Cellular and Molecular Profiling of T-Cell Subsets at the Onset of Human

Cellular and molecular profiling of T-cell subsets at the onset of human acute GVHD Eleonora Latis, David Michonneau, Claire Leloup, Hugo Varet, Régis Peffault de Latour, Elisabetta Bianchi, Gérard Socié, Lars Rogge

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Eleonora Latis, David Michonneau, Claire Leloup, Hugo Varet, Régis Peffault de Latour, et al.. Cellu- lar and molecular profiling of T-cell subsets at the onset of human acute GVHD. Blood Advances, The American Society of Hematology, 2020, 4 (16), pp.3927-3942. 10.1182/bloodadvances.2019001032. pasteur-02918738

HAL Id: pasteur-02918738 https://hal-pasteur.archives-ouvertes.fr/pasteur-02918738 Submitted on 21 Aug 2020

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Cellular and molecular proﬁling of T-cell subsets at the onset of human acute GVHD

Eleonora Latis,1,2,* David Michonneau,3,4,* Claire Leloup,1,* Hugo Varet,5 Regis´ Peffault de Latour,3,4 CRYOSTEM Consortium, † † Elisabetta Bianchi,1 Gerard´ Socie,´ 3,4, and Lars Rogge1,

1Immunoregulation Unit, Department of Immunology, Institut Pasteur, Paris, France; 2Universite´ Paris Diderot, Sorbonne Paris Cite,´ Paris, France; 3Hematology Transplantation, Downloaded from https://ashpublications.org/bloodadvances/article-pdf/4/16/3927/1755611/advancesadv2019001032.pdf by guest on 20 August 2020 Assistance Publique–Hopitauxˆ de Paris, Saint Louis Hospital, Paris, France; 4INSERM U976, Universite´ de Paris, Paris, France; and 5Hub de Bioinformatique et Biostatistique, Departement´ Biologie Computationnelle, USR 3756 CNRS, Institut Pasteur, Paris, France

The cellular and molecular processes involved in acute graft-versus-host disease (aGVHD) Key Points development early after allogeneic hematopoietic cell transplantation (HCT) in humans • 1 1 CD4 and CD8 remain largely unknown. We have performed multiparameter immunophenotyping and 1 1 T cells with a T memory molecular profiling of CD4 and CD8 T cells in 2 independent cohorts of patients stem cell–like pheno- undergoing HCT, as well as in their HLA-identical sibling donors. Cellular profiling using type are expanded at spectral flow cytometry showed an incomplete reconstitution of the T-cell compartment in the onset of aGVHD. recipients without aGVHD early after transplantation, as well as a shift toward an effector • Molecular profiles of memory phenotype, paralleled by depletion of the naive T-cell pool. Molecular profiling of T cells at aGVHD onset T-cell populations in donors vs recipients without aGVHD revealed increased pathway are characterized by activity of .40 gene modules in recipients. These pathways were associated in particular decreased TGF-b and with T-cell activation, adhesion, migration, and effector functions. Cellular profiles from increased NF-kB recipients developing aGVHD displayed an enrichment of cells with a T memory stem signaling. cell–like phenotype compared with recipients without aGVHD. Comparison of gene profiles from these recipients revealed that transforming growth factor-b (TGF-b) signaling was most significantly downregulated, whereas the pathway activity of NF-kB–associated transcription factors and signaling pathways were increased, at aGVHD onset. This study suggests that the integration of cellular and molecular profiles provides new insights into the development of aGVHD in humans.

Introduction

Allogeneic hematopoietic cell transplantation (allo-HCT) is a curative treatment for many malignant and nonmalignant hematologic disorders.1-3 However, its success is hindered by graft-versus-host disease (GVHD), a potentially fatal complication deriving from alloreactive donor T cells attacking recipient tissues.4 Despite advances in the field of hematopoietic cell transplantation (HCT) and GVHD prophylaxis, acute GVHD (aGVHD) remains a major contributing factor to nonrelapse morbidity and mortality, affecting 30% to 50% of allo-HCT patients3,5; it is also a leading cause of death after allo-HCT, with a mortality of nearly 20%.1 Most of our knowledge about aGVHD pathophysiology derives from animal models.6,7 The complex and multifactorial nature of aGVHD, together with limited access to biological specimens, makes the study of the mechanisms involved in the development of human aGVHD particularly challenging. Although donor T cells are critical to the pathophysiology of acute and chronic GVHD,3,8-10 the precise mechanisms underlying their functions and the immune evasion leading to alloreactivity that occurs in allo-HCT recipients, despite immunosuppressive prophylaxis, are unclear.

Submitted 27 September 2019; accepted 7 July 2020; published online 20 August Data sharing requests should be sent to Lars Rogge ([email protected]) or Gerard´ 2020. DOI 10.1182/bloodadvances.2019001032. Socie´ ([email protected]). *E.L., D.M., and C.L. contributed equally to this work. The full-text version of this article contains a data supplement. †G.S. and L.R. contributed equally to this work. © 2020 by The American Society of Hematology

