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Updated: Aug 6, 2026
Multiplexed Immunofluorescence Analysis and Quantification of Intratumoral PD-1+ Tim-3+ CD8+ T Cells
Published on: February 8, 2018
Integrating Multiplexed Imaging and Multiscale Modeling Identifies Tumor Phenotype Transformation as a Critical
John W Hickey1,2, Eran Agmon3, Nina Horowitz3
1Department of Microbiology & Immunology, Stanford University School of Medicine, Stanford, CA 94305, USA.
Abstract:
Cancer progression is a complex process involving interactions that unfold across molecular, cellular, and tissue scales. These multiscale interactions have been difficult to measure and to simulate. Here we integrated CODEX multiplexed tissue imaging with multiscale modeling software, to model key action points that influence the outcome of T cell therapies with cancer. The initial phenotype of therapeutic T cells influences the ability of T cells to convert tumor cells to an inflammatory, anti-proliferative phenotype. This T cell phenotype could be preserved by structural reprogramming to facilitate continual tumor phenotype conversion and killing. One takeaway is that controlling the rate of cancer phenotype conversion is critical for control of tumor growth. The results suggest new design criteria and patient selection metrics for T cell therapies, call for a rethinking of T cell therapeutic implementation, and provide a foundation for synergistically integrating multiplexed imaging data with multiscale modeling of the cancer-immune interface.
Insights
Controlling cancer cell conversion is key for T cell therapy success. This study integrates imaging and modeling to optimize T cell therapies for better tumor control.
Area of Science:
- Cancer biology
- Immunotherapy
- Computational modeling
Background:
- Cancer progression involves complex multiscale interactions (molecular, cellular, tissue) that are challenging to measure and simulate.
- Understanding these interactions is crucial for developing effective T cell therapies against cancer.
Approach:
- Integrated CODEX multiplexed tissue imaging with multiscale modeling software.
- Modeled key action points influencing T cell therapy outcomes in cancer.
- Investigated the role of initial T cell phenotype in tumor cell conversion.
Key Points:
- Therapeutic T cell phenotype impacts their ability to convert tumor cells to an inflammatory, anti-proliferative state.
- Structural reprogramming can preserve T cell phenotype, facilitating continuous tumor conversion and killing.
- Controlling the rate of cancer phenotype conversion is critical for managing tumor growth.
Conclusions:
- Results suggest new design criteria and patient selection metrics for T cell therapies.
- Highlights the need for rethinking T cell therapeutic implementation strategies.
- Provides a foundation for integrating multiplexed imaging data with multiscale modeling of the cancer-immune interface.
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