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The therapeutic landscape for cells engineered with chimeric antigen receptors

Nature Biotechnology volume 38, pages 233–244 (2020)Cite this article

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Abstract

Despite the global rapid increase in the number of clinical trials employing chimeric antigen receptors (CARs), no comprehensive survey of their scope, targets and design exists. In this study, we present an interactive CAR clinical trial database, spanning 64 targets deployed in T cells (CAR-T), natural killer cells (CAR-NK) or mixtures (CAR-NK/T) from over 500 clinical trials in 20 countries, encompassing >20,000 patients. By combining these data with transcriptional and proteomic data, we create a ‘targetable landscape’ for CAR cell therapies based on 13,206 proteins and RNAs across 78 tissues, 124 cell types and 20 cancer types. These data suggest a landscape of over 100 single targets and over 100,000 target pairs using logical switches for CAR cell engineering. Our analysis of the CAR cellular therapeutic landscape may aid the design of future therapies, improve target-to-patient matching, and ultimately help inform our understanding of CAR therapy’s safety and efficacy.

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Fig. 1: Interventional CAR clinical trials initiated before 2019.
Fig. 2: CAR indications and clinical history.
Fig. 3: Expression of clinical CAR targets in normal tissues and cancer.
Fig. 4: The potential landscape of CARs addressing a single target.
Fig. 5: The potential landscape of CAR logical switches.
Fig. 6: CAR treatment design and patient monitoring.

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Data availability

We have created an indexed and searchable online site for displaying clinical CAR targets (https://carglobaltrials.com), which also features the normal (tissue group, tissue and cell type) and pathological gene expression data for those targets.

Code availability

Relevant code for identification of new targets and target pairs, and for parsing the current CAR targets is available in the Supplementary Materials.

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Acknowledgements

This work was supported by STARR Cancer Consortium grants (nos. I7-A765, I9-A9-071) and funding from the Irma T. Hirschl and Monique Weill-Caulier Charitable Trusts, Bert L. and N. Kuggie Vallee Foundation, Igor Tulchinsky and the WorldQuant Foundation, the Pershing Square Sohn Cancer Research Alliance, the National Institutes of Health (grant nos. P01CA214274, 1R01MH117406) and the Leukemia and Lymphoma Society (grant nos. LLS 9238-16, Mak, LLS-MCL-982, Chen-Kiang). Funding also came from the National Natural Science Foundation of China (grant nos. 81402529 and 81672994), Zhejiang Provincial Foundation for Natural Sciences (grant no. LZ15H220001), Zhejiang Provincial Medical Scientific Research Foundation of China (grant nos. 2015KYB325 and 2015PYA009), Hangzhou City Medical Scientific Research Foundation of Zhejiang Province (grant no. 2015Z04) and Hangzhou City Scientific Technology Research Foundation of Zhejiang Province (grant no. 20150733Q64) of the Hangzhou Science and Technology Development Program (grant no. 20150733Q63).

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Authors and Affiliations

  1. Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA

    Matthew MacKay, Ebrahim Afshinnekoo, Jonathan Rub & Christopher E. Mason

  2. The WorldQuant Initiative for Quantitative Prediction, Weill Cornell Medicine, New York, NY, USA

    Matthew MacKay, Ebrahim Afshinnekoo & Christopher E. Mason

  3. The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medicine, New York, NY, USA

    Matthew MacKay, Ebrahim Afshinnekoo, Jonathan Rub & Christopher E. Mason

  4. Tri-Institutional Computational Biology and Medicine Program, Weill Cornell Medicine of Cornell University, New York, NY, USA

    Matthew MacKay

  5. Yale University, New Haven, CT, USA

    Ciaran Hassan, Mihir Khunte, Nithyashri Baskaran, Bryan Owens & Lauren Liu

  6. Division of Hematology/Oncology, Department of Medicine, Weill Cornell Medicine, New York, NY, USA

    Gail J. Roboz, Monica L. Guzman & Ari M. Melnick

  7. National Cancer Center/National Clinical Research Center for Cancer, Cancer Hospital & Shenzhen Hospital, Shenzhen, China

    Shixiu Wu

  8. Chinese Academy of Medical Science, Peking Union Medical College, Shenzhen, China

    Shixiu Wu

  9. The Feil Family Brain and Mind Research Institute, New York, NY, USA

    Christopher E. Mason

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  1. Matthew MacKay
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Contributions

C.E.M., M.M. and S.W. conceived the study. C.E.M. and M.M. performed the clinical site setup and framework. A.M.M., G.R. and M.G. updated the clinical annotation and target maps. C.E.M. and S.W. provided study support and logistics. S.W. led the on-site validation. M.M. led the code and analysis of public and clinical trial data and created the site code base. E.A. and J.R. validated the clinical trial targets. C.H., M.K., N.B., B.O. and L.L. from the Yale CAR Annotation Team cross-validated the parameters.

Corresponding authors

Correspondence to Shixiu Wu or Christopher E. Mason.

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Competing interests

There are no specific, relevant competing interests related to this work. However, in the interest of full disclosure, C.M. is a cofounder and board member for Biotia and Onegevity Health, as well as an advisor or compensated speaker for Abbvie, Acuamark Diagnostics, ArcBio, BioRad, DNA Genotek, Genialis, Genpro, Karius, Illumina, New England Biolabs, QIAGEN, Whole Biome and Zymo Research.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Integrated supplementary information

Supplementary Figure 1 CAR stratification by normal expression and recent usage in the clinic.

(a) The number of trials from 2017–2019 that used a given CAR compare to the percent of tissues with medium-high levels of expression of the CAR target. (b) The percentage of tissue groups with not-detected, low, medium, or high levels of target expression based on maximum expression seen within a cell type for CARs used in multiple recent trials. (c) Tissue group, (d) tissue, and (e) cell types with a given CAR target highly expressed. CARs examined are listed in (b).

Supplementary information

Supplementary Materials

Supplementary Fig. 1.

Reporting Summary

Supplementary Tables

Supplementary Tables 1–3.

Analysis code

CAR_NBT_analysis_expression.js, CAR_NBT_analysis_location.js, CAR_NBT_analysis_logicalAndNotPairs.R, CAR_NBT_analysis_logicalAndPairs.R, CAR_NBT_analysis_meta.js, CAR_NBT_analysis_singleTargets.R

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MacKay, M., Afshinnekoo, E., Rub, J. et al. The therapeutic landscape for cells engineered with chimeric antigen receptors. Nat Biotechnol 38, 233–244 (2020). https://doi.org/10.1038/s41587-019-0329-2

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