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t6A tRNA modification defines RIG-I mediated anti-tumour [Ribo-seq] immune response

GSE286704 Mus musculus (mouse) RNA-seq (gene expression) 12 samples Submitted 2025/12/08 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: 3 × B16F10 shRNA Ctrl replicat vs 3 × B16F10 shRNA OSGEP#2 replicatGroups 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)
The immune response in cancer, particularly in melanoma, is often hindered by tumour-induced immune evasion strategies, but the precise mechanisms for this remains unclear. Here, we reveal how the tRNA modification threonine-6-adenosine (t6A), mediated by O-sialoglycoprotein endopeptidase (OSGEP), maintains proteostasis in melanoma cells to prevent anti-tumour immune recognition.
Read the full summary ↓
Cytoplasmic translation depends on the formation of t6A modification in position 37 of tRNANNU for efficient decoding of ANN codons. Defective protein homeostasis resulting from knockdown of OSGEP triggers accumulation of protein aggregates and the formation of stress granules. This disrupted codon-specific translation induces the activation of RIG-I and type I interferon response. Hence, t6A-deficient tumours prompt recruitment and activation of T-cells, affecting tumour growth. Finally, an OSGEP-driven gene signature in melanoma patients is predictive for T-cell infiltration and overall survival. Together, our results reveal t6A tRNA modification as a novel therapeutic target to fight melanoma.
This dataset
Open GSE286704 in finder → Find more mouse 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 GSE286704_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 PRJNA1209976 and SRA study SRP557069. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
3 × B16F10 shRNA Ctrl replicat vs 3 × B16F10 shRNA OSGEP#2 replicat

Supports a between-group comparison across 6 samples.

How we read this: 2 replicated groups read from 12 sample titles; they account for 6 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

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