25 AUGUST 2020 x VOLUME 4, NUMBER 16 3927 Here, we investigated the phenotypic and molecular characteristics Cell isolation and gene-expression analysis of immune cells in patients after allo-HCT, as well as in their HLA- 1 1 Gene expression in sorted CD4 and CD8 T cells was assessed identical sibling donors, with the goal of defining the early immune using the nCounter Human Immunology V2 codeset (NanoString parameters associated with the development of aGVHD. We Technologies), as described previously12-14 (see supplemental analyzed 2 cohorts of donor-recipient pairs: a multicentric cohort Material and methods for details). from 13 French transplantation centers and a monocentric cohort from the Saint-Louis Hospital. We performed multiparameter Results immunophenotyping using spectral flow cytometry to define the frequencies of different T-cell subpopulations and gene-expression The T-cell compartment is skewed toward an effector profiling of T-cell populations involved in aGVHD pathogenesis. memory phenotype early after HCT in patients Our data demonstrate that the integrated analysis of the distribution without aGVHD of different immune cell subsets with spectral flow cytometry, We evaluated the reconstitution patterns of different T-cell subsets Downloaded from https://ashpublications.org/bloodadvances/article-pdf/4/16/3927/1755611/advancesadv2019001032.pdf by guest on 20 August 2020 together with gene-expression profiling, can contribute to elucidate at day 90 after transplantation in 2 independent cohorts of patients the processes involved in the early immune reconstitution and undergoing allo-HCT, as well as in their respective identical sibling aGVHD development in humans. donors. To avoid potential confounding effects related to aGVHD, only donor-recipient pairs without aGVHD were included in this Materials and methods analysis. Donor and patient characteristics and the study design are Patients shown in Table 1 and supplemental Figure 1, respectively. Two independent cohorts of patients undergoing allogeneic HCT Cellular profiling of recipients 3 months post-HCT showed an incomplete reconstitution of the T-cell compartment, with de- and their respective identical sibling donors were included in this 1 creased CD3 T lymphocytes, compared with their respective study. We recently described the metabolomics serum analyses of 1 11 donors. Within the CD3 T-cell population, significantly decreased these 2 cohorts. Patient and donor characteristics are presented 1 1 in Table 1. Cohort 1 includes 38 donor-recipient pairs for whom frequencies of CD4 T cells and increased frequencies of CD8 peripheral blood mononuclear cells (PBMCs) were provided by the T cells were observed in both cohorts (Figure 1A; supplemental CRYOSTEM biobank (https://doi.org/10.25718/cryostem-collec- Figure 2A), resulting in an inversion of the normal CD4/CD8 ratio tion/2018). Cohort 2 includes 37 donor-recipient pairs for whom (Figure 1B; supplemental Figure 2B). PBMCs samples were prospectively collected at Saint-Louis We next assessed whether early T-cell reconstitution was Hospital and cryopreserved. Blood samples from the donors were associated with imbalances in the distributions of naive and memory collected before the transplantation procedure, and samples from T-cell subsets in recipients after transplantation. Compared with 1 the recipients were collected at aGVHD onset or at day 90 post- their donors, recipients had a significant reduction in CD4 and 1 HCT, for the patients who did not develop aGVHD. Details about CD8 naive T (TNaive) cells, paralleled by an increase in effector the HCT procedure and aGVHD diagnosis are provided in memory T cells (TEMs), in both cohorts (Figure 1C-D; supplemental supplemental Material and methods. Figure 2C). We also observed an increase in the terminally differentiated effector memory cells re-expressing CD45RA (TEMRA) All patients gave their written consent for clinical research. This 1 subset in recipients; it was more pronounced within the CD8 noninterventional research study, with no additional clinical pro- 1 population, but it was also present in the CD4 T-cell compartment, cedure, was carried out in accordance with the Declaration of in particular in cohort 2 (Figure 1D; supplemental Figure 2D). Helsinki. Data analyses were carried out using a database with all Analysis of Ki-67 expression revealed a strong increase in the patient identifiers removed. This study was declared to the 1 1 proliferation of CD4 and CD8 T cell and memory T-cell Commission National Informatique et Liberte´ and was approved Naive subsets in recipients compared with their donors (Figure 1E; by the local ethics committee and Institutional Review Board (IRB 1 supplemental Figure 2D). A significant reduction in CD4 and 00003835). 1 1 CD8 TNaive cells and an increase in effector CD4 T cells were Spectral flow cytometry also observed in recipients at the onset of aGVHD compared with their donors in both cohorts (supplemental Figure 3). Multicolor flow cytometric analysis was performed using a SP6800 Spectral Cell Analyzer (Sony Biotechnology), as described in detail Increased Treg proliferation and expression of in supplemental Material and methods. Cells were stained with the functional markers in recipients after HCT following anti-human monoclonal antibodies: anti-CD95, anti-CD3, Given the importance of Tregs in GVHD prevention and HCT anti-CD45RO, anti-CD8, anti-CD279 (PD1), anti-CD27, anti- 13,15,16 1 1 CD196 (CCR6), anti-CD4, anti-CD45RA, and anti-CD122 (in- outcome, we investigated CD4 FOXP3 Tregs in recipients without aGVHD compared with their sibling donors. Recipients terleukin-2RB [IL-2RB]). A dump channel included anti-CD11c, 1 1 showed a significant increase in CD4 FOXP3 Tregs compared anti-CD14, anti-CD19, and anti-CD34. 1 1 with their donors (Figure 2A), and the CD4 FOXP3 Treg subset 1 A second antibody panel, including intracellular markers, was used displayed increased frequency of Ki-67 cells in the recipients early to analyze regulatory T cells (Tregs) with the following anti-human post-HCT compared with their donors (Figure 2B). Our data also 1 monoclonal antibodies: anti-CD25, anti-CD3, anti-CD4, anti-CD8, revealed an increased frequency of Ki-67 cells within Tregs 1 anti-CD27, anti-CD279 (PD1), anti-CD45RA, anti-CD278 (ICOS), compared with conventional CD4 T cells (Tconvs) in recipients and anti-CD127. After permeabilization, cells were stained with anti- following transplantation (Figure 2C, left panel). These data indicate FOXP3, anti-Ki67, and anti-CD152 (CTLA4). that, in the lymphopenic environment of the host, Tconvs and Tregs

3928 LATIS et al 25 AUGUST 2020 x VOLUME 4, NUMBER 16 Table 1. Patient and donor characteristics

Cohort 1 (multicentric) Cohort 2 (monocentric) Variable Donors (n 5 39) Recipients (n 5 38) Donors (n 5 42) Recipients (n 5 37)

Age, median (range), y 49.5 (14-65) 46 (17-68) 52.5 (15-67) 53 (22-67) Sex

Female 18 (46.1) 19 (50) 24 (57.1) 19 (51.4) Male 20 (51.3) 19 (50) 18 (42.9) 18 (48.6)

Unknown 1 (2.6) ——— HLA-identical sibling donor, % 100 100 Graft type Downloaded from https://ashpublications.org/bloodadvances/article-pdf/4/16/3927/1755611/advancesadv2019001032.pdf by guest on 20 August 2020 Bone marrow 11 (28.9) 3 (8.1)

Peripheral blood 26 (68.5) 34 (91.9) Unknown 1 (2.6) — Sex match

Male to male 10 (26.3) 7 (18.9) Female to female 9 (23.7) 11 (29.7)

Male to female 10 (26.3) 8 (21.7) Female to male 8 (21.1) 11 (29.7)

Unknown 1 (2.6) — Conditioning regimen

Reduced intensity 17 (44.8) 32 (86.5) Myeloablative 20 (52.6) 5 (13.5)

Unknown 1 (2.6) — Total body irradiation

Yes 12 (31.6) 4 (10.8) No 25 (65.8) 33 (89.2) Unknown 1 (2.6) — Chimerism, median (range), %

No GVHD 100 (86-100) 100 (60-100)

GVHD 100 (81-100) 100 (97-100) Unknown 4 (10.5) — GVHD status

GVHD 16 (42.1) 19 (51.4)

No GVHD 22 (57.9) 18 (48.6) GVHD grade

Grade 1 8 (50) 1 (5.3)

Grade 2 5 (31.1) 16 (84.1) Grade 3 1 (6.3) 1 (5.3)

Grade 4 1 (6.3) 1 (5.3) Unknown 1 (6.3) — Delay sample-graft, median (range), d

Donors 227 (2136 to 0) 227 (2119 to 21)

GVHD onset 29 (12-91) 36 (9-94) No GVHD 91 (27-108) 90 (77-95) GVHD prophylaxis

CSA 7 (18.4) 2 (5.4) CSA1MMF 8 (21.1) 26 (70.3)

CSA1MTX 22 (57.9) 8 (21.6) None 0 1 (2.7)

Unless otherwise noted, data are n (%). CMV, cytomegalovirus; CSA, cyclosporine A; D, donor; MMF, mycophenolate mofetil; MTX, methotrexate; R, recipient; —, none; 2, negative; 1, positive.

25 AUGUST 2020 x VOLUME 4, NUMBER 16 T-CELL PROFILES POST-HCT AND AT ACUTE GVHD ONSET 3929 Table 1. (continued)

Cohort 1 (multicentric) Cohort 2 (monocentric) Variable Donors (n 5 39) Recipients (n 5 38) Donors (n 5 42) Recipients (n 5 37)

Unknown 1 (2.6) — Diagnosis

Acute leukemia 17 (44.7) 13 (35.2) Myeloproliferative neoplasm 3 (7.9) 8 (21.6)

Lymphoma 8 (21.1) 5 (13.5) Myeloma 2 (5.3) 3 (8.1)

Myelodysplastic syndrome 4 (10.5) 2 (5.4) Downloaded from https://ashpublications.org/bloodadvances/article-pdf/4/16/3927/1755611/advancesadv2019001032.pdf by guest on 20 August 2020 Aplastic anemia 1 (2.6) 3 (8.1)

Chronic lymphoid leukemia 1 (2.6) 2 (5.4) Other diagnosis 2 (5.3) 1 (2.7) CMV serostatus

Positive 22 (56.4) 20 (52.6) 23 (54.8) 29 (78.4) Negative 16 (41) 16 (42.1) 19 (45.2) 8 (21.6)

Unknown 1 (2.6) 2 (5.3) —— CMV status mismatch

D1/R1 13 (34.2) 21 (56.8) D2/R2 8 (21.1) 7 (18.9)

D1/R2 8 (21.1) 1 (2.7) D2/R1 7 (18.4) 8 (21.6)

Unless otherwise noted, data are n (%). CMV, cytomegalovirus; CSA, cyclosporine A; D, donor; MMF, mycophenolate mofetil; MTX, methotrexate; R, recipient; —, none; 2, negative; 1, positive.

