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A microbiota-derived bile acid controls hepatic cholesterol levels in cachectic mice

GSE265876 Mus musculus (mouse) RNA-seq (gene expression) 22 samples Submitted 2024/10/02 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 22 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
22 samples: 8 × Liver, C26 vs 8 × Liver, C26-TDCA vs 6 × Liver, CTGroups 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
The microbiota-derived bile acid taurodeoxycholic acid improves hepatic cholesterol levels in mice with cancer cachexiaGut microbes · 2025
Summary (written by the submitters)
Our work showed decreased hepatic levels of TDCA in the C26 model of cancer cachexia. We also found gut microbiota composition alterations in cachectic C26 mice, as well as reductions in microbial 7α-dehydroxylase activity, and activity of 7α-HSDH and 12α-HSDH, which drive the production of secondary bile acids. Finally, we showed that TDCA administration induces lower hepatic levels of cholesterol in C26 mice. Published in Thibaut et al, Gut Microbes 2025
Published in
The microbiota-derived bile acid taurodeoxycholic acid improves hepatic cholesterol levels in mice with cancer cachexia
Thibaut MM, Roumain M, Piron E et al. · Gut microbes 2025 · PMID 39780051 · doi:10.1080/19490976.2025.2449586
This dataset
Open GSE265876 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 GSE265876_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 PRJNA1104607 and SRA study SRP504116. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39780051) ↗
Study design
8 × Liver, C26 vs 8 × Liver, C26-TDCA vs 6 × Liver, CT

Supports a between-group comparison across 22 samples.

How we read this: 3 replicated groups read from 22 sample titles; they account for 22 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
Datasets on a similar topic

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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.