Abstract 2897: Overcoming barriers to the natural killer cell response against multiple myeloma: Manipulating the NKG2A/HLA-E checkpoint and CAR engineering of memory-like natural killer cells
Authors: Zhou Alice Y. , Berrien-Elliott Melissa M. , Vij Ravi , Fiala Mark , Becker-Hapak Michelle , Marsala Lynne , Jacobs Miriam T. , Marin Nancy D. , Tran Jennifer , Foltz Jennifer , Wong Pamela , Fortier Julie , Kelley Sarah , Neal Carly , Russler-Germain David , Schappe Timothy , Fehniger Todd A. 
Published: June 2023

Abstract
Recent advances in treatment options for multiple myeloma (MM) have improved patient outcomes, however, MM remains incurable and options are limited for relapsed/refractory disease. Memory-like (ML) differentiation of NK cells using brief IL-12, IL-15, and IL-18 activation generates a safe allogenic NK cellular therapy for acute myeloid leukemia that induce complete remissions. Here, we investigate pre-clinical combinations with ML NK cells for MM, including blockade of the inhibitory NKG2A/HLA-E checkpoint as well as MM-specific targeting via myeloma-targeting monoclonal antibody (mAb) and chimeric antigen receptor (CAR) engineering.
Human ML NK cells generated from healthy donors display IFN-γ responses similar to conventional (cNK) cells, and only modestly increased cytotoxicity against myeloma cell lines (MM1.s and OPM2). MM cell lines and primary MM cells express high levels of HLA-E, a major negative checkpoint for ML NK cells that binds to the inhibitory receptor NKG2A expressed on NK cells. Indeed, mass cytometry analysis of MM patients compared to healthy controls demonstrated enrichment of a NK cell population expressing high levels of NKG2A, but also high levels of activation and cytotoxic markers. Disruption of HLA-E binding to NKG2A with the blocking mAb monalizumab (AstraZeneca) significantly increased healthy donor ML NK cell IFN-γ response (P=0.016), degranulation (surface CD107a, P=0.017), and killing (P=0.009) of MM1.s when compared to isotype mAb. NK cells isolated from patients with MM showed similarly enhanced functionality after ML differentiation and NKG2A blockade (IFN-γ P=0.008). In an NSG mouse model of MM using MM1.s cells, healthy donor ML NK cells combined with monalizumab showed improved control of MM tumor growth compared to ML NK cells without monalizumab (P&lt;0.001), conventional NK cells, or control tumors alone (P&lt;0.001).
To further improve recognition of MM, ML NK cells responses were assessed in combinationwith a mAb against SLAMF7 (elotuzumab) that both targets MM cells and activates NK cells. Elotuzumab treatment increased the functionality of ML NK cells against MM cell lines (IFN-γ, P=0.004) with an additive effect of both elotuzumab and monalizumab (IFN-γ, P=0.003). In an alternative strategy to enhance MM targeting, we engineered an anti-BCMA CAR (anti-BCMA/4-1bb/z) into ML NK cells. BCMA-CAR+ NK cells exhibited increased IFN-γ (P=0.001) production and degranulation (P&lt;0.001) against MM1.s compared to non-transduced control NK cells. These functional responses were additionally enhanced with ML differentiation.
Collectively, these findings suggest that ML NK cell differentiation, combined with strategies to address inhibitory checkpoints (NKG2A) or MM-specific activation (elotuzumab, anti-BMCA CAR), are promising cellular therapy strategies for MM patients.
Citation Format: Alice Y. Zhou, Melissa M. Berrien-Elliott, Ravi Vij, Mark Fiala, Michelle Becker-Hapak, Lynne Marsala, Miriam T. Jacobs, Nancy D. Marin, Jennifer Tran, Jennifer Foltz, Pamela Wong, Julie Fortier, Sarah Kelley, Carly Neal, David Russler-Germain, Timothy Schappe, Todd A. Fehniger. Overcoming barriers to the natural killer cell response against multiple myeloma: Manipulating the NKG2A/HLA-E checkpoint and CAR engineering of memory-like natural killer cells [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 2897.