GEO series

KRAS mutations reprogram RNA m6A modification to drive CD73-dependent immune evasion in colorectal cancer [ChIP-seq]

GSE311797 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 11 samples Submitted 2026/07/25 Platform GPL24676

At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 11 samples

What it is: ChIP-seq / ATAC-seq (genome binding and open chromatin)Where proteins bind the genome, or which regions are open and active.
Organism: Homo sapiens (human)
Topic: Colorectal cancerThis series is part of our curated briefing on it.
Samples: 11 samples: 3 × SW48(G12D/+), ChIP (METTL3), vs 3 × SW48(G12D/+), ChIP (TEAD4), vs 3 × SW48(WT), ChIP (TEAD4),Groups 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)

KRAS mutations, present in about 40% of colorectal cancers (CRCs), are strongly associated with an immunosuppressive tumor microenvironment characterized by restricted immune infiltration and poor responses to immunotherapy. Here, we show that KRAS mutations remodel the m6A epitranscriptome to promote immune evasion. Methylated RNA-immunoprecipitation sequencing of isogenic CRC cells revealed that KRAS-mutant cells exhibit increased N6-methyladenosine (m6A) deposition on CD73 mRNAs, enhancing the stability of the transcripts by promoting interaction with IGF2BP3.

Read the full summary ↓

This m6A modification was driven by TEAD4-dependent recruitment of the METTL3 methyltransferase complex, identifying TEAD4 as a spatial regulator of m6A deposition. Functionally, METTL3 knockdown in KRAS-mutant syngeneic tumors suppressed tumor growth and restored antitumor immunity by increasing CD8⁺ T-cell and natural killer (NK)–cell infiltration in a CD73-dependent manner. Moreover, METTL3 inhibition synergized with anti-PD-1 therapy and a CD73 inhibitor to reduce tumor burden. Together, these findings demonstrate that KRAS-driven m6A remodeling is a key mechanism of immune suppression in CRC and highlight METTL3 as a promising therapeutic target.

This dataset

Open GSE311797 in finder → Find more human ChIP / ATAC / CUT&Tag datasets → Colorectal cancer landscape →

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 GSE311797_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 peak files (.bed, .narrowPeak) and signal tracks (.bigWig) among the supplementary files; the raw reads are on ENA.

Also filed as BioProject PRJNA1370922 and SRA study SRP649724. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

3 × SW48(G12D/+), ChIP (METTL3), vs 3 × SW48(G12D/+), ChIP (TEAD4), vs 3 × SW48(WT), ChIP (TEAD4),

Supports a between-group comparison across 9 samples.

How we read this: 3 replicated groups read from 11 sample titles; they account for 9 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

GSM9332295 SW48(G12D/+), ChIP (METTL3), rep 1 SW48(G12D/+), ChIP (MET…
GSM9332296 SW48(G12D/+), ChIP (METTL3), rep 2 SW48(G12D/+), ChIP (MET…
GSM9332297 SW48(G12D/+), ChIP (METTL3), rep 3 SW48(G12D/+), ChIP (MET…
GSM9332298 SW48(G12D/+), ChIP (TEAD4), rep 1 SW48(G12D/+), ChIP (TEA…
GSM9332299 SW48(G12D/+), ChIP (TEAD4), rep 2 SW48(G12D/+), ChIP (TEA…
GSM9332300 SW48(G12D/+), ChIP (TEAD4), rep 3 SW48(G12D/+), ChIP (TEA…
GSM9332301 SW48(G12D/+), Input
GSM9777098 SW48(WT), ChIP (TEAD4), rep 1 SW48(WT), ChIP (TEAD4),
GSM9777099 SW48(WT), ChIP (TEAD4), rep 2 SW48(WT), ChIP (TEAD4),
GSM9777100 SW48(WT), ChIP (TEAD4), rep 3 SW48(WT), ChIP (TEAD4),
GSM9777101 SW48(WT), Input

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