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Distinct histone 3 lysine methylation states underlie tumor immune surveillance

GSE341379 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 50 samples Submitted 2026/07/27 Platform GPL30172
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 50 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
Mus musculus (mouse)
Samples
50 samples: 20 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.
Summary (written by the submitters)
Mutations in histone 3 at or near lysine 36 (H3K36) have dominantly acting oncogenic effects in multiple tumor types by limiting H3K36-directed methyltransferases. Paradoxically, we find that expression of the H3K36M oncohistone unexpectedly inhibits tumor formation in KRAS-driven lung adenocarcinoma by inducing a potent immune-mediated tumor clearance.
Read the full summary ↓
Mechanistically, oncohistone expression derepresses endogenous retroviral element transcription, results in the accumulation of double-stranded RNA (dsRNA), and activates an innate antiviral-like immune response that eradicates tumor growth. Surprisingly, while inactivation of the H3K36 di-methyltransferase NSD2 replicated all effects of oncohistone expression, inactivation of the H3K36 tri-methyltransferase SETD2 abolished element derepression and all associated downstream anti-cancer effects that are induced by oncohistone expression. These observations restructure our understanding of the roles of H3K36 methylation, the consequences of its deregulation in cancer, and shape our expectations for therapeutic interventions targeting H3K36 methyltransferases.
This dataset
Open GSE341379 in finder → Find more mouse 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 GSE341379_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 PRJNA1266719 and SRA study SRP636349. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
20 conditions, mostly in duplicate
mouse lung adenocarcinoma cell line, KP-Ctrl,… ×3 mouse lung adenocarcinoma cell line, KP-Setd2… ×3 mouse lung adenocarcinoma cell line, KP-H3K36… ×3 mouse lung adenocarcinoma cell line, KP-H3K36… ×3 mouse lung adenocarcinoma cell line, KP-Setd2… ×3 mouse lung adenocarcinoma cell line, KP-H3K36… ×3 mouse lung adenocarcinoma cell line, KP-H3K36… ×3 KP-Ctrl, H3K36me2, biol ×2 +15 more

Supports a case/control comparison: 12 samples read as cases, 13 as controls.

How we read this: 20 replicated groups read from 50 sample titles; they account for 47 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

+ 10 more — browse all 50 samples with per-sample file links →

Datasets on a similar topic

Search all mouse RNA-seq datasets in GEO →

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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.