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m6A Methylation Suppresses anti-tumour immune responses in Colorectal Cancers by Inhibiting Double-stranded RNA accumulation from Alu Repeats [RNA-Seq1]

GSE289971 Homo sapiens (human) DNA methylation 16 samples Submitted 2026/03/09 Platform GPL24676
At a glance

DNA methylation · human · 16 samples

What it is
DNA methylationChemical marks on DNA that help switch genes on or off.
Organism
Homo sapiens (human)
Samples
16 samples: 8 conditions, mostly in duplicateGroups 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(6)A modification suppresses innate anti-tumour immunity in colorectal cancer by limiting alu-derived dsRNA accumulationNature communications · 2026
Summary (written by the submitters)
How cancer cells evade immune detection despite expressing immunostimulatory retroelement (RE) transcripts remains an open question in tumour immunology. In cancer cells, endogenous REs that escape histone and DNA silencing are transcribed into RNA and can form double-stranded RNA (dsRNA), triggering innate immune responses through a process known as viral mimicry.
Read the full summary ↓
However, RNA-level checkpoints can limit this effect. Here, we identify the m6A RNA methyltransferase METTL3 as a key regulator of this suppression in colorectal cancer (CRC). Targeting METTL3 enhances the accumulation of dsRNA derived from both pre-existing and newly transcribed REs, thereby amplifying immunostimulatory signalling and activating cell-intrinsic anti-tumour immunity. Notably, CRCs exhibit differential sensitivity to METTL3 inhibition: tumours with high basal dsRNA levels and RNA methylation respond robustly to METTL3 blockade alone, whereas those with low endogenous dsRNA require combination therapy to achieve comparable immune activation. Co-treatment with DNA methyltransferase inhibitors (DNMTis) restores immune activation in these otherwise resistant tumours. Together, these findings uncover a novel mechanism by which METTL3 functions as an RNA-level immune checkpoint and suggest that combining METTL3 and DNMT inhibition may overcome resistance and serve as an effective therapeutic strategy in CRC.
Published in
m(6)A modification suppresses innate anti-tumour immunity in colorectal cancer by limiting alu-derived dsRNA accumulation
Wang Y, Daddi AA, Hosseini A et al. · Nature communications 2026 · PMID 42135281 · doi:10.1038/s41467-026-73211-z
This dataset
Open GSE289971 in finder → Find more human 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 GSE289971_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 PRJNA1225480 and SRA study SRP564862. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 42135281) ↗
Study design
8 conditions, mostly in duplicate
RNAseq_HT29_TGFP_MT ×2 RNAseq_HT29_TGFP_DAC ×2 RNAseq_HT29_METTL3KD1_MT ×2 RNAseq_HT29_METTL3KD1_DAC ×2 RNAseq_HCT116_TGFP_MT ×2 RNAseq_HCT116_TGFP_DAC ×2 RNAseq_HCT116_METTL3KD1_MT ×2 RNAseq_HCT116_METTL3KD1_DAC ×2

Supports a between-group comparison across 16 samples.

How we read this: 8 replicated groups read from 16 sample titles; they account for 16 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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