GEO series

Lymphatic-derived 25-hydroxycholesterol promotes immunity in melanoma by inhibiting PPAR-γ in tumor associated macrophages and monocytes

GSE239972 Mus musculus (mouse) RNA-seq (gene expression) 20 samples Submitted 2024/11/21 Platform GPL24247

At a glance

RNA-seq (gene expression) · mouse · 20 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: 20 samples: 5 × Monocyte, tumor, HE vs 5 × Monocyte, tumor, WT vs 5 × Macrophage, tumor, HE vs 5 × Macrophage, tumor, WTGroups 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: Lymphatic-derived oxysterols promote anti-tumor immunity and response to immunotherapy in melanomaNature communications · 2025

Summary (written by the submitters)

In melanoma, lymphangiogenesis correlates with metastasis and poor prognosis and promotes immunosuppression. However, it also potentiates immunotherapy by supporting trafficking of immune cells. Lymphatic endothelial cells (LECs) are highly plastic cells that shape their phenotype according to distinct microenvironments, which likely define their functional properties, such as immunomodulation.

Read the full summary ↓

Here, we show in a lymphangiogenic murine melanoma model that LECs upregulate the enzyme Ch25h, which catalyzes the formation of 25-hydroxycholesterol (25-HC) from cholesterol and plays important roles in regulating lipid metabolism, gene expression, and immune activation. LECs represent the main source of extracellular 25-HC in tumors, leading to the inhibition of PPAR- in intra-tumoral macrophages and monocytes. This prevents their immunosuppressive phenotype and instead promotes their conversion into proinflammatory myeloid cells that support effector T cell functions. We identify here in mechanistic detail a novel LEC function that supports anti-tumor immunity, which can be therapeutically exploited in combination with immunotherapy.

Published in

Lymphatic-derived oxysterols promote anti-tumor immunity and response to immunotherapy in melanoma

Sun M, Garnier L, Chevalier R et al. · Nature communications 2025 · PMID 39890772 · doi:10.1038/s41467-025-55969-w

This dataset

Open GSE239972 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 GSE239972_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 PRJNA1001846 and SRA study SRP453165. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39890772) ↗

Study design

5 × Monocyte, tumor, HE vs 5 × Monocyte, tumor, WT vs 5 × Macrophage, tumor, HE vs 5 × Macrophage, tumor, WT

Supports a between-group comparison across 20 samples.

How we read this: 4 replicated groups read from 20 sample titles; they account for 20 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

GSM7679310 Monocyte, tumor, HE1 Monocyte, tumor, HE
GSM7679311 Monocyte, tumor, HE2 Monocyte, tumor, HE
GSM7679312 Monocyte, tumor, HE3 Monocyte, tumor, HE
GSM7679313 Monocyte, tumor, HE4 Monocyte, tumor, HE
GSM7679314 Monocyte, tumor, HE5 Monocyte, tumor, HE
GSM7679315 Monocyte, tumor, WT1 Monocyte, tumor, WT
GSM7679316 Monocyte, tumor, WT2 Monocyte, tumor, WT
GSM7679317 Monocyte, tumor, WT3 Monocyte, tumor, WT
GSM7679318 Monocyte, tumor, WT4 Monocyte, tumor, WT
GSM7679319 Monocyte, tumor, WT5 Monocyte, tumor, WT
GSM7679320 Macrophage, tumor, HE1 Macrophage, tumor, HE
GSM7679321 Macrophage, tumor, HE2 Macrophage, tumor, HE
GSM7679322 Macrophage, tumor, HE3 Macrophage, tumor, HE
GSM7679323 Macrophage, tumor, HE4 Macrophage, tumor, HE
GSM7679324 Macrophage, tumor, HE5 Macrophage, tumor, HE
GSM7679325 Macrophage, tumor, WT1 Macrophage, tumor, WT
GSM7679326 Macrophage, tumor, WT2 Macrophage, tumor, WT
GSM7679327 Macrophage, tumor, WT3 Macrophage, tumor, WT
GSM7679328 Macrophage, tumor, WT4 Macrophage, tumor, WT
GSM7679329 Macrophage, tumor, WT5 Macrophage, tumor, WT

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