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. Author manuscript; available in PMC: 2021 Jan 1.
Published in final edited form as: Biol Blood Marrow Transplant. 2019 Sep 26;26(1):123–131. doi: 10.1016/j.bbmt.2019.09.024

The Predicted Indirectly Recognizable HLA Epitopes (PIRCHE) Score for HLA Class I Graft-Versus-Host Disparity Is Associated with Increased Acute Graft-Versus-Host Disease in Haploidentical Transplantation with Post-Transplant Cyclophosphamide

Joseph Rimando 1, Michael Slade 1, John F DiPersio 1, Peter Westervelt 1, Feng Gao 2, Chang Liu 3,*, Rizwan Romee 4,*
PMCID: PMC7286229  NIHMSID: NIHMS1543652  PMID: 31563575

Abstract

The Predicted Indirectly Recognizable HLA Epitopes (PIRCHE) score quantifies the number of PIRCHE between patient and donor pairs and represents an in silico measure of indirect alloreactivity. This biologic process is defined as T cell recognition of epitopes derived from mismatched, allogeneic HLA peptides that are subsequently presented by shared HLA molecules. Its association with clinical outcome has not been examined in haplo-HCT with PTCy. We hypothesized that PIRCHE scores would correlate with indirect alloreactivity and predict graft-versus-host disease (GvHD) risk and incidence of relapse after haplo-HCT with PTCy. To address this, we retrospectively analyzed 148 patients who received peripheral blood, T cell-replete haplo-HCT with PTCy at a single center between 2009 and 2016. PIRCHE scores (PS) were calculated using the PIRCHE online matching tool. PS were categorized by class and vector. The median class I graft-versus-host (GvH) PS was 11 (range, 0–56), while the median class I host-versus-graft (HvG) PS was 10 (range 0–51). The class I GvH PS was associated with increased grade II-IV aGvHD (adjusted HR or aHR 1.03 per PS unit increase; 95% CI 1.01–1.05; p=0.008) but not chronic GvHD or incidence of relapse. PIRCHE scores represent a novel strategy to predict clinical outcome in haplo-HCT. Further studies using registry data and prospective cohorts are warranted to validate these findings.

Introduction

Allogeneic hematopoietic cell transplantation (allo-HCT) represents a lifesaving therapy for many patients with otherwise refractory hematologic malignancies.1 An HLA-matched related donor (MRD) is considered to be the optimal donor source, but this option is only available to approximately 13–51% of patients requiring an allo-HCT depending on patient age and ethnicity.2,3 The second option is an HLA-matched unrelated donor (MUD), which is typically identified through a national or international donor registry.4 However, a search for a MUD is time-consuming and costly, and donor availability varies widely by race, with patients of European descent having a much higher chance of finding a donor compared with those of Hispanic, Asian, or African American descent.5 Haploidentical hematopoietic cell transplantation (haplo-HCT) represents an attractive alternative to HLA-matched allo-HCT due to its increased donor availability. With the use of post-transplant cyclophosphamide (PTCy) to selectively deplete or functionally impair alloreactive T cells,6–12 haplo-HCT in adults has been shown to have similar outcomes when compared with MUD allo-HCT, MRD allo-HCT, and allo-HCT from other alternative donors.9,13–20 Additionally, haplo-HCT with PTCy appears to have favorable outcomes in the pediatric and young adult population.21,22

