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Targeting the FOXP3–T-bet interaction to restore Treg stability in IFN-γ–driven autoimmunity

GSE253096 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 20 samples Submitted 2025/12/31 Platform GPL24247Platform GPL20795
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 20 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
Homo sapiens (human)
Samples
20 samples: 20 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)
Regulatory T cell (Treg) stability is maintained by dynamic remodeling of the FOXP3 transcriptional complex, and its disruption leads to Treg dysfunction and immune dysregulation. However, how specific FOXP3 mutations alter the dynamic remodeling of the FOXP3-complex and thereby contribute to pathogenic Treg reprogramming in IPEX syndrome remains unclear.
Read the full summary ↓
Here, by uncovering the distinctive pathogenesis of FOXP3V408M mutation in IPEX syndrome, we demonstrate that the FOXP3–T-bet interaction fine-tunes Treg function by repressing IFN-γ production, thereby preventing Th1-driven inflammation. Using an AI-driven virtual screening approach, we identified a first-in-class small molecule, 430C10, that directly binds FOXP3 and reinforces its interaction with T-bet. 430C10 robustly suppressed Treg-derived IFN-γ production and alleviated IFN-γ-driven tissue inflammation in FOXP3V408M knock-in mice as well as in models of acute colitis. Collectively, these findings establish the FOXP3–T-bet interaction as a central checkpoint governing Treg stability and IFN-γ-driven Th1 pathology, providing proof-of-concept that pharmacologic stabilization of FOXP3–T-bet interaction can mitigate IFN-γ–driven immune disorders.
This dataset
Open GSE253096 in finder → Find more 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 GSE253096_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 PRJNA1064029 and SRA study SRP483348. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
20 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 20 sample titles: 20 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.