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Characterisation of the regulatory landscape in Crohn’s disease reveals miRNA-associated alterations that shape anti-TNF response (CIBER-120)

GSE270661 Homo sapiens (human) RNA-seq (gene expression) 119 samples Submitted 2025/07/16 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 119 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
119 samples: 119 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
Characterization of the Regulatory Landscape in Crohn's Disease Reveals microRNA-Associated Alterations that Shape Anti-TNF ResponseInflammatory bowel diseases · 2025
Summary (written by the submitters)
MicroRNAs (miRNAs) play a key role in regulating gene expression in Crohn’s disease (CD). Although several studies have identified miRNAs with biomarker potential, an exhaustive characterisation of the miRNAome in CD is still lacking. We performed the largest miRNA profiling effort to date to analyse miRNA variability across intestinal tissues, disease activity status, and infliximab treatment in CD.
Read the full summary ↓
We generated 120 transcriptomic profiles from terminal ileum and left colon biopsies of 30 individuals (10 with active CD, 10 with quiescent CD, and 10 healthy controls). Half of the samples were cultured ex vivo with infliximab, and the remaining half with basal medium. Using variance analyses and linear mixed differential expression models, we explored the determinants of miRNAome variability in CD. We also generated infliximab response signatures to identify candidates and examine interactions between miRNAs and the coding transcriptome. Tissue location was the main factor in miRNA variability in CD, although with a relevant contribution from patient-specific effects. We identified nine miRNAs with treatment-responsive behaviour particular to the terminal ileum of active CD cases. Incubation with infliximab restored the miRNA-mRNA interactome, although the changes observed in active CD cases suggest that many miRNA alterations are not offset by treatment. Finally, we identified 13 miRNAs-mRNA pairs with potential involvement in the transcriptomic changes induced by anti-TNF treatment. A comprehensive miRNA profiling revealed significant intestinal tissue-specific variability and identified key alterations in the miRNA-mRNA interactome that might be involved in therapeutic response to anti-TNF in CD.
Published in
Characterization of the Regulatory Landscape in Crohn's Disease Reveals microRNA-Associated Alterations that Shape Anti-TNF Response
Cervera-Seco L, Baldán-Martín M, Fernández-Tomé S et al. · Inflammatory bowel diseases 2025 · PMID 40067082 · doi:10.1093/ibd/izaf029
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 GSE270661_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: 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 PRJNA1127647 and SRA study SRP515699. Searching any of these in the dataset finder brings you back here.

Study design
119 samples, each with a distinct title — no replicated groups

Supports a case/control comparison: 79 samples read as cases, 40 as controls.

How we read this: Read from 119 sample titles: 119 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

+ 79 more — browse all 119 samples with per-sample file links →

Datasets on a similar topic

Search all human RNA-seq datasets in GEO →

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