undergo strong proliferation compared with healthy donors. The expression occurring in the same direction (supplemental ratio of proliferating Tregs/Tconvs is higher in donors than in Figure 4C-D), demonstrating the robustness of our observations. recipients (Figure 2C, right panel) because of the low proliferation of Tconvs in donors (Figure 1E). In recipients without aGVHD, an A modular transcriptional framework reveals altered enrichment of Tregs expressing the functional markers CTLA4, biological pathways and molecular processes in ICOS, and PD-1 was also observed (Figure 2D), suggesting T cells following HCT a counterbalancing mechanism to suppress alloreactivity and maintain tolerance in the proinflammatory environment of the host. To characterize the signaling pathways and the molecular functions that are altered in T cells after transplantation, we performed Major changes in the T-cell gene-expression profiles a pathway analysis on the T-cell gene-expression profiles from in patients without aGVHD compared with their donors and recipients using Quantitative Set Analysis for Gene 17 sibling donors Expression (QuSAGE), which quantifies gene module activity as a shift in the mean differential expression of the individual genes To gain insight into the molecular changes associated with T-cell included in the module. We designed 51 gene modules by grouping expansion early after HCT, we performed gene-expression profiling genes belonging to specific signaling pathways, associated with 1 1 on sorted CD4 and CD8 T cells from donors before transplant particular cellular phenotypes, or with specific cellular functions, and on day 90 post-HCT from recipients without aGVHD. Principal 18 1 according to Molecular Signatures Database annotations and component analysis revealed a clear separation of the CD4 and based on current knowledge in the literature (supplemental Table 1), 1 CD8 T-cell gene-expression profiles, whereas samples from the 2 and compared T-cell gene-expression profiles in recipients without cohorts are homogeneously mixed, indicating the absence of “batch aGVHD and in their sibling donors. effects” between cohorts (supplemental Figure 4A). Principal 1 component analysis also showed a clear separation between donor In CD4 T cells, QuSAGE revealed 46 modules with statistically 1 1 and recipient samples in CD4 and CD8 T-cell populations significantly increased pathway activity in recipients compared with (supplemental Figure 4B). donors. Conversely, only few gene sets showed decreased pathway activity, and none of these reached statistical significance Differential expression analysis showed that, in recipients, the (Figure 3A). majority of the genes analyzed are upregulated and only few genes 1 1 are downregulated in the CD4 and CD8 T-cell populations. Among the modules with the greatest increase in pathway activity in Importantly, a high degree of overlap of the differentially expressed recipients and the lowest false discovery rate (FDR), were the “NLR genes between the 2 cohorts was observed, with changes in gene inflammasome,” the “T helper 1 (Th1) profile,” and the “Memory”

3930 LATIS et al 25 AUGUST 2020 x VOLUME 4, NUMBER 16 A B CD3+ T CD4+ T CD8+ T Ratio CD4/CD8 0.0083 0.0001 0.0001 0.0001 100 100 100 10 80 80 80 1 60 60 60 40 40 40 % of CD3 % of CD3 0.1 20 20 20 % of lymphocytes 0 0 0 0.01 DR DR DR DR

C Downloaded from https://ashpublications.org/bloodadvances/article-pdf/4/16/3927/1755611/advancesadv2019001032.pdf by guest on 20 August 2020 Live Dump– CD3+ CD4+ or CD8+ CD27+ CD45RA+ CD45RO-

TCM = T central memory TCM TN-like TEM = T effector memory T = T effector memory CD45RA+ TN TSCM-like EMRA CD27 CD45RO CD45RO T = T naïve TEM TEMRA N

TSCM = T memory stem cells CD45RA CD45RA CD95

D TNaive TSCM-like TCM TEM TEMRA 0.2901 100 0.0001 20 0.3705 0.2221 0.0001 100 100 100 80 15 80 80

T 10 + 60 60 60 10 1 40 40 40 % of CD4 5 0.1 20 20 20

0 0 0 0 0.01 DR DR DR DR DR

0.3535 0.0391 0.0001 20 0.6847 0.0002 100 100 100 100 80 80 15 80 10 T + 60 60 60 10 1 40 40 40 % of CD8 5 0.1 20 20 20

0 0 0 0 0.01 DR DR DR DR DR

E 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0007 0.0001 0.0001 100 D R

1 within T cell subset +

% Ki67 0.1

CD4 CD8 0.01 Total TNaive TCM TEM TEMRA Total TNaive TCM TEM TEMRA

Figure 1. T-cell compartment in recipients without aGVHD after HCT. Shown are results for donor/recipient couples without aGVHD from cohort 1. (A) Frequency of 1 1 1 1 1 CD3 T cells within the lymphocyte population (left panel) and frequencies of CD4 (middle panel) and CD8 (right panel) T cells within CD3 T cells. (B) Ratio of CD4 /

25 AUGUST 2020 x VOLUME 4, NUMBER 16 T-CELL PROFILES POST-HCT AND AT ACUTE GVHD ONSET 3931 module, which includes genes enriched in memory T cells, followed many genes upregulated in memory cells (eg, CD45R0, CD74, by gene sets related to T-cell activation and cytotoxicity, interferon KLRG1, IL2RB, FAS), whereas TNaive cell–associated genes (eg, (IFN)-induced genes, genes associated with exhausted cells, and CCR7, LEF1, TCF7)23-27 were underrepresented in recipients proapoptotic genes. The modules showing reduced pathway (Figure 3E-F; supplemental Figure 7). activity in recipients were the “Naive” module, regrouping genes Cellular correlates of aGVHD onset in recipients upregulated in TNaive cells, and the “WNT signaling” module (Figure 3A; supplemental Table 2). following HCT 1 “ ” QuSAGE of the gene-expression profiles of CD8 T cells To identify potential pathogenic T-cell subsets associated with (Figure 3B) showed that 43 gene modules were significantly aGVHD onset, we next assessed whether the frequency of the different between donors and recipients: 40 had significantly different T-cell subsets and their proliferative status were altered in increased pathway activity and 3 displayed significantly decreased recipients developing aGVHD, before administration of any steroid pathway activity in recipients. Among the gene sets with the therapy, compared with patients without aGVHD. Downloaded from https://ashpublications.org/bloodadvances/article-pdf/4/16/3927/1755611/advancesadv2019001032.pdf by guest on 20 August 2020 strongest and most significant increases in pathway activity, we To increase the power of our analysis, we combined the samples found genes related to T-cell activation and coinhibitory molecules, from the 2 cohorts. We focused our analysis on recipients with IFN-induced genes, genes upregulated in memory T cells, proa- grade 2-4 aGVHD to better identify changes associated with poptotic genes, and genes upregulated in exhausted cells aGVHD. Compared with recipients without aGVHD (n 5 36), at “ ” 1 ( Exhaustion_up ). Interestingly, in CD8 T cells, we also observed aGVHD onset, patients (n 5 22) showed significantly increased 1 1 modules displaying a significant reduction in pathway activity in frequencies of CD4 T cells and decreased CD8 T cells “ ” recipients compared with donors. In particular, the WNT signaling (supplemental Figure 8A), leading to a CD4/CD8 ratio generally “ ” “ ” module, the Naive module, and the Exhaustion_down module, .1 (supplemental Figure 8B). This contrasts with the posttrans- including genes downregulated in exhausted T cells, had decreased plant situation in patients without aGVHD, which is characterized by pathway activity (Figure 3B; supplemental Table 3). Among the 40 1 an inverted CD4/CD8 ratio (Figure 1B). gene modules upregulated in CD8 T cells, 38 were also 1 upregulated in CD4 T cells, suggesting a large overlap in the Analysis of the TNaive cell and memory T-cell subsets revealed that, signaling pathways affected by HCT in the 2 T-cell subsets at aGVHD onset, recipients have significant increases in cells with (supplemental Figure 5). a T memory stem cell-like (TSCM-like) or a central memory T cell (TCM) phenotype compared with recipients without aGVHD, whereas TEM 1 1 The pathway activity of the gene modules showed a good cells were decreased in the CD4 and CD8 compartments correlation in the 2 cohorts (Figure 3C-D). Moreover, the ranking (supplemental Figure 8C). Increased cell proliferation was also 1 1 of the modules based on the pathway activity is similar (supple- observed at aGVHD onset in CD4 and CD8 compartments for 1 mental Figure 6A-B; supplemental Tables 2 through 5), indicating TNaive,TCM, and TEM subsets, as well as within the CD4 that the gene-expression signature associated with HCT and compartment for the TEMRA subset (supplemental Figure 8D). Very immune reconstitution is reproduced in 2 independent cohorts. similar results were obtained when the recipient/donor ratios of cell populations were compared for No GVHD couples vs aGVHD Closer inspection of individual genes within enriched modules 1 couples (Figure 4). In particular, we noted a significant expansion of showed that CD4 T cells in recipients displayed a gene- T relative to the donor sample in the CD4 and CD8 expression profile skewed toward the Th1 phenotype, with SCM-like compartments in aGVHD couples (Figure 4). upregulation of genes such as TBX21, IFNG, and CXCR3.We also observed upregulation of genes involved in T-cell migration, T-cell transcriptional profiling at aGVHD onset reveals such as the chemokine receptors CX3CR1, CCR5, CXCR3, upregulation of proinflammatory mediators and CCR2, and CCR6, as well as many IFN-induced genes (Figure 3E). downregulation of genes involved in 1 Within the CD8 subset (Figure 3F), we noted upregulation of IFN- immune regulation induced genes, as well as an enrichment of inhibitory receptors (HAVCR2, CD160, PDCD1, CTLA4, LAG3, KLRD1, CD244, The mechanisms underlying the immune escape and alloreactivity KLRG1, SLAMF7) and genes associated with exhausted cells that occur, despite ongoing immunosuppression, and lead to aGVHD development in humans are still unclear. We performed (HAVCR2, BATF, CD160, PDCD1, CTLA4, EOMES, TBX21, 1 1 LAG3, CASP3, CD244, KLRG1, SH2D1A)19-22. gene-expression profiling on sorted CD4 and CD8 T cells from recipients without aGVHD and at aGVHD onset, before the start of Consistent with the flow cytometry data showing a depletion of the steroid therapy. We used the same inclusion criteria as for the TNaive cell pool and an increase in cells with an effector memory previous cellular profiling analysis (Figure 4; supplemental phenotype after HCT (Figure 1D), we observed an enrichment of Figure 8D).

