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Transcriptional profiling of skin cancer NK cells reveals the elevated glucocorticoid receptor activity alters their pro-inflammatory features.

GSE242941 Homo sapiens (human) Single-cell RNA-seq 36 samples Submitted 2026/01/14 Platform GPL24676
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. 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
36 samples: 36 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
Glucocorticoid Receptor Activation Reprograms NK Cells to Drive AREG-Mediated Immunosuppression: A Pan-Cancer Role for AREGAdvanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
Summary (written by the submitters)
The interplay between natural killer (NK) cells and tumor microenvironment (TME) is closely associated with tumor progression. We showed NK cells are common constituents in the tissue of skin cancers including basal cell carcinoma (BCC), cutaneous squamous cell carcinoma (cSCC), extramammary paget disease (EMPD) and acral melanoma (aMM).
Read the full summary ↓
scRNA-Seq revealed an inter and intra-tumor transcriptional heterogeneity of NK cells in different skin TMEs. Unexpectedly, compared to peri-tumor, skin tumor NK cells down regulated the production of anti-tumor cytokines, IFN-γ and TNF-α, and up regulated the production of amphiregulin (AREG), a ligand of epidermal growth factor receptor (EGFR), which functions in promoting skin tumor growth and mediating immune tolerance.
Published in
Glucocorticoid Receptor Activation Reprograms NK Cells to Drive AREG-Mediated Immunosuppression: A Pan-Cancer Role for AREG
Wei Q, Liang G, Zeng R et al. · Advanced science (Weinheim, Baden-Wurttemberg, Germany) 2026 · PMID 41082397 · doi:10.1002/advs.202512620
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 GSE242941_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 PRJNA1014930 and SRA study SRP459543. Searching any of these in the dataset finder brings you back here.

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

Supports a case/control comparison: 24 samples read as cases, 6 as controls.

How we read this: Read from 36 sample titles: 36 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
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