← BioTransfer GEO Dataset Finder
GEO series

An annotated biobank of triple negative breast cancer patient-derived xenografts featuring treatment-naïve and longitudinal samples throughout neoadjuvant chemotherapy

GSE291966 Homo sapiens (human) RNA-seq (gene expression) 92 samples Submitted 2025/07/23 Platform GPL20301Platform GPL11154
At a glance

RNA-seq (gene expression) · human · 92 samples

What it is
RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
Organism
Homo sapiens (human)
Topic
Breast cancerThis series is part of our curated briefing on it.
Samples
92 samples
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
An Annotated Biobank of Triple-Negative Breast Cancer Patient-Derived Xenografts Features Treatment-Naïve and Longitudinal Samples during Neoadjuvant ChemotherapyCancer research · 2025
Summary (written by the submitters)
Triple negative breast cancer (TNBC) that fails to respond to neoadjuvant chemotherapy (NACT) can be lethal. Developing effective strategies to eradicate chemoresistant disease requires experimental models that recapitulate the heterogeneity characteristic of TNBC.
Read the full summary ↓
To that end, we established a biobank of 92 orthotopic patient-derived xenograft (PDX) models of TNBC from the tumors of 75 patients enrolled in the ARTEMIS clinical trial (NCT02276443) at MD Anderson Cancer Center, including 12 longitudinal sets generated from serial patient biopsies collected throughout NACT and from metastatic disease. Models were established from both chemosensitive and chemoresistant tumors and nearly 30% of PDX models were capable of lung metastasis. Comprehensive molecular profiling demonstrated conservation of genomes and transcriptomes between patient and corresponding PDX tumors, with representation of all major transcriptional subtypes. Transcriptional changes observed in the longitudinal PDX models highlight dysregulation in pathways associated with DNA integrity, extracellular matrix interactions, the ubiquitin-proteasome system, epigenetics, and inflammatory signaling. These alterations reveal a complex network of adaptations associated with chemoresistance. This PDX biobank provides a valuable resource for tackling the most pressing issues facing the clinical management of TNBC, namely chemoresistance and metastasis.
Published in
An Annotated Biobank of Triple-Negative Breast Cancer Patient-Derived Xenografts Features Treatment-Naïve and Longitudinal Samples during Neoadjuvant Chemotherapy
Rinkenbaugh AL, Qi Y, Cai S et al. · Cancer research 2025 · PMID 40801311 · doi:10.1158/0008-5472.CAN-24-5023
This dataset
Open GSE291966 in finder → Find more human 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 GSE291966_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: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.

Also filed as BioProject PRJNA1236268. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40801311) ↗
Study design
A cohort of 92 individual samples

The grouping that defines any comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Sample titles run PIM010 … PIM411 and carry no group information.

Samples in this study

+ 52 more — browse all 92 samples with per-sample file links →

More Breast cancer datasets

Search all human 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.