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Updated: Dec 25, 2025

Tumor Transplantation for Assessing the Dynamics of Tumor-Infiltrating CD8+ T Cells in Mice
Published on: June 12, 2021
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.
Abstract:
Direct quantification of exhausted T cells in human cancer is lacking, and its predictive value for checkpoint-based treatment remains poorly investigated. We sought to systematically characterize the pan-cancer landscape and molecular hallmarks of T-cell dysfunction for the purpose of precision immunotherapy. Here, we defined a transcriptional signature for T-cell exhaustion through analyzing differential gene expression between PD-1-high and PD-1-negative CD8+ T lymphocytes from primary non-small cell lung cancer (NSCLC), followed by positive correlation tests with PDCD1 in TCGA lung carcinomas. A 78-gene signature for exhausted CD8+ T cells (GET) was identified and validated to reflect dysfunctional immune state spanning different species and disease models. We discovered that GET estimation significantly correlated with intratumoral immune cytolytic activity (CYT) and T-cell-inflamed gene expression profile (GEP) across 30 solid tumor types. Miscellaneous tumor-intrinsic and -extrinsic properties, in particular leukocyte proportions, genomic abnormalities, specific mutational signatures, and signaling pathways, were notably associated with GET levels. Furthermore, higher GET expression predicted an increased likelihood of clinical response to immune checkpoint inhibitors. These findings highlight the interrelation between T-cell exhaustion and immune cytolytic activity at the pan-cancer scale. The resulting inflamed tumor microenvironment may further crosstalk with other molecular and clinicopathological factors, which should be properly considered during immunotherapy biomarker development. © 2020 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.
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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