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Oncostatin M drives multifaceted immune pathogenesis in atopic dermatitis-like inflammation via neutrophil-dependent mechanisms

GSE290386 Mus musculus (mouse) Single-cell RNA-seq 16 samples Submitted 2026/01/06 Platform GPL24247
At a glance

Single-cell RNA-seq · mouse · 16 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
Organism
Mus musculus (mouse)
Samples
16 samples: 5 × WT Skin con vs 5 × WT Skin MC903 vs 3 × WT AD Skin anti OSM vs 3 × WT AD Skin anti Ly6GGroups 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.
Summary (written by the submitters)
Atopic dermatitis (AD) is a chronic inflammatory skin disease characterized by T helper 2 cell dysregulation and accumulation of innate immune cells. While recent studies have highlighted a role for neutrophils in the onset and progression of AD, their precise contributions remain incompletely defined. In a mouse model of AD-like inflammation induced by calcipotriol and ovalbumin, neutrophils were identified as a major source of the cytokine oncostatin M (OSM).
Read the full summary ↓
Neutrophil-derived OSM promoted broad immune cell recruitment, exacerbated skin inflammation, and enhanced the expression of neuronal markers associated with pruritus. Knockdown of OSM and neutrophil depletion both attenuated inflammatory responses and neuronal activation. Publicly available single-cell RNA-sequencing datasets further confirmed increased OSM expression in neutrophils from lesional AD skin, underscoring the translational relevance of our findings. These results reveal a previously unrecognized intercellular communication axis in which neutrophil-derived OSM orchestrates multifaceted immune and neuroinflammatory responses in AD. Targeting this signaling pathway may offer a novel therapeutic avenue for AD and related inflammatory disorders.
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 GSE290386_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA1227867 and SRA study SRP566278. Searching any of these in the dataset finder brings you back here.

Study design
5 × WT Skin con vs 5 × WT Skin MC903 vs 3 × WT AD Skin anti OSM vs 3 × WT AD Skin anti Ly6G

Supports a between-group comparison across 16 samples.

How we read this: 4 replicated groups read from 16 sample titles; they account for 16 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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