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Increased chromatin accessibility drives transition to androgen receptor splice variant dependence in castration-resistant prostate cancer [ChIP-Seq]

GSE252897 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 75 samples Submitted 2025/01/01 Platform GPL21697Platform GPL24676
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 75 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
75 samples: 23 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
Increased nuclear factor I-mediated chromatin access drives transition to androgen receptor splice variant dependence in prostate cancerCell reports · 2025
Summary (written by the submitters)
Androgen receptor (AR) splice variants, of which ARv7 is most common, are increased in prostate cancer (PC) that develops resistance to androgen signaling inhibitor drugs, but the extent to which they drive AR activity, and whether they have novel functions or dependencies, remain to be determined. We generated a subline of VCaP PC cells (VCaP16) that was resistant to the AR inhibitor enzalutamide (ENZ) and found that AR activity was independent of the full length AR (ARfl), despite its continued high level expression, and was instead driven by ARv7.
Read the full summary ↓
The ARv7 cistrome and transcriptome in these cells mirrored that of the ARfl in VCaP cells, although ARv7 chromatin binding was weaker, and strong ARv7 binding sites correlated with higher affinity ARfl binding sites across multiple models and clinical samples. Notably, although ARv7 expression increased rapidly in response to ENZ, there was a long lag before it gained chromatin binding and transcriptional activity. This lag was associated with an increase in chromatin accessibility, with the AR and nuclear factor I (NFI) motifs being most enriched at these more accessible sites. Moreover, the transcriptional effects of combined NFIB and X knockdown versus ARv7 knockdown were highly correlated. These findings indicate that ARv7 can drive the AR program, but that its activity is dependent on adaptations that increase chromatin accessibility to enhance its intrinsically weak chromatin binding.
Published in
Increased nuclear factor I-mediated chromatin access drives transition to androgen receptor splice variant dependence in prostate cancer
Poluben L, Nouri M, Liang J et al. · Cell reports 2025 · PMID 39709604 · doi:10.1016/j.celrep.2024.115089
This dataset
Open GSE252897 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 GSE252897_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 PRJNA1063193 and SRA study SRP482894. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39709604) ↗
Study design
23 conditions, mostly in duplicate
VCaP, H3K27Ac, IP ×3 VCaP16, H3K27Ac, IP ×3 VCaP16 ARCC-32, H3K27Ac, IP ×3 VCaP16 DMSO, H3K27Ac, IP ×3 VCaP16 ARCC-32, BRD4, IP ×3 VCaP16 DMSO, BRD4, IP ×3 VCaP16 ARCC-32, p300, IP ×3 VCaP16 DMSO, p300, IP ×3 +36 more

Supports a between-group comparison across 54 samples.

How we read this: 23 replicated groups read from 75 sample titles; they account for 54 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

+ 35 more — browse all 75 samples with per-sample file links →

Datasets on a similar topic

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