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TL1A-activated Tcells as upstream regulators of perianal fistulizing disease-associated changes in the rectum of Crohn's Disease patients [RNA-seq]

GSE291014 Homo sapiens (human) Single-cell RNA-seq 28 samples Submitted 2026/01/20 Platform GPL34281
At a glance

Single-cell RNA-seq · human · 28 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
Organism
Homo sapiens (human)
Samples
28 samples: 10 × CTRL vs 6 × LTB vs 6 × TGFB vs 6 × TNFGroups 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
TL1A-activated T cells remodel the rectal mucosa in patients with Crohn's disease with perianal fistulising diseaseGut · 2025
Summary (written by the submitters)
Perianal fistulizing disease (PFD) is one of the complications observed in Crohn's Disease patients, which consist of the formation of new tracks connecting the anal canal or the rectum with the perianal region. Applying scRNA-seq analysis in the rectum of patients with and without PFD revealed alterations in the stromal compartment as a response to cytokines such as TNF, TGFb and LTB. To investigate the downstream signature of these cytokines especifically in intestinal fibroblasts, we sequenced human intestinal primary fibroblasts upon stimulation to TNF, TGFb and LTB.
Published in
TL1A-activated T cells remodel the rectal mucosa in patients with Crohn's disease with perianal fistulising disease
Gudiño V, Cho JW, Caballol B et al. · Gut 2025 · PMID 41448881 · doi:10.1136/gutjnl-2025-336246
This dataset
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.

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 GSE291014_RAW.tar (it can run to tens of gigabytes).

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.

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 PRJNA1231395 and SRA study SRP567779. Searching any of these in the dataset finder brings you back here.

Study design
10 × CTRL vs 6 × LTB vs 6 × TGFB vs 6 × TNF

Supports a between-group comparison across 28 samples.

How we read this: 4 replicated groups read from 28 sample titles; they account for 28 of them. 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
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