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The CARM1 Epigenetic Enzyme Inhibits Cross-presenting Dendritic Cell Function in Cancer Immunity [multiome]

GSE300019 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 8 samples Submitted 2026/06/30 Platform GPL24247
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 8 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
8 samples: 8 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)
The cancer-immunity cycle requires cross-presenting dendritic cells (cDC1) that induce T cell-mediated immunity, but therapeutic strategies for enhancing intratumoral cDC1 function are inadequate. We discovered the epigenetic enzyme Carm1 as a selective negative regulator of cancer antigen presentation by cDC1s, but not cDC2s. Carm1 inactivation promoted cDC1 antigen cross-presentation, activation, and accumulation in tumors; and a Carm1 inhibitor enhanced cDC1-mediated priming of T cells by a cancer vaccine.
Read the full summary ↓
Carm1 inhibition increased chromatin accessibility at BATF3-JUN and RELA sites critical for cDC1 function and activation. Carm1 expression was regulated by TGF-beta, explaining why Carm1 inactivation enhanced intratumoral cDC1 function without altering cDC1 homeostasis. These studies identify Carm1 as a therapeutic target for enhancing the anti-tumor function of murine and human cDC1.
This dataset
Open GSE300019 in finder → Find more mouse ChIP / ATAC / CUT&Tag 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 GSE300019_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 PRJNA1278715 and SRA study SRP592733. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
8 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 8 sample titles: 8 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

Search all mouse ChIP / ATAC / CUT&Tag 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.