Several studies have investigated the impact of donor characteristics on clinical outcomes in haplo-HCT, with HLA disparity being a topic of particular interest. HLA disparity is traditionally measured by counting mismatched antigens or alleles, which is limited by a narrow range of measurement. Greater HLA mismatch has been associated with worse overall survival and non-relapse mortality in the unrelated donor setting.23–29 In the haplo-HCT setting, however, the impact of HLA disparity on clinical outcomes remains unclear, as previous studies have reported inconsistent results.30–35 Eplet-based epitope mismatch using the HLA Matchmaker algorithm provides a wider range of measurement and has also been studied in haplo-HCT with PTCy.36–38 We recently showed that class II epitope mismatch is associated with reduced relapse and delayed engraftment.38 We did not, however, find an association between epitope mismatch and graft-versus-host disease (GvHD).38 The Predicted Indirectly ReCognizable HLA Epitopes (PIRCHE) program offers a novel, in silico method for predicting the number of PIRCHE between a donor and host pair.39 The program calculates the number of allogeneic HLA peptides, or PIRCHE, capable of causing an indirect alloreactive response, which involves T cell recognition of epitopes derived from mismatched, allogeneic HLA peptides that are subsequently presented by HLA molecules shared between the donor and recipient.40,41 In comparison, direct alloreactivity involves direct contact between the T-cell receptors of previously primed, crossreactive T cells with an intact, allogeneic HLA antigen.42–50 The PIRCHE program predicts pertinent allogeneic HLA peptide sequences presented by HLA class I molecules (Class I PIRCHE) by accounting for proteasomal cleavage of HLA molecules, transport of those peptides via transporter-associated proteins into the endoplasmic reticulum, and binding affinities of the predicted cleavage products to class I molecules.39 Prediction of class II-presented epitopes (Class II PIRCHE) relies mainly on HLA-binding affinity predictions of peptides, as enzyme cleavage patterns have not been described yet.39 The program then calculates the number of HLA-derived peptides that differ up to one amino acid between the donor and recipient in order to quantify HLA disparity.

PIRCHE scores have been previously associated with reduced relapse in the setting of cord blood transplantation.51 However, in the setting of ATG-based haplo-HCT using the GIAC protocol, PIRCHE scores were not found to be associated with outcomes after multivariate adjustment.52 To the best of our knowledge, the impact of PIRCHE scores has not been studied in patients receiving haplo-HCT with PTCy. Since the PTCy used in haplo-HCT is thought to eliminate or functionally impair the primed, cross-reactive T cells responsible for direct alloreactivity, indirect alloreactivity may underlie the graft-versus-leukemia effects and graft-versus-host disease occurring after haplo-HCT.6–12,42–50 We hypothesized that PIRCHE scores would correlate with indirect alloreactivity and predict graft-versus-host disease (GvHD) risk and incidence of relapse. We present a single-center retrospective cohort study to examine the association between PIRCHE scores and clinical outcome after haplo-HCT with PTCy.

Materials and Methods

Patients and demographics

We performed a retrospective study on patients receiving PTCy-based, peripheral blood, T-cell replete haplo-HCT at a single center from July 2009 to May 2016 with November 2017 as the date of last follow-up. Diagnoses included acute myelogenous leukemia, acute lymphoblastic leukemia, chronic myelogenous leukemia, Hodgkin’s lymphoma, non-Hodgkin’s lymphoma, myelodysplastic syndrome, and multiple myeloma. All patients of age 18 years or older with a malignant hematologic diagnosis receiving PTCy-based, peripheral blood, T-cell replete haploHCT were included. Patients with a benign hematologic diagnosis, particularly aplastic anemia, were excluded given that one of the primary endpoints of the study, namely incidence of relapse, involves the graft-versus-tumor effect. Per protocol, the majority of the patients (95%) received tacrolimus and mycophenolate mofetil (MMF) for graft-versus-host disease prophylaxis in addition to PTCy unless intolerant. The Institutional Review Board at Washington University in St. Louis approved this study. Data collection on patient demographics and clinical variables was conducted systematically by a single chart reviewer.

HLA Disparity

High-resolution HLA typing data were collected for the following HLA loci: A, B, C, DRB1, and DQB1. High-resolution HLA typing was performed by a combination of sequence-based typing, reverse sequence-specific oligos, or sequence-specific primers methods. For patients or donors with intermediate-resolution HLA typing data only, their two-field, high-resolution HLA typing were inferred using the online tool Haplostats (www.haplostats.org).53 High-resolution HLA typing for donor and recipient pairs were then entered into the online PIRCHE matching service (https://www.pirche.com/pirche/#/) to obtain PIRCHE scores (PS) corresponding to the number of allogeneic HLA peptides capable of inducing an indirect alloreactive response. PS for allogeneic peptides presented by class I and class II HLA molecules were computed separately in both the host-versus-graft (HvG) and graft-versus-host (GvH) directions. Class I PS represent the number of PIRCHE presented by HLA class I molecules, while class II PS represent the number of PIRCHE presented by HLA class II molecules. As the PIRCHE matching service defaults to calculating GvH PS, HvG PS were calculated by entering the host typing into the donor field and the donor typing into the host field (Figure I).

Figure I. Calculation of Predicted Indirectly Recognizable HLA Epitopes (PIRCHE) scores.

Figure I.

