GEO series

HER2∆16 directs luminal cell identity and estrogen receptor signaling in HER2+ breast cancer

GSE301629 Mus musculus (mouse) RNA-seq (gene expression) 10 samples Submitted 2026/05/16 Platform GPL24247

At a glance

RNA-seq (gene expression) · mouse · 10 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: Mus musculus (mouse)
Samples: 10 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.

Summary (written by the submitters)

Co-expression of the estrogen receptor (ER) and human epidermal growth factor receptor 2 (HER2) contributes to breast cancer heterogeneity and therapeutic resistance. Tumors expressing both ER and HER2 comprise up to 10% of diagnosed breast cancer cases, yet advances in the field have been hindered by the lack of suitable genetically engineered mouse models (GEMMs) to study the interactions between HER2 and ER in an immune-competent setting.

Read the full summary ↓

Here, we demonstrate that expression of the oncogenic HER2 splice variant lacking exon 16 (HER2∆16) within the mammary epithelium promotes the development of aggressive luminal tumors, resembling HER2+/ER+ human breast cancer. Expression of HER2∆16 facilitates luminal cell differentiation and drives an ER-mediated transcriptional program that is sensitive to endocrine-based therapies in both murine and human models. Using a knock-in GEMM where HER2∆16 is under the transcriptional control of the endogenous murine ErbB2 promoter we show that this model recapitulates many features of HER2+/ER+ human breast cancer including genomic amplification of the endogenous ErbB2 allele, ER-expression and sensitivity to anti-estrogens, providing a vital preclinical platform to model ER+/HER2+ disease. HER2∆16 is expressed across HER2+ human breast cancer cell lines with higher levels correlating with increased expression of both ER and downstream transcriptional targets. Interestingly, expression of HER2∆16 is increased upon resistance to HER2-targeted therapy, leading to an ER-driven transcriptional program which can be effectively targeted using ER-antagonists. Overall, these findings offer valuable mechanistic insights into the therapeutic efficacy of combining anti-HER2 and endocrine therapy in tumors expressing high levels of the HER2∆16 isoform either in neoadjuvant or adjuvant settings to better treat HER2+ disease.

This dataset

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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 GSE301629_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 PRJNA1285845 and SRA study SRP598106. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Samples in this study

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+ 10 more — browse all 10 samples with per-sample file links →

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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.