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Modeling T cell temporal response to cancer immunotherapy rationalize development of combinatorial treatments protocols

GSE249630 Mus musculus (mouse) Single-cell RNA-seq 1372 samples Submitted 2024/03/01 Platform GPL24247Platform GPL19057
At a glance

Single-cell RNA-seq · mouse · 1372 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
1372 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
Modeling T cell temporal response to cancer immunotherapy rationalizes development of combinatorial treatment protocolsNature cancer · 2024
Summary (written by the submitters)
Successful immunotherapy relies on triggering complex responses involving T-cells dynamics in tumors and the periphery. Characterizing these responses remains challenging using static human single-cell atlases or mouse models. To address this, we developed a framework for in vivo tracking of tumor-specific CD8+ T cells over time and at single-cell resolution.
Read the full summary ↓
Our tools facilitate the modeling of gene program dynamics in the tumor microenvironment (TME) and tumor-draining lymph node (tdLN). Using this approach, we characterize two modes of anti-PD1 (aPD1) activity, decoupling induced differentiation of tumor-specific activated precursor cells from cDC1-dependent proliferation and recruitment to the TME. We demonstrate that combining aPD1 with anti-4-1BB agonist enhances the recruitment and proliferation of activated precursors resulting in tumor control. These data suggest that effective response to aPD1 therapy is dependent on sufficient influx of activated precursor CD8+ cells to the TME, and highlight the importance of understanding system-level dynamics in optimizing immunotherapies.
Published in
Modeling T cell temporal response to cancer immunotherapy rationalizes development of combinatorial treatment protocols
Barboy O, Bercovich A, Li H et al. · Nature cancer 2024 · PMID 38429414 · doi:10.1038/s43018-024-00734-z
This dataset
Open GSE249630 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 GSE249630_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 PRJNA1049846 and SRA study SRP476542. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 38429414) ↗
Study design
A cohort of 1372 individual samples

The grouping that defines any comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Sample titles run AB10120 … AB13981 and carry no group information.

Samples in this study

+ 1332 more — browse all 1372 samples with per-sample file links →

Datasets on a similar topic

Search all mouse RNA-seq datasets in GEO →

Share this dataset

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.