Discriminatory Power of Combinatorial Antigen Recognition in Cancer T Cell Therapies.

Autor:	Dannenfelser R; Department of Computer Science, Princeton University, Princeton, NJ 08540, USA; Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ 08544, USA., Allen GM; Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, CA 94158, USA; Division of Hematology and Oncology, Department of Medicine, University of California, San Francisco, San Francisco, CA 94143, USA; Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA 94158, USA; Howard Hughes Medical Institute, University of California, San Francisco, San Francisco, CA 94158, USA; Center for Systems and Synthetic Biology, University of California, San Francisco, San Francisco, CA 94158, USA; Cell Design Institute and Center for Synthetic Immunology, University of California, San Francisco, San Francisco, CA 94158, USA., VanderSluis B; Center for Computational Biology, Flatiron Institute, New York, NY 10010, USA., Koegel AK; Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, CA 94158, USA; Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA 94158, USA; Howard Hughes Medical Institute, University of California, San Francisco, San Francisco, CA 94158, USA; Center for Systems and Synthetic Biology, University of California, San Francisco, San Francisco, CA 94158, USA; Cell Design Institute and Center for Synthetic Immunology, University of California, San Francisco, San Francisco, CA 94158, USA; Division of Pediatric Oncology, Department of Pediatrics, University of California, San Francisco, San Francisco, CA 94158, USA., Levinson S; Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, CA 94158, USA; Center for Systems and Synthetic Biology, University of California, San Francisco, San Francisco, CA 94158, USA., Stark SR; Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, CA 94158, USA; Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA 94158, USA; Howard Hughes Medical Institute, University of California, San Francisco, San Francisco, CA 94158, USA; Center for Systems and Synthetic Biology, University of California, San Francisco, San Francisco, CA 94158, USA; Cell Design Institute and Center for Synthetic Immunology, University of California, San Francisco, San Francisco, CA 94158, USA., Yao V; Department of Computer Science, Princeton University, Princeton, NJ 08540, USA; Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ 08544, USA; Department of Computer Science, Rice University, Houston, TX 77005, USA., Tadych A; Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ 08544, USA., Troyanskaya OG; Department of Computer Science, Princeton University, Princeton, NJ 08540, USA; Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ 08544, USA; Center for Computational Biology, Flatiron Institute, New York, NY 10010, USA. Electronic address: ogt@genomics.princeton.edu., Lim WA; Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, CA 94158, USA; Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA 94158, USA; Howard Hughes Medical Institute, University of California, San Francisco, San Francisco, CA 94158, USA; Center for Systems and Synthetic Biology, University of California, San Francisco, San Francisco, CA 94158, USA; Cell Design Institute and Center for Synthetic Immunology, University of California, San Francisco, San Francisco, CA 94158, USA. Electronic address: wendell.lim@ucsf.edu.
Jazyk:	angličtina
Zdroj:	Cell systems [Cell Syst] 2020 Sep 23; Vol. 11 (3), pp. 215-228.e5. Date of Electronic Publication: 2020 Sep 10.
DOI:	10.1016/j.cels.2020.08.002
Abstrakt:	Precise discrimination of tumor from normal tissues remains a major roadblock for therapeutic efficacy of chimeric antigen receptor (CAR) T cells. Here, we perform a comprehensive in silico screen to identify multi-antigen signatures that improve tumor discrimination by CAR T cells engineered to integrate multiple antigen inputs via Boolean logic, e.g., AND and NOT. We screen >2.5 million dual antigens and ∼60 million triple antigens across 33 tumor types and 34 normal tissues. We find that dual antigens significantly outperform the best single clinically investigated CAR targets and confirm key predictions experimentally. Further, we identify antigen triplets that are predicted to show close to ideal tumor-versus-normal tissue discrimination for several tumor types. This work demonstrates the potential of 2- to 3-antigen Boolean logic gates for improving tumor discrimination by CAR T cell therapies. Our predictions are available on an interactive web server resource (antigen.princeton.edu). Competing Interests: Declaration of Interests W.A.L. is on the Scientific Advisory Board for Allogene Therapeutics and O.G.T. is on the Scientific Advisory Board for Caris Life Sciences. W.A.L. and O.G.T. have filed patents related to this work. (Copyright © 2020. Published by Elsevier Inc.)
Databáze:	MEDLINE
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