Allogeneic hematopoietic cell transplantation (allo-HCT) hinges on a delicate trade-off between graft-versus-tumor control and graft-versus-host disease (GvHD), mediated by donor T-cell recognition of antigens presented by recipient human leukocyte antigen (HLA) molecules. We hypothesized that, beyond allele-level matching, sequence divergence at peptide-binding grooves across donor and recipient HLA loci shapes these responses. To this end, we evaluated the effect of HLA evolutionary divergence (HED), a metric quantifying amino acid variability at HLA peptide-binding sites, on selected hematological malignancies in 4,695 patients undergoing allo-HCT from a 9/10 mismatched unrelated donor (MMUD), reported to the EBMT database. We examined (i) locus-specific recipient HED (HED-R) and (ii) “HED-mismatch” (HED-MM), capturing immunopeptidome divergence at the mismatched locus. While dichotomous mismatch status explained differences in survival and acute GvHD risk (with overall greater detriment for class I loci), HED metrics uncovered substantial within-mismatch heterogeneity. In DRB1 mismatched subgroup, HED-MM at this locus, independently predicted inferior relapse-free survival (RFS) with an attenuating time-dependent association, further modulated by cross-locus HED-R. In this subgroup, higher HED-R at HLA-A and HLA-C associated with increased risks of acute GvHD and non-relapse mortality, respectively. Among HLA-B–mismatched pairs, higher DRB1 HED-R associated with worse overall survival (OS) and RFS and higher relapse risk. In the HLA-A–mismatched subgroup, higher HED-R at HLA-A increased chronic GvHD risk. Collectively, HED-derived metrics complement conventional mismatch classification by capturing qualitative differences in donor–recipient immunopeptidome interactions and reveal a complex, non-linear interplay among alleles across mismatch subgroups that modulates the clinical impact of mismatching.

Keypoints

In mismatched unrelated HCT, baseline risk varies across mismatch constellations, with class I mismatches more detrimental than class II.

HED complements conventional HLA mismatch classification by capturing qualitative donor-recipient immunopeptidome interactions.

SP has received travel expenses or honoraria for participation in advisory boards, symposia or other scientific events by Alexion, Novartis, Jazz Pharmaceutical, Sobi as well as research funding by JANSSEN HORIZON program. TLL is co-inventor on a patent application for using HED as a prognostic marker for immunotherapy success. DM received research funding from Novartis, Sanofi and CSL Behring, and consulting fee from Novartis, Incyte, Jazz Pharmaceuticals, Sanofi, Mallinckrodt. CC has received travel expenses or honoraria for participation in advisory boards, symposia or other scientific events by BMS, Kite/Gilead, Jazz Pharmaceuticals, Johnson & johnson, Miltenyi biotec, Novartis, Terumo BC. FK received honoraria from Jazz, Therakos, Sanofi, Vertex and Incyte, and research funding from Gilead. R.Z. received honoraria from Novartis, Incyte, Sanofi, Medac, Neovii, and Mallinckrodt. The remaining authors declare no competing financial interests.

This work was supported by EBMT. We acknowledge all participating centers. TLL was supported by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) 437857095. SP received funding from Fondation ARC pour la Recherche sur le Cancer, Force Hemato. KF was supported by the Deutsche Jose Carreras Leukemie Stiftung (DJCLS 17 R/2023).

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The study was conducted in accordance with the Declaration of Helsinki. Data were collected within the EBMT Registry after patients provided written, GDPR (General Data Protection Regulation)-compliant informed consent for data registration and research use, according to EBMT Registry governance; participating centres complied with applicable national/institutional requirements for registry reporting. The data have been de identified prior inclusion in the registry and use in the study.

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