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Rebound Polarization of Monocyte-derived Tumor Macrophages Under Repeated Anti-CD40 Immunotherapy II

GSE290326 Mus musculus (mouse) Single-cell RNA-seq 2 samples Submitted 2025/10/10 Platform GPL34290
At a glance

Single-cell RNA-seq · mouse · 2 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
Organism
Mus musculus (mouse)
Samples
2 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.
Paper
Stress-NRF2 response axis polarizes tumor macrophages and undermines immunotherapyJournal for immunotherapy of cancer · 2025
Summary (written by the submitters)
To confirm that both pro-inflammatory and immunosuppressive subsets arise from common monocyte precursors, we employed Ms4a3-Cre Rosa26-tdTomato fate-mapping mice. Flow cytometry of dissociated tumors showed that most F4/80+ macrophages were tdTomato+, with subpopulations differing in MHC class II expression. scRNA-seq of sorted CD45+tdTomato+ cells confirmed a bifurcated differentiation trajectory that yields pro-inflammatory, MHC II–high macrophages (Cxcl9+, H2-Eb1), as well as Spp1+ Arg1+ immunocompromised phenotypes.
Published in
Stress-NRF2 response axis polarizes tumor macrophages and undermines immunotherapy
Schaer DJ, Schulthess-Lutz N, Baselgia L et al. · Journal for immunotherapy of cancer 2025 · PMID 41176316 · doi:10.1136/jitc-2025-013063
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 GSE290326_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: 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 PRJNA1227482 and SRA study SRP565925. Searching any of these in the dataset finder brings you back here.

Samples in this study

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