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Single-cell RNA sequencing reveals ulcerative colitis patients’ response to anti-TNF-α therapy

GSE298464 Homo sapiens (human) Single-cell RNA-seq 16 samples Submitted 2025/11/18 Platform GPL24676
At a glance

Single-cell RNA-seq · human · 16 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
16 samples: 4 × Intestinal mucosa,lesions,before IFX treatment,response, vs 4 × Intestinal mucosa,lesions,before IFX treatment,no-response, vs 4 × Intestinal mucosa,lesions,after IFX treatment,response, vs 4 × Intestinal mucosa,lesions,after IFX treatment,no-response,Groups 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 RNA sequencing reveals the adverse role of cDC3s in the response of ulcerative colitis patients to anti-TNF-α therapyJournal of translational medicine · 2025
Summary (written by the submitters)
We performed single-cell sequencing of intestinal mucosal tissue from eight UC patients at pre- and post- anti-TNF-α therapy prescription and analyzed them with relation to therapy response (response and no-response). We found that responders have different immune cell profiles from non-responders between pre- and post- anti-TNF-α therapy.
Read the full summary ↓
Specifically, the proportion of cDC3 decreased in all responders after receiving anti-TNF-α therapy, whereas non-responders could not be distinguished from UC patients who had not received anti-TNF-α therapy. When further compared the difference of type 3 conventional dendritic cells (cDC3) from pre- and post-therapy of anti-TNF-α, distinct transcriptomes were identified in responders, while no significantly different genes were found in cDC3 from non-responders. The interactions analysis of ligands and receptors showed that the interactions between HLA-DPA1/DPB1 in fibroblast and TNFSF9 in cDC3, CD44 in fibroblast and TYROBP in cDC3 were significantly weakened in Post-R group compared with Pre-R group. Cell trajectory analysis demonstrated that the cells differentiated to cDC3 significantly decreased in the Post-R group, and the genes related MAPK signaling pathway obviously increased in these cells.
Published in
Single-cell RNA sequencing reveals the adverse role of cDC3s in the response of ulcerative colitis patients to anti-TNF-α therapy
Li Z, Ma R, Nie Z et al. · Journal of translational medicine 2025 · PMID 41029683 · doi:10.1186/s12967-025-06909-1
This dataset
Open GSE298464 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 GSE298464_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 PRJNA1269232 and SRA study SRP588406. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41029683) ↗
Study design
4 × Intestinal mucosa,lesions,before IFX treatment,response, vs 4 × Intestinal mucosa,lesions,before IFX treatment,no-response, vs 4 × Intestinal mucosa,lesions,after IFX treatment,response, vs 4 × Intestinal mucosa,lesions,after IFX treatment,no-response,

Supports a between-group comparison across 16 samples.

How we read this: 4 replicated groups read from 16 sample titles; they account for 16 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
Datasets on a similar topic

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