1 Figure 1. (continued) CD8 T cells in recipients (R) at day 90 post-HCT compared with their respective sibling donors (D). (C) Gating strategy used to identify naive and 1 1 memory subsets within the CD4 and CD8 T-cell compartments in donors and recipients after transplantation by polychromatic flow cytometry. (D) Frequencies of TNaive, 1 1 TSCM-like,TCM,TEM,andTEMRA cells within the CD4 (upper panels) and CD8 (lower panels) T-cell compartments in recipients (R) at day 90 post-HCT compared with their 1 1 1 1 respective sibling donors (D). (E) Frequency of proliferating Ki-67 cells in total CD4 and CD8 T cells and in the different naive and memory subsets in CD4 (left panel) 1 1 1 and CD8 (right panel) compartments in donors and recipients. The frequency of Ki-67 cells is represented as the percentage of Ki-67–expressing cells within total CD4 or 1 CD8 T cells and as the percentage Ki-67–expressing cells within the parent gate for TNaive,TCM,TEM, and TEMRA cell subsets. Horizontal lines indicate the median. P values were calculated using the Wilcoxon matched-pairs Student t test (donor vs respective recipient). Differences are considered significant for P , .05.

3932 LATIS et al 25 AUGUST 2020 x VOLUME 4, NUMBER 16 A B Treg FOXP3+ Treg proliferation <0.0001 25 <0.0001 100 20 10 T +

15 in Treg

+ 1 10 % of CD4 5 % Ki67 0.1

0 0.01

DR DR Downloaded from https://ashpublications.org/bloodadvances/article-pdf/4/16/3927/1755611/advancesadv2019001032.pdf by guest on 20 August 2020 C <0.0001 70 <0.0001 D Ki67+ cells <0.0001 <0.0001 R <0.0001 60 100

40 10 Treg/Tconv +

within T cell subset 30 +

20 1 % Ki67 Ratio Ki67 10

0 0.1 D _R D_R DR Tconv Treg D CTLA4+ ICOS+ PD1+ 0.0028 0.0001 50 80 0.0037 30 40 60 20 30 40 20 10 20 10

0 0 0 % of Treg expressing this marker % of Treg DR DR DR

Figure 2. Treg homeostasis in recipients without aGVHD after HCT. Shown are results for donor/recipients couples without aGVHD from cohort 1. (A) Frequency of 1 1 1 1 1 FOXP3 cells within the CD4 population in donors (D) and recipients (R) at day 90 post-HCT. (B) Frequencies of Ki-67 , within the CD4 FOXP3 Treg population, in 1 1 1 1 2 donors (D) and recipients (R) at day 90 post-HCT. (C) Frequency of proliferating (Ki-67 ) cells within the CD4 FOXP3 Treg and CD4 FOXP3 Tconv populations in 1 donors (D) and recipients (R) (left panel) and ratios of proliferating (Ki-67 ) Treg/Tconv in donors (D) and recipients (R) at day 90 post-HCT (right panel). (D) Frequencies of 1 1 1 1 1 CTLA4 , ICOS , and PD1 cells within the CD4 FOXP3 Treg population in donors (D) and recipients (R) at day 90 post-HCT. Horizontal lines indicate the median. P values were calculated using a Wilcoxon matched-pairs Student t test or a Mann-Whitney U test. Differences are considered significant for P , .05.

1 1 Gene-expression profiles of CD4 T cells showed differential transcripts within this module showed that CD4 T cells from expression of 18 genes in patients with aGVHD compared with No recipients at aGVHD onset had significantly lower expression levels GVHD recipients (FDR , 0.05). Of these, 2 were expressed at of genes encoding TGFBR1, SMAD3, and IGF2R compared with higher levels and 16 were expressed at lower levels in patients with the No GVHD group (Figure 5C). In contrast, we noticed increased aGVHD (Figure 5A). QuSAGE revealed 6 modules with significantly levels of genes involved in the NF-kB signaling pathway (eg, BCL10 decreased pathway activity at aGVHD onset. Interestingly, genes and BCL3) at aGVHD onset. Expression of PSMD7, encoding associated with “transforming growth factor-b (TGF-b) signal- a component of the 26S proteasome, and of ICOS (Figure 5D), 1 1 ing” were downregulated most significantly (Figure 5B; supple- a member of the CD28 superfamily, induced in CD4 and CD8 mental Table 6). Closer inspection of the differentially expressed T cells during T-cell activation,28 was also higher at aGVHD onset.

25 AUGUST 2020 x VOLUME 4, NUMBER 16 T-CELL PROFILES POST-HCT AND AT ACUTE GVHD ONSET 3933 A CD4 1 0.1 –0.1 0.05 0.01 –0.01 –0.05 1.5 0.005 0.001 –0.001 –0.005

1.0 Downloaded from https://ashpublications.org/bloodadvances/article-pdf/4/16/3927/1755611/advancesadv2019001032.pdf by guest on 20 August 2020 0.5 Pathway activityPathway

0.0

–0.5

MAPK Naive Memory Adhesion Th1_profile Autophagy JAK_STAT Tfh_profile NFAT_TFs NFKB_TFsTh2_profile Coinhibitory Treg_profile Th17_profile Proapoptotic ComplementIL2_signaling Costimulatory IL7_signaling Antiapoptotic Tcell_activation Exhaustion_up TLR_signaloing TNF_signaling TCR_signaling ProinflammatoryCTL_Cytotoxicity TGFb_signaling Antiinflammatory WNT _signaling NOTCH_signalingExhaustion _down IFN_induced genes Energy_Metabolism NLR_inflammasome Type1_IFN_signaling NFKB_Target_genes Chemotaxis_MigrationJAK_STAT_Regulation Ubiquitin_Proteasome NOTCH_target genes Nucleotide_Metabolism IL1_IL18_IL33_signaling NFAT_pathway_Biocarta Homeostatic_proliferation NFKB_Positive_regulators NFKB_Negative_regulators Regulation_of_Tcell_activation Cell_cycle_and_its_regulation

