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Isolation and immortalization of human portal vein endothelial cells: a novel research tool for investigating splanchnic vasculature

GSE296600 Homo sapiens (human) RNA-seq (gene expression) 27 samples Submitted 2025/12/02 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 27 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
27 samples: 27 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
Isolation and immortalization of human portal vein endothelial cells: A novel research tool for studying splanchnic vasculatureJHEP reports : innovation in hepatology · 2025
Summary (written by the submitters)
Cirrhosis profoundly impacts extrahepatic vasculature, particularly altering the portal venous system (PVS), leading to increased portal pressure, portosystemic collaterals, and portal vein thrombosis, which heightens morbidity and reduced survival in patients with liver disease. Despite extensive research on intrahepatic vasculature in cirrhosis, understanding of extrahepatic changes in the splanchnic territory at the molecular level remains limited.
Read the full summary ↓
The distinct characteristics of the PVS suggest a unique endothelial profile crucial for elucidating vascular dysfunction in liver diseases. However, current research is hampered by the inaccessibility of the portal vein and imperfect preclinical models. Here, we aim to isolate and immortalize primary human portal vein endothelial cells (hPVECs) to enhance understanding of pathophysiological changes during liver disease and establish a platform for future drug testing.
Published in
Isolation and immortalization of human portal vein endothelial cells: A novel research tool for studying splanchnic vasculature
Anton A, Shalaby S, Campalans J et al. · JHEP reports : innovation in hepatology 2025 · PMID 41070100 · doi:10.1016/j.jhepr.2025.101543
This dataset
Open GSE296600 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 GSE296600_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 PRJNA1260039 and SRA study SRP583685. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41070100) ↗
Study design
27 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 27 sample titles: 27 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

Search all human RNA-seq datasets in GEO →

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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.