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Cholangiocarcinoma tumorigenesis in Abcb4(Mdr2)-/- and wild-type mice by transposon-based oncogenes integration

GSE268905 Mus musculus (mouse) RNA-seq (gene expression) 24 samples Submitted 2024/06/03 Platform GPL34328
At a glance

RNA-seq (gene expression) · mouse · 24 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
24 samples: 24 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
Transposon-based oncogene integration in Abcb4(Mdr2)(-/-) mice recapitulates high susceptibility to cholangiocarcinoma in primary sclerosing cholangitisJournal of hepatology · 2025
Summary (written by the submitters)
Cholangiocarcinoma (CCA) is a dreaded complication of primary sclerosing cholangitis (PSC), difficult to diagnose and associated with high mortality. Lack of animal models of CCA recapitulating the hepatic microenvironment of sclerosing cholangitis hinders development of novel treatments. We have developed and characterized a new mouse model of PSC-CCA through hydrodynamic tail vein injection of oncogenes pT3-EF1a-HA-myrAKT (AKT) and pT3-EF1a-YapS127A (YAP1), termed SB CCA.Mdr2-/-, which features reliable tumor induction in PSC-like background of biliary injury and fibrosis.
Read the full summary ↓
To unravel the potential molecular profile of CCA developed in different liver context, we profiled the transcriptomes of tumor-bearing fibrotic (Mdr2-/-) (n = 6) and tumor-bearing wild-type liver tissues (n = 6) and compared to corresponding control nontumor-bearing fibrotic (Mdr2-/-) (n = 6) and healthy liver tissues (n = 6). RNA-seq analysis revealed profound transcriptional differences in CCA evolving in PSC-like context, compared to CCA in healthy liver.
Published in
Transposon-based oncogene integration in Abcb4(Mdr2)(-/-) mice recapitulates high susceptibility to cholangiocarcinoma in primary sclerosing cholangitis
Huang P, Wei G, Kirkpatrick JD et al. · Journal of hepatology 2025 · PMID 39089631 · doi:10.1016/j.jhep.2024.07.016
This dataset
Open GSE268905 in finder → Find more mouse 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 GSE268905_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 PRJNA1119438 and SRA study SRP511359. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39089631) ↗
Study design
24 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 24 sample titles: 24 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

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