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The Impact of PPARβ/ agonism/antagonism on human bone-marrow-derived Mesenchymal Stromal Cells

GSE281162 Homo sapiens (human) RNA-seq (gene expression) 18 samples Submitted 2026/05/06 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 18 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
18 samples: 6 conditions, mostly in triplicateGroups 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 PPARβ/Delta-Induced Mesenchymal Stromal Cell Secretome Has Cytoprotective Effects via ANGPTL4 in a Pre-Clinical Model of Acute Lung InflammationFASEB journal : official publication of the Federation of American Societies for Experimental Biology · 2026
Summary (written by the submitters)
PPARβ/ -ligands are present in the acute respiratory syndrome (ARDS) lung in abundance. Mesenchymal Stromal Cells (MSCs) have shown poor results in ARDS-based clinical trials. In order to determine the potential impact of PPARβ/ agonism/antagonism on human bone-marrow-derived MSCs in vitro, we activated or inhibited the receptor on the cells and/or licensed them with 5ng/ml TNF⍺.
Published in
The PPARβ/Delta-Induced Mesenchymal Stromal Cell Secretome Has Cytoprotective Effects via ANGPTL4 in a Pre-Clinical Model of Acute Lung Inflammation
Tunstead C, Dunlop M, Ryan S et al. · FASEB journal : official publication of the Federation of American Societies for Experimental Biology 2026 · PMID 42007763 · doi:10.1096/fj.202504659R
This dataset
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.

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 GSE281162_RAW.tar (it can run to tens of gigabytes).

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.

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 PRJNA1182579 and SRA study SRP543431. Searching any of these in the dataset finder brings you back here.

Study design
6 conditions, mostly in triplicate
MSC_control ×3 MSC_agonist ×3 MSC_antagonist ×3 MSC_TNF ×3 MSC_TNF_agonist ×3 MSC_TNF_antagonist ×3

Supports a between-group comparison across 18 samples.

How we read this: 6 replicated groups read from 18 sample titles; they account for 18 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
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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.