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Novel KIR2DS4:HLA-B*35 interaction predicts HLA-B*35 positive patient survival post hematopoietic stem cell transplant.

Sep 2026 · Blood Advances · 0 citations
Medicine

Abstract

Haplo-identical hematopoietic cell transplantation (haploHCT) is an integral treatment paradigm for patients with leukemia. While overall survival (OS) post-haploHCT has steadily improved, relapse-free survival (RFS) remains relatively stagnant. Upon the discovery of killer immunoglobulin-like receptors (KIRs) on natural killer (NK) cells and their cognate human leukocyte antigen (HLA) ligands, algorithms have been developed to enhance graft versus leukemia effects. However, these algorithms fail to yield consistent predictions in patient outcomes. We utilized a combination of in silico protein folding and interactions to determine KIR:HLA reactivity in conjunction with in vitro acoustic force microscopy to measure cell avidity (CA) as a readout for KIR signal strength. CA was determined using monoallelic HLA expressing K562 cell lines, monoallelic KIR Jurkat cells, and peripheral blood NK cells. We extended the CA results and performed standard cytotoxicity assays as well. We discovered that HLA-B*35 interacts with KIR2DS4. We applied the newly discovered interaction to predict outcomes for HCT patients. Stratifying patients based on their HLA-B*35 positivity and donor KIR2DS4 status, we delineated a correlation to survival (P=0.061) when donors only had full-length KIR2DS4. Patients who received a haploHCT and NK cell addback from donors with only full-length KIR2DS4 had a significantly improved RFS (P=0.001) and OS (P=0.016) compared to truncated (KIR1D) and full-length KIR2DS4 donors. This was independently validated in a diverse 10/10 HLA matched European cohort with RFS (P=0.0255) and OS (P=0.0388). Thus, the identified novel KIR2DS4:HLA-B*35 interaction axis predicts patient survival, in both haplo-identical and fully matched, HCT and highlights that our current understanding of the KIR:HLA interactome is incomplete and requires remapping for enhanced therapeutic applications.

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