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FGF2 Mediated USP42-PPAR Axis Activation Ameliorates Liver Oxidative Damage and Promotes Regeneration

GSE286997 Mus musculus (mouse) RNA-seq (gene expression) 12 samples Submitted 2025/01/15 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 12 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
12 samples: 4 × Saline vs 4 × EV vs 4 × EV@FGF2-RSGGroups 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
FGF2 Mediated USP42-PPARγ Axis Activation Ameliorates Liver Oxidative Damage and Promotes RegenerationAdvanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025
Summary (written by the submitters)
Liver regeneration is critical for maintaining whole-body homeostasis, especially under the exposure to deadly chemical toxins. Understanding the molecular mechanisms underlying liver repair is critical for the development of intervention strategies to treat liver diseases. In this study, we identified ubiquitin-specific Proteases 42 (USP42) as a novel deubiquitinases (DUB) of peroxisome proliferators-activated receptor γ (PPARγ) in hepatocytes.
Read the full summary ↓
This DUB interacted, deubiquitinated and stabilized PPARγ, and increased PPAR targeted proliferative and anti-oxidative gene expressions, which protects liver from carbon tetrachloride (CCL4) induced oxidative injury and promotes liver regeneration. In addition, fibroblast growth factor 2 (FGF2) initiated USP42 expression and enhanced the interaction between USP42 and PPARduring liver regeneration process. Moreover, the PPARfull agonist, rosiglitazone (RSG), possesses the ability to further reinforce the USP42-PPARinterplay, which enlightens us to construct an extracellular vesicle-based targeting strategy to activate liver USP42-PPAR axis and promote liver regeneration. In summary, our work uncovers the importance of USP42-PPAR axis mediated liver tissue homeostasis, and provides a promising regimen to target this protein-protein interplay for liver regeneration.
Published in
FGF2 Mediated USP42-PPARγ Axis Activation Ameliorates Liver Oxidative Damage and Promotes Regeneration
Yang N, Tian Q, Lei Z et al. · Advanced science (Weinheim, Baden-Wurttemberg, Germany) 2025 · PMID 40091484 · doi:10.1002/advs.202408724
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 GSE286997_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 PRJNA1210640 and SRA study SRP557323. Searching any of these in the dataset finder brings you back here.

Study design
4 × Saline vs 4 × EV vs 4 × EV@FGF2-RSG

Supports a between-group comparison across 12 samples.

How we read this: 3 replicated groups read from 12 sample titles; they account for 12 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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