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Minimally invasive 1 mm skin biopsies capture regional transcriptomic heterogeneity in vitiligo

GSE311770 Homo sapiens (human) RNA-seq (gene expression) 105 samples Submitted 2026/06/03 Platform GPL34295
At a glance

RNA-seq (gene expression) · human · 105 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
105 samples: 105 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
Minimally invasive 1 mm skin biopsies capture site-specific transcriptomic heterogeneity in vitiligoFrontiers in immunology · 2026
Summary (written by the submitters)
Vitiligo is an autoimmune depigmentation disorder characterized by melanocyte loss and complex immune dysregulation. Despite therapeutic advances, variable efficacy and frequent relapse highlight the need for deeper insight into its pathophysiology. Conventional 3–5 mm skin biopsies are invasive and require suturing, limiting their use in clinical and translational research.
Read the full summary ↓
Here, we demonstrate that minimally invasive 1 mm punch biopsies yield adequate RNA compatible with bulk transcriptomic profiling and enable comprehensive molecular characterization of vitiligo skin. RNA sequencing of 105 biopsies spanning lesional, perilesional, non-lesional, and control skin revealed distinct region-specific transcriptional signatures involving interferon signaling, immune activation, and metabolic reprogramming. Beyond canonical melanocyte and immune pathways, we identify underexplored dysregulation of cellular clearance and structural regulatory mechanisms, implicating ferroptosis, peroxisome, and efferocytosis pathways in lesion persistence. Connectivity Map analysis further predicted candidate compounds capable of reversing the lesional transcriptional signature, pointing to epigenetic regulators, tyrosine kinase inhibitors, and metabolic modulators. These findings establish 1 mm skin biopsies as a feasible and biologically informative tool for minimally invasive molecular profiling and highlight new therapeutic axes in vitiligo pathogenesis.
Published in
Minimally invasive 1 mm skin biopsies capture site-specific transcriptomic heterogeneity in vitiligo
Berrevoet D, Belpaire A, Van Caelenberg E et al. · Frontiers in immunology 2026 · PMID 42220516 · doi:10.3389/fimmu.2026.1829996
This dataset
Open GSE311770 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 GSE311770_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 PRJNA1370894. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 42220516) ↗
Study design
105 samples, each with a distinct title — no replicated groups

Supports a case/control comparison: 51 samples read as cases, 54 as controls.

How we read this: Read from 105 sample titles: 105 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

+ 65 more — browse all 105 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.