Codominant Role of Interferon-γ– and Interleukin-17–Producing T Cells During Rejection in Full Facial Transplant Recipients

Abstract

Facial transplantation is a life-changing procedure for patients with severe composite facial defects. However, skin is the most immunogenic of all transplants, and better understanding of the immunological processes after facial transplantation is of paramount importance. Here, we describe six patients who underwent full facial transplantation at our institution, with a mean followup of 2.7 years. Seum, peripheral blood mononuclear cells, and skin biopsy specimens were collected prospectively, and a detailed characterization of their immune response (51 time points) was performed, defining 47 immune cell subsets, 24 serum cytokines, anti-HLA antibodies, and donor alloreactivity on each sample, producing 4269 data points. In a nonrejecting state, patients had a predominant T helper 2 cell phenotype in the blood. All patients developed at least one episode of acute cellular rejection, which was characterized by increases in interferon-c/interleukin-17–producing cells in peripheral blood and in the allograft’s skin. Serum monocyte chemotactic protein-1 level was significantly increased during rejection compared with prerejection time points. None of the patients developed de novo donor-specific antibodies, despite a fourfold expansion in T follicular helper cells at 1 year posttransplantation. In sum, facial transplantation is frequently complicated by a codominant interferon-γ/interleukin-17–mediated acute cellular rejection process. Despite that, medium-term outcomes are promising with no evidence of de novo donor-specific antibody development.

Introduction

Facial deformities significantly affect the quality of life, function, and social interactions of patients, predisposing them to permanent disability, depression, and social isolation. Conventional reconstructive surgeries are frequently unable to appropriately correct complex deformities. Face transplantation has emerged as a viable and successful strategy to restore the appearance and function of patients with severe facial injuries (1–4).

Face transplantation involves multiple tissues with different degrees of immunogenicity, which for many years was considered an unsurpassable immunological barrier. Among the components of facial allografts, the skin is the most immunogenic and the main target of rejection based on its rich content of antigen-presenting cells (5–8). Unlike other solid organ transplants that are lifesaving, facial transplantation aims to improve the quality of life rather than to save the patient’s life. Therefore, the consequences of applying life-long immunosuppression regimens available for solid organ transplantation in this unique patient population must be carefully balanced to minimize risks of malignancies, infections, and metabolic disorders. Understanding the alloimmune response of face transplant recipients is of paramount importance to optimize their immunosuppressive regimen, increase the understanding of the immune system, and further determine differences with respect to solid organ transplants.

Since the first face transplantation performed in 2005, >30 face transplantations have been performed worldwide, with seven of those performed at our institution (1,2,9). Here, we report the outcomes and the immunological characterization of six patients in this unique cohort of face transplantation, in which we collected serum, skin, and peripheral blood mononuclear cells (PBMCs) prospectively since 2009. We believe that this is the largest cohort with prospectively collected samples in the world and a rich resource to better understand the immunological response on full face transplantation compared with solid organ transplantation.

Methods

Face transplant subjects

All patients provided written informed consent to participate in the clinical trial (ClinicalTrials.gov NCT01281267) for face transplantation, as approved by the Human Research Committee at Brigham and Women’s Hospital (2008BP00055). All patients were evaluated by our multidisciplinary team before participation. Donors and recipients were matched according to sex, skin color, and ABO compatibility, in addition to a negative T and B cell cytotoxic crossmatch. The only exception was a highly sensitized patient with a high panel-reactive antibody (PRA; 98%), in whom transplantation occurred across a weakly positive cytotoxic T cell crossmatch (20%). Further demographic details are given in Table 1. Patients were followed on a weekly basis during the first 4–6 weeks after transplantation and, if stable, clinical visits were further spaced to every 2 weeks, every month, and then every 3 months.

Table 1.