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(A) Sample donor and host high resolution HLA typing for a 7/8 matched unrelated donor-recipient pair are shown. This sample HLA typing was provided by the PIRCHE online matching service (https://www.pirche.com/pirche/#/). The HLA antigen generating an allogeneic graft-versus-host (GvH) response in this example is HLA-B*27:05, while the HLA antigen generating an allogeneic host-versus-graft (HvG) response in this example is HLA-B*27:14. In order to calculate GvH PIRCHE scores, the host and donor typing are entered in the corresponding fields in the online matching service. In order to calculate HvG PIRCHE scores, the host and donor typing are entered in opposite fields. (B) The peptide sequence alignment, obtained from the European Bioinformatics Institute’s online services (https://www.ebi.ac.uk/cgi-bin/ipd/imgt/hla/align.cgi), is shown for HLA-B*27:05 and B*27:14, with polymorphic amino acids highlighted in blue or red. (C) The mismatched target allele, predicted allogeneic peptides, presenting HLA alleles, and corresponding PIRCHE scores are shown. The class (I or II) of the PIRCHE score is determined by the presenting HLA allele, not the allogeneic peptide.

Outcomes

The primary outcomes were grade II-IV acute graft-versus-host disease (aGvHD) and incidence of relapse. Secondary outcomes were overall survival (OS), relapse-free survival (RFS), treatment-related mortality (TRM), chronic graft-versus-host disease (cGvHD) (any grade), time to neutrophil engraftment, time to platelet engraftment, and graft failure. OS was defined as the time from day 0 of the haplo-HCT to time of last follow up or death from any cause. RFS was defined as the time from day 0 of the haplo-HCT to relapse or death from a cause other than relapse of disease. Relapse was defined per accepted criteria.54 TRM was defined as death prior to D+28 or due to any cause other than relapsed disease. Acute and chronic GvHD were defined by previously accepted criteria.55,56 The time of neutrophil engraftment was defined as the first of three consecutive days with an absolute neutrophil count greater than 500 cells/uL. The time of platelet engraftment was defined as the start of two weeks with a platelet count greater than 20,000 cells/uL without transfusion support. Primary engraftment failure was defined as undetectable (<5%) donor chimerism on short tandem repeat testing in the absence of disease relapse leading to death or re-transplantation. Secondary engraftment failure was defined as the loss of donor chimerism or decline of ANC to below 500 cells/uL in the absence of relapse, GvHD, and CMV infection. Engraftment failure in this study included patients with both primary and secondary failure. Patients with death prior to D+28 were excluded from consideration for graft failure.

Data Analysis and Statistics

Patient demographics and disease characteristics were summarized using counts and frequencies for categorical variables or means and standard deviations for continuous variables. The distributions of patient demographics and disease characteristics across class I GvH and HvG PS (dichotomized by its median) were compared using the Student t-test, Chi-square test, or Mann-Whitney rank-sum test as appropriate.

PS, stratified by class and vector, were analyzed as a continuous variable in relation to the primary and secondary outcomes, and the assumption of linearity was assessed graphically based on residuals out of the corresponding regression models. Associations between PS and OS or RFS were assessed using Cox proportional hazards regression models. The correlation between PS and allele mismatch was summarized using non-parametric Spearman’s rank-order correlation coefficients (rho). Cumulative incidences of relapse, TRM, aGvHD, cGvHD, neutrophil engraftment, and platelet engraftment were estimated using Gray’s sub-distribution regression to account for competing risks. Death without relapse was considered a competing risk for relapse. Relapse was considered a competing risk for TRM. Death without count recovery was considered a competing risk for count recovery. Graft failure, relapse, or death without GvHD were considered competing risks for GvHD. To facilitate graphical presentation, PS were also dichotomized by tertiles and the curves of survival or cumulative incidence were estimated using Kaplan-Meier product limit methods and compared by the log-rank test or Gray’s test as appropriate.

