Receptor-Ligand Matching for Precision Allogeneic NK Cell Cancer Therapies

Allogeneic natural killer (NK) cell therapies have a favorable safety profile. NK cell cytotoxicity is the result of interactions between activating and inhibitory receptors and tumor-cell ligands expressed in the tumoral cell. This complex, donor-dependent interaction could explain variable persistence and limited durability across clinical trials. Here, we discuss an emergent framework for improving NK cell efficacy through systemic receptor-ligand matching grounded in NK licensing and donor-recipient immunogenetics, particularly KIR-HLA class I interactions, integrated with tumor ligand landscapes such as stress-induced NKG2D ligands. This review synthesizes how inhibitory and activating receptor repertoires calibrate NK functional competence, why identical KIR-HLA configurations yield context-dependent outcomes across malignancies and treatments, and how tumor immune evasion can decouple ligand expression from NK recognition. Based on this evidence hierarchy, we propose a biomarker-driven stratification framework to guide decisions on donor selection, redosing, and combination therapy. We further discuss how emerging machine learning classifiers and multiscale computational models could extend this framework to the clinical scale. Finally, we propose that the systematic incorporation of receptor-ligand immunogenetics into the design of an adoptive NK cell clinical trial is a necessary and tractable step toward improving the mechanistic interpretability, clinical development, and reproducibility of allogeneic NK-cell therapies.