Survey
* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
Plenary Paper IMMUNOBIOLOGY AND IMMUNOTHERAPY HLA informs risk predictions after haploidentical stem cell transplantation with posttransplantation cyclophosphamide Michael R. Grunwald,8 Taiga Nishihori,9 Michelle Kuxhausen,10 Stephanie Fingerson,10 Caroline McKallor,11 Asad Bashey,3 Yvette L. Kasamon,1 Yung-Tsi Bolon,10 Ayman Saad,12 Joseph McGuirk,13 Sophie Paczesny,14 Shahinaz M. Gadalla,15 Steven G. E. Marsh,16 Bronwen E. Shaw,4 Stephen R. Spellman,10 Stephanie J. Lee,11,17 and Effie W. Petersdorf11 1 Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins Hospital, Baltimore, MD; 2Hospital of the University of Pennsylvania, Philadelphia, PA; 3Northside Hospital Cancer Institute, Blood and Marrow Transplant Program, Atlanta, GA; 4Department of Medicine, Center for International Blood and Marrow Transplant Research (CIBMTR), Medical College of Wisconsin, Milwaukee, WI; 5Division of Biostatistics, Institute for Health and Equity, Medical College of Wisconsin, Milwaukee, WI; 6Roswell Park Cancer Institute, Buffalo, NY; 7Karmanos Cancer Institute, Detroit, MI; 8Department of Hematologic Oncology and Blood Disorders, Levine Cancer Institute, Atrium Health, Charlotte, NC; 9Department of Blood and Marrow Transplant and Cellular Immunotherapy (BMT CI), Moffitt Cancer Center, Tampa, FL; 10CIBMTR, National Marrow Donor Program/Be The Match Foundation, Minneapolis, MN; 11Division of Clinical Research, Fred Hutchinson Cancer Research Center, Seattle, WA; 12Division of Hematology, Ohio State University, Columbus, OH; 13Division of Hematologic Malignancies and Cellular Therapeutics, The University of Kansas Cancer Center, Kansas City, KS; 14Department of Microbiology and Immunology, Medical University of South Carolina, Charleston, SC; 15Division of Cancer Epidemiology and Genetics, National Institutes of Health, National Cancer Institute, Clinical Genetics Branch, Rockville, MD; 16Anthony Nolan Research Institute–University College London Cancer Institute, Royal Free Campus, London, United Kingdom; and 17Department of Medicine, CIBMTR, Medical College of Wisconsin, Milwaukee, WI Hematopoietic cell transplantation from HLA-haploidentical related donors is increasingly used to treat hematologic cancers; however, characteristics of the optimal haploidentical HLA mismatching is donor have not been established. We studied the role of donor HLA mismatching in associated with relapse graft-versus-host disease (GVHD), disease recurrence, and survival after haploidentical and survival after haploidentical donor transplantation with posttransplantation cyclophosphamide (PTCy) for 1434 acute transplantation utilizing leukemia or myelodysplastic syndrome patients reported to the Center for International posttransplant Blood and Marrow Transplant Research. The impact of mismatching in the graft-versus-host cyclophosphamide. vector for HLA-A, -B, -C, -DRB1, and -DQB1 alleles, the HLA-B leader, and HLA-DPB1 T-cell HLA should inform the epitope (TCE) were studied using multivariable regression methods. Outcome was selection of associated with HLA (mis)matches at individual loci rather than the total number of HLA haploidentical donors for transplantation. mismatches. HLA-DRB1 mismatches were associated with lower risk of disease recurrence. HLA-DRB1 mismatching with HLA-DQB1 matching correlated with improved disease-free survival. HLA-B leader matching and HLA-DPB1 TCE-nonpermissive mismatching were each associated with improved overall survival. HLA-C matching lowered chronic GVHD risk, and the level of HLA-C expression correlated with transplant-related mortality. Matching status at the HLA-B leader and HLA-DRB1, -DQB1, and -DPB1 predicted disease-free survival, as did patient and donor cytomegalovirus serostatus, patient age, and comorbidity index. A web-based tool was developed to facilitate selection of the best haploidentical-related donor by calculating disease-free survival based on these characteristics. In conclusion, HLA factors influence the success of haploidentical transplantation with PTCy. HLA-DRB1 and -DPB1 mismatching and HLA-C, -B leader, and -DQB1 matching are favorable. Consideration of HLA factors may help to optimize the selection of haploidentical related donors. KEY POINTS Introduction Improvements in HLA-haploidentical transplantation have increased its safety and efficacy for the treatment of lifethreatening hematologic cancers.1-8 Particularly, the use of cyclophosphamide after hematopoietic cell infusion (posttransplantation cyclophosphamide [PTCy]) has substantially reduced 1452 blood® 10 MARCH 2022 | VOLUME 139, NUMBER 10 severe acute and chronic graft-versus-host disease (GVHD) and is now the most widely used GVHD prevention strategy in haploidentical transplantation.9 A haploidentical family member shares 1 complete HLA haplotype with the patient and differs for a variable number of alleles on the nonshared haplotype. The probability that a patient has Downloaded from http://ashpublications.org/blood/article-pdf/139/10/1452/1879351/bloodbld2021013443.pdf by Adriana Seber on 10 March 2022 Ephraim J. Fuchs,1,* Shannon R. McCurdy,2,* Scott R. Solomon,3 Tao Wang,4,5 Megan R. Herr,6 Dipenkumar Modi,7 at least 1 haploidentical family member exceeds 90% because biologic parents and children by definition are haploidentical, and siblings and more distant relatives may be haploidentical.6 Haploidentical transplantation provides an expeditious therapy for patients, such as non-Caucasians, with a lower likelihood of identifying a suitable unrelated donor10-12 and patients who require urgent transplantation for high-risk disease. In 2019, the number of haploidentical transplantations performed in the US approached that of genotypically matched siblings.13 In contrast, haploidentical donors are currently selected on the basis of non-HLA factors, but information on the role of HLA in haploidentical transplantation is emerging.22-26 Although the number of HLA mismatches on the nonshared haplotype has not correlated with outcomes,27 the association of lower relapse with HLA-DRB1–mismatched haploidentical donors offers new insight into the mechanisms of graft-versus-host (GVH) allorecognition.7,22,24 Whether HLA mismatches in haploidentical transplantation confer similar effects on GVHD, relapse, and mortality as those observed in unrelated donor transplantation is unknown. We performed a retrospective analysis on the largest clinical cohort to date to study the effect of individual and combined HLA locus mismatching after haploidentical transplantation using PTCy. Our goal was to identify functional HLA characteristics that could help guide donor selection to improve the overall success of haploidentical transplantation. Biostatistical methods The primary clinical endpoints were survival without disease recurrence (“disease-free survival”) and overall survival. Secondary endpoints were acute (grades 2-4 and 3-4) and chronic GVHD (present/absent), relapse, and mortality from causes other than relapse (“transplant-related mortality”). Cox proportional hazards models were used to compare the hazards of failure between appropriate groups. Patients were censored at date of last follow-up or second transplant. All clinical variables known to potentially affect the endpoint of interest were tested first for the affirmation of the proportional hazard assumption including donor age, patient age, race/ethnicity, disease and stage, cytomegalovirus (CMV) serostatus, time from diagnosis to transplant, transplant comorbidity index,31 donor relationship, conditioning intensity, graft type, Karnofsky performance score, and sex matching (Table 1). Factors violating the