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Crosstalk between the polycomb repressive complex 2 and DNA methylation mediates neuroendocrine prostate cancer lineage plasticity [ChIP-Seq]

GSE289247 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 35 samples Submitted 2025/11/25 Platform GPL24247Platform GPL24676
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 35 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
Prostate cancerThis series is part of our curated briefing on it.
Samples
35 samples: 35 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
Crosstalk between EZH2 and DNA methylation mediates neuroendocrine prostate cancer lineage plasticityNature communications · 2026
Summary (written by the submitters)
Acquired changes in DNA methylation have been proposed as a mechanism underlying epigenetic plasticity in several cancer types. In prostate cancer, methylation changes are dynamic, with preclinical studies pointing to a tumor suppressor role of the DNA methyltransferase DNMT1 in early stage, in contrast to an oncogenic function of DNMT1 in later stage.
Read the full summary ↓
The importance of DNA methylation dynamics during normal development and cell lineage fate decisions also points to DNA methylation having a critical function in lineage plasticity, yet the mechanisms by which DNA methylation changes drives lineage transitions in prostate cancer is not well understood. DNA methylation can directly repress gene expression but also cooperate with other epigenetic pathways to modulate downstream transcriptional activity. The enhancer of zeste homolog 2 (EZH2) protein is a subunit of the polycomb repressive complex 2 (PRC2) and catalyzer of the repressive histone 3 lysine 27 tri-methylation (H3K27me3) mark that also acts to suppress downstream transcriptional activity and has also been implicated in lineage plasticity. EZH2 is overexpressed in castration-resistant prostate cancer (CRPC) including NEPC and is an emerging therapeutic target. Although, the compensatory relationship between DNA methylation and EZH2 has been shown in embryonic stem cell studies and in some cancer types during acquired treatment resistance or immune evasion, how DNA methylation and EZH2/PRC2 interact to modulate prostate cancer lineage plasticity has not been characterized. In this study, we address the potential crosstalk between epigenetic pathways in advanced prostate cancer and demonstrate how DNA methylation and H3K27me3 profiles overlap and cooperate to reprogram the epigenome during prostate cancer lineage plasticity. Using both mouse and patient-derived models, we highlight the compensatory roles of these two repressive machineries during progression of CRPC towards a NE-lineage state. We predict their specific impact on NEPC progression by assessing the associated molecular alterations following genetic and pharmacological perturbations of each.
Published in
Crosstalk between EZH2 and DNA methylation mediates neuroendocrine prostate cancer lineage plasticity
Singh R, Venkadakrishnan VB, Imada E et al. · Nature communications 2026 · PMID 41720768 · doi:10.1038/s41467-026-69308-0
This dataset
Open GSE289247 in finder → Find more ChIP / ATAC / CUT&Tag datasets → Prostate 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 GSE289247_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 PRJNA1222007 and SRA study SRP563080. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41720768) ↗
Study design
35 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 35 sample titles: 35 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
More Prostate cancer datasets

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