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Pbrm1 loss induces a permissive chromatin state for cholangiocytic differentiation and cholangiocarcinoma formation

GSE291359 Mus musculus (mouse) RNA-seq (gene expression) 12 samples Submitted 2025/04/21 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 12 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
Mus musculus (mouse)
Samples
12 samples: 3 × w/ DDC, WT, P vs 3 × w/ DDC, Pbrm1 KO, PA vs 3 × w/o DDC, WT, P vs 3 × w/o DDC, Pbrm1 KO, PAGroups 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
Pbrm1 Loss Induces a Permissive Chromatin State for Cholangiocytic Differentiation and Cholangiocarcinoma FormationCellular and molecular gastroenterology and hepatology · 2026
Summary (written by the submitters)
Background and Aims: The SWI/SNF ATP-dependent chromatin remodeling complex regulates transcrip-tional machinery access and is critical in normal physiology and cancer development. Pbrm1, a key subunit of this complex, is frequently mutated in intrahepatic cholan-giocarcinoma (ICC), though how its loss contributes to tumorigenesis remains poor-ly understood.
Read the full summary ↓
This study aims to explore the role of Pbrm1 in liver physiology and its involvement in ICC development. Methods: Liver-specific Pbrm1 knockout (Pbrm1 KO) mice were generated to assess the ef-fects of Pbrm1 loss under various conditions. These mice were exposed to a 3,5-diethoxycarbonyl-1,4-dihydrocollidine (DDC) diet to induce cholestatic injury and were also subjected to a high-fat diet to evaluate susceptibility to liver steatosis. Chromatin accessibility and gene expression under both normal and injury condi-tions were examined. Additionally, the impact of Pbrm1 loss was analyzed in com-bination with an activating KrasG12D mutation to study cancer development. Results: Pbrm1 KO mice exhibited increased susceptibility to cholestatic injury, with an en-hanced ductular reaction. Loss of Pbrm1 reduced chromatin accessibility at hepato-cyte-specific and metabolically important genes, though RNA expression remained unaffected during homeostasis. Following cholestatic injury, hepatocyte-specific gene expression was significantly reduced compared to wild-type controls. Pbrm1 KO mice also showed heightened vulnerability to high-fat diet-induced liver steato-sis. When combined with KrasG12D mutation, Pbrm1 KO/KrasG12D mice had shorter survival and were more likely to develop cholangiocarcinomas, whereas Pbrm1 wild type/KrasG12D mice predominantly developed hepatocellular neoplasms. Conclusion: Pbrm1 maintains chromatin accessibility for hepatocyte differentiation-related genes. Its loss promotes differentiation toward cholangiocytes during injury or tu-morigenesis, driving ICC development.
Published in
Pbrm1 Loss Induces a Permissive Chromatin State for Cholangiocytic Differentiation and Cholangiocarcinoma Formation
Chiou LW, Jhuang YL, Hsu CL et al. · Cellular and molecular gastroenterology and hepatology 2026 · PMID 41513002 · doi:10.1016/j.jcmgh.2025.101720
This dataset
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.

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 GSE291359_RAW.tar (it can run to tens of gigabytes).

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.

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 PRJNA1233233 and SRA study SRP568664. Searching any of these in the dataset finder brings you back here.

Study design
3 × w/ DDC, WT, P vs 3 × w/ DDC, Pbrm1 KO, PA vs 3 × w/o DDC, WT, P vs 3 × w/o DDC, Pbrm1 KO, PA

Supports a between-group comparison across 12 samples.

How we read this: 4 replicated groups read from 12 sample titles; they account for 12 of them. 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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