proportional hazards assumption were adjusted through stratification. Following this, stepwise forward and backward elimination procedures were performed to determine the adjusted clinical variables (with a threshold of P 5 .05 for both entry and retention in the model). The total number of HLA-A, -B, -C, -DRB1, and -DQB1 allele mismatches and HLA-DPB1 TCE (non)permissive mismatches, all in the GVH vector, were also examined. Patients with missing data for a particular outcome were excluded from the appropriate regression analysis. Two-sided P values were obtained from the Wald test for Cox regression models. To adjust for multiple testing of HLA variables, an overall value of P of , .01 was considered significant. Informed consent Methods Patients and HLA typing HLA typing and clinical data were available from the Center for International Blood and Marrow Transplant Research for 1434 patients who received a haploidentical-related donor transplant with PTCy between January 2008 and December 2017 for the treatment of acute myeloid leukemia, acute lymphoblastic leukemia, or myelodysplastic syndrome (Table 1). Patients included in any prior analysis of HLA (mis)matching and outcomes were excluded from the current study. HLA-A, -B, -C, -DRB1, -DQB1, and -DPB1 alleles were typed as described and a mismatch was defined at the highest level of resolution of the allele.28 The HLA IN HAPLOIDENTICAL TRANSPLANTATION Informed consent was obtained from patients and donors in accordance with the Declaration of Helsinki. Protocols were approved by the institutional review boards of the National Institutes of Health Office for Human Research Protections and the National Marrow Donor Program Institutional review board. The funding agencies had no role in study design, data collection and analysis, the decision to submit the manuscript for publication, or the preparation of the manuscript. Results For the entire population of patients transplanted at 111 centers in this study, the 100-day cumulative incidence of grades 2-4 blood® 10 MARCH 2022 | VOLUME 139, NUMBER 10 1453 Downloaded from http://ashpublications.org/blood/article-pdf/139/10/1452/1879351/bloodbld2021013443.pdf by Adriana Seber on 10 March 2022 Most of the information on the importance of HLA in hematopoietic cell transplantation comes from analyses of the results of unrelated donor transplantations without PTCy. In that context, increasing numbers of donor HLA mismatches are detrimental to survival, and the clinical implications of specific HLA mismatches depend on the locus and sequence features of the mismatched alleles.14-16 The immunogenicity of a given HLA mismatch may relate to specific amino acid epitopes recognized by T cells and allogeneic HLA peptides presented by HLA.17,18 In the case of HLA-DPB1 (T-cell epitopes [TCE]), matching or permissive mismatching is associated with less acute GVHD and better survival but also higher disease recurrence (“relapse”) after unrelated transplantation.18-20 The importance of functional variation outside of the peptide-binding region is illustrated by a dimorphism unique to HLA-B leader peptides that differentially affects mortality after unrelated transplantation and cord blood transplantation and defines HLA-B mismatches that are better tolerated than others.15,16,21 presence of a GVH and host-versus-graft (HVG) vector of incompatibility was determined for each patient/donor HLA mismatch. Transplant pairs were defined as HLA-A, -B, -C, -DRB1, or -DQB1 mismatched in the GVH direction (bi- or unidirectional) vs matched (HLA matched or HVG unidirectional mismatch) for each locus. HLA-B mismatches were additionally defined as leader matched or leader mismatched.15 HLA-DPB1 typing was available for a total of 677 patient/donor pairs, of which 435 (64%) were retrospectively typed on available research samples from the National Marrow Donor Program repository as previously described.29 Several methods are available to define permissive and nonpermissive HLA-DPB1 mismatches.17-20 The TCE model was previously validated in unrelated donor transplants and was used to determine TCE nonpermissive or permissive mismatches and complete matches in the current study.19,20 The current study did not use HLA-DP expression to define permissive or nonpermissive mismatching.30 acute GVHD was 34.7% and 3-4 was 9.3%; the 1-year cumulative incidence of chronic GVHD was 25.8%; the 3-year cumulative incidences of nonrelapse mortality and of relapse were 19.7% and 39.1%, respectively, and the 3-year actuarial overall and disease-free survivals were 52.5% and 41.3%, respectively. Effect of the number of mismatches on clinical outcome We tested the hypothesis that the number of matched alleles informs clinical outcome. Compared with patients matched for 5 alleles, the hazard ratios (HRs) of relapse were 1.06 (95% confidence interval [CI], 0.87-1.28) for HLA-6/10 matches and 1.35 (95% CI, 1.08-1.69) for HLA-7/10 and higher matches (P 5 .03) (supplemental Table 1). The total number of matched alleles was not significantly associated with the risks of GVHD, diseasefree survival, transplant-related mortality, or overall mortality. Locus-specific risks To test the hypothesis that clinical outcomes differ based on the specific location (locus) of the HLA mismatch, we assessed the risks associated with patient/donor mismatching relative to matching at HLA-A, -B, -C, -DRB1, and -DQB1 individually (Figure 1; supplemental Table 2) and in multivariable analysis accounting as well for non-HLA factors (Table 2). The frequencies of HLA characteristics were similar across races/ethnicities and therefore were examined for the entire study population (Table 1). HLA-B was evaluated with both the classical definition of allele (mis)matching, which captures variation within the peptidebinding region, as well as leader (mis)matching. HLA mismatching at HLA-A, -B, or -DQB1 alone was not significantly associated with any clinical endpoint; however, when HLA-B was defined by leader match status, leader mismatching was associated with significantly lower overall survival (Figure 1A) (HR, 1.23; 95% CI, 1.07-2.18; P 5 .004) and higher transplant-related mortality (HR, 1.43; 95% CI, 1.13-1.82; P 5 .003) relative to leader matching. The effect of HLA-B mismatching was furthermore dissected from the effect of leader mismatching: compared with HLA-B–matched (ie, leader-matched) transplants, a leader-matched HLA-B allele or antigen mismatch was not associated with significantly increased risk of mortality (HR 0.93; 95% CI, 0.71-1.22; P 5 .62) or transplant-related mortality (HR 1.26; 95% CI, 0.56-2.85; P 5 0.57). These results suggest that HLA-B leader (mis)matching, more so than classic allele and antigen (mis)matching, is a clinically relevant model of immunogenicity for HLA-B. HLA-DRB1 mismatching in the GVH direction was associated with significantly lower relapse compared with matching (HR, 0.65; 95% CI, 0.53-0.80; P , .0001) (Table 2; Figure 1B). HLADPB1 TCE-nonpermissive mismatches were associated with improved overall survival relative to matches or TCE-permissive mismatches (HR, 0.59; 95% CI, 0.43-0.82; P 5 .002) (Table 2; Figure 1C). The risk of acute GVHD did not correlate with 1454 blood® 10 MARCH 2022 | VOLUME 139, NUMBER 10 In summary, the effects of HLA mismatching in the GVH direction depend on the mismatched locus. HLA-DRB1 mismatches decrease relapse and nonpermissive HLA-DPB1 mismatches decrease mortality. HLA-B leader matching lowers transplantrelated mortality and improves overall survival. These observations suggest different underlying mechanisms through which HLA-DRB1, -DPB1, and -B mismatches influence clinical outcome after haploidentical