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m1A inhibition fuels oncolytic virus-elicited antitumor immunity via downregulating PD-L1 expression

GSE247024 Homo sapiens (human) RNA-seq (gene expression) 18 samples Submitted 2024/03/31 Platform GPL29480
At a glance

RNA-seq (gene expression) · human · 18 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
Homo sapiens (human)
Samples
18 samples: 6 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
m(1)A inhibition fuels oncolytic virus-elicited antitumor immunity via downregulating MYC/PD-L1 signalingInternational journal of oral science · 2024
Summary (written by the submitters)
RNA N1-methyladenosine methylation (m1A) modification is critical in regulating mRNA translation and thus protein synthesis, but the role of m1A modification in the occurrence, progression, and immunotherapy of head and neck squamous cell cancer (HNSCC) remains largely unknown. In Tgfbr1/Pten 2cKO mice, we found that the spontaneous neoplastic transformation of oral mucosa is accompanied by elevated levels of m1A modification.
Read the full summary ↓
Analysis of m1A-associated genes identified TRMT61A as the key m1A writer associated with cancer progression, and poor prognosis. Mechanically, TRMT61A-induced tRNA-m1A modification promotes MYC protein synthesis and subsequent programmed death-ligand 1 (PD-L1) expression. In Tgfbr1/Pten 2cKO mice, RNA-m1A modification levels are also elevated in tumors that developed resistance to oncolytic herpes simplex virus (oHSV) treatment. Therapeutic inhibition of m1A modification sustains oncolytic virus-induced antitumor immunity and reduces tumor growth, providing a promising strategy for alleviating resistance to oHSV therapy. These findings indicate that m1A inhibition can prevent immune escape after oHSV therapy by reducing the expression of PD-L1. Our results provide a mutually reinforcing strategy for clinical combination immunotherapy.
Published in
m(1)A inhibition fuels oncolytic virus-elicited antitumor immunity via downregulating MYC/PD-L1 signaling
Li S, Feng T, Liu Y et al. · International journal of oral science 2024 · PMID 38730256 · doi:10.1038/s41368-024-00304-0
This dataset
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.

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 GSE247024_RAW.tar (it can run to tens of gigabytes).

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.

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 PRJNA1035770 and SRA study SRP470182. Searching any of these in the dataset finder brings you back here.

Study design
6 conditions, mostly in triplicate
CAL-27, shCtrl, PBS, ×3 CAL-27, sh61A, PBS, ×3 CAL-27, shCtrl, IFNγ, ×3 CAL-27, sh61A, IFNγ, ×3 WSU-HN6, shCtrl, ×3 WSU-HN6, sh61A, ×3

Supports a between-group comparison across 18 samples.

How we read this: 6 replicated groups read from 18 sample titles; they account for 18 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
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