Baseline characteristics of vascularized composite allotransplantation transplant recipients and donors

	Patient 1	Patient 2	Patient 3	Patient 4	Patient 5	Patient 6
Recipients’ characteristics
Age at transplantation (years)	57	25	30	44	38	33
Gender	F	M	M	F	M	M
Ethnicity	White	White	White	White	White	White
Cause of injury	Animal Attack	Electrical Burn	Electrical Burn	Chemical Bum	Gunshot	Gunshot
Surgery	Face, Bilateral Hands	Face	Face	Face	Face	Face
PRA (%)	0	68	0	97	22	32
Donor-specific antibodies	Negative	Negative	Negative	Positive	Negative	Positive
HLA mismatch (A, B, C, DR, DQ, DP)	8	8	5	11	8	7
CMV status	Positive	Positive	Negative	Positive	Negative	Positive
EBV status	Positive	Positive	Positive	Positive	Positive	Positive
Induction type and dose	Antithymocyte globulin 1.5 mg/kg/day ×4; high-dose steroids	Antithymocyte globulin 1.5 mg/kg/day ×4; high-dose steroids	Antithymocyte globulin 1.5 mg/kg/day ×4; high-dose steroids	Antithymocyte globulin 1.5 mg/kg/day ×4; high-dose steroids	Antithymocyte globulin 1.5 mg/kg/day ×2/0.75 mg/kg/day ×2; high-dose steroids	Antithymocyte globulin 1.5 mg/kg/day ×3; high-dose steroids
Follow-up (years)	4	4.2	4.1	2.3	1.1	0.6
Donors’ characteristics
Age, years	42	48	31	56	51	23
Gender	F	M	M	F	M	M
CMV status	Positive	Positive	Positive	Negative	Positive	Negative
EBV status	Positive	Positive	Positive	Positive	Positive	Positive
Ischemia time	2 h	4 h	2 h	3 h	3 h	1 h 30 min

CMV, cytomegalovirus; EBV, Epstein-Barr virus; VCA, vascularized composite allotransplantation.

Immunosuppression

All patients received mycophenolate mofetil (1000 mg), methylprednisolone (500 mg), and rabbit antithymocyte globulin (1.5 mg/kg/day × 4 days) for induction therapy starting at the time of transplantation. Maintenance immunosuppression consisted of mycophenolate mofetil (1000 mg twice daily), tacrolimus (adjusted to achieve target levels of 10–12 ng/mL), and prednisone taper (down to 20 mg on day 5) (Table 1). Prednisone withdrawal was attempted in all patients posttransplantation (9). Perioperative antibacterial prophylaxis consisted of vancomycin and cefazolin and was modified according to perioperative findings. All patients received trimethoprim–sulfamethoxazole and valganciclovir prophylaxis against Pneumocystis jirovecii and cytomegalovirus, respectively, for ≥6 months. In the presence of clinical acute cellular rejection, patients were treated with pulse solumedrol 500 mg/day for 3 days and maintenance immunosuppression was increased. In case of no response, rabbit antithymocyte globulin 3–6 mg/kg was administered. Topical steroids or tacrolimus was also used in a few patients as adjuvant therapy. For antibody-mediated rejection, solumedrol and plasmapheresis with intravenous immunoglobulin (IVIG) were initially attempted. For refractory cases, eculizumab, bortezomib, and further T cell–depletion therapy (rabbit antithymocyte globulin, alemtuxumab) were considered.

Blood and skin sample processing, anti-HLA antibody testing, cytokine measurement, flow cytometry, and cell culture experiments are detailed in Supplementary Methods.

Statistical analysis

Statistical analyses were performed using Prism software (version 6.01, GraphPad Software Inc., La Jolla, CA). All data are represented as mean ± SEM. Percentages and absolute numbers of cells at the different time points were analyzed as nonparametric using the Mann–Whitney test. Significance was defined as a value of p<0.05.

Results

Acute cellular rejection is highly prevalent on full facial transplantation

Between April 2009 and February 2014, six patients received face transplants in our institution and were included in this analysis. Mean follow-up was 2.7 years. Clinical characteristics of these patients are detailed in Table 1, and preoperative and postoperative appearances are shown in Figure S1. Induction therapy consisted of rabbit antithymocyte globulin and high-dose steroids followed by maintenance immunosuppression with tacrolimus, mycophenolate mofetil, and prednisone taper (further details are given in Methods). All patients developed at least one episode of acute cellular rejection (total of 15 episodes) with a bimodal pattern (Figures 1A and B); two-thirds occurred during the first 3 postoperative months, while the remaining occurred later (>1 year after transplantation). Acute cellular rejection was assessed by using the Banff grading of skin-containing composite tissue (10), and the majority of clinical rejection episodes were classified as between grades II and III (Figures 1A and C). One highly sensitized patient (patient 4) with preformed donor-specific antibodies (DSAs) developed an early acute antibody-mediated rejection with neutrophil vascular margination and positive C4d staining (Figures 1D and E). Early surgical site infections occurred in three patients, while two patients developed pneumonia and one developed intravenous line–associated bacteremia posttransplantation. Opportunistic infections included cytomegalovirus (CMV) infection (in two patients with negative CMV serostatus before transplantation, PODs 176 and 420), herpes simplex virus infection of face allograft (POD 420), and shingles (POD 502). There were no graft failures or patient deaths.

