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Inhibition of Salt-Inducible Kinases 2 and 3 reduces inflammatory signature in Psoriasis

GSE331382 Homo sapiens (human) Single-cell RNA-seq 60 samples Submitted 2026/05/20 Platform GPL24676
At a glance

Single-cell RNA-seq · human · 60 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
Organism
Homo sapiens (human)
Samples
60 samples: 60 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.
Summary (written by the submitters)
Psoriasis is a highly prevalent inflammatory skin disease for which good systemic therapeutic agents are available. However, there still is a great need for new treatment options, especially oral ones. Salt-inducible kinases (SIKs) are emerging as new druggable targets in immune diseases and the SIK2/SIK3 inhibitor GLPG3970 recently proved to efficiently reduce psoriasis lesions in a phase Ib trial.
Read the full summary ↓
This study assesses molecular events underlying beneficial effects of SIK2/SIK3 inhibition via GLPG3970 in psoriasis. Using spatial transcriptomics and single cell sequencing, abundant expression of SIK2 and SIK3, but not of SIK1, was observed in psoriatic skin. In vitro, GLPG3970 reduced psoriasis marker cytokines and chemokines (TNF, IFN-, IL-1, IL-6, CXCL8, CXCL10) in peripheral mononuclear cells, T cells and fibroblasts, but not in keratinocytes. Bulk RNA sequencing of lesional psoriasis biopsies treated ex vivo with GLPG3970 and of biopsies received from responders vs. placebo-treated patients of the clinical trial showed downregulation of inflammatory pathways with suppression of IL1B, CXCL1, CXCL8, CEBPB, CD177, and CLEC5A in both settings. In summary, this study suggests that specific inhibition of SIK2/SIK3 reduces acute phase immunity and neutrophil recruitment in psoriasis.
This dataset
Open GSE331382 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 GSE331382_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 PRJNA1467986 and SRA study SRP701965. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
60 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 60 sample titles: 60 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

+ 20 more — browse all 60 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.