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Spatiotemporal organisation of residual disease in mouse and human BRCA1-deficient mammary tumors and breast cancer

GSE299631 Homo sapiens (human) Single-cell RNA-seq 50 samples Submitted 2025/06/19 Platform GPL24676Platform GPL24247
At a glance

Single-cell RNA-seq · human · 50 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)
Topic
Breast cancerThis series is part of our curated briefing on it.
Samples
50 samples: 11 conditions, mostly in duplicateGroups 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.
Summary (written by the submitters)
Breast cancer remains one of the prominent causes of death worldwide. Although chemotherapeutic agents often result in substantial reduction of primary or metastatic tumors, remaining drug-tolerant tumor cell populations, known as minimal residual disease (MRD), pose a significant risk of recurrence and therapy resistance. In this study, we describe the spatiotemporal organisation of therapy response and MRD in BRCA1;p53-deficient mouse mammary tumors and human clinical samples using a multimodal approach.
Read the full summary ↓
By integrating single-cell RNA sequencing, spatial transcriptomics, and imaging mass cytometry across multiple treatment timepoints, we characterise dynamic interactions between tumor cell subpopulations and their surrounding microenvironment. Our analysis identifies a distinct, drug-tolerant epithelial-mesenchymal transition (EMT) cancer cell population, which exhibits a conserved expression program in human BRCA1-deficient tumors and significantly correlates with adverse clinical outcomes. We further reveal the spatial distribution of residual EMT-like tumor cells within specific anatomical niches, providing a framework for understanding the persistence of MRD and potential therapeutic vulnerabilities. These findings yield a comprehensive molecular roadmap of MRD, opening new avenues for therapeutic strategies targeting EMT-driven drug tolerance and tumor relapse.
This dataset
Open GSE299631 in finder → Find more RNA-seq datasets → Breast cancer 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 GSE299631_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 PRJNA1275757 and SRA study SRP592141. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
11 conditions, mostly in duplicate
Mouse, Visium ST, Primary tumor, # ×6 Mouse, Visium ST, Cisplatin 12dpt, # ×3 Human, Visium ST, Residual tumor, # ×3 Mouse, Visium ST, Mammary gland, # ×2 Mouse, Visium ST, Cisplatin 7dpt, # ×2 Mouse, Visium ST, Cisplatin Recurrent, # ×2 Mouse, Visium ST, TAC 7dpt, # ×2 Mouse, Visium ST, TAC Recurrent, # ×2 +25 more

Supports a between-group comparison across 28 samples.

How we read this: 11 replicated groups read from 50 sample titles; they account for 28 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

+ 10 more — browse all 50 samples with per-sample file links →

More Breast cancer datasets

Search all RNA-seq datasets in GEO →

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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.