← BioTransfer GEO Dataset Finder
GEO series

Mogat1 drives metabolic adaptations to evade immune surveillance

GSE274902 Mus musculus (mouse) RNA-seq (gene expression) 32 samples Submitted 2024/08/16 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 32 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
32 samples: 10 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.
Paper
Mogat1 drives metabolic adaptations to evade immune surveillanceNature communications · 2025
Summary (written by the submitters)
Despite immune checkpoint blockades have achieved remarkable success, most patients with solid tumors do not respond or develop resistance, suggesting additional treatment strategies are needed. Concentrated efforts are directed toward revitalizing the IFNγ pathway or amplifying antigen presentation capabilities, alternative mechanisms underlying immune evasion remain poorly understood.
Read the full summary ↓
Using an unbiased whole-genome in vivo natural selection screen, we identified an uncharacterized role of Monoacylglycerol O-Acyltransferase 1 (Mogat1) as a critical modulator of tumor immune evasion. As tumors progress and expand, they undergo systemic metabolic adaptations to evade immune surveillance. Tumor cells exploit Mogat1 to sequester excess fatty acids into triglycerides, orchestrating metabolic reprogramming that simultaneously fuels tumor growth and creates an immunosuppressive microenvironment. Mogat1 inhibition suppresses tumor growth by promoting T-cell infiltration and cytotoxicity. Remarkably, Mogat1 loss facilitates the circumvention of PD-1 checkpoint blockade resistance. This heightened inflammatory response, characterized by increased interferon sensitivity, circumvents the need for conventional antigen presentation. Our findings reveal a novel lipid metabolism-centered mechanism of immune evasion and offer a potential strategy to enhance cancer immunotherapy efficacy.
Published in
Mogat1 drives metabolic adaptations to evade immune surveillance
Wei H, Niu C, Shi Y et al. · Nature communications 2025 · PMID 40745160 · doi:10.1038/s41467-025-62134-w
This dataset
Open GSE274902 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 GSE274902_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 PRJNA1148433 and SRA study SRP526597. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40745160) ↗
Study design
10 conditions, mostly in triplicate
MMTV-PyMT tumor cells,week3 ×4 MMTV-PyMT tumor cells,week4 ×4 MMTV-PyMT tumor cells,week2 ×3 MMTV-PyMT CD8T cells,week2 ×3 MMTV-PyMT CD8T cells,week3 ×3 MMTV-PyMT CD8T cells,week4 ×3 MMTV-PyMT tumor cells shCTRL ×3 MMTV-PyMT tumor cells shMogat1 ×3 +2 more

Supports a case/control comparison: 14 samples read as cases, 3 as controls.

How we read this: 10 replicated groups read from 32 sample titles; they account for 32 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
Datasets on a similar topic

Search all mouse RNA-seq datasets in GEO →

Share this dataset

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.