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HER2 heterogeneous breast cancer models reveal novel therapeutic targets and subclonal dynamics during evolution to resistance to HER2-targeted therapies

GSE300628 Homo sapiens (human) RNA-seq (gene expression) 60 samples Submitted 2026/03/20 Platform GPL18573Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 60 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
60 samples: 21 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.
Paper
HER2 Heterogeneous Breast Cancer Models Reveal Novel Therapeutic Targets and Subclonal Dynamics during Evolution to Resistance to HER2-Targeted TherapiesCancer discovery · 2026
Summary (written by the submitters)
Intratumor heterogeneity for HER2 expression and amplification, observed in up to 40% of HER2-positive breast cancer is a driver of resistance to HER2-targeted therapies. The advancement of treatment for HER2 heterogeneous tumors has been hindered by the lack of preclinical models that accurately replicate the human disease. Here we describe human HER2 heterogeneous breast cancer cell models composed of ERBB2 amplified (HER2hi) and non-amplified (HER2lo) cell populations derived from the same tumor.
Read the full summary ↓
Utilizing these models and cellular barcoding technology, we provide evidence for subclonal cooperation between HER2hi and HER2lo subpopulations and that HER2lo cells drive resistance to HER2-targeting antibody-drug conjugates (ADC) such as T-DXd but are sensitive to HER2 kinase inhibitors. CRISPR screens in heterogeneous co-cultures identified sensitizers of HER2lo cells to T-DXd including the USP9X deubiquitinating enzyme. USP9X inhibition enhances the lysosomal targeting of HER2 to potentiate ADC payload release, diminishing tumor recurrence after T-DXd treatment. Our results elucidate the functional relevance of HER2 heterogeneity and propose improved therapies for these tumors.
Published in
HER2 Heterogeneous Breast Cancer Models Reveal Novel Therapeutic Targets and Subclonal Dynamics during Evolution to Resistance to HER2-Targeted Therapies
Goyette MA, Graser C, Seehawer M et al. · Cancer discovery 2026 · PMID 41925564 · doi:10.1158/2159-8290.CD-25-1459
This dataset
Open GSE300628 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 GSE300628_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 PRJNA1281579 and SRA study SRP594264. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41925564) ↗
Study design
21 conditions, mostly in duplicate
HCChi ×2 HCClo ×2 HCC_DMSO ×2 HCC_TDXd ×2 HCC_TDM ×2 HCC_Ne ×2 HCC_Tuc ×2 NThi ×2 +31 more

Supports a case/control comparison: 2 samples read as cases, 6 as controls.

How we read this: 21 replicated groups read from 60 sample titles; they account for 42 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

+ 20 more — browse all 60 samples with per-sample file links →

More Breast cancer datasets

Search all human 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.