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Proximity-dependent labeling identifies dendritic cells that prime the antitumor CD4+ T cell response

GSE275471 Mus musculus (mouse) Single-cell RNA-seq 857 samples Submitted 2024/10/04 Platform GPL19057
At a glance

Single-cell RNA-seq · mouse · 857 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
Organism
Mus musculus (mouse)
Samples
857 samples: 400 × Smartseq2_Lipstic_TdLNGroups 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
Proximity-dependent labeling identifies dendritic cells that drive the tumor-specific CD4(+) T cell responseScience immunology · 2024
Summary (written by the submitters)
Dendritic cells (DCs) are uniquely capable of transporting tumoral antigens to tumor-draining lymph nodes (tdLNs), and also interact with effector T cells within the tumors themselves, mediating both natural antitumor immunity and the response to checkpoint blockade immunotherapy. Using LIPSTIC (Labeling Immune Partnerships by SorTagging Intercellular Contacts)-based single-cell transcriptomics, we identify individual DCs capable of presenting antigen to CD4+ T cells in the tdLN as well as inside tumors.
Read the full summary ↓
These represent only a fraction of all DCs present and display a distinctive activated phenotype that in the LN includes production of cytokine IL-27, required for efficient T cell priming and tumor rejection. Tumor progression results in loss of effective priming of naïve CD4+ T cells, downstream of transcriptional changes in DCs that are manifested already when they arrive at the tdLN, which can be rescued by CTLA4 checkpoint blockade.
Published in
Proximity-dependent labeling identifies dendritic cells that drive the tumor-specific CD4(+) T cell response
Chudnovskiy A, Castro TBR, Nakandakari-Higa S et al. · Science immunology 2024 · PMID 39365874 · doi:10.1126/sciimmunol.adq8843
This dataset
Open GSE275471 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 GSE275471_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA1151000 and SRA study SRP528116. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39365874) ↗
Study design
400 × Smartseq2_Lipstic_TdLN

Supports a between-group comparison across 400 samples.

How we read this: 1 replicated groups read from the first 400 of 857 sample titles; they account for 400 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

+ 817 more — browse all 857 samples with per-sample file links →

Datasets on a similar topic

Search all mouse RNA-seq datasets in GEO →

Share this dataset

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