Ag_Presentation_MHC_Interaction Transcription_Translation_Regulation

B CD8 1 0.1 –0.1 0.05 0.01 –0.01 –0.05 0.005 0.001 –0.001 –0.005 1.0

0.5

0.0 Pathway activityPathway

–0.5

–1.0

MAPK Naive Memory Adhesion Th1_profile Autophagy NFAT_TFs Th2_profile NFKB_TFs Tfh_profile Coinhibitory JAK2_STAT Treg_profile Th17_profile Proapoptotic IL2_signaling ComplementCostimulatoryIL7_signalingAntiapoptotic Exhaustion_up Tcell_activationTNF_signalingTLR_signaloingTCR_signaling CTL_Cytotoxicity Proinflammatory TGFb_signaling Antiinflammatory WNT _signaling NOTCH_signaling Exhaustion _down IFN_induced genes Energy_Metabolism NLR_inflammasome Type1_IFN_signaling NFKB_Target_genes Ubiquitin_Proteasome JAK_STAT_Regulation Chemotaxis_MigrationNOTCH_target genes Nucleotide_Metabolism NFAT_pathway_Biocarta IL1_IL18_IL33_signaling Homeostatic_proliferation NFKB_Positive_regulators NFKB_Negative_regulators Regulation_of_Tcell_activation Cell_cycle_and_its_regulation

Ag_Presentation_MHC_Interaction Transcription_Translation_Regulation

1 1 Figure 3. Molecular signature of T cells in recipients without aGVHD after HCT compared with their donors. QuSAGE of CD4 (A) and CD8 (B) T-cell gene- expression profiles in recipients at day 90 post-HCT compared with their respective donors before transplant in cohort 1. For each pathway, the mean fold change and the 95% confidence intervals are plotted and color-coded according to their FDR-corrected P values compared with 0. Red and green bars indicate a statistically significant 1 1 increased or decreased pathway activity, respectively, in recipients compared with donors. Correlation between cohorts 1 and 2 for QuSAGE in CD4 (C) and CD8 (D) T cells. Red dots correspond to modules significantly enriched (FDR # 0.05) in both cohorts, blue dots correspond to modules enriched in only 1 cohort, and black dots

3934 LATIS et al 25 AUGUST 2020 x VOLUME 4, NUMBER 16 C E Memory Chemotaxis QuSAGE R vs D – CD4

No signif Sample Status Sample Status One signif CX3CR1 CX3CR1 1.5 Both signif CCR5 CCR5 IFNG CXCR6 HLA-DRA PPBP ITGAM CXCR3 FAS LTB4R S100A9 CCR2 1.0 HLA-DPA1 CCL4 DUSP4 LTB4R2 MAF CCL5 GZMA CMKLR1 TBX21 S1PR1 HLA-DPB1 IL16 0.5 CD74 CCR6 TNFSF10 GPR183 KLRG1 CXCR4 PRF1 CCR7

Averagel og2FCAveragel cohort 2 CXCR3 IL18RAP NCF4 0.0 CD244 Th1 profile Downloaded from https://ashpublications.org/bloodadvances/article-pdf/4/16/3927/1755611/advancesadv2019001032.pdf by guest on 20 August 2020 IL18R1 CCC=0.82 CCR2 ITGA4 CD160 GZMB 0.0 0.5 1.0 CD58 Sample Status IL12RB1 CCR5 Average log2FC cohort 1 PTPN22 IFNG TNFRSF1B TBX21 GZMK CXCR3 BATF IL18RAP LY 9 6 IL18R1 TNF STAT1 D SLAMF1 IL12RB1 CASP1 TNF ITGB2 IFNGR1 CCL5 CD46 QuSAGE R vs D – CD8 ITGB1 IFNAR2 IFNGR1 STAT4 IL2RB No signif LTA 1.5 One signif ITGAL Both signif CD45R0 EOMES SMAD3 IL10RA IFN-induced LGALS3 1.0 CD2 IL2RG NFATC2 PRDM1 Sample Status ITGA5 IRF5 0.5 NFATC3 GBP1 KLRC1 IFI35 KLRF1 IRF7 CCR6 CD74 IL7R TNFSF10 0.0 CD7 STAT1 CFH PSMB8 Averagelog 2FCAveragelog cohort 2 IFIT2 IFI16 PML -0.5 STAT2 SOCS1 CCC=0.71 IFIH1 Relative gene expression level IRF4 IFNGR1 -0.5 0.0 0.5 1.0 BST2 IRF1 MX1 Average log2FC cohort 1 -2.0 -1.8 -1.6 -1.4 -1.2 -1.0 -0.8 -0.6 -0.4 -0.2 0.0 2.0 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0 HLA-C HLA-A IRF3 SOCS3 IFITM1 HLA-B JAK1

F Exhaustion Coinhibitory IFN-induced Donor

Recipient

Sample Status Sample Status Sample Status HAVCR2 HAVCR2 GBP1 CD160 CD160 IRF7 CASP3 LAG3 CD74 BATF CTLA4_all STAT1 LAG3 CTLA4-TM IFI35 CTLA4_all TNFSF10 PDCD1 IFIT2 PDCD1 SLAMF7 IFI16 TBX21 KLRD1 IRF3 NFIL3 KLRG1 IRF4 IRF4 sCTLA4 PSMB8 KLRG1 TNFRSF14 IRF1 CCL4 BTLA STAT2 EOMES CD244 PML SH2D1A CD5 IFIH1 JAK3 PECAM1 BST2 IFIH1 TIGIT MX1 BTLA LAIR1 HLA-A PTGER4 CD96 HLA-C MX1 LILRB1 IRF5 CD244 IFITM1 IL2RB HLA-B MAP4K4 JAK1 TIGIT SOCS1 PRDM1 IFNGR1 IL18R1 SOCS3 NFATC1A ETS1 CD7 MAF TNFRSF4 ICOS NFKBIZ ICAM2 NFKBIA CD27 CD28 TCF7 IKZF2 LEF1 IL7R

Figure 3. (continued) correspond to modules not enriched. The concordance correlation coefficient (CCC) is displayed to quantify the reproducibility of the results between the 2 cohorts. Relative gene-expression levels of genes in selected enriched modules in recipients at day 90 post-HCT compared with their respective donors before transplant 1 1 in cohort 1 in CD4 (E) and CD8 (F) T cells. In the heat maps, columns represent samples and are ordered by hierarchical clustering, whereas rows represent genes and are ranked by fold change. Yellow indicates high levels of expression, and blue indicates low levels of expression. Ag, antigen; CTL, cytotoxic T lymphocyte; MHC, major histocompatibility complex; TCR, T-cell receptor; TF, transcription factor; TGF, transforming growth factor; TLR, Toll-like receptor; TNF, tumor necrosis factor.