transplantation with PTCy. Two-locus mismatch combinations The effects of individual mismatches on specific clinical endpoints motivated us to examine 2-locus combinations for disease-free survival and relapse (HLA-B leader with HLA-DRB1) and survival (HLA-B leader with HLA-DPB1 TCE). The known strong positive linkage disequilibrium between HLA-DRB1 and HLA-DQB1 prompted additional dissection of locus-associated effects. The limited numbers of transplants with HLA-DPB1 typing precluded meaningful analysis of 3-way effects of HLA-B with HLA-DRB1 and HLA-DPB1. HLA-B leader with HLA-DRB1 We defined 4 transplant groups by the presence of concurrent (mis)matching for the HLA-B leader and HLA-DRB1: 152 (10.8%) leader-matched and HLA-DRB1–matched; 704 (50.2%) leader-matched but HLA-DRB1–mismatched; 62 (4.4%) leader-mismatched but HLADRB1–matched; and 484 (34.5%) leader-mismatched and HLADRB1–mismatched. The beneficial individual effects of HLA-B leader matching and HLA-DRB1 mismatching were additive for leader-matched/HLA-DRB1–mismatched patients who comprised more than half of the pairs in this unselected cohort and had superior disease-free survival and lower relapse compared with leader-mismatched/HLA-DRB1–matched patients (Figure 2). These data suggest that optimization of the HLA-B leader and HLA-DRB1 match status between patients and haploidentical donors may help to improve transplant outcomes even more for future patients. HLA-DRB1 with HLA-DQB1 The linkage disequilibrium between HLA-DRB1 and -DQB1 favors mismatching of both loci of the nonshared haplotype and less frequent mismatching at only HLA-DRB1 or -DQB1. Consistent with this genetic relationship, 983 (68.7%) of the transplant pairs were mismatched at both loci, 168 (11.7%) were matched at both, 49 (3.4%) were HLADRB1–matched/DQB1–mismatched, and 231 (16.2%) were HLA-DRB1–mismatched/DQB1–matched. HLA-DRB1–mismatched/ DQB1–matched patients had the highest disease-free survival (Table 3). HLA-B leader with HLA-DPB1 The combined effects of HLAB leader and HLA-DPB1 (mis)matching were studied in 4 patient groups: leader-matched/DPB1 nonpermissive mismatch; leadermatched/no DPB1 nonpermissive mismatch; leader-mismatched/ DPB1 nonpermissive mismatch; leader-mismatched/no DPB1 nonpermissive mismatch (supplemental Table 3). Survival was FUCHS et al Downloaded from http://ashpublications.org/blood/article-pdf/139/10/1452/1879351/bloodbld2021013443.pdf by Adriana Seber on 10 March 2022 Haploidentical patients and donors are matched for the 5 HLAA, -B, -C, -DRB1, and -DQB1 alleles of the shared haplotype and may be fortuitously matched for any number of alleles on the nonshared haplotype. The majority of pairs were matched for 5/10 (928, 65%) or 6/10 (314, 22%) alleles at HLA-A, -B, -C, -DRB1, and -DQB1. mismatching at any locus. The risk of chronic GVHD was higher with HLA-C mismatching compared with HLA-C matching (HR, 1.46; 95% CI, 1.17-1.83, P 5 .0008) (Figure 1D). The level of HLA-C expression correlated with transplant-related mortality and models adjusted for the expression level of the mismatch as previously described.32 blood® 10 MARCH 2022 | VOLUME 139, NUMBER 10 195 313 510 30-39 40-49 50-59 $60 574 Female Myelodysplastic syndrome Missing N/A - no disease risk index for patient characteristics Very high High Intermediate – cytogenetics not collected Intermediate Low 92 148 41 378 1 721 53 334 269 Acute lymphocytic leukemia Disease risk index 831 Acute myeloid leukemia Disease 860 Male Sex 54 135 18-29 Median (range) 73 159 10-17 49 n 0-10 Recipient age at transplant (yrs) Variable (6) (10) (3) (26) (,1) (50) (4) (19) (23) (58) (40) (60) (1-78) (36) (22) (14) (9) (11) (5) (3) (%) Full population (n 5 1434) Table 1. Demographics of the study population 55 81 26 238 1 445 32 163 206 509 352 526 55 319 195 123 83 92 42 24 n (6) (9) (3) (27) (,1) (51) (4) (19) (23) (58) (40) (60) (1-78) (36) (22) (14) (9) (10) (5) (3) (%) HLA-B-leader matched (n 5 878) 37 67 15 140 0 276 21 106 128 322 222 334 53 191 118 72 52 67 31 25 n (7) (12) (3) (25) (50) (4) (19) (23) (58) (40) (60) (1-78) (34) (21) (13) (9) (12) (6) (4) (%) HLA-B-leader mismatched (n 5 556) .68 .96 .95 .12 0.53 P 14 20 4 58 0 116 5 40 41 136 84 133 57 85 57 30 13 17 8 7 n (6) (9) (2) (27) (53) (2) (18) (19) (63) (39) (61) (1-78) (39) (26) (14) (6) (8) (4) (3) (%) HLA-DRB1 matched (n 5 217) Downloaded from http://ashpublications.org/blood/article-pdf/139/10/1452/1879351/bloodbld2021013443.pdf by Adriana Seber on 10 March 2022 HLA IN HAPLOIDENTICAL TRANSPLANTATION 1455 78 128 37 320 1 604 47 229 293 693 489 726 53 424 256 165 121 142 65 42 n (6) (11) (3) (26) (,1) (50) (4) (19) (24) (57) (40) (60) (1-78) (35) (21) (14) (10) (12) (5) (3) (%) HLA-DRB1 mismatched (n 5 1215) .79 .20 .67 .004 .13 P blood® 10 MARCH 2022 | VOLUME 139, NUMBER 10 FUCHS et al 325 190 191 1-2 y Greater than 2 y 401 292 Negative/positive Negative/negative 302 210 210 712 0 1 2 .3 Hematopoietic cell transplantation comorbidity index 10 119 Positive/negative Missing 612 75 6 212 Positive/positive Donor/recipient cytomegalovirus serostatus Missing Hispanic, African American Hispanic, White (,1) 6 6 Pacific islander, non-Hispanic Native American, non-Hispanic (50) (15) (15) (21) (1) (20) (28) (8) (43) (5) (,1) (15) (,1) (6) (16) (57) (13) (13) (23) (51) (%) 90 227 African American, non-Hispanic Asian, non-Hispanic 812 White, non-Hispanic Race/Ethnicity 728 7-12 mos n Full population (n 5 1434) 0-6 mos Time from diagnosis to transplant Variable Table 1. (continued) 438 128 115 197 4 174 252 74 374 41 4 126 3 3 63 135 503 111 120 192 455 n (50) (15) (13) (22) (,1) (20) (29) (8) (43) (5) (,1) (14) (,1) (,1) (7) (15) (57) (13) (14) (22) (52) (%) HLA-B-leader matched (n 5 878) 274 82 95 105 6 118 149 45 238 34 2 86 3 3 27 92 309 80 70 133 273 n (49) (15) (17) (19) (1) (21) (27) (8) (43) (6) (,1) (15) (1) (1) (5) (17) (56) (14) (13) (24) (49) (%) HLA-B-leader mismatched (n 5 556) .12 .61 .57 .53 P 108 32 26 51 1 43 65 18 90 12 1 19 2 0 15 43 125 24 32 44 117 n (50) (15) (12) (24) (,1) (20) (30) (8) (41) (6) (,1) (9) (1) (7) (20) (58) (11) (15) (20) (54) (%) HLA-DRB1 matched (n 5 217) Downloaded from http://ashpublications.org/blood/article-pdf/139/10/1452/1879351/bloodbld2021013443.pdf by Adriana Seber on 10 March 2022 1456 603 178 184 250 9 249 334 101 522 63 5 193 4 6 75 184 685 167 157 281 610 n (50) (15) (15) (21) (1) (20) (27) (8) (43) (5) (,1) (16) (,1) (,1) (6) (15) (56) (14) (13) (23) (50) (%) HLA-DRB1 mismatched (n 5 1215) .57 .95 .11 .45 P blood® 10 MARCH 2022 | VOLUME 139, NUMBER 10 814 43 Missing 820 Peripheral blood 808 Nonmyeloablative/reduced intensity 411 310 240 30-39 40-49 $50 Median (range) 35 2 343 20-29 Missing 128 0-19 Donor age (yrs) 3 467 Not collected Missing 15 Other relative 488 140 Parent Child 321 Sibling Donor relationship to recipient 626 Myeloablative Conditioning regimen intensity 614 Bone marrow Graft type 577 90-100 n (2-73) (,1) (17) (22) (29) (24) (9) (,1) (33) (1) (34) (10) (22) (56) (44) (57) (43) (3) (57) (40) (%) Full population (n 5 1434) 10-80 Karnofsky performance score (percent) Variable Table 1. (continued) 36 2 152 192 260 204 68 0 278 9 307 85 199 492 386 491 387 29 506 343 n (2-73) (,1) (17) (22) (30) (23) (8) (32) (1) (35) (10) (23) (56) (44) (56) (44) (3) (58) (39) (%) HLA-B-leader matched (n 5 878) 35 0 88 118 151 139 60 3 189 6 181 55 122 316 240 329 227 14 308 234 n (9-73) (16) (21) (27) (25) (11) (1) (34) (1) (33) (10) (22) (57) (43) (59) (41) (3) (55) (42) (%) HLA-B-leader mismatched (n 5 556) .05 .26 .31 .77 .23 .31 P 36 0 40 55 51 55 16 1 79 3 81 14 39 138 79 134 83 6 113 98 n (4-73) (18) (25) (24) (25) (7) (,1) (36) (1) (37) (6) (18) (64) (36) (62) (38) (3) (52) (44) (%) HLA-DRB1 matched (n 5 217) Downloaded from http://ashpublications.org/blood/article-pdf/139/10/1452/1879351/bloodbld2021013443.pdf by Adriana Seber on 10 March 2022 HLA IN HAPLOIDENTICAL TRANSPLANTATION 1457 35 2 200 255 360 286 112 2 386 12 407 126 282 669 546 685 530 37 701 477 n (2-73) (,1) (16) (21) (30) (24) (9) (,1) (32) (1) (33) (10) (23) (55) (45) (56) (44) (3) (58) (39) (%) HLA-DRB1 mismatched (n 5 1215) .32 .33 .15 .020 .14 .11 P blood® 10 MARCH 2022 | VOLUME 139, NUMBER 10 FUCHS et al 757 Missing Median, mo (range) No. evaluable 34 774 103 Nonpermissive GVH mismatch Follow-up among survivors 574 1 1032 401 2 1215 217 1168 No nonpermissive GVH mismatch HLA-DPB1 match status Missing Mismatched Matched HLA-DQB1 match status Missing Mismatched Matched HLA-DRB1 match status Mismatched Matched 266 556 HLA-C match status 878 Mismatched 1261 173 1170 264 n (2-119) (53) (7) (40) (,1) (72) (28) (,1) (85) (15) (81) (19) (39) (61) (88) (12) (82) (18) (%) Full population (n 5 1434) Matched HLA-B leader match status Mismatched Matched HLA-B match status Mismatched Matched HLA-A match status Variable Table 1. (continued) 35 492 450 57 371 0 628 250 2 722 154 688 190 0 878 738 140 718 160 n (4-111) (51) (6) (42) (0) (72) (28) (,1) (82) (18) (78) (22) (0) (100) (84) (16) (82) (18) (%) HLA-B-leader matched (n 5 878) 33 282 307 46 203 1 404 151 0 493 63 480 76 556 0 523 33 452 104 n (2-119) (55) (8) (37) (,1) (73) (27) (0) (89) (11) (86) (14) (100) (0) (94) (6) (81) (19) (%) HLA-B-leader mismatched (n 5 556) .23 .25 .40 .003 ,.001 ,.001 .82 P 31 110 130 15 72 0 49 168 0 0 217 151 66 63 154 168 49 180 37 n (11-73) (60) (7) (33) (0) (23) (77) (0) (0) (100) (70) (30) (29) (71) (77) (23) (83) (17) (%) HLA-DRB1 matched (n 5 217) Downloaded from http://ashpublications.org/blood/article-pdf/139/10/1452/1879351/bloodbld2021013443.pdf by Adriana Seber on 10 March 2022 1458 34 662 625 88 502 1 983 231 0 1215 0 1016 199 493 722 1091 124 988 227 n (2-119) (51) (7) (41) (,1) (81) (19) (0) (100) (0) (84) (16) (41) (59) (90) (10) (81) (19) (%) HLA-DRB1 mismatched (n 5 1215) .40 .14 ,.001 ,.001 .001 ,.001 .57 P A HLA-B leader and overall survival Adjusted probability, % 100 p=0.0025 80 Match (n=871) 60 Mismatch (n=553) 40 20 0 1 2 3 Years # at risk Match 871 711 594 525 426 291 227 Mismatch 553 432 346 302 239 164 118 B HLA-DRB1 and relapse Adjusted cumulative incidence, % 100 p<0.0001 80 60 No GVH mismatch (n=214) 40 GVH mismatch (n=1188) 20 0 0 1 2 3 Years # at risk No GVH mismatch 214 137 105 87 70 46 31 GVH mismatch 1188 821 661 572 453 318 237 Figure 1. HLA-B, -DRB1, -DPB1, and -C mismatching and clinical outcome. Adjusted probabilities are derived from multivariable models. (A) HLA-B leader and overall survival. (B) HLA-DRB1 and relapse. (C) HLA-DPB1 and overall survival. (D) HLA-C and chronic GVHD. Survival models (A, C) were adjusted for comorbidities, disease type and status, recipient and donor age, recipient-donor cytomegalovirus match, time from diagnosis to transplant and stratified by graft type. Model A was also adjusted for HLA-DPB1. Model C was also adjusted for HLA-B leader. Relapse model (B) adjusted for conditioning intensity and time from diagnosis to transplant and stratified for disease type and status. Chronic GVHD model (D) was adjusted for disease type, recipient age, recipient-donor sex match, time from diagnosis to transplant, and graft type. superior for leader-matched/nonpermissive mismatched compared with any other combination. The optimal haploidentical donor and a tool for prospective donor selection Contrasting in part to the unrelated donor setting, disease-free survival is optimized when a haploidentical donor is HLA-B leader-matched, HLA-DRB1–mismatched, HLA-DQB1–matched, and HLA-DPB1 TCE-non permissive–mismatched (Table 3). Furthermore, a CMV2 donor is preferred for CMV2 patients. Donor age was not associated with disease-free survival (P 5 .23), nor was donor relationship (P 5 .88). Because it is difficult to simultaneously consider all HLA and clinical factors, we developed an online calculator in R Shiny using the R-based statistical models for research purposes to aid prospective selection of haploidentical donors for patients undergoing PTCy-based HLA IN HAPLOIDENTICAL TRANSPLANTATION haploidentical transplantation for acute leukemia or myelodysplastic syndrome (http://haplodonorselector.b12x.org/v1. 0/). Based on the patient and donor information entered, 1and 2-year disease-free survivals are estimated from the haploidentical transplants in the current study, aiding in the prioritization of candidate donors (supplemental Figure 1). The online calculator automates HLA-B leader and HLA-DPB1 TCE match assignment. Results of donor rankings can be exported for user convenience. Discussion The development of GVHD prophylaxis regimens that allow safe crossing of the HLA barrier has provided a life-saving therapy for patients who lack matched sibling and unrelated donors, blood® 10 MARCH 2022 | VOLUME 139, NUMBER 10 1459 Downloaded from http://ashpublications.org/blood/article-pdf/139/10/1452/1879351/bloodbld2021013443.pdf by Adriana Seber on 10 March 2022 0 C HLA-DPB1 and overall survival Adjusted probability, % 100 p=0.0028 Non-permissive GVH mismatch (n=102) 80 60 No non-permissive GVH mismatch (n=570) 40 20 0 1 2 3 Years # at risk No non-permissive 570 GVH mismatch Non-permissive 102 GVH mismatch 452 368 319 258 172 129 90 79 66 53 33 26 D HLA-C and chronic GVHD Adjusted cumulative incidence, % 100 p=0.0008 80 60 40 GVH mismatch (n=1149) 20 No GVH mismatch (n=260) 0 0 1 2 3 Years # at risk No GVH mismatch 260 183 131 100 74 50 32 GVH mismatch 1149 732 475 384 291 194 149 Figure 1. Continued especially patients with less common alleles and haplotypes and patients from races and ethnicities that are under-represented in unrelated donor registries. In particular, the low toxicity and ease of giving PTCy has advanced haploidentical relatives as the preferred alternative donors for many clinical centers worldwide.1,3,9 Patients often have more than 1 available haploidentical donor, and selection is currently based on non-HLA characteristics. Data on the role of HLA and transplant success are emerging and may help further refine haploidentical donor selection algorithms. Although high-resolution HLA matching clearly improves the outcome of unrelated donor transplantation without PTCy,15 the current study sought to understand the role of high-resolution HLA mismatching in the setting of haploidentical transplantation with PTCy. We found that the match status at HLA-C, -B, -DRB1, -DQB1, and -DPB1 each impact outcome 1460 blood® 10 MARCH 2022 | VOLUME 139, NUMBER 10 and that the effects of particular combinations of loci are independent and important. Our findings have implications not only for clinical practice and donor selection but also provide new information on the potential biological mechanisms through which HLA gene products participate in the transplantation barrier. We identified novel associations of HLA-C and -B with clinical outcome after haploidentical transplantation with PTCy and furthermore confirmed previous observations for HLA-DRB1 and -DPB1.5,27 The association of HLA-C mismatching with chronic GVHD risk mirrors its effects after unrelated donor transplantation performed with traditional methotrexate-based GVHD prevention.16 The association of HLA-C expression level with transplant-related mortality in the current haploidentical-related FUCHS et al Downloaded from http://ashpublications.org/blood/article-pdf/139/10/1452/1879351/bloodbld2021013443.pdf by Adriana Seber on 10 March 2022 0 blood® 10 MARCH 2022 | VOLUME 139, NUMBER 10 1461 — 1.0 (P , .0001) 0.72 (0.38-1.35; .30) 2.04 (1.44-2.88; .0001) 0.66 (0.42-1.03; .07) 1.17 (0.59-2.32; .65) 1.95 (0.73-5.25; .18) 0.70 (0.36-1.35; .29) 1.51 (1.10-2.06; .10) — — — — — — — — 1.0 (P , .0001) 1.10 (0.76-1.60; .60) 2.10 (1.60-2.75; ,.0001) 0.56 (0.41-0.76; .0002) 1.59 (1.04-2.43; .03) 2.51 (1.60-3.93; .0001) 1.22 (0.85-1.76; .28) 1.33 (1.05-1.68; .02) AML/CR1 AML/CR2, CR3 AML/advanced ALL/CR1 ALL/CR2 ALL/$CR3 MDS/early MDS/advanced 0.98 (0.66-1.44; .90) — — — — MDS — — — 1.0 (P 5 .085) 1.62 (1.13-2.32; .008) 50-59 — — 1.33 (1.03-1.71; .03) 1.52 (1.06-2.18; .02) 40-49 — — — 1.46 (1.17-1.83; .0008) 1.0 — ALL 1.35 (0.97-1.87; .07) — — 1.04 (1.02-1.07; .0003) — — — — — — — — — Chronic GVHD AML 1.32 (0.94-1.85; .11) — — — — Match Mismatch 30-39 0.65 (0.53-0.80; ,.0001) — GVH mismatch 20-29 1 — Match/HVG mismatch 1.0 (P 5 .05) — — 0.92 (0.81-1.06; .26) Missing ,20 — — 0.59 (0.43-0.82; .002) TCE nonpermissive — — — 1.0 (P 5 .006) TCE match or permissive 1.43 (1.13-1.82; .003) — 1.24 (1.08-1.43; .003) Mismatch 1.0 — 1.0 Transplant-related mortality Relapse Match Mortality The model for mortality is stratified by graft source, and the model for relapse is stratified by disease type and stage. P values in reference group rows represent the whole group comparison for the variable of interest on the designated outcome. AML, acute myeloid leukemia; ALL, acute lymphoblastic leukemia; MDS, myelodysplastic syndrome; CR, complete remission. Disease/stage Disease type Donor age (y) Recipient HLA-C MFI (by 10 increment) HLA-C HLA-DRB1 HLA-DPB1 HLA-B leader Variable Hazard ratio (95% confidence interval; P) Table 2. Multivariable models for mortality, relapse, transplant-related mortality, and chronic GVHD Downloaded from http://ashpublications.org/blood/article-pdf/139/10/1452/1879351/bloodbld2021013443.pdf by Adriana Seber on 10 March 2022 HLA IN HAPLOIDENTICAL TRANSPLANTATION blood® 10 MARCH 2022 | VOLUME 139, NUMBER 10 FUCHS et al 0.84 (0.70-1.00; .04) 0.39 (0.24-0.64; .0002) 1.06 (0.83-1.36; .64) 0.85 (0.66-1.10; .21) 0.69 (0.48-0.98; .04) 6-12 12-24 .24 — 1.0 (P , .0001) 1.18 (0.58-2.41; .65) 0.88 (0.40-1.92; .74) 1.29 (0.57-2.94; .54) 1.77 (0.78-4.01; .17) — — — — — — — — — — 1.0 1.57 (1.33-1.86; ,.0001) — — — — — — 1.0 (P , .0001) 0.81 (0.53-1.24; .33) 0.77 (0.53-1.11; .16) 0.80 (0.54-1.20; .29) 1.05 (0.72-1.52; .80) 1.34 (0.90-2.00; .15) — — — — Male/male Male/female Female/male Female/female 1-18 19-29 30-39 40-49 50-59 $60 Myeloablative Reduced intensity/ nonmyeloablative Marrow Peripheral blood stem cells — — 0.72 (0.54-0.96; .03) 1.0 2.88 (1.34-6.17; .007) — — — — 2.19 (1.43-3.34; .0003) — 1.68 (1.30-2.18; .0001) $3 1.84 (1.17-2.89; .008) — 1.42 (1.09-1.84; .009) 2 1.0 (P 5 .003) 1.54 (0.96-2.46; .07) — — 1.0 (P 5 .0006) 1.29 (0.99-1.67; .06) 0 2.33 (1.61-3.37; ,.0001) 1.0 — — 0.77 (0.43-1.38; .39) 0.83 (0.48-1.46; .53) 1.20 (0.71-2.03; .49) 0.77 (0.42-1.39; .38) 0.84 (0.50-1.41; .50) 1.0 (P 5 .02) 1.33 (0.99-1.79; .05) 1.36 (1.06-1.74; .02) 1.28 (0.95-1.72; .11) 1.0 (P 5 .09) — — — — 1.41 (1.09-1.82; .009) 0.97 (0.75-1.25; .79) 1.44 (1.14-1.81; .002) — — 1.0 (P 5 .0004) — — — — — Chronic GVHD — 1 0.54 (0.39-0.75; .0003) 1.0 (P 5 .0003) 1.0 (P 5 .04) #6 1.66 (0.70-3.90; .25) — 1.53 (0.78-3.03; .22) Missing 0.50 (0.32-0.78; .002) — 0.68 (0.53-0.86; .001) 0.75 (0.54-1.05; .10) — Negative/negative 1.22 (0.78-1.91; .39) — 0.93 (0.71-1.22; .59) 0.96 (0.79-1.16; .67) Positive/negative 1.0 (P 5 .0001) — 1.0 (P 5 .001) Negative/positive Positive/positive Relapse Mortality Transplant-related mortality Hazard ratio (95% confidence interval; P) The model for mortality is stratified by graft source, and the model for relapse is stratified by disease type and stage. P values in reference group rows represent the whole group comparison for the variable of interest on the designated outcome. AML, acute myeloid leukemia; ALL, acute lymphoblastic leukemia; MDS, myelodysplastic syndrome; CR, complete remission. Graft source Conditioning regimen Patient Age (y) Donor/patient sex HCT comorbidity index Time from diagnosis to transplant (mos). Donor/patient CMV serostatus Variable Table 2. (continued) Downloaded from http://ashpublications.org/blood/article-pdf/139/10/1452/1879351/bloodbld2021013443.pdf by Adriana Seber on 10 March 2022 1462 The selection of haploidentical donors based on HLA requires no additional testing beyond the current standards which include high-resolution definition of HLA-A, -B, -C, -DRB1, and -DQB1. Typing of HLA-DPB1 is currently included with nextgeneration HLA typing platforms. The assignment of the HLA-B leader furthermore requires no additional testing of the locus, and new tools are available to automate the assignment of the leader to each allele.47 When multiple haploidentical family members are available, our results may be applied to prioritize the donor providing the highest likelihood of a successful transplant. With prospective consideration of HLA-B leader matching and HLA-DRB1 mismatching, the proportion of transplants with both favorable features is likely to greatly increase the 50% observed in the current study. The recent discovery of the HLA-B leader as a transplantation determinant in unrelated donor and cord blood transplantation has provided insight into the potential mechanisms underlying alloresponses.15,16,21 The current study shows that HLA-B influences clinical outcome after haploidentical transplantation through its leader and not through classical allele matching.7 In the setting of PTCy, mismatching within the peptide-binding region of HLA-B is not associated with GVHD risk, suggesting a potential contribution of pathways that involve the recognition of nonclassical class 1 ligands by natural killer (NK) cells.36,37 Although this study did not characterize the potential for NK cell alloreactivity to mediate antileukemia effects, the lack of association of HLA-C mismatch with relapse is consistent with the finding that alloreactive single–killer immunoglobulin-like receptor–positive NK cells are eliminated by PTCy and do not contribute significantly to relapse prevention.38 Our current tool provides estimates of disease-free survival based on HLA and non-HLA characteristics in the patient and donor and will facilitate a rank ordering of preferred donors based on the best available data. The tool automates assignment of HLA-B leader genotype and HLA-DPB1 TCE status to further simplify data entry. Results of HLA antibody testing were not available to us and so were not incorporated into the selection model. In light of the association of donor-specific HLA antibodies with graft rejection and poor transplantation outcomes, a donor should not be selected if the patient has high-level antibody against that donor’s HLA molecules. Likewise, data on killer immunoglobulin-like receptor gene polymorphisms in the donor were not available to us, but their impact on donor selection should be investigated in the future as these polymorphisms may affect NK cell alloreactivity and the outcome of haploidentical transplantation. We confirmed the beneficial effect of HLA-DRB1 mismatching on lower relapse in an independent patient population.7,24,27 Furthermore, we found that the protective effect of HLA-DRB1 mismatching is greatest among HLA-DQB1–matched patients, suggesting that one should first consider HLA-DRB1–mismatched potential donors, then select a HLA-DQB1–matched donor if available. The dissociation of GVHD from relapse with HLA-DRB1 mismatching provides a model for understanding the mechanisms underlying graft-versus-leukemia in the setting of PTCy. We previously observed improved event-free survival among patients transplanted from HLA-DRB1 mismatched donors27 and hypothesized that donor alloreactive CD41 T cells help