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Glucocorticoid Receptor Suppresses GATA6-Mediated RNA Polymerase II Pause Release to Modulate Classical Subtype Identity in Pancreatic Cancer

GSE271737 Homo sapiens (human) Single-cell RNA-seq 110 samples Submitted 2025/01/07 Platform GPL30173Platform GPL20301
At a glance

Single-cell RNA-seq · human · 110 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
Organism
Homo sapiens (human)
Samples
110 samples: 80 distinct titles, 15 of them repeatedGroups 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
Glucocorticoid receptor suppresses GATA6-mediated RNA polymerase II pause release to modulate classical subtype identity in pancreatic cancerGut · 2025
Summary (written by the submitters)
Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal cancer with a five-year survival rate of 12%. It has two major molecular subtypes: classical and basal, regulated by the master transcription factors (MTFs) GATA6 and ΔNp63, respectively. This study aims to uncover the transcriptional regulatory mechanisms controlling PDAC subtype identity.
Read the full summary ↓
We integrated primary tumor single-cell RNA-seq, patient-derived xenograft RNA-seq, and multispectral imaging to identify MTF-dependent, subtype-specific markers. We created subtype-specific fluorescent reporter systems and conducted drug screenings to find actionable targets. We analyzed genome-wide occupancy (ChIP-seq) for epigenetic status (H3K27ac), MTFs (GATA6, ΔNp63), RNA polymerase II (Pol II), nascent RNA capture sequencing (PRO-seq), and H3K4me3-anchored chromatin topology (HiChIP). Additionally, we used nuclease-dead Cas9 (dCas9) to manipulate transcriptional regulatory mechanisms. Our approach identified glucocorticoid receptor (GR) agonists as agents that suppress the classical transcriptional program by modulating GATA6 activity. GATA6 regulates classical-specific transcription through promoter-proximal pause (PPP) release. Depletion of GATA6 increased Pol II occupancy at GATA6-bound enhancers and transcriptional start sites, stabilizing enhancer-promoter interactions. Artificially inducing pausing at GATA6-bound enhancers with dCas9 abrogated target gene expression and induced pausing at both the enhancer and target gene promoter. Conversely, ΔNp63 in basal PDAC promotes Pol II recruitment and stabilizes enhancer-promoter interactions. This study provides new insights into the transcriptional control of PDAC subtypes and suggests potential therapeutic strategies, highlighting the role of glucocorticoids in PDAC chemotherapy.
Published in
Glucocorticoid receptor suppresses GATA6-mediated RNA polymerase II pause release to modulate classical subtype identity in pancreatic cancer
Ekstrom TL, Rosok RM, Abdelrahman AM et al. · Gut 2025 · PMID 39884837 · doi:10.1136/gutjnl-2024-334374
This dataset
Open GSE271737 in finder → Find more human 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 GSE271737_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA1131618 and SRA study SRP517903. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39884837) ↗
Study design
80 distinct titles, 15 of them repeated
RNAseq_AsPC1_siNT5_a ×3 RNAseq_AsPC1_siCDH17_a ×3 RNAseq_AsPC1_siLGALS4_a ×3 RNAseq_HPAFII_DMSO ×3 RNAseq_HPAFII_BI653048 ×3 RNAseq_TCCPAN2_DMSO ×3 RNAseq_TCCPAN2_BI653048 ×3 RNAseq_TCCPAN2_siNT5 ×3 +7 more

How we read this: Read from 110 sample titles: 80 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

+ 70 more — browse all 110 samples with per-sample file links →

Datasets on a similar topic

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