Significant univariate associations between PS and outcomes were adjusted for other significant demographic and clinical variables in a multivariate analysis. Covariates considered for adjustment were: male gender; age at transplant; donor age at transplant; presence of sex mismatch; CMV match status; donor relationship; use of ablative regimen; disease status at transplant (active versus remission); refined disease risk index (DRI)57 (low/intermediate versus high/very high); hematopoietic cell transplant comorbidity index (HCT-CI)58,59; presence of donor-specific antibodies (DSA); and presence of any, class I, or class II anti-HLA antibodies. Multivariate analysis was performed using the Cox proportional hazards regression model or Gray’s sub-distribution regression, with backwards selection of covariates that were associated with the outcome of interest with a p-value below 0.2. All tests were two-sided and significance was set at a p-value of 0.05. All analyses were performed using SAS 9.4 (SAS Institutes, Cary, NC). J.R., M.S., F.G, C.L, and R.R. all participated in data analysis.

Results

Patient characteristics

We identified 141 patients meeting inclusion criteria during the study period (Table I). Seventy-one (50.4%) patients were male. The median age at transplant was 53 (range 19–73), and the median donor age at transplant was 42 (range 15–70). Ninety-five (67.4%) patients had acute myelogenous leukemia. Sixty-one (43.3%) patients received a myeloablative regimen. Seventy-seven (54.6%) patients had high or very high-risk disease based on the refined DRI. Seventy (49.6%) patients had a sex-mismatched donor, and 55 (39.0%) patients had a CMV-mismatched donor.

Table I.

Patient characteristics, stratified by HLA class I PIRCHE scores (PS) in the GvH and HvG directions

Patient Characteristic Total, N=141 Class I GvH PS below the median, N=71 Class I GvH PS above the median, N=70 P* Class I HvG PS below the median, N=73 Class I HvG PS above the median, N=68 P*
Male Gender 71 (50.4%) 35 (49.3%) 36 (51.4%) NS 31 (42.5%) 40 (58.8%) 0.052
Male Gender, Donor 87 (61.7%) 44 (62.0%) 43 (61.4%) NS 46 (63.0%) 41 (60.3%) NS
Median Age at Transplant 53 (Range 19–73) 53 52 NS 51 53 NS
Median Donor Age at Transplant 42 (Range 15–70) 42 45 NS 39 48 NS
Patient Ethnicity
 Black 21 (14.9%) 10 (14.1%) 11 (15.7%) NS 13 (17.8%) 8 (11.8%) 0.15
 White 114 (80.8%) 60 (84.5%) 54 (77.1%) 59 (80.8%) 55 (80.9%)
 Other 6 (4.2%) 1 (1.4%) 5 (7.1%) 1 (1.4%) 5 (7.4%)
Sex Mismatch
 Female Patient/Donor 27 (19.1%) 12 (16.9%) 15 (21.4%) NS 15 (20.6%) 12 (17.6%) NS
 Female Patient, Male Donor 43 (30.5%) 24 (33.8%) 19 (27.1%) 27 (37.0%) 16 (23.5%)
 Male Patient, Female Donor 27 (19.1%) 15 (21.1%) 12 (17.1%) 12 (16.4%) 15 (22.1%)
 Male Patient/Donor 44 (31.2%) 20 (28.2%) 24 (34.3%) 19 (26.0%) 25 (36.8%)
Donor Relationship
 Child 49 (37.1%) 25 (34.8%) 26 (39.4%) NS 26 (38.2%) 23 (35.9%) NS
 Parent 21 (15.9%) 10 (15.2%) 11 (16.7%) 10 (14.7%) 11 (17.2%)
 Sibling 62 (47.0%) 33 (50.0%) 29 (43.9%) 32 (47.1%) 30 (46.9%)
 Other/Missing 9 (6.4%) - - - -
CMV Serostatus
 Donor/Recipient + 43 (30.5%) 17 (23.9%) 26 (37.1%) NS 20 (27.4%) 23 (33.8%) NS
 Donor +, Recipient - 19 (13.5%) 12 (16.9%) 7 (10.0%) 10 (13.7%) 9 (13.2%)
 Donor -, Recipient + 36 (25.5%) 20 (28.2%) 16 (22.9%) 20 (27.4%) 16 (23.5%)
 Donor, Recipient - 43 (30.5%) 22 (31.0%) 21 (30.0%) 23 (31.5%) 20 (29.4%)
ABO Mismatch
 Bidirectional 5 (3.5%) 4 (5.6%) 1 (1.4%) NS 2 (2.7%) 3 (4.4%) NS
 Major 21 (14.9%) 11 (15.5%) 10 (14.3%) 12 (16.4%) 9 (13.2%)
 Minor 27 (19.1%) 13 (18.3%) 14 (20.0%) 18 (24.7%) 9 (13.2%)
 Matched 88 (62.4%) 43 (60.6%) 45 (64.3%) 41 (56.2%) 47 (69.1%)
Median KPS 80 (Range 50–100) 80 80 NS 80 90 NS
Median HCT-CI47 3 (Range 0–9) 3 3 NS 4 3 NS
Median CD34 Cell Dose (106 cells/kg) 5 (Range 1.6–14.2) 5 5 NS 5 5 NS
Median CD3 Cell Dose (107 cells/kg) 17.9 (Range 0–68.5) 18.0 17.8 NS 18.2 17.3 NS
Myeloablative Regimen Received 61 (43.3%) 25 (35.2%) 36 (51.4%) 0.052 27 (37.0%) 34 (50.0%) 0.119
Diagnosis
 AML 95 (67.4%) 48 (67.6%) 47 (67.1%) NS 51 (69.9%) 44 (64.7%) NS
 Other (ALL, MDS, Lymphoma, Multiple Myeloma, other Leukemia) 46 (32.6%) 23 (32.4%) 23 (32.9%) 22 (30.1%) 24 (35.3%)
Active Disease at Transplant 60 (42.6%) 29 (40.8%) 31 (44.3%) NS 25 (34.2%) 35 (51.5%) 0.039
Refined Disease Risk Index46
 Low/intermediate 64 (45.4%) 32 (45.1%) 32 (45.7) NS 34 (46.6%) 30 (44.1%) NS
 High/Very High 77 (54.6%) 39 (54.9%) 38 (54.3%) 39 (53.4%) 38 (55.9%)
Presence of Donor Specific Antibodies 21 (14.9%) 8 (11.3%) 13 (18.6%) NS 10 (13.7%) 11 (16.2%) NS
 Not Tested 21 (14.9%) 11 (15.5%) 10 (14.3%) 11 (15.1%) 10 (14.7%)
Recipient anti-HLA Antibodies
 Class I 56 (46.7%) 26 (43.3%) 30 (50.0%) NS 28 (45.2%) 28 (48.3%) NS
 Class II 33 (27.5%) 17 (28.3%) 16 (26.7%) NS 17 (27.4%) 16 (27.6%) NS
 Class I and II 61 (50.4%) 31 (50.8%) 30 (50.0%) NS 33 (52.4%) 28 (48.3%) NS
 Not Tested 21 (14.9%) - - - -
History of Prior Allo-HCT 42 (29.8%) 20 (28.2%) 22 (31.4%) NS 24 (32.9%) 18 (26.5%) NS
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KPS indicates Karnofsky Performance Status. HCT-CI indicates the Hematopoietic Cell Transplantation-Comorbidity Index.47 NS (non-significant) indicates a p-value greater than 0.2.

