Skip to content

azizilab/chemokine_receptor_reproducibility

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

4 Commits
 
 
 
 

Repository files navigation

chemokine_receptor_reproducibility

Chemokine Receptor Co-expression Analysis in External Clinical Melanoma Cohort scRNA-seq

Overview

This repository contains the data analysis code to validate findings in a study of chemokine receptor (CR) co-expression by CD8+ T cells in the setting of dual checkpoint blockade, in collaboration with Reshef Lab. Combined checkpoint inhibitors are transformative cancer therapies, but their efficacy is limited, and severe immune-related adverse events (IRAEs) are common. A central challenge is identifying T cells that effectively infiltrate and destroy tumors without causing off-target damage. Here, we show that the co-expression landscape of chemokine receptors CXCR3, CCR5, and CXCR6 on CD8+ T cells defines functionally distinct subsets with divergent roles in tumor immunity and off-target inflammation in both mice and humans.

Study Design

In a mouse model of melanoma treated with dual checkpoint blockade, a triple-positive (CXCR3+CCR5+CXCR6+) T-cell subset is essential for tumor control and its genetic signature correlates with response in patients. Conversely, a subset co-expressing CCR5 and CXCR6 (R6R5) is associated with migration to the liver, a site of IRAEs. This chemokine receptor "code" helps separate therapeutic efficacy from toxicity, providing a new framework for developing safer, more effective immunotherapies. We analyzed external scRNA-seq of CD8+ T cells from a clinical cohort of metastatic melanoma patients treated with immune checkpoint blockade (Pozniak Cell 2024; https://www.sciencedirect.com/science/article/pii/S0092867423013223) for co-expression of CR markers. After batch correction, we examine continuous phenotypic differentiation with respect to CR co-expression patterns using diffusion mapping and pseudotime calculation, and we compare CR expression and co-expression signature between cclinical groups using pseudobulked expression across samples.

Figures

  • Fig 1f: Diffusion maps of CD8+ T cell differentiation (TCF7, TOX) and CR marker expression (CCR7, CXCR3, CCR5, CXCR6)
  • Fig 1g: Pseudotemporal expression patterns of CR markers
  • Extended Data 2a: Pseudotime rank sorted expression of CR markers
  • Extended Data 2b: Sliding window expression of CR markers across pseudotime
  • Extended Data 2c: Distribution of sliding window normalized CR marker expression
  • Fig 4d: CR co-expression signature comparisons between ICB responders and non-responders (MWU test)
  • Extended Data 6d: CR marker expression comparisons between ICB responders and non-responders (MWU test)

Data Access

Data analyzed for this work is publically available as described in the original publication (Pozniak Cell 2024; https://www.sciencedirect.com/science/article/pii/S0092867423013223) under access code EGAD00001009291 in the European Genome-phenome Archive.

Acknowlegement

This work was made possible by the collaboration between the Azizi Lab and Reshef Lab, as well as our external collaborators.

Citation

About

No description, website, or topics provided.

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

 
 
 

Contributors