25 AUGUST 2020 x VOLUME 4, NUMBER 16 T-CELL PROFILES POST-HCT AND AT ACUTE GVHD ONSET 3935 1 CD8 T cells from recipients at aGVHD onset showed differential The simultaneous analysis of multiple surface and intracellular expression of 134 genes compared with recipients without aGVHD markers of Tregs and Tconvs was facilitated by the use of spectral (FDR , 0.05): higher expression levels for 23 genes and lower flow cytometry, which allowed the analysis of limited numbers of levels for 111 transcripts at aGVHD onset (Figure 6A). Among the cells for each patient sample. The introduction of mass cytometry transcripts with higher levels in patients with aGVHD were genes would allow an even more comprehensive analysis of immune involved in NF-kB signaling (NFKB1, BCL3) and the negative cells38; however, this technology was not accessible when this 1 regulator NFKBIA. Similarly to CD4 T cells, PSMD7 and ICOS study was designed. showed higher expression in patients with aGVHD. In addition, 1 In patients without aGVHD, we found an incomplete reconstitution CD8 T cells displayed increased expression of the costimulatory of the T-cell compartment after transplant with a bias toward an molecule CD28, the inflammatory mediator MIF, and the glycolytic effector/memory phenotype and a depletion of T cells enzyme GAPDH (Figure 6B). The switch from oxidative phosphor- Naive compared with their sibling donors. We noted increased pro- ylation to aerobic glycolysis is a hallmark of T-cell activation, and 1 1 liferation of all CD4 and CD8 T and T memory subsets Downloaded from https://ashpublications.org/bloodadvances/article-pdf/4/16/3927/1755611/advancesadv2019001032.pdf by guest on 20 August 2020 aerobic glycolysis was shown to facilitate full effector status and Naive analyzed in recipients compared with donors. In particular, we found IFN-g production in T cells.29 high proliferation of the Treg compartment, confirming our previous QuSAGE identified 24 gene modules that were significantly results and those from other investigators.13,16 Increased T-cell different between patients with and without aGVHD (Figure 6C; proliferation in recipients after HCT could be driven by increased supplemental Table 7). Of these, 23 modules had significantly availability of the homeostatic cytokines IL-7 and IL-15 after decreased pathway activity, and only 1 module had significantly transplantation,16,39,40 as well as stimulation by the host alloanti- higher activity, at aGVHD onset. The latter is the “NF-kB–TFs” gens. Tregs in recipients may also acquire increased activity, as module, which includes the NF-kB transcription factors NFKB1, shown by increased expression of CTLA4 and ICOS, molecules of NFKB2, RELA, and RELB, suggesting an important role for the key importance for their suppressive functions.41,42 NF-kB signaling pathway in alloreactive T cells mediating aGVHD in To investigate the molecular mechanisms underlying T-cell expan- humans. 1 sion after HCT, we analyzed gene expression in sorted CD4 and 1 1 Similarly to CD4 T cells, the “TGF-b signaling” module was most CD8 T cells from donors before transplant and from patients 1 significantly downregulated in CD8 T cells at aGVHD onset without aGVHD on day 90 post-HCT, using nCounter assays. This (Figure 6C; supplemental Table 7; P 5 .00005; FDR 5 0.002). We approach is well adapted to the analysis of the low T-cell numbers also observed the “Coinhibitory” and “Anti-inflammatory” modules recovered, in particular in recipients post-HCT, and is very robust among those with significantly lower pathway activity. Transcript because no enzymatic reaction or polymerase chain reaction 14,43 levels of representative genes belonging to these modules are amplification is needed. Our gene-expression analysis revealed 1 shown in Figure 6D. We found downregulation of genes involved in that HCT is associated with major transcriptional changes in CD4 1 TGF-b signaling (TGFBR2, SMAD3, IGF2R), as well as genes and CD8 T cells in recipients compared with their donors. encoding inhibitory receptors (LAIR1, BTLA, KLRG1)30-33 and 34 We found that donor T cells react to the environment of the host by molecules mediating immunosuppressive signals (IL10RA), acquiring an activated phenotype with upregulation of genes suggesting that decreased expression of genes involved in associated with T-cell activation and its regulation, adhesion, and regulation and dampening of immune responses may be implicated migration, as well as effector functions, especially linked to a Th1 in the development of aGVHD. cell profile and cytotoxicity. Consistent with our flow cytometry data, Discussion we observed an enrichment of many genes reported to be expressed in memory T cells and an underrepresentation of genes In this study, we investigated the cellular and molecular mechanisms associated with TNaive cells. The increased activation may be underlying aGVHD development or the absence of significant associated with T-cell dysfunction, as suggested by the increased aGVHD at 3 months posttransplant in 2 cohorts of patients expression of proapoptotic genes and genes upregulated in undergoing allo-HCT from their HLA-identical sibling donors. We exhausted cells. 1 provide one of the first transcriptional analyses of sorted CD4 and 1 Analysis of the different T cell and memory T-cell subsets in CD8 T cells showing striking differences between healthy donors Naive recipients, using spectral flow cytometry, revealed that patients had and recipients without aGVHD, as well as noticeable differences in 1 1 a significant increase in CD4 and CD8 cells with a T patients with and without aGVHD. To the best of our knowledge, an SCM-like phenotype at aGVHD onset compared with recipients without analysis of T-cell gene-expression profiles at steady-state in healthy aGVHD. T memory stem cells (T ) have been shown to sustain donors vs allogeneic recipients without aGVHD in the same system SCM alloreactive T cells mediating GVHD upon serial transplantation into has not been performed. allogeneic hosts in mice.27 Gattinoni and colleagues reported the 44 Although previous work in an experimental mouse model has identification of TSCM in humans, but an association between this demonstrated that naive cells are more likely to respond to weak- or cell subset and human aGVHD has not been described. The ability 35 low-affinity antigens in lymphopenic conditions, and that homeo- of TSCM to sustain the generation of all memory and effector T-cell static proliferation of TNaive cells is associated with the acquisition of subsets while maintaining their own pool through self-renewal has 36 27,44,45 a memory-like phenotype in these conditions, data on early important implications for aGVHD pathophysiology. TSCM immune reconstitution are scarce. The largest cohort analyzed so cells could represent a cellular reservoir for alloreactive T cells in far,37 included only the simultaneous study of 5 surface T-cell recipients developing GVHD, sustaining the production of allor- markers; most studies aiming to analyze T-cell reconstitution eactive donor T cells in the presence of persistent antigens in hosts. posttransplantation were performed at a later time point.3,8,16,38 Further investigation including additional markers for a more

3936 LATIS et al 25 AUGUST 2020 x VOLUME 4, NUMBER 16 A CD3+ T CD4+ T CD8+ T 0.0001 2.0 0.0278 3 6 0.0004 1.5 2 4 1.0 Ratio R/D Ratio R/D Ratio R/D 1 2 0.5

0.0 0 0 No GVHD No GVHD No GVHD GVHD GVHD GVHD Downloaded from https://ashpublications.org/bloodadvances/article-pdf/4/16/3927/1755611/advancesadv2019001032.pdf by guest on 20 August 2020 B Tnaive TSCM-like Tcm TEM TEMRA 0.0022 0.1019 0.0975 0.1329 0.0754 10 100 4 20 1000

8 10 3 15 100 6 1 CD4 2 10 10 4 0.1 Ratio R/D 2 0.01 1 5 1 0 0.001 0 0 0.1 No GVHD No GVHD No GVHD No GVHD No GVHD GVHD GVHD GVHD GVHD GVHD

0.0075 0.0067 0.2062 0.0139 0.2452 10 100 4 20 1000

8 10 3 15 100 6 1 CD8 2 10 10 4 0.1 Ratio R/D 2 0.01 1 5 1 0 0.001 0 0 0.1 No GVHD No GVHD No GVHD No GVHD No GVHD GVHD GVHD GVHD GVHD GVHD

1 1 1 Figure 4. Cellular correlates of aGVHD onset. (A) Ratios of the frequency of CD3 T cells within lymphocytes (left panel), CD4 T cells within CD3 T cells (middle 1 1 panel), and CD8 T cells within CD3 T cells (right panel) between recipients and donors (R/D) in aGVHD vs No aGVHD couples. (B) Ratios of the frequency of TNaive,TSCM- 1 1 like,TCM,TEM, and TEMRA cells within CD4 cells (upper panels) and CD8 cells (lower panels) between R/D in aGVHD vs No aGVHD couples. Horizontal lines indicate the median. For this analysis, samples from the 2 cohorts were pooled. All recipients without aGVHD or with grade $2 aGVHD were included in the analysis (No GVHD, n 5 36; GVHD, n 5 22). P values were calculated using the Mann-Whitney U test; differences are considered significant for P , .05. detailed phenotypic characterization, together with functional Our analysis of signaling pathways associated with aGVHD studies, may elucidate the role of this cell subset in aGVHD. onset also showed downregulation of genes involved in TGF-b signaling,46 whereas genes involved in the NF-kB signaling To investigate genes and pathways involved in aGVHD pathogen- 1 pathway, which plays a central role in mediating T-cell receptor esis, we performed gene-expression profiling of sorted CD4 and 50 1 signaling and T-cell activation and differentiation, were upregu- CD8 T cells from recipients without aGVHD and at aGVHD onset, lated at aGVHD onset. These data support an important role for the before the start of steroid therapy. With regard to the cellular 1 1 NF-kB pathway in alloreactive CD4 and CD8 T cells mediating profiling, we focused this analysis on recipients with grades 2-4 human aGVHD. Consistently, inhibition of NF-kB was shown to aGVHD. protect mice from lethal GVHD.51 1 1 Perreault et al performed CD4 and CD8 T-cell gene-expression profiling of donors and found that TGF-b signaling and genes We noted that the proteasome subunit PSMD7 is expressed at 1 1 implicated in cell proliferation characterized “dangerous” donors higher levels in CD4 and CD8 T cells at aGVHD onset. with regard to the recipient’s risk for developing chronic GVHD.46 Proteasome activity has been shown to induce memory at the Only a few other studies in small cohorts have analyzed the gene- expense of effector T-cell differentiation in a mouse model,52 expression profile associated with aGVHD in humans.47-49 These consistent with the downregulation of the gene module “CTL 1 studies used microarray analyses of PBMCs47,49 or microbead- cytotoxicity” that we observed at aGVHD onset in CD8 T cells. enriched immune cell subpopulations48; the sets of genes that were These data are further corroborated by the higher frequencies of up- or downregulated before or at aGVHD onset in the different TSCM-like and TCM subsets and the lower frequencies of TEMs at studies are not consistent, possibly because of the heterogeneity of aGVHD onset. Together, these findings may suggest an important the patient populations. role for memory T-cell subsets in aGVHD pathogenesis.

