Integrating multiplexed imaging and multiscale modeling identifies tumor phenotype conversion as a critical component of therapeutic T cell efficacy

John W Hickey; Eran Agmon; Nina Horowitz; Tze-Kai Tan; Matthew Lamore; John B Sunwoo; Markus W Covert; Garry P Nolan

doi:10.1016/j.cels.2024.03.004

Integrating multiplexed imaging and multiscale modeling identifies tumor phenotype conversion as a critical component of therapeutic T cell efficacy

Cell Syst. 2024 Apr 17;15(4):322-338.e5. doi: 10.1016/j.cels.2024.03.004.

Authors

John W Hickey¹, Eran Agmon², Nina Horowitz³, Tze-Kai Tan⁴, Matthew Lamore⁵, John B Sunwoo⁶, Markus W Covert⁷, Garry P Nolan⁸

Affiliations

¹ Department of Microbiology & Immunology, Stanford University School of Medicine, Stanford, CA 94305, USA; Department of Pathology, Stanford University School of Medicine, Stanford, CA 94305, USA; Department of Biomedical Engineering, Duke University, Durham, NC 27708, USA.
² Department of Bioengineering, Stanford University, Stanford, CA 94305, USA; Center for Cell Analysis and Modeling, University of Connecticut Health, Farmington, CT 06032, USA.
³ Department of Bioengineering, Stanford University, Stanford, CA 94305, USA.
⁴ Department of Pathology, Stanford University School of Medicine, Stanford, CA 94305, USA; Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA.
⁵ Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21205, USA.
⁶ Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA; Department of Otolaryngology, Head and Neck Surgery, Stanford Cancer Institute Stanford University School of Medicine, Stanford, CA 94305, USA.
⁷ Department of Bioengineering, Stanford University, Stanford, CA 94305, USA. Electronic address: [email protected].
⁸ Department of Pathology, Stanford University School of Medicine, Stanford, CA 94305, USA. Electronic address: [email protected].

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. A record of this paper's transparent peer review process is included in the supplemental information.

Keywords: T cells; agent-based modeling; cellular therapy; computational analysis of tissue imaging data; immunotherapy; multiplexed tissue imaging; multiscale modeling; spatial biology; systems biology; tumor cell phenotype.

MeSH terms

Humans
Neoplasms* / pathology
Neoplasms* / therapy
Phenotype
T-Lymphocytes

Abstract

MeSH terms

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