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Single cell analysis of splenic control and ICOS deficient P14 cells from LCMV chronically infected mice

GSE270606 Mus musculus (mouse) Single-cell RNA-seq 2 samples Submitted 2025/07/07 Platform GPL24247
At a glance

Single-cell RNA-seq · mouse · 2 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
Organism
Mus musculus (mouse)
Samples
2 samples
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
The costimulatory molecule ICOS limits memory-like properties and function of exhausted PD-1(+)CD8(+) T cellsImmunity · 2025
Summary (written by the submitters)
During persistent antigen stimulation, PD-1+CD8 T cells are maintained by progenitor exhausted PD-1+TCF-1+CD8 T cells (Tpex). Tpex respond to PD-1 blockade, and regulation of Tpex differentiation into more functional Tex is of major interest for cancer immunotherapies. Tpex express high levels of Inducible T-cell Costimulator (ICOS), but the role of ICOS for PD-1+CD8 T cell responses has not been addressed.
Read the full summary ↓
In chronic infection, ICOS-deficiency increased both number and quality of virus-specific CD8 T cells, with accumulation of effector-like Tex due to enhanced survival. Mechanistically, loss of ICOS signaling potentiated FoxO1 activity and memory features of Tpex. In mice with established chronic infection, ICOS-Ligand blockade resulted in expansion of effector-like Tex and reduction in viral load. In a mouse model of hepatocellular carcinoma, ICOS inhibition improved cytokine production by tumor-specific PD-1+CD8 T cells and delayed tumor growth. Overall, we show that ICOS constrains CD8 T cell responses during chronic antigen exposure.
Published in
The costimulatory molecule ICOS limits memory-like properties and function of exhausted PD-1(+)CD8(+) T cells
Humblin E, Korpas I, Prokhnevska N et al. · Immunity 2025 · PMID 40628269 · doi:10.1016/j.immuni.2025.06.001
This dataset
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.

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 GSE270606_RAW.tar (it can run to tens of gigabytes).

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.

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 PRJNA1127558 and SRA study SRP515804. Searching any of these in the dataset finder brings you back here.

Samples in this study

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