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Single Cell Immune Profiling in Ankylosing Spondylitis Reveals Resistance of CD8+ T cells to Immune Exhaustion

GSE288581 Homo sapiens (human) Single-cell RNA-seq 30 samples Submitted 2025/02/06 Platform GPL24676
At a glance

Single-cell RNA-seq · human · 30 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
Organism
Homo sapiens (human)
Samples
30 samples: 30 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
Single cell immune profiling in ankylosing spondylitis reveals resistance of CD8(+) T cells to immune exhaustioniScience · 2025
Summary (written by the submitters)
Persistent chronic inflammation is a hallmark of Ankylosing Spondylitis (AS), with cytotoxic T cells (CTLs) increasingly implicated in its pathogenesis. Ordinarily, T cell exhaustion follows sustained, persistent T cell activation to limit collateral tissue damage. Using mass cytometry and single-cell RNA sequencing (scRNA-seq), we identified a clonally expanded CTL subset in AS synovial fluid that expresses inhibitory receptors (PD-1, TIGIT, LAG-3) yet retains its effector capacity to express granzymes, perforin, TNF-a, and IFN-g.
Read the full summary ↓
Gene expression profile of this CTL subset show downregulation of canonical exhaustion markers. At the protein level, TOX, a critical transcription factor regulating CTL exhaustion, is downregulated in PD-1+TIGIT+LAG-3+CTLs. In-silico trajectory analyses suggest these cells may differentiate into other effector CTL subsets. Our findings reveal a checkpoint-expressing CTL population in AS that resists exhaustion and retains an activated, effector phenotype. We propose that failure to undergo exhaustion may be a fundamental mechanism sustaining AS chronic inflammation.
Published in
Single cell immune profiling in ankylosing spondylitis reveals resistance of CD8(+) T cells to immune exhaustion
Tang M, Qaiyum Z, Lim M et al. · iScience 2025 · PMID 40687839 · doi:10.1016/j.isci.2025.112715
This dataset
Open GSE288581 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 GSE288581_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA1218631 and SRA study SRP561214. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40687839) ↗
Study design
30 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 30 sample titles: 30 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.