Genetic Associations with Immune-mediated Outcomes after Allogeneic Hematopoietic Cell Transplantation

T cell receptor-engineered T cells derived from target human leukocyte antigen-DPB1-specific T cell can be a potential tool for therapy against leukemia relapse following allogeneic hematopoietic cell transplantation

Human leukocyte antigen (HLA)-DPB1 antigens are mismatched in approximately 70% of allogeneic hematopoietic stem cell transplantations (allo-HSCT) from HLA 10/10 matched unrelated donors. HLA-DP-mismatched transplantation was shown to be associated with an increase in acute graft-versus-host disease (GVHD) and a decreased risk of leukemia relapse due to the graft-versus-leukemia (GVL) effect. Immunotherapy targeting mismatched HLA-DP is considered reasonable to treat leukemia following allo-HCT if performed under non-inflammatory conditions. Therefore, we isolated CD4+ T cell clones that recognize mismatched HLA-DPB1 from healthy volunteer donors and generated T cell receptor (TCR)-gene-modified T cells for future clinical applications. Detailed analysis of TCR-T cells expressing TCR from candidate clone #17 demonstrated specificity to myeloid and monocytic leukemia cell lines that even expressed low levels of targeted HLA-DP. However, they did not react to non-hematopoietic cell lines with a substantial level of targeted HLA-DP expression, suggesting that the TCR recognized antigenic peptide is only present in some hematopoietic cells. This study demonstrated that induction of T cells specific for HLA-DP, consisting of hematopoietic cell lineage-derived peptide and redirection of T cells with cloned TCR cDNA by gene transfer, is feasible when using careful specificity analysis.

The use of prognostic models in allogeneic transplants: a perspective guide for clinicians and investigators

Allogeneic hematopoietic cell transplant (HCT) can cure many hematologic diseases, but it carries the potential risk of increased morbidity and mortality rates. Prognostic evaluation is a scientific entity at the core of care for potential recipients of HCT. It can improve the decision-making process of transplant vs no transplant, help choose the best transplant strategy and allows for future trials targeting patients' intolerances to transplant; hence, it ultimately improves transplant outcomes. Prognostic models are key for appropriate actuarial outcome estimates, which have frequently been shown to be better than physicians' subjective estimates. To make the most accurate prognostic evaluation for HCT, one should rely on >1 prognostic model. For relapse and relapse-related mortality risks, the refined disease risk index is currently the most informative model. It can be supplemented with disease-specific models that consider genetic mutations as predictors in addition to information on measurable residual disease. For nonrelapse mortality and HCT-related morbidity risks, the HCT-comorbidity index and Karnofsky performance status have proven to be the most reliable and most accepted by physicians. These can be supplemented with gait speed as a measure of frailty. Some other global prognostic models might add additional prognostic information. Physicians' educated perceptions can then put this information into context, taking into consideration conditioning regimen and donor choices. The future of transplant mandates (1) clinical investigators specifically trained in prognostication, (2) increased reliance on geriatric assessment, (3) the use of novel biomarkers such as genetic variants, and (4) the successful application of novel statistical methods such as machine learning.