25 AUGUST 2020 x VOLUME 4, NUMBER 16 T-CELL PROFILES POST-HCT AND AT ACUTE GVHD ONSET 3937 A B Downregulated Upregulated 5 CD4 FDR<0.05 FDR<0.05

IGF2R Enriched downregulated 4 pathways (FDR<0.05)

NOD1 CRADD TGFBR1 4 LAIR1

IRF3 PSMD7 BCL3 LTB4R SMAD5 3 IL1RAP IKBKAP CD244 IRAK4 TYK2 CD46 IRF5 ATG7 IKZF3 ZAP70 3 HLA-DMB IKBKB SIGIRR LTB4R2 TRAF5 CX3CR1 TRAF2 SMAD3 MAPK1 RELB CASP STAT6 BCL10 FAS NOTCH2 LILRA6 ICOS SLAMF6 POLR1B ITGAL IKBKE ITGA IL7R IKZF1 SDHA Downloaded from https://ashpublications.org/bloodadvances/article-pdf/4/16/3927/1755611/advancesadv2019001032.pdf by guest on 20 August 2020 MAF PTPN6

-Log10 (P value) -Log10 2 PYCARD 2 -Log10 (P value) -Log10 1 1

0 0 -3 -2 -1 0 1 Log2 fold change (GVHD vs no GVHD) _signaling Adhesion E IL7_signaling TGF NLR_inflammasome NOTCH_target genes NFKB_Positive_regulators C D 500 No GVHD 700 GVHD 0.0009 0.0054 600 400 0.0077 500

300 400 0.0009 0.0066 Counts Counts 0.0003 <0.0001 300 200

200 100 100

0 0 TGFBR1SMAD3 IGF2R BCL3BCL10 ICOS PSMD7

1 Figure 5. CD4 T-cell gene-expression signature at aGVHD onset. For this analysis, samples from the 2 cohorts were pooled. All recipients without aGVHD or with 1 grade $2 aGVHD were included in the analysis (No GVHD, n 5 35; GVHD, n 5 24). (A) Gene-expression profiles of CD4 T cells from 24 patients at aGVHD onset compared with 35 patients without aGVHD in cohorts 1 and 2. Orange and light blue dots represent transcripts that were significantly up- and downregulated in recipients at aGVHD onset compared with No GVHD recipients, respectively, with FDR , 0.05. P values were calculated using an unpaired Student t test. Adjusted P values (FDR) were 1 calculated using the Benjamini-Hochberg method to correct for multiple comparisons. (B) Results of QuSAGE conducted on CD4 T-cell gene-expression profiles from aGVHD and No GVHD recipients. Plotted is the negative logarithm to the base 10 of the P values for the 6 modules with significantly different pathway activity (FDR , 0.05) 1 at GVHD onset compared with No GVHD recipients. (C) Transcript levels of TGFBR1, SMAD3,andIGF2R in CD4 T cells from recipients without aGVHD (No GVHD) and at aGVHD onset (GVHD). These genes showed decreased expression at aGVHD onset compared with recipients without GVHD (P , .05; FDR , 0.1). (D) Transcript levels 1 of BCL3, BCL10, ICOS, and PSMD7 in CD4 T cells from recipients without aGVHD and at aGVHD onset. These genes showed increased expression at aGVHD onset compared with recipients without aGVHD (P , .05; FDR , 0.1). P values were calculated using an unpaired Student t test. Adjusted P values (FDR) were calculated using the Benjamini-Hochberg method to correct for multiple comparisons. Nominal P values are shown in panels B and D.

1 1 Finally, we found higher expression of ICOS in CD4 and CD8 established that using neutralizing anti-ICOS antibodies to block T cells at aGVHD onset. This observation may be of particular ICOS significantly ameliorated GVHD in multiple strain combina- interest, because previous studies in mouse models have tions, even when used in a therapeutic setting (injection 5 days after

3938 LATIS et al 25 AUGUST 2020 x VOLUME 4, NUMBER 16 AB Downregulated Upregulated 6 CD8 FDR 0.05 FDR 0.05

CMKLR1 No GVHD GVHD

LTB4R2 16384 0.0024 KLRK1

SMAD3 IKBKB ITGB1 4 SELPLG NOD1 SIGIRR 4096 0.0099 TGFBR1 FAS KLRC4 CD58 STAT4 CRADD CUL9 ZAP70 KLRG1 CD244 TMEM173 MAPK1 SLAMF6 NFATC2 24 0.0016 IL18RAP TBX21 TYK2 ICOS TOLLIP IKBKG PTPRC IL10RA S100A9 0.0046 LTB4R KLRAP1 ABCB1 IRAK4 CCND3 0.0023 KLRD1 TRAF1 MIF ATG7 IGF2R ITGA4 CD46 ITGA5 CD2 MAPK14 GAPDH BCL3 S100A8 CX3CR1 BATF MBP CD247 0.0009 STAT6 ITGAM LCP2 IFNAR2 56 IKZF1 ITGAL C14orf166 IKBKAP CD28 GPR183 CD160 GFI1 SLAMF7 ATG10 FYN TBP 0.0122 LILRB1 ABL1RUNX1IICAM1 EEF1G - Log10 (P value) - Log10 TRAF2 Downloaded from https://ashpublications.org/bloodadvances/article-pdf/4/16/3927/1755611/advancesadv2019001032.pdf by guest on 20 August 2020 NFATC3 STAT5BSKI PSMD7 TRAF5 CD45RB IKZF3 LCKTAGAP IL2RA BTLA GUSB PTPN22 IL4R XBP1 NFKBIA TNFSF8 Counts IRF3 PTPN6 LIF SDHA C1QBP NOTCH2 LILRA6 2 NOTCH1PRKCDJAK2MAP4K1 CD7 RELB ITGAX IL21R PRF1 TGFBR2 IL6ST NFKB1 64 HLA-DMB CD45R0 TNFSF12 GNLY HRAS CASP8 MAP4K4 CD4 SMAD5 RAF1 CD6 CCR7 NCR1 TAP2 FCGR3A/B HAVCR2 16

0 1

-2 -1 0 1 2 MIF BCL3 ICOS CD28 Log2 fold change (GVHD vs no GVHD) NFKB1 NFKBIA GAPDH

