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Ms4a7 expression in cDC1s determines cross-presentation and anti-tumor immunity

GSE255477 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 40 samples Submitted 2025/11/30 Platform GPL24247
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 40 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
40 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)
Type 1 conventional dendritic cells (cDC1s) capture antigens in peripheral tissues and migrate to draining lymph nodes (dLNs) to prime antigen-specific CD8+ T cells. How tumor antigens are processed for activating CD8+ T cell immunity are not well understood. Here, we found that Ms4a7 was selectively expressed in cDC1s after engulfing tumor antigens or exposed to exogenous antigens, and required for their cross-priming ability and migration to dLNs.
Read the full summary ↓
Ms4a7-/- mice showed normal cDC1 development and turnover but failed to prime antigen-specific CD8+ T cells after infection or tumor development. In human cancers, MS4A7 specifically expressed in a subset of cDC1s which preferentially enriched in dLNs, playing a crucial role in patient survival. Our findings reveal a critical role of Ms4a7 in cDC1 migration, cross-presentation and anti-tumor CD8+ T cell responses.
This dataset
Open GSE255477 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 GSE255477_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 PRJNA1075093 and SRA study SRP489153. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
20 conditions, mostly in duplicate
dLN GFP-nAPCs ×2 dLN GFP-cDCs ×2 dLN GFP+nAPCs ×2 dLN GFP+cDCs ×2 TME GFP-nAPCs ×2 TME GFP-cDCs ×2 TME GFP+nAPCs ×2 TME GFP+cDCs ×2 +12 more

Supports a between-group comparison across 40 samples.

How we read this: 20 replicated groups read from 40 sample titles; they account for 40 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
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.