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Inhibiting CXCR4 Attenuates TOX-Programmed Exhausted Phenotype of CD8+ T cells via Regulating JAK2/STAT3 Pathway [RNA-Seq]

GSE255180 Mus musculus (mouse) Single-cell RNA-seq 20 samples Submitted 2025/01/28 Platform GPL24247
At a glance

Single-cell RNA-seq · mouse · 20 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
20 samples: 5 × Solution, replication vs 5 × Plerixafor, replication vs 5 × anti-PD-1, replication vs 5 × Combination, replicationGroups 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
CXCR4 orchestrates the TOX-programmed exhausted phenotype of CD8(+) T cells via JAK2/STAT3 pathwayCell genomics · 2024
Summary (written by the submitters)
T-cell exhaustion (Tex) phenotype has limited the efficacy of single-agent immune checkpoint blockade (ICB) in cancer immunotherapy, underscoring the need to target upstream pathways. Clinical trials have indicated that CXCR4 antagonists enhance anti-cancer activity. However, the specific mechanisms through which CXCR4 contributes to immune cell phenotypes are not fully understood.
Read the full summary ↓
By targeting CXCR4 using antagonists or transgenic mice (Cxcr4flox/flox LckCre), we effectively attenuated the Tex phenotype and enhanced the functional T-cell phenotype in vivo. Additionally, single-cell RNA/TCR-seq analyses demonstrated that CXCR4 inhibition promotes anti-PD-1 immunotherapy by reducing CD8+ Tex phenotype and enriching the abundance of TCR clonotypes in vivo. Mechanically, we found that CXCR4-blocking T cells mitigate Tex phenotype by regulating the JAK2-STAT3 pathway, reducing the interaction between p-STAT3 and TOX. Single-cell ATAC/RNA-seq validated that CXCR4 deficiency epigenetically orchestrates the transition from functional to exhausted phenotypes in CD8+ T cells. Altogether, we demonstrate a mechanism of targeting CXCR4 to orchestrate CD8+ Tex cells in cancers and provide a rationale for the combined CXCR4 antagonists and ICBs in clinical trials.
Published in
CXCR4 orchestrates the TOX-programmed exhausted phenotype of CD8(+) T cells via JAK2/STAT3 pathway
Cao C, Xu M, Wei Y et al. · Cell genomics 2024 · PMID 39317187 · doi:10.1016/j.xgen.2024.100659
This dataset
Open GSE255180 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 GSE255180_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 PRJNA1073902 and SRA study SRP488486. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39317187) ↗
Study design
5 × Solution, replication vs 5 × Plerixafor, replication vs 5 × anti-PD-1, replication vs 5 × Combination, replication

Supports a between-group comparison across 20 samples.

How we read this: 4 replicated groups read from 20 sample titles; they account for 20 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
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