GEO series

Single Cell Sequencing of Human Langerhans Cells Identifies Altered Gene Expression Profiles in Patients with Atopic Dermatitis

GSE266239 Homo sapiens (human) Single-cell RNA-seq 13 samples Submitted 2024/05/03 Platform GPL18573

At a glance

Single-cell RNA-seq · human · 13 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: 13 samples: 4 × LC_AD vs 3 × LC_HC vs 3 × Tcell_HC vs 3 × Tcell_ADGroups 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 sequencing of human Langerhans cells identifies altered gene expression profiles in patients with atopic dermatitisImmunoHorizons · 2025

Summary (written by the submitters)

Atopic dermatitis (AD) is characterized by dysregulated T cell immunity and skin microbiome dysbiosis with predominance of Staphylococcus aureus (S. aureus). Emerging evidence suggests a role for S. aureus in exacerbating AD skin inflammation. Interestingly, specific glycosylation of S. aureus cell wall structures amplifies skin inflammation through interaction with Langerhans cells (LCs).

Read the full summary ↓

However, the role of LCs in AD remains poorly characterized. Here, we performed single cell RNA-sequencing of primary epidermal LCs and dermal T cells isolated from skin biopsies of AD patients and healthy controls, alongside specific glycoanalysis of S. aureus strains isolated from the AD lesions. Our findings reveal four LC subpopulations, including two steady-state clusters (LC1 and LC1H) and two pro-inflammatory/matured subsets (LC2 and migratory LCs). The latter two subsets were enriched in AD skin. AD LCs showed enhanced expression of C-type lectin receptors, the high-affinity IgE receptor (FcεR1), and activation of prostaglandin and leukotrienes biosynthesis pathways, as well as upregulated transcriptional signatures related to T cell activation pathways and increased expression of CCL17 (specifically LC2) compared to healthy LCs. Correspondingly, T helper 2 and regulatory T cell populations were increased in AD lesions. Our study provides proof-of-concept for an active role of LCs in connecting the S. aureus-T cell axis in the AD inflammatory cycle.

Published in

Single-cell sequencing of human Langerhans cells identifies altered gene expression profiles in patients with atopic dermatitis

Tamminga SM, Van Der Wal MM, Saager ES et al. · ImmunoHorizons 2025 · PMID 39849992 · doi:10.1093/immhor/vlae009

This dataset

Open GSE266239 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 GSE266239_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 PRJNA1106436 and SRA study SRP504975. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39849992) ↗

Study design

4 × LC_AD vs 3 × LC_HC vs 3 × Tcell_HC vs 3 × Tcell_AD

Supports a between-group comparison across 13 samples.

How we read this: 4 replicated groups read from 13 sample titles; they account for 13 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

GSM8242943 LC_HC02 LC_HC
GSM8242944 LC_HC03 LC_HC
GSM8242945 LC_HC01 LC_HC
GSM8242946 Tcell_HC01 Tcell_HC
GSM8242947 LC_AD03 LC_AD
GSM8242948 Tcell_AD03 Tcell_AD
GSM8242949 LC_AD02 LC_AD
GSM8242950 Tcell_AD02 Tcell_AD
GSM8242951 Tcell_HC03 Tcell_HC
GSM8242952 Tcell_HC02 Tcell_HC
GSM8242953 Tcell_AD01 Tcell_AD
GSM8242954 LC_AD01 LC_AD
GSM8242955 LC_AD04 LC_AD

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