies to enhance treatment efficacy.
Published in
Single amino-acid differences define H2B variants and modify chromatin accessibility to induce EMT in breast cancer
Dhahri H, Lau KH, Saintilnord WN et al. · Oncogene 2026 · PMID 41580505 · doi:10.1038/s41388-025-03636-1
This dataset
Open GSE285390 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 GSE285390_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 PRJNA1203267 and SRA study SRP553958. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41580505) ↗
Study design
32 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 32 sample titles: 32 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
Datasets on a similar topic

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