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

GSE242026 Mus musculus (mouse) RNA-seq (gene expression) 15 samples Submitted 2024/11/21 Platform GPL17021

At a glance

RNA-seq (gene expression) · mouse · 15 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: 15 samples: 5 × NdLN vs 5 × TdLN vs 5 × TumoGroups 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.

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.

This dataset

Open GSE242026 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 GSE242026_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 PRJNA1011230 and SRA study SRP457740. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

5 × NdLN vs 5 × TdLN vs 5 × Tumo

Supports a between-group comparison across 15 samples.

How we read this: 3 replicated groups read from 15 sample titles; they account for 15 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

GSM7747681 NdLN 1 NdLN
GSM7747682 NdLN 2 NdLN
GSM7747683 NdLN 3 NdLN
GSM7747684 NdLN 4 NdLN
GSM7747685 NdLN 5 NdLN
GSM7747686 TdLN 1 TdLN
GSM7747687 TdLN 2 TdLN
GSM7747688 TdLN 3 TdLN
GSM7747689 TdLN 4 TdLN
GSM7747690 TdLN 5 TdLN
GSM7747691 Tumor 1 Tumo
GSM7747692 Tumor 2 Tumo
GSM7747693 Tumor 3 Tumo
GSM7747694 Tumor 4 Tumo
GSM7747695 Tumor 5 Tumo

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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.