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Single-cell transcriptomics suggest distinct upstream drivers of IL-17A/F in hidradenitis versus psoriasis

GSE220116 Homo sapiens (human) Single-cell RNA-seq 36 samples Submitted 2023/06/02 Platform GPL24676Platform GPL18573Platform GPL30173
At a glance

Single-cell RNA-seq · human · 36 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
36 samples
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.
Summary (written by the submitters)
Background: Based on the mounting evidence that Type 17 T-cells (T17 cells) and increased IL-17 play a key role in driving hidradenitis suppurativa (HS) lesion development, biologics previously used in psoriasis that block signaling of IL-17A and/or IL-17F isoforms have been repurposed to treat HS. Objective: Our aim was to characterize the transcriptome of HS T17 cells compared to the transcriptome of psoriasis T17 cells, and their ligand-receptor interactions with neighborhood immune cell subsets.
Read the full summary ↓
Methods: Single-cell data of 12,300 cutaneous immune cells from 8 de-roofing surgical HS skin samples that included dermal tunnels were compared with single-cell data of psoriasis skin (19,525 cells from 11 samples) and control skin (11,920 cells from 10 samples). All the single-cell data were generated by the identical protocol. Results: HS T17 cells expressed lower levels of IL23R and higher levels of IL1R1 and IL17F compared to psoriasis T17 cells (p < 0.05). HS regulatory T-cells (Tregs) expressed higher levels of IL1R1 and IL17F compared to psoriasis Tregs (p < 0.05). Semimature dendritic cells (DCs) were the major immune cell subsets expressing IL1B in HS, and IL-1B ligand-receptor interactions between semimature DCs and T17 cells were increased in HS compared to psoriasis (p < 0.05). HS dermal tunnel keratinocytes (KCs) expressed inflammatory cytokines (IL17C, IL1A, IL1B, and IL6) different from HS epidermis KCs (IL36G) (p < 0.05). IL6, which synergizes with IL1B to maintain cytokine expression in T17 cells, was mainly expressed by fibroblasts in HS, which also expressed IL11+ inflammatory fibroblast genes (IL11, IL24, IL6, and POSTN) involved in paracrine IL-1/IL-6 loop. Conclusion: The IL-1B-T17 cell cytokine axis is likely a dominant pathway in HS with HS T17 cells activated by IL-1B signaling, unlike psoriasis T17 cells which are activated by IL-23 signaling. Clinical Implication: Biologics targeting IL-17 isoforms and IL-1B may be effective for HS but biologics targeting IL-23 may be less effective for HS.
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 GSE220116_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 PRJNA912600 and SRA study SRP413215. Searching any of these in the dataset finder brings you back here.

Samples in this study

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