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Castration Increases Aggressiveness of Prostatic Luminal Progenitor Cells in Prostate Cancer Through FosL1/AP-1-Mediated Transcriptional Reprogramming

GSE273079 Mus musculus (mouse) Single-cell RNA-seq 384 samples Submitted 2025/12/05 Platform GPL19057
At a glance

Single-cell RNA-seq · mouse · 384 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
Mus musculus (mouse)
Samples
384 samples: 96 × poolA vs 96 × poolB vs 96 × poolC vs 96 × poolDGroups 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
Targeting pre-existing club-like cells in prostate cancer potentiates androgen deprivation therapyEMBO molecular medicine · 2026
Summary (written by the submitters)
In this study, we show that the castration-tolerance potential of prostatic LSCmed (Lin-/Sca-1+/CD49fmed) cells is not intrinsic but rather results from transcriptomic reprogramming that further enhances their aggressiveness. Using scRNAseq specifically applied to Ptenpc-/- LSCmed cells sorted from intact versus castrated mice, we identified three distinct LSCmed cell clusters and we show that castration favors the emergence of a more stem-like LSCmed subpopulation.
Published in
Targeting pre-existing club-like cells in prostate cancer potentiates androgen deprivation therapy
Baurès M, Vieira Aleixo AS, Pacreau E et al. · EMBO molecular medicine 2026 · PMID 41629661 · doi:10.1038/s44321-026-00375-y
This dataset
Open GSE273079 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 GSE273079_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 PRJNA1140106 and SRA study SRP522137. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41629661) ↗
Study design
96 × poolA vs 96 × poolB vs 96 × poolC vs 96 × poolD

Supports a between-group comparison across 384 samples.

How we read this: 4 replicated groups read from 384 sample titles; they account for 384 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

+ 344 more — browse all 384 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.