Targeting a novel glyco-immune checkpoint for cancer immunotherapy

Yale University, New Haven CT

Investigators

Abstract

Targeting a novel glyco-immune checkpoint for cancer immunotherapy ABSTRACT: Immunotherapies have revolutionized cancer treatment in recent decades, but most patient responses are of limited duration, and primary or secondary resistance is the norm. There is an urgent need to identify additional immune checkpoints and develop inhibitory drugs to allow immune attack of established tumors. Checkpoints typically function through cell-cell contact between ligand-receptor pairs, so identifying novel interactions is of great benefit. To this end, we constructed a protein library comprising the extracellular domains of 512 molecular species from IgSF and TNFSF families for specific protein-protein interaction screening. Using these techniques, we identified the novel interaction between IgSF members VSIG4 and Siglec-7. Of note, these proteins diverge significantly from non-primates. Our data implicate Siglec-7 as an innate immune inhibitory receptor for NK cell activation, suggesting that the Siglec-7-VSIG4 interaction functions as an immune checkpoint. Here we propose to develop in vivo models to elucidate the mechanisms of function of these novel human-specific interactions. We will utilize our humanized mouse platform, MISTRG6-A2, which affords us the opportunity to manipulate innate (and adaptive) immune cells in vivo. Given the overexpression of VSIG4 on multiple myeloma (MM) cells (especially after lenalidomide treatment) and acute myeloid leukemia inv(16) cells (AMLinv(16)), we will explore the impacts of the Siglec-7- VSIG4 checkpoint on these malignancies in vitro and in vivo. Completion of these aims will enhance our understanding of immune activation and tumor immuno-evasion, as well as pinpoint the disease(s) most relevant for future clinical development of immune checkpoint inhibitory antibodies. Intervening on novel checkpoints will open the door to new therapies with the capacity to improve patient outcomes in MM and AMLinv(16), with potential applicability across many other tumor types.