*

The parametric p-value is calculated by ANOVA for numerical covariates and the chi-square test for categorical covariates.

Patients were stratified by the median class I PS in the GvH and HvG directions (Table I). A greater percentage of patients with class I HvG PS above the median had active disease at the time of transplant (51.5% versus 34.2%; p=0.039). No other patient characteristics differed significantly between these groups.

High Resolution HLA typing

Twenty-eight patients (19.8%), 7 donors (4.9%), and 3 (2.1%) patient-donor pairs had HLA high-resolution typing at HLA-A, B, C, DRB1, and DQB1. Thirty-one (22.0%) patients, 7 (4.9%) donors, and 4 (2.8%) patient-donor pairs had HLA class I high-resolution typing at A, B, and C. HLA high-resolution typing provided by Haplostats had a median likelihood percentage of 86.4% (range 27.2%−100%) for patients and 75.9% (range 7.5%−100%) for donors.

Distributions of PIRCHE Scores

The median class I GvH PS was 11 (range 0–56), while the median class I HvG PS was 10 (range 0–51), respectively (Table IIA–B). All PS categories were modestly nonetheless significantly correlated with their corresponding measurements of allele mismatch except for class I GvH disparity (rho=0.140; p=0.097) (Figure IIA-D). Substantial overlay in PS were observed at each level of allele mismatch.

Table IIA.

