GEO series

Chronic compression recapitulates transcriptional, metabolic, and functional state changes in macrophages associated with pro-tumor phenotypes

GSE304867 Mus musculus (mouse) RNA-seq (gene expression) 12 samples Submitted 2025/12/15 Platform GPL34328

At a glance

RNA-seq (gene expression) · mouse · 12 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: 12 samples: 6 × Agarose vs 6 × WeightedGroups 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: Chronic compression induces transcriptional, metabolic, and functional state changes in macrophages that recapitulate tumor-associated phenotypesFrontiers in immunology · 2025

Summary (written by the submitters)

Macrophages comprise a significant portion of the glioblastoma tumor microenvironment and are essential in promoting immunosuppression and tumor progression. Solid tumors such as glioblastoma generate solid stress as they expand, creating a compressive microenvironment for mechanosensitive immune cells including macrophages. Macrophages are known to respond to various mechanical stimuli but have not yet been studied in the context of chronic compression observed in growing tumors.

Read the full summary ↓

Here, we used a custom in vitro compression system to elucidate the effects of compressive solid stress on murine macrophages. We found that macrophages have significant morphological, transcriptional, metabolic, and functional responses to compression. These changes corresponded to both canonical pro- and anti-inflammatory macrophage states. The gene expression signatures of compressed macrophages more closely resembled those of glioma-associated macrophages known to be associated with worse patient outcomes. These results indicate that compression alone, independent from tumor cell-derived biochemical factors, may contribute to the pathological tumor-associated macrophage phenotype. This could represent a vicious cycle of tumor immunomechanics and mechano-immunology. Targeting solid stress in tumors or the response to solid stress by macrophages may interrupt this feedback loop to help normalize the tumor immune microenvironment and improve glioblastoma response to immunotherapy.

Published in

Chronic compression induces transcriptional, metabolic, and functional state changes in macrophages that recapitulate tumor-associated phenotypes

Burchett Darantiere A, Chen H, Najera J et al. · Frontiers in immunology 2025 · PMID 41445746 · doi:10.3389/fimmu.2025.1626024

This dataset

Open GSE304867 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 GSE304867_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 PRJNA1303093 and SRA study SRP607425. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41445746) ↗

Study design

6 × Agarose vs 6 × Weighted

Supports a between-group comparison across 12 samples.

How we read this: 2 replicated groups read from 12 sample titles; they account for 12 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

GSM9158810 Agarose 1 Agarose
GSM9158811 Agarose 2 Agarose
GSM9158812 Agarose 3 Agarose
GSM9158813 Agarose 4 Agarose
GSM9158814 Agarose 5 Agarose
GSM9158815 Agarose 6 Agarose
GSM9158816 Weighted 1 Weighted
GSM9158817 Weighted 2 Weighted
GSM9158818 Weighted 3 Weighted
GSM9158819 Weighted 4 Weighted
GSM9158820 Weighted 5 Weighted
GSM9158821 Weighted 6 Weighted

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