← BioTransfer GEO Dataset Finder
GEO series

Single cell transcriptomes of genetic landscape from actinic keratosis to cutaneous squamous cell carcinoma

GSE200334 Homo sapiens (human) Single-cell RNA-seq 14 samples Submitted 2025/10/28 Platform GPL24676
At a glance

Single-cell RNA-seq · human · 14 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)
Topic
Cutaneous squamous cell carcinomaThis series is part of our curated briefing on it.
Samples
14 samples: 8 × skin tissue-AK vs 3 × skin tissue-NS vs 3 × skin tissue-SCCGroups 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 transcriptomic landscape of keratinocyte transformation from actinic keratosis to skin carcinomaiScience · 2025
Summary (written by the submitters)
Here, we performed scRNA-seq to compare the transcriptomes of individual cells from three groups: (1) healthy sun-exposed skin; (2) AK samples; (3) cSCC samples. A total of 81792 cells from 8 AK samples, 3 cSCC samples and 3 control skin tissue were characterized, which comprising representatives from each of the major dermal cell types.
Read the full summary ↓
Our results demonstrate the heterogeneity within tissues/patients and corroborated the effect of the tumor environment during carcinogenesis, especially immune cell populations. Additionally, we identified a list of gene expression changes that affected several known cancerous pathways, with potential evolution trajectory from a subset of AK premalignant cells to cSCC cells. Our findings will improve current understanding about the mechanism of AK-cSCC progression, and are potentially valuable in providing novel precautionary/ therapeutic markers.
Published in
Single-cell transcriptomic landscape of keratinocyte transformation from actinic keratosis to skin carcinoma
Xu T, Wang Z, Wu H et al. · iScience 2025 · PMID 41446728 · doi:10.1016/j.isci.2025.114169
This dataset
Open GSE200334 in finder → Find more human RNA-seq datasets → Cutaneous squamous cell carcinoma landscape →
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 GSE200334_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 PRJNA824113. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41446728) ↗
Study design
8 × skin tissue-AK vs 3 × skin tissue-NS vs 3 × skin tissue-SCC

Supports a between-group comparison across 14 samples.

How we read this: 3 replicated groups read from 14 sample titles; they account for 14 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
More Cutaneous squamous cell carcinoma datasets

Search all human RNA-seq datasets in GEO →

Share this dataset

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.