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RNA Sequencing Facilitates Quantitative Analysis of Humanized Normal Livers, NASH Livers, and HCC Transcriptomes

GSE205881 Mus musculus (mouse) RNA-seq (gene expression) 66 samples Submitted 2025/01/01 Platform GPL16512
At a glance

RNA-seq (gene expression) · mouse · 66 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)
Topic
Hepatocellular carcinomaThis series is part of our curated briefing on it.
Samples
66 samples: 66 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
Circadian dysfunction induces NAFLD-related human liver cancer in a mouse modelJournal of hepatology · 2024
Summary (written by the submitters)
RNAseq analysis that will help to define 1) the circadian dysfunction induced liver transcriptome that drives fatty liver disease induced hepatocarcinogenesis in a humanized mouse model; 2) the currently unknown circadian profile of NASH and HCC gene signatures specifically associated with human hepatocytes and liver or tumor microenvironment. These gene signatures will significantly advance our understanding of the mechanism of spontaneous HCC and have important preclinic values for developing novel therapeutic strategies for prevention and treatment of HCC in humans.
Published in
Circadian dysfunction induces NAFLD-related human liver cancer in a mouse model
Padilla J, Osman NM, Bissig-Choisat B et al. · Journal of hepatology 2024 · PMID 37890720 · doi:10.1016/j.jhep.2023.10.018
This dataset
Open GSE205881 in finder → Find more RNA-seq datasets → Hepatocellular carcinoma landscape →
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 GSE205881_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 PRJNA847988 and SRA study SRP379616. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 37890720) ↗
Study design
66 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 66 sample titles: 66 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

+ 26 more — browse all 66 samples with per-sample file links →

More Hepatocellular carcinoma datasets

Search all RNA-seq datasets in GEO →

Share this dataset

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.