[Risk prediction and function evaluation by T-cell epitope model and expression model of HLA-DPB1 mismatching in unrelated-donor hematopoietic stem cell transplantations].

ABSTRACT

Objective: To evaluate the risk prediction and assessment function of HLA-DPB1 T-cell epitope (TCE) model and expression model in human leukocyte antigen (HLA)-matched unrelated hematopoietic stem cell transplantation (MUD-HSCT) with HLA-DPB1 mismatching. Methods: A total of 364 (182 pairs) potential MUD-HSCT donors and recipients confirmed by HLA high-resolution typing in Shaanxi Blood Center from 2016 to 2019 were analyzed retrospectively. Of the 182 recipients, there were 121 males and 61 females with an average age of (26.3±14.2) years. Of the 182 donors, there were 148 males and 34 females with an average age of (33.7±7.5) years. Polymerase chain reaction-sequence-based typing (PCR-SBT), next-generation sequencing (NGS) and polymerase chain reaction-sequence specific oligonucleotide probe (PCR-SSO) based on LABScan®3D platform were used for high-resolution typing of HLA-A, B, C, DRB1, DQB1, DPB1 gene, and PCR-SBT was used for single nucleotide polymorphism (SNP) typing. TCE model and expression model were used to predict and evaluate the HLA-DPB1 mismatch pattern and acute graft-versus-host-disease (aGVHD) risk. Results: A total of 26 HLA-DPB1 alleles and their 3'-UTR rs9277534 SNP genotypes were detected in this study population, and two new alleles HLA-DPB1*1052∶01 and HLA-DPB1*1119∶01 were found and officially named. The overall mismatch rate of HLA-DPB1 in MUD-HSCT donors and recipients was 90.66% (165/182). In TCE model, the HLA-DPB1 mismatch rates of permissible mismatch (PM) and non-permissible mismatch (non-PM) were 47.80% (87/182) and 42.86% (78/182), respectively. The non-PM in GvH direction was 13.73% (25/182), and which in HvG direction was 29.12% (53/182). A total of 73 pairs of donors and recipients in TCE model met the evaluation criteria of expression model. Among of TCE PM group, recipient DP5 mismatches accounted for 34.25% (25/73) were predicted as aGVHD high risk according to expression model. For the TCE non-PM group, both the recipient DP2 mismatches of 6.85% (5/73) and recipient DP5 mismatches of 10.86% (8/73) were predicted to be at high risk for aGVHD. Risk prediction by TCE model and expression model was 27.27% concordant and 16.97% unconcordant. Conclusions: TCE model and expression model are effective tools to predict aGVHD risk of MUD-HSCT. Comprehensive application of the two models is helpful to the hierarchical assessment of HSCT risk.