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HNF4G and FOXA1 are context-specific drivers of pancreatic cancer progression [ChIP-seq]

GSE245731 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 172 samples Submitted 2025/09/16 Platform GPL24247Platform GPL21103Platform GPL24676
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 172 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
172 samples: 172 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
Transcription factor switching drives subtype-specific pancreatic cancerNature genetics · 2025
Summary (written by the submitters)
Despite recent advances in the treatment of pancreatic adenocarcinoma (PDAC), clinical outcome remains poor. Previous work identified the pioneer transcription factor FOXA1 as a mediator of new regulatory elements that drive tumour progression in models of late-stage disease. Given the critical role of FOXA1 as a pioneer factor for nuclear receptor (NR) transcription factors (TF) in breast and prostate cancer (Estrogen Receptor and Androgen Receptor), we hypothesised that FOXA1 might function with a NR in PDAC.
Read the full summary ↓
Using RIME, our unbiased approach for discovering endogenous protein complexes, we identified HNF4A and HNF4G as reproducible, FOXA1-associated proteins, a finding that was validated in clinical samples of PDAC. Using complex and diverse PDAC models, we show that gene transcription in the classical subtype of pancreatic cancer is regulated by FOXA1/GATA5/6 and HNF4G. We show that HNF4G drives primary disease, in part by recruiting the methyltransferase PRMT1 to regulatory regions. In a primary tumour context, HNF4G is the dominant protein and the presence of HNF4G masks FOXA1 activity, resulting in FOXA1 being present, but functionally redundant in primary disease. During the transition to metastasis however, HNF4G expression decreases, which unmasks FOXA1 activity, where it becomes transcriptionally active and a subsequent driver of metastasis. We provide new molecular insight into the key TFs in PDAC and the stage-specific activity of these proteins.
Published in
Transcription factor switching drives subtype-specific pancreatic cancer
Rao SV, Young L, Cheeseman D et al. · Nature genetics 2025 · PMID 41168397 · doi:10.1038/s41588-025-02389-7
This dataset
Open GSE245731 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 GSE245731_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 PRJNA1029639 and SRA study SRP467211. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41168397) ↗
Study design
172 samples, each with a distinct title — no replicated groups

Supports a case/control comparison: 19 samples read as cases, 8 as controls.

How we read this: Read from 172 sample titles: 172 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

+ 132 more — browse all 172 samples with per-sample file links →

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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.