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tRNA m1A modification regulates cholesterol biosynthesis to promote antitumor immunity of CD8+ T cells

GSE275602 Mus musculus (mouse) RNA-seq (gene expression) 12 samples Submitted 2025/01/07 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 12 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
12 samples: 12 samples, each with a distinct title — no replicated groupsGroups 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
tRNA m1A modification regulates cholesterol biosynthesis to promote antitumor immunity of CD8+ T cellsThe Journal of experimental medicine · 2025
Summary (written by the submitters)
Activation of CD8+ T cells necessitates rapid metabolic reprogramming to fulfill the substantial biosynthetic demands of their effector functions. However, the post-transcriptional mechanisms underpinning this process remain obscure. The tRNA N1-methyladenine (m1A) modification, which plays a role in maintaining tRNA stability and modulating protein translation, has an undefined physiological function in CD8+ T cells, particularly in antitumor responses.
Read the full summary ↓
Here, we demonstrate that the tRNA m1A 'writer' gene Trmt61a enhances the tumor-killing capacity of CD8+ T cells by regulating cholesterol biosynthesis. We find that Trmt61a expression in CD8+ T cells is upregulated upon activation and correlates positively with T cell-mediated cytotoxicity within the tumor microenvironment of colorectal cancer (CRC) patients. Deletion of Trmt61a in CD8+ T cells leads to a compromised tumor-killing function in both in vivo and in vitro assays, which is dependent on the m1A catalytic activity of TRMT61A. Mechanistically, tRNA m1A promotes antitumor immunity in CD8+ T cells by enhancing the translation of ATP citrate lyase (ACLY), a key enzyme for cholesterol biosynthesis. Supplementation with cholesterol can rescue the impaired tumor-killing function and proliferation of TRMT61A-deficient CD8+ T cells. Our findings underscore the significance of tRNA m1A modification as a regulatory checkpoint in cholesterol metabolism in CD8+ T cells, suggesting potential novel strategies for cancer immunotherapy.
Published in
tRNA m1A modification regulates cholesterol biosynthesis to promote antitumor immunity of CD8+ T cells
Miao S, Li H, Song X et al. · The Journal of experimental medicine 2025 · PMID 39873720 · doi:10.1084/jem.20240559
This dataset
Open GSE275602 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 GSE275602_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 PRJNA1152006 and SRA study SRP528445. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39873720) ↗
Study design
12 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 12 sample titles: 12 distinct titles with little repetition. 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

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