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Targeting tumor-intrinsic N7-methylguanosine tRNA modification inhibits MDSC recruitment and improves anti-PD-1 efficacy

GSE214631 Homo sapiens (human) DNA methylation 14 samples Submitted 2024/09/22 Platform GPL19057Platform GPL30209Platform GPL30215
At a glance

DNA methylation · human · 14 samples

What it is
DNA methylationChemical marks on DNA that help switch genes on or off.
Organism
Homo sapiens (human)
Samples
14 samples: 14 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.
Summary (written by the submitters)
We found that PMN-MDSCs level is elevated in the advanced ICCs tissues and is positively associated with the METTL1 and m7G tRNA modification levels. We further showed that impaired m7G tRNA modification impedes the PMN-MDSCs infiltration and inhibits ICC progression. Mechanistically, METTL1-mediated m7G tRNA modification selectively regulates the translation of human CXCL8 and mouse Cxcl5 transcripts, which facilitates the migration of PMN-MDSCs via binding to their cognate receptor CXCR2.
Read the full summary ↓
Co-blockade of METTL1 and CXCR2 significantly enhances the efficacy of anti-PD-1 treatment in ICC. Taken together, our study reveals the cellular and molecular basis of crosstalk between ICC cells and MDSCs in shaping TIME and affecting ICIs efficacy, which enables reasonable design of new combined therapy targeting dysregulated mRNA translation and suppressive TIME.
This dataset
Open GSE214631 in finder → Find more methylation 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 GSE214631_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: Look for beta-value tables or raw IDAT files among the supplementary files.

Also filed as BioProject PRJNA886424 and SRA study SRP400696. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
14 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 14 sample titles: 14 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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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.