Cell avidity as a parameter for optimal CAR-antigen combinations
This study aimed to identify CAR T cells that bind high antigen-expressing targets but not low antigen-expressing cells.
Researchers validated low functioning and high functioning CAR T cells based on functional assays and used non-transduced T cells as a negative control (NC). T cell avidities were tested on adherent cells with low antigen expression, high antigen expression, or no antigen expression.
The cell avidity data correlated with a corresponding in vitro cell killing assay, showing antigen-dependent binding strengths and cell killing (Figure 1). The cell killing results also demonstrated significantly higher toxicity induced by high functioning CAR T cells on low antigen-expressing healthy-like cells (Figure 2).
The z-Movi can distinguish between T cell specificities to improve CAR T cell therapy. Cell avidity is a reliable readout for identifying optimal CARs that can minimize on-target/off-tumor activity by CAR T cells.
Rapidly evaluate immunotherapeutic strategies with cell avidity
Here, researchers from the Dana-Farber Cancer Institute and Hospital Clinic Barcelona employed the z-Movi to evaluate two immunotherapeutic strategies that simultaneously target two multiple myeloma antigens, BCMA and GRC5F. Immunotherapies targeting BCMA have yielded a high response rate in multiple myeloma patients, however, BCMA antigen escape has caused remissions due to absent or low expression of the antigen. Targeting GPRC5D as an alternative or in addition to BCMA is a strategy to tackle BCMA antigen escape in especially relapsed patients. The illustration at the right shows the four different CAR configurations that were assessed in this study.
Illustration of the CAR designs evaluated in the study.
The aim of this study is to evaluate which CAR design is the most clinically relevant by predicting the CAR T-cell functionality using the z-Movi. The cell avidity of different CAR approaches was measured and compared against each other and with non-transduced (NTD) T cells. Both dtCAR populations required significantly higher force to detach from their target cells, compared with both mtCAR and NTD populations (Figures 3 and 4). With other words, dtCARs show exceptionally stronger binding strength to BCMA- and GPRC5D expressing multiple myeloma cells.
Most notably, subsequent in vivo studies evaluating the survival of mtCAR- or dtCAR-treated xenograft mouse models injected with myeloma cells expressing both antigens, showed a lower tumor burden and improved overall survival for the mice injected with dtCAR treatment. The results support the cell-avidity measurements, indicating that dtCARs effectively bind and kill cells expressing both BCMA and GPRC5D and demonstrate that measurements with the z-Movi® Cell Avidity Analyzer correlate with treatment outcomes in mouse models.
Cell avidity acts as a unique and reliable parameter to predict CAR T-cell functionality and provides information about clinical relevance. Furthermore, the fast and simple workflow of the z-Movi allows researchers to rapidly assess immunotherapeutic strategies, producing high-throughput data from different CAR T-cell populations within 24 hours without compromising cell viability.
3 Avidity curve showing the average proportion of bound CAR T cells and NTD T cells to BCMA and GPRC5D expressing cells upon application of an acoustic force ramp. The dashed line at 200 pN indicates plateau force (the force required to detach NTD cells). rForce represents forces calibrated on 10 μm polystyrene beads. 4 Bar graph representing fold increases of bound CAR T cells at the plateau force gated from the avidity curve (figure 3).