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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
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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
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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
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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
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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
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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)
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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)
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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)
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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)
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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,
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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
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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
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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)
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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
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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
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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.
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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
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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.,
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Submitted 30 July 2021; accepted 18 October 2021; prepublished
online on Blood First Edition 1 November 2021. DOI 10.1182/blood.
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*E.J.F. and S.R.M. contributed equally to this study.
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