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Interleukin-23 promotes a pro-inflammatory Th17 cell state by stabilizing RORγt and suppressing glucocorticoid receptor activity I

GSE296187 Homo sapiens (human) RNA-seq (gene expression) 28 samples Submitted 2026/06/12 Platform GPL16791
At a glance

RNA-seq (gene expression) · human · 28 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
Homo sapiens (human)
Samples
28 samples: 28 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)
Interleukin-23 receptor (IL-23R) signaling is critical for the generation of pro-inflammatory CD4+ IL-17-producing T cells (Th17) that can drive autoimmune tissue inflammation, but the underlying mechanisms are not clear. We integrated phosphoproteomic and transcriptomic data downstream of IL-23R and IL-12R, which share a common subunit, to identify mechanisms engaged specifically by IL-23.
Read the full summary ↓
We identified chromodomain helicase DNA-binding protein 1 (CHD1), an epigenetic regulator, and the glucocorticoid receptor (GR), a transcription factor (TF), as mediators of IL-23R signaling. IL-23R activation promoted CHD1 interaction with TF STAT3 and co-binding at the TF RORγt locus to enforce a pro-inflammatory Th17 state. Conversely, IL-23R signaling altered phosphorylation of the GR, thereby preventing its activation and nuclear translocation, ultimately impairing GR-driven inhibition of pro-inflammatory Th17 gene programs. Our findings uncover two mechanisms by which IL-23 promotes a pro-inflammatory Th17 cell state, offering potential therapeutic targets for treating Th17-driven autoimmune tissue inflammation and restoring homeostasis.
This dataset
Open GSE296187 in finder → Find more human 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 GSE296187_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 PRJNA1258170 and SRA study SRP582780. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
28 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 28 sample titles: 28 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

Search all human RNA-seq datasets in GEO →

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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.