effector cells to mount cytotoxic elimination of residual host leukemia. Alloreactive donor CD41 T cells can provide help to reverse exhaustion in the patient’s tumor-specific CD81 T cells,39-42 potentially explaining the observed dissociation of graft-versus-leukemia effects from GVHD. The differential effects of HLA-DRB1 vs HLA-DQB1 mismatching on relapse may relate to the higher cell surface expression of HLA-DRB1;43 with fewer HLA-DQB1 molecules on the cell surface, CD41 T cells alloreactive against HLA-DQ may be unable to deliver effective help to cytotoxic effector cells. The demonstration that downregulation of HLA class II antigens from host cells is an immune escape mechanism further showcases the vigorous role of class II recognition in antileukemic recognition.24,44-46 The association of HLA-DPB1 nonpermissive T-cell epitopes with improved survival confirms previous studies and suggests mechanisms involving direct recognition of these highly immunogenic motifs of HLA-DP molecules.18-20 HLA IN HAPLOIDENTICAL TRANSPLANTATION The current study examined the effect of HLA features in patients who received a haploidentical transplant with PTCy for the treatment of acute leukemia or myelodysplastic syndrome. The study population was the largest available cohort not previously examined for HLA factors; however, the numbers of transplants matched for the HLA-B leader, DRB1, and DQB1 were limited, and our findings warrant confirmation in independent populations. Although the associations of HLA-DPB1 to outcome mirrored those observed in other cohorts, the low number of HLA-DPB1–typed pairs in the current study limited the ability to investigate synergistic effects of multilocus mismatching. Furthermore, although the current study used the TCE model to evaluate the effects of HLA-DPB1 mismatching, the role of HLADPB1 expression levels of outcomes of haploidentical transplantation is an area of interest for future study.30 Future analysis of patients receiving haploidentical transplantation for other blood disorders or regimens will also provide new information on the immunogenicity of HLA factors. Given that PTCy modifies the effect of HLA mismatching on outcomes in haploidentical transplantation, further exploration of the effects of mismatching in unrelated donor transplantation utilizing PTCy is also warranted. We hypothesize that the effects of HLA matching in unrelated donor transplantation using traditional immunosuppression may shift when PTCy is employed, and future studies of the significance of HLA factors in allogeneic transplantation using PTCy are needed to reassess the “ideal” donor. This is especially relevant because it may be easier to identify optimal combinations of (mis)matches among large blood® 10 MARCH 2022 | VOLUME 139, NUMBER 10 1463 Downloaded from http://ashpublications.org/blood/article-pdf/139/10/1452/1879351/bloodbld2021013443.pdf by Adriana Seber on 10 March 2022 donor cohort mirrors the findings previously observed in unrelated donor transplantation and suggests that the level of expression of the mismatched HLA-C allele is functional.32 The lack of association of HLA mismatching with acute GVHD is striking. Potential mechanisms by which PTCy reduces acute GVHD include destruction of proliferating alloreactive T cells33 and/or preservation of regulatory T cells34 and suggests the efficacy of PTCy in ameliorating early alloimmune responses. The reason why PTCy does not abrogate the association of HLA-C mismatching with chronic GVHD is not clear but may relate to the late breakdown of thymic clonal deletion of GVH-reactive cells and their reemergence in the periphery late after PTCy.35 More detailed mechanistic studies will be required to correlate PTCyinduced molecular and cellular events with clinical outcomes. A Overall survival Adjusted probability, % 100 p=0.028 80 60 40 No HLA-DRB1 GVH mismatch, B-leader match (n=153) No HLA-DRB1 GVH mismatch, B-leader mismatch (n=62) HLA-DRB1 GVH mismatch, B-leader match (n=716) HLA-DRB1 GVH mismatch, B-leader mismatch (n=491) 20 0 1 2 3 Downloaded from http://ashpublications.org/blood/article-pdf/139/10/1452/1879351/bloodbld2021013443.pdf by Adriana Seber on 10 March 2022 0 Years # at risk No HLA-DRB1 153 GVH mismatch, B-leader match 126 103 87 69 45 32 62 51 38 33 28 20 16 HLA-DRB1 716 GVH mismatch, B-leader match 583 489 436 356 245 194 HLA-DRB1 491 GVH mismatch, B-leader mismatch 381 308 269 211 144 102 No HLA-DRB1 GVH mismatch, B-leader mismatch B Disease-free survival Adjusted probability, % 100 p=0.0058 80 60 40 No HLA-DRB1 GVH mismatch, B-leader match (n=152) No HLA-DRB1 GVH mismatch, B-leader mismatch (n=62) HLA-DRB1 GVH mismatch, B-leader match (n=704) HLA-DRB1 GVH mismatch, B-leader mismatch (n=484) 20 0 0 1 2 3 Years # at risk No HLA-DRB1 152 GVH mismatch, B-leader match 104 81 64 50 30 18 62 33 24 23 20 16 13 HLA-DRB1 704 GVH mismatch, B-leader match 495 411 357 283 203 156 HLA-DRB1 484 GVH mismatch, B-leader mismatch 326 250 215 170 115 81 No HLA-DRB1 GVH mismatch, B-leader mismatch Figure 2. Effect of concurrent (mis)matching for the HLA-B leader and HLA-DRB1. (A) Overall survival. (B) Disease-free survival. (C) Relapse. (D) Transplant-related mortality. Probabilities are derived from multivariable models that adjusted for HLA-DPB1 mismatching. Survival model (A) was adjusted for comorbidities, disease type and status, recipient and donor age, recipient-donor cytomegalovirus match, time from diagnosis to transplant, HLA-DPB1, and stratified by graft type. Disease-free survival model (B) was adjusted for comorbidities, recipient age, recipient-donor cytomegalovirus match, donor relationship, and HLA-DPB1 and stratified by disease type and status. Relapse model (C) was adjusted for conditioning intensity and time from diagnosis to transplant and stratified by disease type and status. Transplant-related mortality model (D) was adjusted for comorbidities, conditioning intensity, disease type and status, recipient age, recipient-donor cytomegalovirus match, and recipient mean HLA-C surface expression. 1464 blood® 10 MARCH 2022 | VOLUME 139, NUMBER 10 FUCHS et al C Relapse Adjusted cumulative incidence, % 100 p=0.0003 No HLA-DRB1 GVH mismatch, B-leader match (n=152) No HLA-DRB1 GVH mismatch, B-leader mismatch (n=62) HLA-DRB1 GVH mismatch, B-leader match (n=704) HLA-DRB1 GVH mismatch, B-leader mismatch (n=484) 80 60 40 20 0 1 2 Downloaded from http://ashpublications.org/blood/article-pdf/139/10/1452/1879351/bloodbld2021013443.pdf by Adriana Seber on 10 March 2022 0 3 Years # at risk No HLA-DRB1 152 GVH mismatch, B-leader match 104 81 64 50 30 18 62 33 24 23 20 16 13 HLA-DRB1 704 GVH mismatch, B-leader match 495 411 357 283 203 156 HLA-DRB1 484 GVH mismatch, B-leader mismatch 326 250 215 170 115 81 No HLA-DRB1 GVH mismatch, B-leader mismatch D Transplant-related mortality Adjusted cumulative incidence, % 100 p=0.035 80 60 No HLA-DRB1 GVH mismatch, B-leader match (n=152) No HLA-DRB1 GVH mismatch, B-leader mismatch (n=62) HLA-DRB1 GVH mismatch, B-leader match (n=704) HLA-DRB1 GVH mismatch, B-leader mismatch (n=484) 40 20 0 0 1 2 3 Years # at risk No HLA-DRB1 152 GVH mismatch, B-leader match 104 81 64 50 30 18 62 33 24 23 20 16 13 HLA-DRB1 704 GVH mismatch, B-leader match 495 411 357 283 203 156 HLA-DRB1 484 GVH mismatch, B-leader mismatch 326 250 215 170 115 81 No HLA-DRB1 GVH mismatch, B-leader mismatch Figure 2. Continued HLA IN HAPLOIDENTICAL TRANSPLANTATION blood® 10 MARCH 2022 | VOLUME 139, NUMBER 10 1465 Table 3. Multivariate model for disease-free survival. The prospective selection of haploidentical donors may include consideration for the characteristics that most strongly influence disease-free survival. Estimates of disease-free