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Single-cell RNA profiling of mammary gland tumours in MMTV-PyMT mouse model of breast cancer upon Prrx1 knock out

GSE291211 Mus musculus (mouse) Single-cell RNA-seq 10 samples Submitted 2026/02/11 Platform GPL30172
At a glance

Single-cell RNA-seq · mouse · 10 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
10 samples: 4 × MMTV-PyMT Prrx1 f/f Tumors Homo vs 3 × MMTV-PyMT Prrx1 +/+ Tumors WT vs 3 × MMTV-PyMT Prrx1 +/f Tumors HetGroups 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
A hormetic transcriptional program coregulates invasion, proliferation and dormancy to define metastatic potentialNature communications · 2026
Summary (written by the submitters)
Disseminated cancer cells rarely succeed in forming macrometastases, yet they continue to be the most life-threatening cause of patient mortality. The determinants driving metastatic competence, however, are still poorly understood. Using data from human breast cancer patients and genetic mouse models, we uncover a non-linear relationship between the expression of the EMT transcription factor Prrx1 in the primary tumor and metastatic outcome.
Read the full summary ↓
Multi-omics analyses in mouse tumors reveal that Prrx1 functions as a dual regulator, promoting invasive behavior while simultaneously inducing dormancy. Cells with intermediate Prrx1 levels exhibit the highest metastatic fitness, whereas extreme levels (negative or too high) lead to less metastasis, typical of a hormetic behavior, and respectively due to insufficient invasiveness or to dormancy. These findings provide mechanistic insight into the regulation of dormancy and its link to metastatic potential. Additionally, we propose that combined signatures of invasion and proliferation allow robust prognosis prediction in breast cancer patients. Our study further highlights Prrx1-driven heterogeneity, established in the primary tumor, as a key determinant of metastatic competence.
Published in
A hormetic transcriptional program coregulates invasion, proliferation and dormancy to define metastatic potential
Jiménez-Castaño R, Narwade N, Moreno-Bueno G et al. · Nature communications 2026 · PMID 41781391 · doi:10.1038/s41467-026-70242-4
This dataset
Open GSE291211 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 GSE291211_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 PRJNA1232205 and SRA study SRP568158. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41781391) ↗
Study design
4 × MMTV-PyMT Prrx1 f/f Tumors Homo vs 3 × MMTV-PyMT Prrx1 +/+ Tumors WT vs 3 × MMTV-PyMT Prrx1 +/f Tumors Het

Supports a between-group comparison across 10 samples.

How we read this: 3 replicated groups read from 10 sample titles; they account for 10 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
Datasets on a similar topic

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