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.

中文翻译：

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整合多重成像和多尺度建模确定肿瘤表型转换是治疗性 T 细胞功效的关键组成部分

癌症进展是一个复杂的过程，涉及分子、细胞和组织尺度上的相互作用。这些多尺度相互作用很难测量和模拟。在这里，我们将 CODEX 多重组织成像与多尺度建模软件集成，以对影响癌症 T 细胞治疗结果的关键作用点进行建模。治疗性 T 细胞的初始表型影响 T 细胞将肿瘤细胞转化为炎症、抗增殖表型的能力。这种 T 细胞表型可以通过结构重编程来保留，以促进持续的肿瘤表型转换和杀伤。一个要点是控制癌症表型转换的速度对于控制肿瘤生长至关重要。结果提出了 T 细胞疗法的新设计标准和患者选择指标，呼吁重新思考 T 细胞治疗的实施，并为将多重成像数据与癌症免疫界面的多尺度建模协同整合奠定了基础。补充信息中包含了本文透明同行评审过程的记录。