← BioTransfer GEO Dataset Finder
GEO series

Single cell RNA sequencing of CD45+ immune cells from tumor and tumor-adjacent mammary adipose tissue in a postmenopausal breast cancer model of lean, obese, and weight loss Trem2+/+ and Trem2-/- mice

GSE278003 Mus musculus (mouse) Single-cell RNA-seq 92 samples Submitted 2024/11/05 Platform GPL24247
At a glance

Single-cell RNA-seq · mouse · 92 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
Organism
Mus musculus (mouse)
Samples
92 samples: 92 samples, each with a distinct title — no replicated groupsGroups 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
Trem2 deficiency attenuates breast cancer tumor growth in lean, but not obese or weight loss, mice and is associated with alterations of clonal T cell populationsbioRxiv : the preprint server for biology · 2024
Summary (written by the submitters)
Triggering receptor expressed on myeloid cells 2 (Trem2) has been shown to be immunosuppressive in cancer and increased in obese adipose tissue. We utilized high fat and low fat diet to generate lean, obese, and weight loss mice in Trem2 wild-type (Trem2+/+) and Trem2 deficient (Trem2-/-) conditions. Once obesity and weight loss were established, mice were injected with E0771 breast cancer cells and tumors were allowed to grow for 4 weeks.
Read the full summary ↓
We wanted to better understand the immune landscape of both the tumor and the surrounding adjacent mammary adipose tissue (mAT). Therefore, the CD45+ immune cells from both the tumor and tumor-adjacent mAT were isolated and sequenced using single-cell RNA sequencing and V(D)J sequencing.
Published in
Trem2 deficiency attenuates breast cancer tumor growth in lean, but not obese or weight loss, mice and is associated with alterations of clonal T cell populations
Pierro EW, Cottam MA, An H et al. · bioRxiv : the preprint server for biology 2024 · PMID 39386686 · doi:10.1101/2024.09.25.614811
This dataset
Open GSE278003 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 GSE278003_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA1163859 and SRA study SRP534223. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39386686) ↗
Study design
92 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 92 sample titles: 92 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

+ 52 more — browse all 92 samples with per-sample file links →

Datasets on a similar topic

Search all mouse RNA-seq datasets in GEO →

Share this dataset

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.