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Insulin Resistance Increases TNBC Aggressiveness and Brain Metastasis via Adipocyte-derived Exosomes

GSE286275 Mus musculus (mouse) RNA-seq (gene expression) 38 samples Submitted 2025/06/16 Platform GPL34290
At a glance

RNA-seq (gene expression) · mouse · 38 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
38 samples: 10 conditions, mostly with about 5 replicates eachGroups 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
Insulin Resistance Increases TNBC Aggressiveness and Brain Metastasis via Adipocyte-Derived ExosomesMolecular cancer research : MCR · 2025
Summary (written by the submitters)
This dataset includes mRNA sequencing data obtained from 4T1 cells, either from in vitro cell culture, or clonogenic assay from brain, or primary tumor treated with exosomes from insulin sensitive (IS) or induslin resistant (IR) adipocytes; and 4T1 cells cultured in vitro and treated with miR-145a-3p. Exosomal small RNA from IS and IR aidpocytes derived exsomes were also included.
Read the full summary ↓
RNA was extracted and sequenced to investigate differential gene expression and associated biological pathways. The aim of the study is to elucidate how insulin resistance in adipocytes influences gene expression, cancer aggressiveness and metastasis. Data include raw and processed mRNA sequencing files from replicates for each condition.
Published in
Insulin Resistance Increases TNBC Aggressiveness and Brain Metastasis via Adipocyte-Derived Exosomes
Qiu Y, Chen A, Yu R et al. · Molecular cancer research : MCR 2025 · PMID 40047645 · doi:10.1158/1541-7786.MCR-24-0494
This dataset
Open GSE286275 in finder → Find more mouse 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 GSE286275_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 PRJNA1208516 and SRA study SRP556301. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40047645) ↗
Study design
10 conditions, mostly with about 5 replicates each
Brain, Clonogenic Assay, control, ×5 Brain, Clonogenic Assay, IS, ×5 Brain, Clonogenic Assay, IR, ×5 Primary Tumor, IR, ×5 Primary Tumor, control, ×4 In vitro, control, ×3 In vitro, IS adipocyte exosome treated, ×3 In vitro, IR adipocyte exosome treated, ×3 +2 more

Supports a case/control comparison: 11 samples read as cases, 10 as controls.

How we read this: 10 replicated groups read from 38 sample titles; they account for 38 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
Datasets on a similar topic

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