T-cell exhaustion interrelates with immune cytolytic activity to shape the inflamed tumor microenvironment

Mei-Chun Cai1, Xiaojing Zhao2, Min Cao2

  • 1State Key Laboratory of Oncogenes and Related Genes, Shanghai Cancer Institute, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, PR China.

Insights

Directly quantifying exhausted T cells in cancer is crucial for predicting immunotherapy response. This study identifies a 78-gene signature (GET) for exhausted T cells, correlating with treatment outcomes and tumor microenvironment characteristics.

Area of Science:

  • Immunology
  • Oncology
  • Genomics

Background:

  • Direct quantification of exhausted T cells in human cancers is limited.
  • The predictive value of T-cell exhaustion for checkpoint inhibitor therapy is poorly understood.
  • A pan-cancer characterization of T-cell dysfunction is needed for precision immunotherapy.

Purpose of the Study:

  • To define a transcriptional signature for T-cell exhaustion.
  • To investigate the pan-cancer landscape and molecular hallmarks of T-cell dysfunction.
  • To assess the predictive value of T-cell exhaustion for immunotherapy response.

Main Methods:

  • Differential gene expression analysis between PD-1-high and PD-1-negative CD8+ T cells in NSCLC.
  • Validation of a 78-gene exhausted CD8+ T cell (GET) signature across species and disease models.
  • Correlation analysis of GET with intratumoral immune cytolytic activity (CYT), T-cell-inflamed gene expression profile (GEP), and tumor properties in 30 solid tumor types.

Main Results:

  • A 78-gene signature (GET) for exhausted CD8+ T cells was identified and validated.
  • GET estimation correlated significantly with CYT and T-cell-inflamed GEP across 30 tumor types.
  • Higher GET expression predicted increased clinical response to immune checkpoint inhibitors.

Conclusions:

  • T-cell exhaustion is interconnected with immune cytolytic activity on a pan-cancer scale.
  • Tumor-intrinsic and -extrinsic properties are associated with T-cell exhaustion levels.
  • The GET signature holds potential as a biomarker for immunotherapy response prediction.

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