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Gene expression profile at single cell level of Braf-mutant mouse melanoma tumor and skin

GSE279468 Mus musculus (mouse) Single-cell RNA-seq 53 samples Submitted 2025/03/30 Platform GPL21103
At a glance

Single-cell RNA-seq · mouse · 53 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
Organism
Mus musculus (mouse)
Samples
53 samples: 53 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
Uncovering minimal pathways in melanoma initiationNature communications · 2025
Summary (written by the submitters)
Melanomas are genetically heterogeneous, displaying mitogen-activated protein kinase mutations and homozygous loss of tumor suppressor genes. Mouse models combining such mutations produce fast-growing, pigmented tumors. In contrast, rare, slow-growing, lowly-pigmented tumors arise in mice combining Braf activation with heterozygous loss of Pten or, as we show here, in albino mice bearing only a Braf mutation.
Read the full summary ↓
Incidence kinetics suggest a stochastic event underlies tumorigenesis, but responsible de novo mutations or structural variants were not found. Single-cell transcriptomics of tumors identified a cell type resembling “neural crest-like” cells in human and mouse melanomas. These exist in normal mouse skin, expand upon Braf activation, and persist through serial transplantation; analyses of gene expression suggest they serve as precursors of malignant cells. This state may serve as an intermediate on a slow path to malignancy that, while not abundant in fast-growing, heavily-mutated tumors, may provide a diagnostically and therapeutically important source of cellular heterogeneity.
Published in
Uncovering minimal pathways in melanoma initiation
Xiao H, Shiu J, Chen CF et al. · Nature communications 2025 · PMID 40571713 · doi:10.1038/s41467-025-60742-0
This dataset
Open GSE279468 in finder → Find more mouse 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 GSE279468_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 PRJNA1172319 and SRA study SRP538262. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40571713) ↗
Study design
53 samples, each with a distinct title — no replicated groups

Supports a case/control comparison: 17 samples read as cases, 15 as controls.

How we read this: Read from 53 sample titles: 53 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

+ 13 more — browse all 53 samples with per-sample file links →

Datasets on a similar topic

Search all mouse 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.