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A Receptor-Clamped IL-2 Uncouples Treg Expansion from Injection Site Reactions

GSE316048 Mus musculus (mouse) RNA-seq (gene expression) 24 samples Submitted 2026/07/23 Platform GPL34328
At a glance

RNA-seq (gene expression) · mouse · 24 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
24 samples: 24 samples, each with a distinct title — no replicated groupsGroups 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)
Low-dose interleukin-2 (IL-2) and IL-2 muteins are being developed to expand regulatory T cells (Tregs) as therapies for autoimmune diseases, but IL-2 mediated injection site reactions (ISRs) remain frequent and poorly understood. Here we show IL2Mut24, a murine surrogate of IL-2 mutein with reduced CD122 binding and extended half-life, robustly promotes Treg expansion yet causes more severe ISRs than wild-type IL-2.
Read the full summary ↓
Through studies using immune-deficient mice, antibody blockade, and adoptive transfers, we identify CD25⁺ group 2 innate lymphoid cells (ILC2s) as key ISR mediators and sufficient to trigger ISR. To address safety, we engineered anti-CD25–IL2Mut24 fusion proteins (“receptor clamps”) with graded CD25 antagonism. This approach reveals an optimal window that preserves Treg selectivity, suppresses ISRs, and outperforms IL2Mut24 in experimental autoimmune encephalomyelitis. These findings uncover cellular basis of IL-2-induced ISRs and support the development of receptor-tuned IL-2 fusion proteins as a next-generation therapeutic strategy for autoimmune diseases.
This dataset
Open GSE316048 in finder → Find more mouse RNA-seq 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 GSE316048_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: 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 PRJNA1400519 and SRA study SRP661177. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
24 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 24 sample titles: 24 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
Datasets on a similar topic

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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.