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Antigen-restricted Candida albicans Th17 cells link oral-gut immunity and adopt pathogenic features during intestinal inflammation

GSE329527 Homo sapiens (human) RNA-seq (gene expression) 81 samples Submitted 2026/07/04 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 81 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
81 samples: 81 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.
Paper
Antigen-restricted Candida albicans Th17 cells link oral-gut immunity and adopt pathogenic features during intestinal inflammationImmunity · 2026
Summary (written by the submitters)
The commensal yeast Candida albicans is a major inducer of human Th17 cells. How C. albicans drives Th17 responses at homeostasis, and whether such responses contribute to inflammatory diseases, remains poorly understood. Here, we show that C. albicans-reactive Th17 cells exhibit a surprisingly narrow antigen-specificity, targeting a limited set of proteins enriched in fungal extracellular vesicles.
Read the full summary ↓
At homeostasis, these cells predominantly reside in the oral mucosa. T cell receptor profiling reveals shared clonotypes across oral and gut tissues with C. albicans emerging as the major driver of this repertoire overlap. In Crohn’s disease (CD), C. albicans-specific Th17 cells with features of oral priming are enriched in intestinal tissues where they retain specificity for the same protein targets but acquire pathogenic Th17 traits. Together, our results reveal a stable, antigen-restricted C. albicans Th17 response shared across mucosal sites that undergoes functional adaptation in the inflamed intestine, thus representing a novel target for immune modulation in CD.
Published in
Antigen-restricted Candida albicans Th17 cells link oral-gut immunity and adopt pathogenic features during intestinal inflammation
Martini GR, Hofmann P, Kamps AK et al. · Immunity 2026 · PMID 42447860 · doi:10.1016/j.immuni.2026.06.013
This dataset
Open GSE329527 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 GSE329527_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 PRJNA1459421 and SRA study SRP696099. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 42447860) ↗
Study design
81 samples, each with a distinct title — no replicated groups

Supports a case/control comparison: 32 samples read as cases, 14 as controls.

How we read this: Read from 81 sample titles: 81 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

+ 41 more — browse all 81 samples with per-sample file links →

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.