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Lack of synergy between AR targeted therapies and PARP inhibition in homologous recombination- proficient prostate cancer [ATAC-seq]

GSE315883 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 32 samples Submitted 2026/01/13 Platform GPL34281
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
Lack of synergy between AR-targeted therapies and PARP inhibitors in homologous recombination-proficient prostate cancerProceedings of the National Academy of Sciences of the United States of America · 2026
Summary (written by the submitters)
Recent clinical trials have explored the combination of androgen receptor (AR) pathway inhibitors and poly (ADP-ribose) polymerase (PARP) inhibitors as a potential treatment for castration-resistant prostate cancer. This combination treatment is based on the premise that AR directly regulates expression of DNA repair genes, leading to synergy between PARP and AR inhibition.
Read the full summary ↓
Despite some promising preclinical evidence, this combination therapy has shown limited efficacy in patients with homologous recombination (HR)-proficient tumors. To investigate this discrepancy between preclinical and clinical results, we profiled the effects of PARP inhibition in prostate cancer models in the presence or absence of AR inhibition. Surprisingly, AR inhibition impaired response to PARP inhibitors in castration-sensitive cells and had no effect on response in castration-resistant cells. AR inhibition also did not regulate DNA repair in either the castration-resistant or castration-sensitive setting. Instead, we find that cell cycle progression is required for response to PARP inhibition in homologous-recombination proficient prostate cancer.
Published in
Lack of synergy between AR-targeted therapies and PARP inhibitors in homologous recombination-proficient prostate cancer
Traphagen NA, Wheeler E, Li R et al. · Proceedings of the National Academy of Sciences of the United States of America 2026 · PMID 41591905 · doi:10.1073/pnas.2515790122
This dataset
Open GSE315883 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 GSE315883_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 PRJNA1399499 and SRA study SRP660502. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41591905) ↗
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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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.