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Age-associated modulation of TREM1/TREM2 expressing macrophages promotes melanoma progression and metastasis

GSE280640 Mus musculus (mouse) RNA-seq (gene expression) 3 samples Submitted 2025/02/27 Platform GPL34475
At a glance

RNA-seq (gene expression) · mouse · 3 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
3 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
Age-Associated Modulation of TREM1/2-Expressing Macrophages Promotes Melanoma Progression and MetastasisCancer research · 2025
Summary (written by the submitters)
Aging is a known risk factor for melanoma, yet the mechanisms underlying melanoma progression and metastasis in the older population remain largely unexplored. Among remaining gaps is the role of changes in melanoma microenvironment in key phenotypes exacerbated by age. Here we demonstrate that age enriches immunosuppressor tumor microenvironment which can be linked with melanoma metastasis phenotype.
Read the full summary ↓
Age-associated macrophages with a tolerogenic phenotype and dysfunctional CD8 positive cells with an exhausted phenotype were identified in melanomas of aged mice and human. Macrophages of the older population were enriched of the immunosuppressor subcluster expressing Trem2 while the profibrotic subcluster expressing Trem1 was reduced. Notably, inhibition of TREM1 decreased melanoma growth in young but not old mice, whereas inhibition of TREM2 prevented lung metastasis in aged mice. These data identify novel targets in melanoma metastasis which may guide aged-dependent immunotherapies.
Published in
Age-Associated Modulation of TREM1/2-Expressing Macrophages Promotes Melanoma Progression and Metastasis
Scortegagna M, Murad R, Bina P et al. · Cancer research 2025 · PMID 40126543 · doi:10.1158/0008-5472.CAN-24-4317
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 GSE280640_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 PRJNA1179868 and SRA study SRP541983. Searching any of these in the dataset finder brings you back here.

Samples in this study

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+ 3 more — browse all 3 samples with per-sample file links →

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