CD CD8 GVHD vs No GVHD 16384 0.0008 0.0004 1

0.1 0.0013 0.0069 –0.1 0.05 0.01 0.0124 –0.01 –0.05 0.005 0.001

–0.001 –0.005 4096 0.5 0.0001 0.0088

0.0 64 Counts

–0.5 16 Pathway activityPathway

4 –1.0 1

Naive MAPK Memory IGF2R LAIR1 BTLA4 Adhesion SMAD3 KLRG1 IL10RA Tfh_profile Autophagy JAK_STAT NFAT_TFs NFKB_TFs Treg_profile Th2_profile Th1_profile TGFBR2 Th17_profile Coinhibitory IL2_signalingAntiapoptotic Proapoptotic IL7_signaling Complement Costimulatory TLR_signaling TNF_signaling Tcell_activation Exhaustion_up TCR_signaling WNT_signalingProinflammatory TGFb_signaling Antiinflammatory CTL_Cytotoxicity Exhaustion _down NOTCH_signaling Energy_Metabolism IFN_induced genes NLR_inflammasome NFKB_Target_genes Type1_IFN_signaling Ubiquitin_ProteasomeNOTCH_target genes Chemotaxis_Migration AJAK_STAT_Regulation Nucleotide_Metabolism IL1_IL18_IL33_signalingNFAT_pathway_Biocarta Homeostatic_proliferation NFKB_Positive_regulators NFKB_Negative_regulators Regulation_of_Tcell_activation Cell_Cycle_and_its_Regulation

Ag_Presentation_MHC_Interaction Transcription_Translation_Regulation

1 Figure 6. CD8 T-cell gene-expression signature at aGVHD onset. For this analysis, samples from the 2 cohorts were pooled. All recipients without aGVHD or with 1 aGVHD grade $2 were included in the analysis (No GVHD, n 5 36; GVHD, n 5 22). (A) Gene-expression profiles of CD8 T cells from 22 patients at aGVHD onset compared with 36 patients without aGVHD in cohorts 1 and 2. Orange and light blue dots represent transcripts that were significantly up- or downregulated in recipients at aGVHD onset compared with No GVHD recipients, respectively, with FDR , 0.05. P values were calculated using an unpaired Student t test. Adjusted P values (FDR) were calculated using the Benjamini-Hochberg method to correct for multiple comparisons. (B) Transcript levels of NFKB1, BCL3, NFKBIA, ICOS, CD28, MIF,andGAPDH in 1 CD8 T cells from recipients without aGVHD and at aGVHD onset. These genes showed increased expression at aGVHD onset compared with recipients without GVHD 1 (P , .05; FDR , 0.05). (C) QuSAGE of CD8 T-cell gene-expression profiles in recipients at aGVHD onset compared with recipients without aGVHD from cohorts 1 and 2. For each pathway, the mean fold change and the 95% confidence intervals are plotted and color-coded according to their FDR-corrected P values compared with 0. Red and green bars indicate a statistically significant increased or decreased pathway activity, respectively, in recipients at aGVHD onset compared with recipients without GVHD. (D) 1 Transcript levels of TGFBR2, SMAD3, IGFR2, LAIR1, BTLA, KLRG1, and IL10RA in CD8 T cells from recipients without aGVHD and at aGVHD onset. These genes showed decreased expression at aGVHD onset compared with recipients without aGVHD (P , .05; FDR , 0.05). P values were calculated using an unpaired Student t test. Adjusted P values (FDR) were calculated using the Benjamini-Hochberg method to correct for multiple comparisons. Nominal P values are shown in panels C and D. Tfh, T follicular helper cell. transplantation).53,54 More recently, Burlion and colleagues dem- mice.55 Importantly, ICOS blockade did not reduce the graft-versus- onstrated that blockade of human ICOS prevented GVHD in leukemia effect. Higher ICOS expression in T cells at aGVHD onset a xenogeneic GVHD model, in which human PBMCs were may provide additional evidence to explore ICOS blockade as 2 2 transferred into irradiated immunocompromised NOD.SCID.gc / a therapeutic strategy for aGVHD treatment.

25 AUGUST 2020 x VOLUME 4, NUMBER 16 T-CELL PROFILES POST-HCT AND AT ACUTE GVHD ONSET 3939 This study has some limitations. One issue is how to compare Cellular Therapy for providing patient samples used in this study, as human immune dysregulation at disease onset. We designed the well as the Center for Translational Science/Cytometry Biomarkers study to be able to compare our findings at disease onset with Unit of Technology and Service (Institut Pasteur) for support in 2 “comparators”: the immune system at “baseline” (ie, data conducting this study. recovered from the donor samples) and recipients without aGVHD This work was supported by grants from the Agence National de at day 90. Comparing patients at the onset of aGVHD with those la Recherche (ANR-PRTS 13002), the Institut National du Cancer without aGVHD leads to intrinsic differences between groups of (INCa 2014-1-PL BIO-07-IP-1), and the Direction Gen´ erale´ de patients (supplemental Figure 1B). Furthermore, we acknowledge l’Offre de Soins, as well as by institutional funds from Institut that using day-90 profiles in patients without aGVHD as a compar- Pasteur. E.L. was supported by a grant from the Universite´ Paris ator for profiles of patients with aGVHD at disease onset can be Diderot and the Ministere` de la Recherche. G.S. received a research criticized. However, other comparators, such as patients without grant from ALEXION Pharmaceuticals. The CRYOSTEM project is aGVHD at the same mean elapse time as those with aGVHD, was supported by a grant from the Institut National du Cancer and the Downloaded from https://ashpublications.org/bloodadvances/article-pdf/4/16/3927/1755611/advancesadv2019001032.pdf by guest on 20 August 2020 not chosen because these “non-GVHD” controls may eventually Agence Nationale de la Recherche and is under the auspices of the develop GVHD a few days after sampling at a time during which the Societ´ e´ Francophone de Greffe de Moelle et de Therapie´ Cellulaire. processes were already ongoing. This was a discovery-driven study; future studies may address these potential confounders. In Authorship particular, future studies should be designed to include prospective Contribution: E.L. and C.L. performed experiments; E.L., C.L., D.M., phenotypic and molecular evaluation of T-cell subsets (including E.B., and L.R. collected and analyzed the data; H.V. performed bio- TSCM) at different time points (including disease onset) in all informatics analyses; E.L., C.L., and H.V. prepared the figures; D.M. “ patients, considering for analyses patients classified as no GVHD, and G.S. had overall medical oversight, provided patient samples and ” active GVHD, or before the onset of GVHD at a given time point. clinical data, performed clinical data analysis, and revised the man- Other transplant-related factors (including the heterogeneity of uscript; R.P.d.L coordinated the CRYOSTEM Consortium and pro- GVHD prophylaxes) may have influenced our results, in particular in vided access to samples from cohort 1; E.L., E.B., G.S., and L.R. patients without aGVHD. This exploratory study was not designed wrote the manuscript; L.R. and G.S. conceived the project, secured or powered to evaluate these factors in multivariate analyses (which funding, and supervised the work; and all authors approved the final better reflect the multifactorial nature of allo-HCT). version of the manuscript. However, this is the first study to integrate spectral flow cytometry Conflict-of-interest disclosure: The authors declare no compet- and gene-expression profiling in the investigation of aGVHD at ing financial interests. disease onset. Our data suggest that the integrated analysis of the distribution of different immune cell subsets with flow cytometry, A complete list of the members of the CRYOSTEM Consortium together with gene-expression profiling, can contribute to the appears in the supplemental Data. elucidation of the processes involved in aGVHD development in ORCID profiles: D.M., 0000-0003-4553-3065; C.L., 0000- humans. Assessment of other potentially interesting cell subsets 0003-3525-0854; H.V., 0000-0003-3980-4463; E.B., 0000-0001- (eg, B-cell subsets, innate lymphoid cells), as well as single-cell 6612-8881; G.S., 0000-0002-2114-7533; L.R., 0000-0003-1262- gene expression and epigenetics analyses, will be of particular 9204. importance for future investigations to elucidate disease processes in humans and guide novel strategies for the prevention and Correspondence: Lars Rogge, Immunoregulation Unit, De- treatment of GVHD. partment of Immunology, Institut Pasteur, 25 Rue du Docteur Roux, 75015 Paris, France; e-mail: [email protected]; and Gerard´ Acknowledgments Socie,´ Service d’Hematologie´ Greffe, Hopitalˆ Saint Louis, 1 Av The authors thank all the members of the CRYOSTEM Consortium Claude Vellefaux, 75010 Paris, France; e-mail: gerard.socie@ and the Francophone Society of Marrow Transplantations and aphp.fr.

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