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Rethinking cancer targeting strategies in the era of smart cell therapeutics

Abstract

In the past several decades, the development of cancer therapeutics has largely focused on precision targeting of single cancer-associated molecules. Despite great advances, such targeted therapies still show incomplete precision and the eventual development of resistance due to target heterogeneity or mutation. However, the recent development of cell-based therapies such as chimeric antigen receptor (CAR) T cells presents a revolutionary opportunity to reframe strategies for targeting cancers. Immune cells equipped with synthetic circuits are essentially living computers that can be programmed to recognize tumours based on multiple signals, including both tumour cell-intrinsic and microenvironmental. Moreover, cells can be programmed to launch broad but highly localized therapeutic responses that can limit the potential for escape while still maintaining high precision. Although these emerging smart cell engineering capabilities have yet to be fully implemented in the clinic, we argue here that they will become much more powerful when combined with machine learning analysis of genomic data, which can guide the design of therapeutic recognition programs that are the most discriminatory and actionable. The merging of cancer analytics and synthetic biology could lead to nuanced paradigms of tumour recognition, more akin to facial recognition, that have the ability to more effectively address the complex challenges of treating cancer.

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Fig. 1: Facial recognition as inspiration for smarter tumour recognition.
Fig. 2: Emerging capabilities of engineering multi-antigen recognition circuits in CAR T cells.
Fig. 3: Computational analysis of tumour profiling data to identify optimal tumour versus normal tissue discrimination circuits.
Fig. 4: Navigating precision and robustness to escape using nuanced combinatorial recognition circuits.

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Acknowledgements

The authors acknowledge O. Troyanskaya and H. Okada (and their groups) who have played key roles in the development of ideas presented in this manuscript. They also thank current and past members of the Lim Lab and the UCSF Cell Design Institute. The work in the authors’ laboratories is supported by the following grants: NIH/NCI U54CA244438 (W.A.L.), NIH/NCI R01CA258789 (W.A.L.), NIH/NCI R01CA249018 (W.A.L.) and NIH/NCI K08CA259610 (G.M.A.). Research by the authors reported in this publication was supported by the National Cancer Institute of the National Institutes of Health under the aformentioned award numbers. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

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W.A.L holds equity in Gilead and Intellia, is an adviser for Allogene Therapeutics and has filed patents related to this work. G.M.A. declares no competing interests.

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Allen, G.M., Lim, W.A. Rethinking cancer targeting strategies in the era of smart cell therapeutics. Nat Rev Cancer 22, 693–702 (2022). https://doi.org/10.1038/s41568-022-00505-x

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