← BioTransfer GEO Dataset Finder
GEO series

Investigate FOXA2 mediated DNA demethylation during NEPC transformation by Nanopore Long Read sequencing.

GSE239274 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 13 samples Submitted 2025/06/06 Platform GPL28975
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 13 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
13 samples: 13 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
NKX2-1 drives neuroendocrine transdifferentiation of prostate cancer via epigenetic and 3D chromatin remodelingNature genetics · 2025
Summary (written by the submitters)
Emerging evidence suggests that the epigenetic state, including the DNA methylation, chromatin accessibility and histone modification, is substantially remodeled, leading to transcriptional reprogramming during the transformation of castration resistant adenocarcinoma (CRPC-Adeno) to neuroendocrine (CRPC-NE) lineage and LUAD to LUAD-SCLC lineage .
Read the full summary ↓
However, the underlying mechanism is largely unknown. Here, we found FOXA2 transdifferentiates prostate adenocarcinoma away from an AR+/AR gene signature positive (AR+/ARS+) luminal cell lineage to an embryonic and neuroendocrine-lineage by inducing a population of AR+/ARS- transient cells through NKX2-1. Mechanistically, as a pioneer factor, FOXA2 primes NE lineage enhancers by inducing regional chromatin accessibility and DNA demethylation at early stage of transformation. Whereas, once the expression of NKX2-1 is induced by FOXA2, FOXA2 interacts with NKX2-1, mediates gene promoter and enhancer looping and cooperatively recruits P300/CBP complex to NE lineage enhancers, thereby activates NE lineage gene transcription. Interestingly, similar mechanism is also observed in SCLC cancer, suggesting FOXA2 and NKX2-1 are general regulators orchestrating the epigenetic landscape of NE lineage cancer. Finally, therapeutic targeting P300/CBP with CCS1477 which is in clinical trial for lethal PCa significantly impairs NEPC tumor growth.
Published in
NKX2-1 drives neuroendocrine transdifferentiation of prostate cancer via epigenetic and 3D chromatin remodeling
Lu X, Keo V, Cheng I et al. · Nature genetics 2025 · PMID 40691407 · doi:10.1038/s41588-025-02265-4
This dataset
Open GSE239274 in finder → Find more human methylation 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 GSE239274_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 PRJNA998731 and SRA study SRP451651. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40691407) ↗
Study design
13 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 13 sample titles: 13 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

Search all human methylation 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.