survival may be calculated for a given patient based on patient and donor characteristics shown below (http://haplodonorselector.b12x.org/v1.0/) Characteristic N Hazard ratio (95% confidence interval; P) [global P 5 .01] HLA-B leader match status Leader-matched 856 1.0 Leader-mismatched 545 1.20 (1.04-1.37; .01) [global P 5 .003] HLA-DRB1/DQB1 match status* 959 1.0 Mismatch/match 228 0.80 (0.67-0.95; .01) 48 1.30 (0.95-1.78; .10) 166 1.32 (1.05-1.65; .02) Match/mismatch Match/match [global P 5 .04] HLA-DPB1 TCE status No nonpermissive GVH mismatch 562 1.0 Nonpermissive GVH mismatch 101 0.72 (0.56-0.93; .01) Missing data 738 0.97 (0.85-1.12; .71) [global P 5 .005] Patient/donor CMV serostatus Positive/positive 596 1.0 Positive/negative 116 1.00 (0.78-1.28; .98) Negative/positive 393 1.10 (0.93-1.30; .25) Negative/negative 286 0.79 (0.61-1.03; .08) 10 1.30 (0.77-2.21; .33) Missing data [global P , .0001] Patient comorbidity index 0 298 1.0 1 205 1.21 (0.96-1.52; .11) 2 209 1.24 (0.98-1.58; .07) $3 689 1.54 (1.27-1.87; ,.0001) [global P 5 .0001] Patient age (years) 0-18 121 1.0 19-29 155 1.03 (0.73-1.46; .85) 30-39 128 0.99 (0.70-1.41; .97) 40-49 191 0.90 (0.64-1.26; .54) 50-59 307 1.07 (0.74-1.53; .73) $60 499 1.41 (0.94-2.11; .09) *Match/mismatch relative to match/match: HR 0.98 (0.70-1.39; .93); mismatch/match relative to match/match: HR 0.61 (0.46-0.80; .0004); and mismatch/match relative to match/ mismatch: HR 0.62 (0.43-0.88; .007). registries of unrelated donors than among a more restricted number of haploidentical-related donors. In summary, the outcome of haploidentical transplantation using PTCy is improved when the donor is HLA-B leader-matched, HLADRB1 mismatched, HLA-DQB1 matched, and nonpermissive TCE HLA-DPB1 mismatched. These novel data provide a means to optimize donor selection and clinical outcomes for future patients. Acknowledgments This work was supported by grants AI069197 (E.W.P., Y.-T.B., T.W., and C.M.), CA100019 (E.W.P.), and CA218285 (E.W.P.) from the National 1466 blood® 10 MARCH 2022 | VOLUME 139, NUMBER 10 Institutes of Health (NIH), National Cancer Institute (NCI). The Center for International Blood and Marrow Transplant Research (CIBMTR) is supported primarily by Public Health Service U24CA076518 from the NIH/ NCI, the NIH/National Heart, Lung and Blood Institute (NHLBI), and the NIH/National Institute of Allergy and Infectious Diseases (NIAID), HHSH250201700006C from the Health Resources and Services Administration (HRSA), and N00014-20-1-2705 and N00014-20-1-2832 from the Office of Naval Research. Additional federal support is provided by R01AI128775, R01HL130388, and the Biomedical Advanced Research and Development Authority (BARDA). Support is also provided by Be the Match Foundation, the Medical College of Wisconsin the National Marrow Donor Program, and from the following commercial entities: Actinium Pharmaceuticals, Inc; Adienne SA; Allovir, Inc; Amgen, Inc; Angiocrine Bioscience; Astellas Pharma US; bluebird bio, Inc; Bristol Myers Squibb Co; Celgene Corp; CSL Behring, CytoSen Therapeutics, FUCHS et al Downloaded from http://ashpublications.org/blood/article-pdf/139/10/1452/1879351/bloodbld2021013443.pdf by Adriana Seber on 10 March 2022 Mismatch/mismatch Inc.; Daiichi Sankyo Co, Ltd; ExcellThera; Fate Therapeutics; GamidaCell, Ltd; Genentech, Inc; Incyte Corporation; Janssen/Johnson & Johnson; Jazz Pharmaceuticals, Inc; Kiadis Pharma; Kite, a Gilead Company; Kyowa Kirin; Legend Biotech; Magenta Therapeutics; Merck Sharp & Dohme Corp; Millennium, the Takeda Oncology Co; Miltenyi Biotec, Inc; Novartis Pharmaceuticals Corporation; Omeros Corporation; Oncoimmune, Inc; Orca Biosystems, Inc; Pfizer, Inc; Pharmacyclics, LLC; Sanofi Genzyme; Stemcyte; Takeda Pharma; Vor Biopharma; and Xenikos BV. The views expressed in this article do not reflect the official policy or position of the National Institutes of Health, the Department of the Navy, the Department of Defense, Health Resources and Services Administration, or any other agency of the US Government. Authorship Conflict-of-interest disclosure: The authors declare no competing financial interests. ORCID profiles: T.W., 0000-0002-2596-6843; M.R.H., 0000-0001-57689396; D.M., 0000-0001-6525-8844; T.N., 0000-0002-2621-7924; C.M., REFERENCES 1. Luznik L, O’Donnell PV, Fuchs EJ. Posttransplantation cyclophosphamide for tolerance induction in HLA-haploidentical BMT. Semin Oncol. 2012;39:683-693. 2. Locatelli F, Bauquet A, Palumbo G, Moretta F, Bertaina A. Negative depletion of a/b1 T cells and of CD191 B lymphocytes: a novel frontier to optimize the effect of innate immunity in HLA-mismatched hematopoietic stem cell transplantation. Immunol Lett. 2013;155(1-2):21-23. 3. Bashey A, Zhang X, Sizemore CA, et al. T-cell-replete HLA-haploidentical hematopoietic transplantation for hematologic malignancies using post-transplantation cyclophosphamide results in outcomes equivalent to those of contemporaneous HLA-matched related and unrelated donor transplantation. J Clin Oncol. 2013;31(10): 1310-1316. 4. McCurdy SR, Kanakry JA, Showel MM, et al. Risk-stratified outcomes of nonmyeloablative HLA-haploidentical BMT with high-dose posttransplantation cyclophosphamide. Blood. 2015;125(19):3024-3031. 5. Lorentino F, Labopin M, Fleischhauer K, et al. The impact of HLA matching on outcomes of unmanipulated haploidentical HSCT is modulated by GVHD prophylaxis. Blood Adv. 2017;1(11):669-680. 6. Elmariah H, Kasamon YL, Zahurak M, et al. Haploidentical Bone Marrow Transplantation with Post-Transplant Cyclophosphamide Using Non-First-Degree Related Donors. Biol Blood Marrow Transplant. 2018;24(5): 1099-1102. 7. Solomon SR, Aubrey MT, Zhang X, et al. Class II HLA mismatch improves outcomes following haploidentical transplantation with posttransplant cyclophosphamide. Blood Adv. 2020;4(20):5311-5321. HLA IN HAPLOIDENTICAL TRANSPLANTATION Correspondence: Effie W. Petersdorf, Fred Hutchinson Cancer Research Center, Division of Clinical Research, 1100 Fairview Avenue North, Seattle, WA 98109; e-mail: [email protected]. Footnotes Submitted 30 July 2021; accepted 18 October 2021; prepublished online on Blood First Edition 1 November 2021. DOI 10.1182/blood. 2021013443. *E.J.F. and S.R.M. contributed equally to this study. The final analysis dataset will be posted to the CIBMTR website at https://www.cibmtr.org/ReferenceCenter/PubList/PubDsDownload/ Pages/default.aspx. The online version of this article contains a data supplement. There is a Blood Commentary on this article in this issue. 8. Fuchs EJ, O’Donnell PV, Eapen M, et al. Double unrelated umbilical cord blood vs HLA-haploidentical bone marrow transplantation: the BMT CTN 1101 trial. Blood. 2021; 137(3):420-428. 9. D'Souza, A, Fretham C, Lee SJ, et al. Current Use of and Trends in Hematopoietic Cell Transplantation in the United States. Biol Blood Marrow Transplant. 2020;26(8): e177-e182. 10. Gragert L, Eapen M, Williams E, et al. HLA match likelihoods for hematopoietic stemcell grafts in the U.S. registry. N Engl J Med. 2014;371(4):339-348. 11. Dew A, Collins D, Artz A, et al. Paucity of HLA-identical unrelated donors for AfricanAmericans with hematologic malignancies: the need for new donor options. Biol Blood Marrow Transplant. 2008;14(8):938-941. 12. Solomon SR, Martin AS, Zhang MJ, et al. Optimal donor for African Americans with hematologic malignancy: HLA-haploidentical relative or umbilical cord blood transplant. Biol Blood Marrow Transplant. 2020;26(10): 1930-1936. 13. Center for International Blood and Marrow Transplant Research. The US Summary Slides – HCT Trends and Survival Data. https://www.cibmtr.org/ReferenceCenter/ SlidesReports/SummarySlides/pages/index. aspx. Accessed 17 March 2021. 