Graft-versus-host PIRCHE scores (PS) and clinical outcomes: univariate analysis

Class I PS (Median 11, Range 0–56) Class II PS (Median 29, Range 0–122)
Outcome HR 95% CI P HR 95% CI P
aGvHD (Grade II-IV) 1.021 1.002–1.041 0.0342 1.006 0.993–1.018 NS
Relapse 1.012 0.991–1.034 NS 0.997 0.987–1.007 NS
Overall Survival 1.017 1.000–1.035 0.0516 0.999 0.991–1.007 NS
Relapse-Free Survival 1.016 1.000–1.033 0.0549 0.997 0.990–1.005 NS
Treatment-Related Mortality 1.006 0.982–1.031 NS 0.999 0.988–1.011 NS
cGvHD (any) 0.978 0.953–1.004 0.102 1.009 0.998–1.020 0.120
Neutrophil Engraftment 1.010 0.997–1.024 0.130 1.003 0.996–1.010 NS
Platelet Engraftment 1.004 0.988–1.019 NS 1.000 0.993–1.007 NS
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Table IIB.

Host-versus-graft PIRCHE scores (PS) and clinical outcomes: univariate analysis

Class I PS (Median 10, Range 0–51) Class II PS (Median 32, Range 0–97)
Outcome HR 95% CI P HR 95% CI P
aGvHD (Grade II-IV) 1.016 0.996–1.036 0.121 1.003 0.987–1.019 NS
Relapse 1.02 0 0.995–1.046 0.111 1.000 0.986–1.014 NS
Overall Survival 1.015 0.997–1.032 0.106 1.003 0.993–1.013 NS
Relapse-Free Survival 1.014 0.997–1.032 0.111 1.001 0.991–1.011 NS
Treatment-Related Mortality 0.998 0.975–1.022 NS 1.001 0.987–1.015 NS
cGvHD (any) 0.982 0.954–1.011 NS 1.007 0.990–1.023 NS
Neutrophil Engraftment 1.001 0.983–1.013 NS 0.994 0.985–1.003 0.194
Platelet Engraftment 1.001 0.984–1.017 NS 0.998 0.989–1.006 NS
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aGvHD indicates acute graft-versus-host disease, while cGvHD indicates chronic graft-versus-host disease. NS (non-significant) indicates a p-value greater than 0.2.

Figure II. The correlation between PIRCHE Scores and HLA allele mismatch.

Figure II.

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PIRCHE scores correlated with allele mismatch in all class and vector categories (A-D) (Rho ranging from 0.140 to 0.336) except for HLA class I graft-versus-host disparity (rho=0.140; p=0.097). Significant overlap existed between the ranges of PIRCHE scores for each level of allele mismatch in all categories.

Patient Outcomes

The median follow-up for survivors was 34 months (range 14.5–78.3 months). Ninety-five (67.4%) patients were deceased, and 61 (43.3%) patients had relapsed disease by the time of the last follow-up. Forty-five (31.9%) patients developed grade II-IV aGvHD, 15 (10.8%) developed grade III-IV aGvHD, and 46 (32.6%) developed cGvHD (any). The median time to neutrophil engraftment was 17 days (range 10–126 days) among the 127 neutrophil-engrafted patients, and the median time to platelet engraftment was 29 days (range 8–214 days) among the 109 platelet-engrafted patients. Five patients (3.5%) had engraftment failure.

The Class I GvH PIRCHE Score and Acute Graft-Versus-Host Disease

In the univariate analysis, the class I GvH PS was associated with increased grade II-IV aGvHD (HR 1.021 per PS unit increase; 95% CI 1.002–1.041; p=0.0342) (Table IIA; Figure III). The class I GvH PS was not associated with relapse, cGvHD, RFS, OS, TRM, or engraftment. After adjustment for disease status (active versus remission), the class I GvH PS remained associated with grade II-IV aGvHD (adjusted HR 1.03 per unit increase; 95% CI 1.01–1.05; p=0.008) (Table III). The class I GvH PS was not associated with grade III-IV aGvHD (HR 0.998 per unit increase; 95% CI 0.957–1.039; p=0.907).

Figure III. The class I graft-versus-host PIRCHE score and grade II-IV acute graft-versus-host disease.

Figure III.

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A greater HLA class I graft-versus-host (GvH) PIRCHE score was associated with increased grade II-IV acute graft-versus-host disease (aGvHD), and this association was significant when PIRCHE scores were treated as a continuous variable. This association remained significant in the multivariate analysis.

Table III.

