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Hickey JW, Agmon E, Horowitz N, Tan TK, Lamore M, Sunwoo JB, Covert MW, Nolan GP. Integrating multiplexed imaging and multiscale modeling identifies tumor phenotype conversion as a critical component of therapeutic T cell efficacy. Cell Syst 2024; 15:322-338.e5. [PMID: 38636457 PMCID: PMC11030795 DOI: 10.1016/j.cels.2024.03.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2022] [Revised: 03/07/2023] [Accepted: 03/19/2024] [Indexed: 04/20/2024]
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.
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Affiliation(s)
- John W Hickey
- 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
| | - Eran Agmon
- Department of Bioengineering, Stanford University, Stanford, CA 94305, USA; Center for Cell Analysis and Modeling, University of Connecticut Health, Farmington, CT 06032, USA
| | - Nina Horowitz
- Department of Bioengineering, Stanford University, Stanford, CA 94305, USA
| | - Tze-Kai Tan
- 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
| | - Matthew Lamore
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21205, USA
| | - John B Sunwoo
- 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
| | - Markus W Covert
- Department of Bioengineering, Stanford University, Stanford, CA 94305, USA.
| | - Garry P Nolan
- Department of Pathology, Stanford University School of Medicine, Stanford, CA 94305, USA.
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Hickey JW, Agmon E, Horowitz N, Lamore M, Sunwoo J, Covert M, Nolan GP. Integrating Multiplexed Imaging and Multiscale Modeling Identifies Tumor Phenotype Transformation as a Critical Component of Therapeutic T Cell Efficacy. bioRxiv 2023:2023.12.06.570168. [PMID: 38106218 PMCID: PMC10723382 DOI: 10.1101/2023.12.06.570168] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/19/2023]
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.
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Affiliation(s)
- John W. Hickey
- 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
| | - Eran Agmon
- Department of Bioengineering, Stanford University, Stanford, CA 94305, USA
| | - Nina Horowitz
- Department of Bioengineering, Stanford University, Stanford, CA 94305, USA
| | - Matthew Lamore
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21205, USA
| | - John Sunwoo
- Department of Otolaryngology, Head and Neck Surgery, Stanford Cancer Institute, Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, CA 94305
| | - Markus Covert
- Department of Bioengineering, Stanford University, Stanford, CA 94305, USA
| | - Garry P. Nolan
- Department of Pathology, Stanford University School of Medicine, Stanford, CA 94305, USA
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Bhate SS, Barlow GL, Schürch CM, Nolan GP. Tissue schematics map the specialization of immune tissue motifs and their appropriation by tumors. Cell Syst 2021; 13:109-130.e6. [PMID: 34653369 DOI: 10.1016/j.cels.2021.09.012] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2020] [Revised: 05/28/2021] [Accepted: 09/22/2021] [Indexed: 12/31/2022]
Abstract
A schematic of a biological system, i.e., a representation of its pieces, how they are combined, and what they do, would facilitate understanding its essential organization and alteration in pathogenesis or evolution. We present a computational approach for constructing tissue schematics (TSs) from high-parameter imaging data and a biological model for interpreting them. TSs map the spatial assembly of cellular neighborhoods into tissue motifs, whose modular composition, we propose, enables the generation of complex outputs. We developed our approach in human lymphoid tissue (HLT), identifying the follicular outer zone as a potential relay between neighboring zones and a core lymphoid assembly with modifications characteristic of each HLT type. Applying the TS approach to the tumor microenvironment in human colorectal cancer identified a higher-order motif, whose mutated assembly was negatively associated with patient survival. TSs may therefore elucidate how immune architectures can be specialized and become vulnerable to reprogramming by tumors.
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Affiliation(s)
- Salil S Bhate
- Department of Microbiology and Immunology, Stanford University School of Medicine, Stanford University, Stanford, CA 94305, USA; Department of Pathology, Stanford University School of Medicine, Stanford University, Stanford, CA 94305, USA; Department of Bioengineering, Stanford University Schools of Medicine and Engineering, Stanford University, Stanford, CA 94305, USA
| | - Graham L Barlow
- Department of Microbiology and Immunology, Stanford University School of Medicine, Stanford University, Stanford, CA 94305, USA; Department of Pathology, Stanford University School of Medicine, Stanford University, Stanford, CA 94305, USA; Program in Immunology, Stanford University School of Medicine, Stanford University, Stanford, CA 94305, USA
| | - Christian M Schürch
- Department of Microbiology and Immunology, Stanford University School of Medicine, Stanford University, Stanford, CA 94305, USA; Department of Pathology, Stanford University School of Medicine, Stanford University, Stanford, CA 94305, USA; Department of Pathology and Neuropathology, University Hospital and Comprehensive Cancer Center Tübingen, Tübingen, Germany
| | - Garry P Nolan
- Department of Microbiology and Immunology, Stanford University School of Medicine, Stanford University, Stanford, CA 94305, USA; Department of Pathology, Stanford University School of Medicine, Stanford University, Stanford, CA 94305, USA.
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