← BioTransfer GEO Dataset Finder
GEO series

Determinants of long-term response to patritumab deruxtecan (HER3-DXd) in breast cancer patient-derived xenografts

GSE307574 Homo sapiens (human) RNA-seq (gene expression) 58 samples Submitted 2025/11/28 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 58 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)
Samples
58 samples: 58 samples, each with a distinct title — no replicated groupsGroups 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
Determinants of long-term response to patritumab deruxtecan in breast cancer patient-derived xenograftsNPJ precision oncology · 2025
Summary (written by the submitters)
Purpose: Novel antibody-drug conjugates (ADCs) have shown potent antitumor activity across multiple cancer types. Here, we aimed to identify potential determinants of response to patritumab deruxtecan (HER3-DXd), a HER3-directed ADC linked to a potent topoisomerase I inhibitor (TOP1i) payload, in breast cancer (BC) patient-derived xenograft (PDX) models.
Read the full summary ↓
Experimental Design: The antitumor activity of HER3-DXd was assessed in 31 BC PDXs and classified according to tumor growth inhibition and duration of response. We analyzed the sensitivity to HER3-DXd according to the molecular characteristics of the PDX models, the sensitivity to the TOP1i irinotecan, and prior patient treatments. The biological effects following treatment with HER3- DXd were assessed and associated to treatment response. Results: Fourteen out of 31 (45%) PDXs exhibited a profound and sustained response to HER3-DXd. Basal-like PAM50 intrinsic subtype was associated with long-term response, across HER3/ERBB3 expression levels. We also observed a positive association between HER3-DXd and irinotecan sensitivity in the PDXs, as well as short-lasting antitumor response in models derived from patients with prior repeated exposure to chemotherapy. HER3-DXd showed sustained activity in BRCA1/BRCA2-mutated PARPi-resistant PDX models. Long-term responders exhibited persistent DNA damage and lacked early transcriptional activation of the G2/M cell cycle checkpoint to allow for DNA repair and R-loop resolution, in parallel resulting in immune pathways activation. Conclusions: HER3-DXd exhibited potent antitumor activity in breast cancer PDX models, including those with BRCA1/BRCA2 alterations and PARPi resistance. Notably, characteristics linked to long-term response were primarily associated with the TOP1i payload activity.
Published in
Determinants of long-term response to patritumab deruxtecan in breast cancer patient-derived xenografts
Òdena A, Monserrat L, Brasó-Maristany F et al. · NPJ precision oncology 2025 · PMID 41272064 · doi:10.1038/s41698-025-01172-5
This dataset
Open GSE307574 in finder → Find more human 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 GSE307574_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 PRJNA1322320 and SRA study SRP618728. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41272064) ↗
Study design
58 samples, each with a distinct title — no replicated groups

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

How we read this: Read from 58 sample titles: 58 distinct titles with little repetition. 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

+ 18 more — browse all 58 samples with per-sample file links →

Datasets on a similar topic

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.