Research published in the journal Haematologic, suggests that molecular modeling can predict the permissiveness of HLA-DPB1 mismatches and host-versus-graft (HVG) or graft-versus-host (GVH) response. These findings validate the molecular algorithms which predict the risks associated with HLA-DPB1 mismatches and clinical outcomes.
For certain hematological malignancies, allogeneic hematopoietic stem cell transplantation (HSCT) remains the only available treatment. Complications such as graft-versus-host disease (GVHD) pose a risk to the patients and are more prevalent when HLA-mismatched unrelated donors are used. In patients who have received HLA-A, -B, -C, -DRB1, and -DQB1 matched (10/10) grafts from unrelated donors, differences between the HLA-DPB1 locus are associated with increased risks of GVHD. Therefore, the authors hypothesized that in silico modeling, which measures mismatched eplets (ME) and the Predicted Indirectly Recognizable HLA Epitopes Score (PS), may be used to predict clinical outcomes and GVHD risk.
To validate this model, the authors investigated 1,514 patients who underwent HSCT from unrelated donors. The authors found that mismatches (high ME/PS) in the GVH direction were associated with reduce risk of relapse (hazard ratio [HR]=0.83, P=0.05 for ME) and increased GVHD (HR=1.44, P<0.001 for ME) and non-relapse mortality risk. Conversely, mismatches in the HVG direction were only associated with increased risk of GVHD (HR=1.26, P=0.004 for ME). These findings help validate in silico models which may be used to predict clinical outcomes.
Zou J, Kongtim P, Oran B, et al. Refined HLA-DPB1 mismatch with molecular algorithms predicts outcomes in hematopoietic stem cell transplantation. Haematologica. 2022;107(4):844-856. Published 2022 Apr 1. https://doi.org/10.3324/haematol.2021.278993