The class I graft-versus-host PIRCHE score and acute graft-versus-host disease: multivariate analysis

Outcome Covariate Univariate Analysis Multivariate Analysis
HR 95% CI P HR 95% CI P
aGvHD (Grade II-IV) Class I GvH PS 1.021 1.002–1.041 0.034 1.03 1.01–1.05 0.008
Disease
Status
 Active
Disease - - - - - -
 Remission 1.750 0.969–3.159 0.064 2.01 1.09–3.72 0.026
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aGvHD indicates acute graft-versus-host disease. GvH indicates graft-versus-host. PS indicates PIRCHE score. Multivariate analyses were conducted using cox proportional hazards regression models, with adjustment for variables with a P<0.2. Covariates considered for adjustment were: sex; sex mismatch; diagnosis of AML; CMV serostatus; disease status (remission versus active); refined Disease Risk Index46; donor relationship (parent, sibling, child); presence of myeloablative regimen; presence of DSA; presence of anti-HLA antibodies (any, class I, or class II); age at transplant; donor age; and Hematopoietic Cell Transplantation-Comorbidity Index47.

Given these findings, we examined the relationship between allele mismatch and aGvHD. Class I GvH allele mismatch was not associated with grade II-IV aGvHD (HR 0.950; 95% CI 0.700–1.290; p=0.742).

The Class I HvG PIRCHE Score and Clinical Outcomes

The class I HvG PS was not associated with clinical outcomes in the univariate analysis (Table IIB).

Class II PIRCHE Scores and Clinical Outcomes

Class II PS in the GvH and HvG directions were not significantly associated with any of the clinical outcomes in univariate analyses (Table IIA–B).

Discussion

This study is the first to evaluate the relationship between HLA disparity as measured by the PIRCHE program and clinical outcomes in patients undergoing haplo-HCT with PTCy. In contrast to HLA disparity as measured by allele mismatch or eplet-derived epitope mismatch, PIRCHE scores predict the level of HLA-restricted, indirect T-cell alloreactivity between a donor and host pair.36,37,39 In our study, higher class I GvH PS was associated with an increased risk of aGvHD. Given the unique rationale of the PIRCHE model, our findings indicate a link between indirect T-cell alloreactivity against mismatched HLA and outcomes after haplo-HCT with PTCy.

Previous studies have examined the role of PS in non-PTCy based allo-HCT.51,52,60 In a 2014 study of 88 patients receiving a MUD allo-HCT that was mismatched at HLA-DPB1, DPB1 disparity as measured by the PIRCHE model correlated with a greater incidence of aGvHD while DPB1 disparity as determined by the T-cell epitope model did not.60 In a 2016 study of patients receiving HLA-mismatched unrelated cord blood transplantation, greater class I GvH PS was associated with a reduced risk of relapse in patients transplanted for a hematologic malignancy.51 The PIRCHE model was also evaluated by Huo et al in a retrospective cohort analysis of 557 patients undergoing ATG-based haplo-HCT under the GIAC protocol.52 This study did find a univariate association between class I GvH PS divided by quartiles and increased cGvHD (p=0.007). This association, however, was not significant after multivariate adjustment (HR 0.993; 95% CI 0.858–1.149; p=0.926). In contrast to the study by Huo et al, our study analyzed PS as a continuous variable and found a significant association between class I GvH PS and grade II-IV aGvHD. Distinct from all of these previous studies, our study evaluated the clinical significance of PS in a peripheral blood, T cell-replete haplo-HCT platform with the use of PTCy for GvHD prophylaxis.

As seen in figure II, substantial overlay in PS existed at each level of allele mismatch in all HLA class and vector categories. Given that PS predict indirect alloreactivity primarily, they may provide a unique insight into the role of HLA disparity in haplo-HCT that allele mismatch or epitope mismatch cannot. In support of this notion, the class I GvH PS, but not class I GvH allele mismatch, was associated with increased aGvHD. Further, dedicated studies are needed to delineate the difference in predictive value between these methods of measurement.

