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Inhibition of the cancer stem cell immune checkpoint SOAT1 suppresses regulatory T cell functions through a trans-cellular 20(S)-Hydroxycholesterol-GPR132 pathway in mice.

GSE309517 Mus musculus (mouse) RNA-seq (gene expression) 45 samples Submitted 2025/12/08 Platform GPL17021
At a glance

RNA-seq (gene expression) · mouse · 45 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
45 samples: 13 conditions, mostly in triplicateGroups 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)
SOAT1 (sterol O-acyltransferase 1) serves as a cancer stem cell-specific immune checkpoint that facilitates trans-cellular signaling through the release of 20-Hydroxycholesterol (20-OHC) and subsequent activation of GPR132 on regulatory T cells (Tregs). This pathway plays a crucial role in modulating the tumor immune microenvironment and can significantly influence the balance between immune activation and suppression.
Read the full summary ↓
In the context of cancer, SOAT1 is instrumental in regulating the cholesterol metabolism of cancer stem cells. When SOAT1 is inhibited, there is an increase in the secretion of 20-OHC by tumor cells. This oxysterol not only functions as a signaling molecule but also acts as a ligand that binds to GPR132, a G protein-coupled receptor primarily expressed on immune cells, including Tregs. This binding triggers a cascade of intracellular signaling pathways that ultimately enhances the immunosuppressive functions of Tregs. Mechanistically, the activation of GPR132 by 20-OHC leads to downstream signaling events that may involve pathways such as JAK-STAT and PKC signaling, promoting the development and survival of Tregs while enabling them to exert their immunosuppressive effects within the tumor microenvironment. This results in the downregulation of effector T cell activities and impairs the maturation and activation of dendritic cells (DCs), which are pivotal for effective anti-tumor immune responses. The presence of Tregs, particularly in elevated frequencies within tumors, can contribute to an immunosuppressive environment that protects cancer cells from immune-mediated destruction. Thus, the SOAT1-20OHC-GPR132 axis represents a critical mechanism through which cancer cells can evade immune surveillance. By controlling cholesterol metabolism through SOAT1, tumors can manipulate the availability of 20-OHC, amplifying the immunosuppressive capacity of Tregs and facilitating an environment conducive to tumor growth and progression. Targeting SOAT1 and the associated 20-OHC signaling pathway may offer a promising therapeutic strategy to neutralize Treg-mediated immunosuppression. Inhibiting SOAT1 not only disrupts the tumor's ability to produce 20-OHC but also potentially reprograms the immune landscape, promoting a more activated and effective anti-tumor immune response. Overall, SOAT1's dual role as a cancer stem cell-specific immune checkpoint and its involvement in the trans-cellular signaling of 20-OHC make it a valuable target for innovative cancer immunotherapies aimed at enhancing immune recognition and attack on cancer cells.
This dataset
Open GSE309517 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 GSE309517_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 PRJNA1336197 and SRA study SRP629587. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
13 conditions, mostly in triplicate
Hepa_stk ×6 CT26_stk ×5 CT26_dmso ×3 Hepa_dmso ×3 CT26_lucif ×3 CT26_sh1 ×3 CT26_sh2 ×3 CT26_sh3 ×3 +6 more

Supports a between-group comparison across 44 samples.

How we read this: 13 replicated groups read from 45 sample titles; they account for 44 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

+ 5 more — browse all 45 samples with per-sample file links →

Datasets on a similar topic

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