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Interleukin-33 activated group 2 innate lymphoid cells drive type 2 immune dysfunction in endometriosis

GSE339493 Mus musculus (mouse) RNA-seq (gene expression) 41 samples Submitted 2026/08/03 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 41 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
41 samples: 11 conditions, mostly with about 4 replicates eachGroups 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)
Immune dysfunction is a key contributor to endometriosis (EM) pathophysiology, with a type 2-skewed immune response thought to support EM lesion maintenance and establishment. The alarmin interleukin-33 (IL-33) is elevated in EM patient plasma, peritoneal fluid (PF), and lesions compared to controls, and in an EM mouse model IL-33 drives lesion progression, although exact mechanisms remain unclear.
Read the full summary ↓
Here we validate that IL-33/ST2 signaling contributes to EM pathophysiology, identifying IL-33/ST2 axis dysregulation in EM lesions compared to control endometrial tissue and characterize PF group 2 innate lymphoid cells (ILC2s) with upregulation of ST2+ in severe stage patients. Using ILC2-deficient mice, we demonstrate that ILC2s are critical for the IL-33-driven inflammatory response in EM. IL-33 treatment in EM-induced ILC2-deficient mice resulted in reduced type 2 effector cytokine production and dysregulated immune infiltration, as well as an altered lesion transcriptional signature compared to ILC2-sufficient controls. Notably, reintroducing ILC2s was insufficient to rescue the IL-33-mediated response; however, we identified ILC2 homing to EM lesions. Finally, we identify ST2 neutralization as a promising therapeutic technique to blunt the IL-33/ILC2 type 2 response in EM.
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 GSE339493_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 PRJNA1499058 and SRA study SRP720304. Searching any of these in the dataset finder brings you back here.

Study design
11 conditions, mostly with about 4 replicates each
Endometriosis lesion, IL-33 treated, C57Bl/6J, ×4 Endometriosis lesion, IL-33 treated, Nmur1iCr… ×4 Endometriosis lesion, IL-33 treated, Id2fl/fl, ×4 Endometriosis lesion, IL-33 treated, Nmur1iCr… ×4 Endometriosis lesion, PBS treated, Nmur1iCre-… ×4 Endometriosis lesion, IL-33 treated, lesion t… ×4 Endometriosis lesion, IL-33 treated, lesion t… ×4 Endometriosis lesion, IL-33 treated, ILC2 ado… ×4 +3 more

Supports a between-group comparison across 41 samples.

How we read this: 11 replicated groups read from 41 sample titles; they account for 41 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

+ 1 more — browse all 41 samples with per-sample file links →

Datasets on a similar topic

Search all mouse RNA-seq datasets in GEO →

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