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MERTK inhibition for the treatment of tissue fibrosis [CUT&Tag]

GSE234196 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 48 samples Submitted 2024/03/05 Platform GPL24247
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 48 samples

What it is
ChIP-seq / ATAC-seq (genome binding and open chromatin)Where proteins bind the genome, or which regions are open and active.
Organism
Mus musculus (mouse)
Samples
48 samples: 43 distinct titles, 5 of them repeatedGroups 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
Inhibition of MERTK reduces organ fibrosis in mouse models of fibrotic diseaseScience translational medicine · 2024
Summary (written by the submitters)
Fibrosis is a core pathway that drives the progression of multiple chronic diseases for which there is a paucity of safe and effective treatments. In these diseases, transforming growth factor–β (TGF-β)–driven scarring propels disease progression. However, targeting this ubiquitously expressed cytokine is unlikely to yield a viable and safe antifibrotic therapy; thus, identification of alternative mechanisms to inhibit TGF-β signalling is required.
Read the full summary ↓
We identified Mer tyrosine kinase (MERTK) as a TGF-β–inducible nodal effector of fibrosis that is up-regulated with fibrosis in multiple organs in both mice and humans. MERTK also induces TGF-β expression and promotes it’s signalling resulting in a positive feedback loop that promotes fibrosis. Mechanistically, MERTK regulates both canonical and non-canonical TGFβ signalling. Further downstream, MERTK modulates the fibrotic regulatory gene transcription network by regulating chromatin accessibility, RNA polymerase II (pol II) pausing and reprograming the enhancer landscape. Using mouse models of kidney, lung, and liver fibrosis, we demonstrate that this fibrosis-promoting signalling loop can be interrupted by loss of MERTK expression, leading to marked attenuation of fibrosis. Pharmacologic MERTK inhibition reduced fibrosis either when initiated immediately after injury or when initiated after fibrosis is established. Together, this data suggests that MERTK plays a critical role in modulating organ fibrosis, while small-molecule MERTK inhibitors are an attractive target for the treatment of diseases characterized by fibrosis.
Published in
Inhibition of MERTK reduces organ fibrosis in mouse models of fibrotic disease
Pan Z, El Sharkway R, Bayoumi A et al. · Science translational medicine 2024 · PMID 38569018 · doi:10.1126/scitranslmed.adj0133
This dataset
Open GSE234196 in finder → Find more mouse ChIP / ATAC / CUT&Tag 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 GSE234196_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: Look for peak files (.bed, .narrowPeak) and signal tracks (.bigWig) among the supplementary files; the raw reads are on ENA.

Also filed as BioProject PRJNA980268 and SRA study SRP441192. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 38569018) ↗
Study design
43 distinct titles, 5 of them repeated
sham WT2 H3K4me ×2 BDL WT1 H3K4me ×2 BDL WT2 H3K4me ×2 BDL KO1 H3K4me ×2 BDL KO2 H3K4me ×2

How we read this: Read from 48 sample titles: 43 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

+ 8 more — browse all 48 samples with per-sample file links →

Datasets on a similar topic

Search all mouse ChIP / ATAC / CUT&Tag datasets in GEO →

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