Developing a membrane-proximal CD33-targeting CAR T cell

开发靶向膜近端 CD33 的 CAR-T 细胞

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作者:Ruby Freeman, Sanam Shahid, Abdul G Khan, Serena C Mathew, Sydney Souness, Erin R Burns, Jasmine S Um, Kento Tanaka, Winson Cai, Sarah Yoo, Andrew Dunbar, Young Park, Devin McAvoy, Kinga K Hosszu, Ross L Levine, Jaap Jan Boelens, Ivo C Lorenz, Renier J Brentjens, Anthony F Daniyan

Background

CD33 is a tractable target in acute myeloid leukemia (AML) for chimeric antigen receptor (CAR) T cell therapy, but clinical success is lacking.

Conclusions

Showing for the first time that a membrane-proximal CAR is superior to a membrane-distal one in the setting of CD33 targeting, our results demonstrate the rationale for targeting membrane-proximal epitopes with high-affinity binders. We also demonstrate the importance of optimizing CAR T cells for functionality in settings of both low antigen density and clinically relevant patient-derived models.

Methods

We developed 3P14HLh28Z, a novel CD33-directed CD28/CD3Z-based CAR T cell derived from a high-affinity binder obtained through membrane-proximal fragment immunization in humanized mice.

Results

We found that immunization exclusively with the membrane-proximal domain of CD33 is necessary for identification of membrane-proximal binders in humanized mice. Compared with clinically validated lintuzumab-based CAR T cells targeting distal CD33 epitopes, 3P14HLh28Z showed enhanced in vitro functionality as well as superior tumor control and increased overall survival in both low antigen density and clinically relevant patient-derived xenograft models. Increased activation and enhanced polyfunctionality led to enhanced efficacy. Conclusions: Showing for the first time that a membrane-proximal CAR is superior to a membrane-distal one in the setting of CD33 targeting, our results demonstrate the rationale for targeting membrane-proximal epitopes with high-affinity binders. We also demonstrate the importance of optimizing CAR T cells for functionality in settings of both low antigen density and clinically relevant patient-derived models.

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