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

GSE310423 Homo sapiens (human) RNA-seq (gene expression) 167 samples Submitted 2025/11/28 Platform GPL24676Platform GPL36324
At a glance

RNA-seq (gene expression) · human · 167 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
167 samples: 158 distinct titles, 9 of them repeatedGroups 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
SuperSeries — this record groups several sub-series.
Summary (written by the submitters)
This SuperSeries is composed of the SubSeries listed below.
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 GSE310423 in finder → Find more 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 GSE310423_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 PRJNA1365916 and SRA study SRP618728. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41272064) ↗
Study design
158 distinct titles, 9 of them repeated
PDX350.2_1038_20_CNTL_1R ×2 PDX509_1070_20_CNTL_1L ×2 PDX288_1069_20_CNTL_1R ×2 PDX044_1060_20_CNTL_1R ×2 PDX474.2_1055_20_CNTL_1L ×2 PDX479_1079_20_CNTL_1L ×2 PDX491_1250_21_U3_24h_11L ×2 PDX491_1250_21_CNTL_1L ×2 +1 more

How we read this: Read from 167 sample titles: 158 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

+ 127 more — browse all 167 samples with per-sample file links →

More Breast cancer datasets

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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.