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Reproducible single-cell annotation of programs underlying T cell subsets, activation states and functions.

Dylan Kotliar1,2,3,4,5, Michelle Curtis1,2,3,4, Ryan Agnew1,2,3,4

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Summary

This study introduces T-CellAnnoTator (TCAT), a new computational tool for detailed T cell analysis. TCAT characterizes T cell states and functions, aiding in predicting responses to cancer immunotherapies.

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Area of Science:

  • Immunology
  • Computational Biology
  • Genomics

Background:

  • T cells orchestrate immune responses through specialized gene expression programs (GEPs).
  • Traditional T cell subset classification (e.g., TH1, TH2, TH17) is challenged by single-cell data revealing a continuum of states.
  • Novel analytical frameworks are needed to accurately characterize diverse T cell populations.

Purpose of the Study:

  • To develop and validate T-CellAnnoTator (TCAT), a computational pipeline for comprehensive T cell characterization.
  • To identify and quantify reproducible gene expression programs (GEPs) associated with T cell functions and states.
  • To assess the utility of TCAT in predicting clinical outcomes, such as response to immune checkpoint inhibitors.

Main Methods:

  • Development of the T-CellAnnoTator (TCAT) pipeline for simultaneous quantification of predefined GEPs.
  • Analysis of a large-scale dataset comprising 1.7 million T cells from 700 individuals across diverse tissues and disease contexts.
  • Experimental validation of identified T cell activation programs.

Main Results:

  • Identification of 46 reproducible GEPs reflecting core T cell functions (e.g., proliferation, cytotoxicity, exhaustion, effector states).
  • Demonstration of novel T cell activation programs.
  • TCAT successfully characterized activation GEPs that predict immune checkpoint inhibitor response in multiple tumor types.
  • The generalized framework, starCAT, enables reproducible annotation in other cell types and tissues.

Conclusions:

  • TCAT provides an advanced analytical framework for precise T cell characterization, moving beyond traditional subset definitions.
  • The identified GEPs offer insights into T cell heterogeneity and function across various biological contexts.
  • TCAT and starCAT are valuable tools for advancing immunological research and precision medicine, particularly in predicting immunotherapy response.