14. Lee SJ, Klein J, Haagenson M, et al. Highresolution donor-recipient HLA matching contributes to the success of unrelated donor marrow transplantation. Blood. 2007; 110(13):4576-4583. 15. Petersdorf EW, Carrington M, O’hUigin C, et al; International Histocompatibility Working Group in Hematopoietic Cell Transplantation. Role of HLA-B exon 1 in graft-versus-host disease after unrelated haemopoietic cell transplantation: a retrospective cohort study. Lancet Haematol. 2020;7(1):e50-e60. 16. Petersdorf EW, Stevenson P, Bengtsson M, et al. HLA-B leader and survivorship after HLA-mismatched unrelated donor transplantation. Blood. 2020;136(3):362-369. 17. Rimando J, Slade M, DiPersio JF, et al. The Predicted Indirectly Recognizable HLA Epitopes (PIRCHE) Score for HLA class I graft-versus-host disease in haploidentical transplantation with post-transplantation cyclophosphamide. Biol Blood Marrow Transplant. 2020;26(1):123-131. 18. Fleischhauer K, Shaw BE, Gooley T, et al; International Histocompatibility Working Group in Hematopoietic Cell Transplantation. Effect of T-cell-epitope matching at HLA-DPB1 in recipients of unrelated-donor haemopoietic-cell transplantation: a retrospective study. Lancet Oncol. 2012;13(4):366-374. 19. Pidala J, Lee SJ, Ahn KW, et al. Nonpermissive HLA-DPB1 mismatch increases mortality after myeloablative unrelated allogeneic hematopoietic cell transplantation. Blood. 2014;124(16): 2596-2606. 20. Crivello P, Heinold A, Rebmann V, et al. Functional distance between recipient and donor HLA-DPB1 determines nonpermissive mismatches in unrelated HCT [published correction appears in Blood. 2016;128(23): 2744]. Blood. 2016;128(1):120-129. 21. Petersdorf EW, Gooley T, Volt F, et al. Use of the HLA-B leader to optimize cord-blood transplantation. Haematologica. 2020; 106(12):3107-3114. 22. McCurdy SR, Fuchs EJ. Selecting the best haploidentical donor. Semin Hematol. 2016; 53(4):246-251. 23. Wang Y, Chang Y-J, Xu L-P, et al. Who is the best donor for a related HLA haplotype- blood® 10 MARCH 2022 | VOLUME 139, NUMBER 10 1467 Downloaded from http://ashpublications.org/blood/article-pdf/139/10/1452/1879351/bloodbld2021013443.pdf by Adriana Seber on 10 March 2022 Contribution: E.J.F., S.R.M., and E.W.P. designed the study; E.J.F. and E.W.P. drafted the manuscript; T.W. performed statistical analysis; and all authors assembled the data, critically reviewed and edited the manuscript, and approved the final version. 0000-0003-2161-8259; A.S., 0000-0003-0003-0130; J.M., 0000-00020539-4796; S.P., 0000-0001-5571-2775; S.M.G., 0000-0002-3255-8143; E.W.P., 0000-0002-6454-3683. mismatched transplant? Blood. 2014;124(6): 843-850. 24. McCurdy SR, Zhang M-J, St Martin A, et al. Effect of donor characteristics on haploidentical transplantation with posttransplantation cyclophosphamide. Blood Adv. 2018;2(3):299-307. 25. Raiola AM, Risitano A, Sacchi N, et al. Impact of HLA disparity in haploidentical bone marrow transplantation followed by high-dose cyclophosphamide. Biol Blood Marrow Transplant. 2018;24(1): 119-126. Transplant Research study. Biol Blood Marrow Transplant. 2015;21(8):1479-1487. 32. Petersdorf EW, Gooley TA, Malkki M, et al; International Histocompatibility Working Group in Hematopoietic Cell Transplantation. HLA-C expression levels define permissible mismatches in hematopoietic cell transplantation. Blood. 2014;124(26):3996-4003. 33. Eto M, Mayumi H, Tomita Y, et al. Specific destruction of host-reactive mature T cells of donor origin prevents graft-versus-host disease in cyclophosphamide-induced tolerant mice. J Immunol. 1991;146(5):1402-1409. 34. Kanakry CG, Ganguly S, Zahurak M, et al. Aldehyde dehydrogenase expression drives human regulatory T cell resistance to posttransplantation cyclophosphamide. Sci Transl Med. 2013;5(211):211ra157. 27. Kasamon YL, Luznik L, Leffell MS, et al. Nonmyeloablative HLA-haploidentical bone marrow transplantation with high-dose posttransplantation cyclophosphamide: effect of HLA disparity on outcome. Biol Blood Marrow Transplant. 2010;16(4):482-489. 35. Eto M, Mayumi H, Tomita Y, Yoshikai Y, Nishimura Y, Nomoto K. Sequential mechanisms of cyclophosphamide-induced skin allograft tolerance including the intrathymic clonal deletion followed by late breakdown of the clonal deletion. J Immunol. 1990;145(5):1303-1310. 28. Nunes E, Heslop H, Fernandez-Vina M, et al. Definitions of histocompatibility typing terms. Blood. 2011;118(23):e180-e183. 29. Mayor NP, Wang T, Lee SJ, et al. Impact of previously unrecognized HLA mismatches using ultrahigh resolution typing in unrelated donor hematopoietic cell transplantation. J Clin Oncol. 2021;39(21):2397-2409. 30. Petersdorf EW, Malkki M, O’hUigin C, et al. High HLA-DP expression and graft-versushost disease. N Engl J Med. 2015;373(7): 599-609. 31. Sorror ML, Logan BR, Zhu X, et al. Prospective Validation of the predictive power of the hematopoeitic cell transplantation comorbidity index: a Center for International Blood and Marrow 1468 36. Braud V, Jones EY, McMichael A. The human major histocompatibility complex class Ib molecule HLA-E binds signal sequence-derived peptides with primary anchor residues at positions 2 and 9. Eur J Immunol. 1997;27(5):1164-1169. 37. Horowitz A, Djaoud Z, Nemat-Gorgani N, et al. Class I HLA haplotypes form two schools that educate NK cells in different ways. Sci Immunol. 2016;1(3):eaag1672. 38. Russo A, Oliveira G, Berglund S, et al. NK cell recovery after haploidentical HSCT with posttransplant cyclophosphamide: dynamics and clinical implications. Blood. 2018;131(2): 247-262. 39. Luznik L, Slansky JE, Jalla S, et al. Successful therapy of metastatic cancer using tumor blood® 10 MARCH 2022 | VOLUME 139, NUMBER 10 40. Symons HJ, Levy MY, Wang J, et al. The allogeneic effect revisited: exogenous help for endogenous, tumor-specific T cells. Biol Blood Marrow Transplant. 2008;14(5): 499-509. 41. Bachireddy P, Hainz U, Rooney M, et al. Reversal of in situ T-cell exhaustion during effective human antileukemia responses to donor lymphocyte infusion. Blood. 2014; 123(9):1412-1421. 42. Arina A, Karrison T, Galka E, Schreiber K, Weichselbaum RR, Schreiber H. Transfer of allogeneic CD41 T cells rescues CD81 T cells in anti-PD-L1-resistant tumors leading to tumor eradication. Cancer Immunol Res. 2017;5(2):127-136. 43. Yamamoto F, Suzuki S, Mizutani A, et al. Capturing differential allele-level expression and genotypes of all classical HLA loci and haplotypes by a new capture RNA-seq method. Front Immunol. 2020;11:941. 44. Christopher MJ, Petti AA, Rettig MP, et al. Immune escape of relapsed AML cells after allogeneic transplantation. N Engl J Med. 2018;379(24):2330-2341. 45. Toffalori C, Zito L, Gambacorta V, et al. Immune signature drives leukemia escape and relapse after hematopoietic cell transplantation. Nat Med. 2019;25(4): 603-611. 46. Dufva O, P€ ol€ onen P, Br€ uck O, et al. Immunogenomic landscape of hematological malignancies [published correction appears in Cancer Cell. 2020;38(3):424-428]. Cancer Cell. 2020; 38(3):380-399.e13. 47. Sajulga R, Bolon Y-T, Maiers M, Petersdorf EW. Assessment of HLA-B genetic variation with an HLA-B leader tool and implications in clinical transplantation. Blood Adv. 2022; 6(1):270-280. FUCHS et al Downloaded from http://ashpublications.org/blood/article-pdf/139/10/1452/1879351/bloodbld2021013443.pdf by Adriana Seber on 10 March 2022 26. Solomon SR, Aubrey MT, Zhang X, et al. Selecting the best donor for haploidentical transplant: impact of HLA, killer cell immunoglobulin-like receptor genotyping, and other clinical variables. Biol Blood Marrow Transplant. 2018;24(4):789-798. vaccines in mixed allogeneic bone marrow chimeras. Blood. 2003;101(4):1645-1652.