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Bulk RNA sequencing of liver biopsy-derived organoids from patients with alcohol-associated liver disease and paired tissues

GSE272014 Homo sapiens (human) RNA-seq (gene expression) 50 samples Submitted 2025/08/28 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 50 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
Homo sapiens (human)
Samples
50 samples: 50 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
Patient-derived liver organoids recapitulate liver epithelial heterogeneity and enable precision modeling of alcohol-related liver diseaseJournal of hepatology · 2026
Summary (written by the submitters)
RNA sequencing was performed on liver organoids obtained from biopsies (b-Orgs) and paired tissues collected at different stages of alcohol-associated liver disease (ALD) using biliary (BEC) and hepatocyte (HEP) culture conditions. Different "generations" and passages of b-Orgs cultured with HEP medium were also sequenced. Besides, sequencing was also performed on vehicle and b-Orgs treated with Alcohol-associated hepatitis (AH)-medium. Finally, standard cholangiocyte organoids (Chol-Orgs) generated by dissociation of end-stage liver resections from ALD patients were sequenced.
Published in
Patient-derived liver organoids recapitulate liver epithelial heterogeneity and enable precision modeling of alcohol-related liver disease
Ariño S, Ferrer-Lorente R, Serrano G et al. · Journal of hepatology 2026 · PMID 40754225 · doi:10.1016/j.jhep.2025.07.014
This dataset
Open GSE272014 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 GSE272014_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 PRJNA1134631 and SRA study SRP519291. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40754225) ↗
Study design
50 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 50 sample titles: 50 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

+ 10 more — browse all 50 samples with per-sample file links →

Datasets on a similar topic

Search all human 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.