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Single cell RNAseq dataset of MDA-MB-231 xenograft and matched metastasis

GSE299393 Homo sapiens (human) Single-cell RNA-seq 17 samples Submitted 2025/06/23 Platform GPL24676
At a glance

Single-cell RNA-seq · human · 17 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)
Samples
17 samples: 4 × Primary tumour, MDA-MB-231 xenograft model, Mouse vs 3 × Liver metastasis, MDA-MB-231 xenograft model, Mouse vs 3 × Lymph node metastasis, MDA-MB-231 xenograft model, Mouse vs 3 × Lung metastasis, MDA-MB-231 xenograft model, MouseGroups 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
AAnet Resolves a Continuum of Spatially Localized Cell States to Unveil Intratumoral HeterogeneityCancer discovery · 2025
Summary (written by the submitters)
Identifying functionally important cell states and structure within heterogeneous tumors remains a significant biological and computational challenge. Current clustering or trajectory-based models are ill-equipped to address the notion that cancer cells reside along a phenotypic continuum. We present Archetypal Analysis network (AAnet), a neural network that learns archetypal states within a phenotypic continuum in single-cell data.
Read the full summary ↓
Unlike traditional archetypal analysis, AAnet learns archetypes in simplex-shaped neural network latent space. Using pre-clinical models and clinical breast cancers, AAnet resolves distinct cell states and processes, including cell proliferation, hypoxia, metabolism and immune interactions. Primary tumor archetypes are recapitulated in matched liver, lung and lymph node metastases. This dataset comprises of the 10X genomics based single cell RNAseq on MDA-MB-231 xenografts and matched metastasis used to perform archetypal analysis to understand tumour hetegeneity as a phenotypic continuum.
Published in
AAnet Resolves a Continuum of Spatially Localized Cell States to Unveil Intratumoral Heterogeneity
Venkat A, Youlten SE, San Juan BP et al. · Cancer discovery 2025 · PMID 40552975 · doi:10.1158/2159-8290.CD-24-0684
This dataset
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.

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 GSE299393_RAW.tar (it can run to tens of gigabytes).

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.

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 PRJNA1274250 and SRA study SRP591205. Searching any of these in the dataset finder brings you back here.

Study design
4 × Primary tumour, MDA-MB-231 xenograft model, Mouse vs 3 × Liver metastasis, MDA-MB-231 xenograft model, Mouse vs 3 × Lymph node metastasis, MDA-MB-231 xenograft model, Mouse vs 3 × Lung metastasis, MDA-MB-231 xenograft model, Mouse

Supports a between-group comparison across 13 samples.

How we read this: 4 replicated groups read from 17 sample titles; they account for 13 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
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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.