Since the PTCy used in haplo-HCT is thought to eliminate or functionally impair the primed, cross-reactive T cells responsible for direct alloreactivity, indirect alloreactivity may underlie the graft-versus-tumor effects and graft-versus-host disease occurring after haplo-HCT.6–12,42–50 Therefore, PS may be uniquely positioned to examine this hypothesis. Previous studies using allele mismatch or eplet-derived epitope mismatch to evaluate HLA disparity were unable to predict aGvHD in haplo-HCT with PTCy.30,32–34,38 In contrast, this study found a significant association between the class I GvH PS and increased grade II-IV aGvHD, which may suggest that PTCy primarily targets T cells mediating direct alloreactivity but not those responsible for indirect recognition. Class I GvH PS was not associated with grade III-IV aGvHD, but only 11.5% of our patient population had grade III-IV aGvHD. Previous research has also shown that that PTCy mitigates GvHD incidence at least in part through the preservation of T regulatory (CD4+ CD25+ Foxp3+) cells.8,12,61,62 It is possible that the indirect alloreactivity measured by PS is incompletely mitigated by T regulatory cells. Additionally, increased indirect alloreactivity as measured by PS may increase the activation of T cells enough to overcome the suppressive effects of T regulatory cells and cause GvHD. Further mechanistic studies evaluating the relationship between PS and aGvHD are needed.

Although greater GvH PS was associated with aGvHD, it did not seem to offer any graft-versus-tumor (GvT) effect as the class I GvH PS was not associated with decreased relapse. Previous research by McCurdy et al has shown a reciprocal relationship between grade II aGvHD and relapse and progression-free survival in both HLA-matched and haploidentical allo-HCT with PTCy.63,64 Given these data, our study may not have been adequately powered to detect an association between PS and incidence of relapse. However, Shimoni et al found no association between aGvHD and GvT in a large cohort of patients receiving haplo-HCT with PTCy.65 Larger, registry-based studies are needed to further evaluate the relationship between PS and incidence of relapse.

Interestingly, class I PS but not class II PS were associated with clinical outcomes in our study. CD8+ T cells may be the primary drivers of indirect alloreactivity, as the literature describing this phenomenon centers around CD8+ T cells.40,41 We previously showed an association between class II but not class I eplet-derived epitope mismatch and relapse but not aGvHD.38 As epitope mismatch focuses on the structural differences between HLA molecules,36,37 this measurement of HLA disparity may be specific to direct alloreactivity. Given the divergent findings of these two studies, we hypothesize that direct alloreactivity could potentially drive the immediate GvT effect, while indirect alloreactivity could potentially drive aGvHD in the setting of PTCy. These two studies also suggest that class I disparity in either direction may be detrimental to patient outcomes, while class II disparity in the GvH direction may be beneficial. Additional studies are needed to further explore these hypotheses.

Our study has several limitations. First, the relatively small sample size limited the power of the study, and findings of modest effect size may not be detected. Second, inferred high-resolution HLA typing was used in some cases as required by the PIRCHE program.53 Additionally, our cohort lacked information on killer immunoglobulin receptor (KIR) mismatching, preventing us from evaluating its association with PIRCHE scores. Previous research has shown a potential association between KIR mismatch and NK cells reconstitution and outcomes in haplo-HCT and MUD allo-HCT.34,66–69 Finally, our cohort lacked information on HLA-DPB1 typing or noninherited maternal antigen (NIMA) mismatch. Inclusion of these data in future studies may refine the predictive value of PIRCHE scores in haplo-HCT.

In conclusion, the class I GvH PS is associated with increased aGvHD. PS represent a novel strategy to predict outcomes and inform donor selection in haplo-HCT. Further prospective and registry-based studies are warranted to better understand the role of PIRCHE scores in haplo-HCT.

Highlights for Rimando et al manuscript on PIRCHE scores in haploidentical transplantation:

  • PIRCHE scores offer a method of quantifying indirect T-cell alloreactivity.

  • PIRCHE scores offer a broad range of measurement of HLA disparity.

  • Graft-versus-host PIRCHE scores correlate with acute graft-versus-host disease.

  • PIRCHE scores may improve donor selection in haploidentical transplantation.

Acknowledgments:

This work was supported by the SCC Biostatistics Shared Resource and NCI Cancer Center Support Grant #P30 CA091842, Eberlein, PI; National Center For Advancing Translational Sciences of the National Institutes of Health, Award Number TL1TR002344; the Washington University Hematology Scholars K12 award (K12-HL08710707 to C.L.); and the Mentors in Medicine Program, Division of Medical Education, Department of Internal Medicine, Washington University School of Medicine. The authors have no financial disclosures to report.

Footnotes

Financial Disclosure Statement: The authors have no conflicts of interest to disclose.

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