Carolin Massalski, Daniel Fürst, Stefan Klein, Joannis Mytilineos, Dietrich W. Beelen, Alexander H. Schmidt, Armin Gerbitz, F Ayuk, Carlheinz Mueller, Vinzenz Lange, Katharina Fleischhauer, Johannes Schetelig, Matthias Stelljes, Sarah Wendler, Gesine Bug, Liesbeth C. de Wreede, Guido Kobbe, Jürgen Sauter, Wolfgang Bethge, Sandra Frank, Falk Heidenreich, Henning Baldauf, Martin Bornhäuser, Hellmut Ottinger, and Julia Luedemann
Introduction: A series of studies suggest that harnessing natural killer (NK) cell reactivity by killer cell immunoglobulin-like receptor (KIR) genotype based unrelated donor selection could further improve outcome after allogeneic hematopoietic cell transplantation (alloHCT). A Receptor-Ligand model has been proposed for donor selection which aims at augmenting NK cell activation while minimizing inhibition. Information on education of KIR2DS1-positive NK cells (Venstrom et al, NEJM 2012) and the predicted Receptor-Ligand interaction of KIR3DL1-positive NK cells is utilized for this algorithm. By combining this information donors can be classified as KIR-advantageous or disadvantageous. Patients with donors, characterized by activating KIR2DS1 and weak/non-inhibiting KIR3DL1, experienced less relapse and improved survival compared to patients with donors, characterized by lacking an activating KIR2DS1 but presence of strong-inhibiting KIR3DL1. This study aimed at validating this predictor in an independent cohort of patients. Methods: Donor samples were retrieved from the Collaborative Biobank (Dresden, Germany) and mapped to patient outcome data extracted from the German Registry for Stem Cell transplantation. KIR typing was performed using a high resolution amplicon-based next generation sequencing method. KIR typing at the allele level was based on sequencing of exons 3, 4, 5, 7, 8, and 9. The patient population was restricted to patients with AML or MDS. Donor and patient mapping was cross-checked by HLA-typing of the donor sample. The impact of the predictor on overall survival was tested in a Cox regression model adjusted for patient age, a modified disease risk index, performance status, donor age, HLA-match, sex match, CMV match, conditioning intensity, type of T-cell depletion and graft type. Results: Clinical data from 2314 patients were analyzed. The median age at alloHCT was 59.4 years (range, 18.1 to 79.6 years). The indication for alloHCT was AML for 80% of patients and MDS for 20% of patients. Disease risk was assessed as low, intermediate, high or very high in 1%, 52%, 42%, and 5%, respectively. Patient and donor were 10/10 matched in 78% of pairs, whereas a one locus mismatch was reported for 21% of pairs. Myeloablative, reduced-intensity and non-myeloablative conditioning regimens were used in 29%, 67%, and 4% of patients, respectively. ATG was administered in 77% and alemtuzumab in 3% of patients. Twenty percent of patients received no T-cell depletion. In total, 535 patients experienced relapse and 945 patients died. This number of events translated into a power of the confirmatory analysis for the predictor of KIR2DS1 and KIR3DL1 of 67%. Two-year overall and event-free survival for the whole cohort was 51% (95%-CI 48% to 53%) and 44% (95%-CI 42% to 47%) and the 2-year incidence of relapse and non-relapse mortality was 28% (95%-CI 26% to 30%) for both endpoints. In univariate analysis, overall survival (54% versus 56%) and the cumulative incidence of relapse of patients with a KIR-advantageous donor were comparable to patients with KIR-disadvantageous donors. The adjusted hazard ratio from the multivariable Cox regression model for the comparison of patients with KIR-advantageous versus KIR-disadvantageous donors was 0.99 (Wald-test, p=0.95) for overall survival and 1.12 (Wald-test, p=0.41) for relapse incidence. When evaluated separately, the two components of the predictor (degree of inhibition by KIR3DL1 & presence of activating KIR2DS1) did not have an impact on overall survival or the incidence of relapse (see Figure). Also, evaluation of the combined predictor in subsets of patients by disease, type of T-cell depletion and HLA-compatibility did not allow prediction of these outcomes. Conclusions: Relapse incidence and overall survival after unrelated donor alloHCT could not be predicted using information on activating KIR2DS1 and inhibiting KIR3DL1 donor genes in an independent cohort of predominantly Caucasian patients. The predictor had been developed in a cohort of patients with AML who were younger and predominantly had received myeloablative conditioning based on total-body irradiation, ATG was administered less often, but donors often were only partially HLA-compatible. The different outcome in the current analysis thus points at potential interactions between NK-cell mediated allo-reactivity and procedural variations of alloHCT. Figure Figure. Disclosures Schetelig: Sanofi: Consultancy, Research Funding; Janssen: Consultancy, Honoraria; Roche: Honoraria; Abbvie: Honoraria; Novartis: Consultancy, Honoraria, Research Funding; Gilead: Consultancy, Honoraria, Research Funding. Stelljes:Novartis: Honoraria; MSD: Consultancy; Pfizer: Consultancy, Honoraria, Research Funding; JAZZ: Honoraria; Amgen: Honoraria. Ayuk:Therakos (Mallinckrodt): Honoraria; Novartis: Honoraria; Celgene: Consultancy; Gilead: Consultancy. Bethge:Neovii GmbH: Honoraria, Research Funding; Miltenyi Biotec GmbH: Consultancy, Honoraria, Research Funding. Bug:Neovii: Other: Travel Grant; Novartis Pharma: Honoraria, Research Funding; Janssen: Other: Travel Grant; Celgene: Honoraria; Amgen: Honoraria; Astellas Pharma: Other: Travel Grant; Jazz Pharmaceuticals: Other: Travel Grant. Kobbe:Roche: Honoraria, Research Funding; Celgene: Honoraria, Other: Travel Support, Research Funding; Amgen: Honoraria, Research Funding. Beelen:Medac: Consultancy, Other: Travel Support. Fleischhauer:GENDX: Research Funding.