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Cytokine–ontogeny interaction shapes macrophage transcriptional states

GSE304868 Mus musculus (mouse) RNA-seq (gene expression) 100 samples Submitted 2025/09/30 Platform GPL34290Platform GPL34328
At a glance

RNA-seq (gene expression) · mouse · 100 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
100 samples: 10 conditions, mostly with about 10 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
An ontogeny-cytokine code determines macrophage response polarity and tumor outcomesCommunications biology · 2026
Summary (written by the submitters)
Macrophage ontogeny and local cytokines jointly govern tumor-associated macrophage behaviour, yet how these signals integrate to generate pro- or antitumor outputs is unknown. Here, we apply a reductionist, multi-scale pipeline to systematically map eight reference macrophage states generated by ex vivo differentiation of mouse bone marrow cells with macrophage colony-stimulating factor (M-CSF) or granulocyte-macrophage CSF (GM-CSF) and subsequent cytokine polarization (IFN-gamma, IL-4, IL-10, TGF-beta).
Read the full summary ↓
We integrated transcriptomic, 3D spheroid, and in vivo metastatic analyses to discover a lineage dependent polarity switch: IL-4 drives an ARG1+, tumor-supportive programme in M-CSF macrophages but, via NfkB, induces a CCR7+ inflammatory phenotype in GM-CSF macrophages. IFN-gamma uniformly activates STAT1/IRF pathways, maintaining antitumor profiles, whereas IL-10 and TGF-beta maximally evoke SPP1+ immunosuppressive signatures after GM-CSF priming. Functional assays confirmed these transcriptional states dictate opposite effects on tumor growth, invasion, and pulmonary metastasis. Integration of all parameters yielded an "ontogeny cytokine code" that predicts macrophage function based on developmental history and cytokine milieu. Identifying CSF-defined lineage as a master regulator of macrophage heterogeneity provides a blueprint for precision immunotherapies that reprogram macrophages in solid tumors. This SuperSeries is composed of the SubSeries listed below.
Published in
An ontogeny-cytokine code determines macrophage response polarity and tumor outcomes
Schaer DJ, Schulthess-Lutz N, Peterhans MJ et al. · Communications biology 2026 · PMID 41826506 · doi:10.1038/s42003-026-09853-y
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 GSE304868_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 PRJNA1303100 and SRA study SRP606615. Searching any of these in the dataset finder brings you back here.

Study design
10 conditions, mostly with about 10 replicates each
BMDC IL4 ×10 BMDC IL10 ×10 BMDM Control ×10 BMDM IFNy ×10 BMDM IL4 ×10 BMDM IL10 ×10 BMDM TGFb ×10 BMDC Control ×8 +8 more

Supports a between-group comparison across 94 samples.

How we read this: 10 replicated groups read from 100 sample titles; they account for 94 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

+ 60 more — browse all 100 samples with per-sample file links →

Datasets on a similar topic

Search all mouse RNA-seq datasets in GEO →

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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.