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

GSE245733 Homo sapiens (human) RNA-seq (gene expression) 29 samples Submitted 2025/09/16 Platform GPL24247Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 29 samples

What it is
RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
Organism
Homo sapiens (human)
Samples
29 samples: 29 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 GSE245733 in finder → Find more RNA-seq 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 GSE245733_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: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.

Also filed as BioProject PRJNA1029636 and SRA study SRP467179. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41168397) ↗
Study design
29 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 29 sample titles: 29 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
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