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Bulk RNA-seq of Genetically Diverse Triple-Negative Breast Cancer Mouse Models Treated with Immunotherapy, Chemotherapy, Erlotinib, or Trametinib

GSE304115 Mus musculus (mouse) RNA-seq (gene expression) 309 samples Submitted 2026/03/09 Platform GPL24247Platform GPL17021
At a glance

RNA-seq (gene expression) · mouse · 309 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
309 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)
To investigate the molecular determinants of response to therapy, we profiled 26 genetically diverse murine models of mammary cancer using bulk RNA sequencing. Tumors were harvested from mice that were either untreated or treated with immunotherapy (anti-PD-1 and anti-CTLA-4), chemotherapy (Carboplatin + Paclitaxel), EGFR inhibition (Erlotinib), or MEK inhibition (Trametinib) for 7 days.
Read the full summary ↓
Each model represents a distinct transcriptional subtype and genetic background, enabling the assessment of intertumoral heterogeneity in treatment response. This dataset includes RNA-seq from 2-9 biological replicates per model per condition. Tumor samples were collected prior to or during treatment response assessment, and are accompanied by corresponding survival from similarly-treated tumors. All sequencing was performed on polyA-selected RNA using Illumina platforms.
This dataset
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.

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 GSE304115_RAW.tar (it can run to tens of gigabytes).

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.

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 PRJNA1298937 and SRA study SRP604692. Searching any of these in the dataset finder brings you back here.

Samples in this study

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+ 309 more — browse all 309 samples with per-sample file links →

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