Figure 1. Clinical and histopathological findings in facial allograft rejection.

(A) Photographs and corresponding hematoxylin and eosin graft stainings of representative patient (patient 5) during clinical cellular rejection episodes with graft erythema and edema (grades II and III) compared with mild rejection on surveillance biopsy (grade I) without significant erythema or edema. Grade I rejection shows normal epithelium, mild dermal edema, and a sparse perivascular lymphocytic infiltrate (arrow and higher magnification). Grade II rejection shows normal epithelium, development of superficial dermal edema, and associated lymphocytic vasculopathy (arrow and higher magnification) characterized by a brisk angiocentric lymphocytic infiltrate, and endothelial prominence and sloughing. Grade III rejection retains lymphocytic vasculopathy (lower arrow) but also shows epithelial apoptosis associated with lymphoid exocytosis (higher arrow and magnification). (B) Timing of rejection in days and (C) grade of rejection according to time after transplantation. Highly sensitized patient 4 who developed early acute humoral rejection characterized by neutrophil margination on hematoxylin and eosin (arrow) (D) and positive C4d staining on endothelium by immunofluorescence, indicating local complement activation (E). Patient had provided written consent for publication of his photographs.

Effector memory T cells represent the predominant subset after transplantation with a dominant Th2 phenotype

Allospecific T cells are activated primarily in secondary lymphoid organs and then migrate to target tissue to elicit injury (11). In our cohort, we characterized circulating T cell subsets over time posttransplantation. All face transplant recipients received rabbit antithymocyte globulin as induction therapy. As expected, both CD4 and CD8 T cells were significantly depleted at 24 h posttransplantation with progressive recovery at 3 months posttransplantation (data not shown). Analyses of the effector and memory T cell subsets (Figure S2) revealed that CD4 effector memory T cells (TEMs: CD45RA⁻CCR7⁻) were the predominant T phenotype within the pool of CD4⁺ T cells posttransplantation (Figure 2A), while the pool of CD8⁺ T cells was dominated by both TEMs and effector memory RA T cell (TEMRAs) posttransplantation (Figure 2B). Next, we assessed the T helper (Th) phenotypes based on surface marker profiles (Figure S2 and Table S1 for phenotype details), according to the Human Immunology Project (12). Circulating Th2 cells were the predominant phenotype in most patients posttransplantation (Figures 2C and D), followed by Th17 and Th1 cells. The only exception was the highly sensitized patient 4 who had a predominant Th17 phenotype (Figures 2E and F). This Th17 skewing was confirmed with intracellular cytokine staining (Figure 2G). In solid organ transplantation, an increase in Foxp3⁺ regulatory T cells (Tregs) has been associated with better long-term graft survival (13–15). In our face transplant cohort, the percentage of circulating Tregs (CD4⁺Foxp3⁺ cells) had no statistically significant expansion over time (4.215 ± 1.134% at pretransplantation vs. 10.23 ± 5.549% at 12 months, p = 0.2737). Last, we evaluated donor T cell alloreactivity based on the frequency of interferon (IFN)γ-producing donor-reactive PBMCs by using a standardized and cross-validated ELISPOT assay (16) (Figures S3A–C). This assay has been proposed as an important tool to quantify cellular donor reactivity in kidney transplantation and to determine subsequent risk of rejection (17–21). Pretransplantation, none of the patients had positivity to either direct or indirect T cell alloreactivity against their respective donors (Figure S3B). Among the 51 time points analyzed posttransplantation, only one time point exhibited positivity at 6 months posttransplantation and there was no correlation with rejection occurrence. In sum, Th2 cells were the dominant phenotype in nonrejection time points posttransplantation with exception of the highly sensitized recipient with a Th17-dominant phenotype. Quantifying the frequency of IFNγ-producing donor-reactive PBMCs by ELISPOT did not predict rejection in face recipients.

Figure 2. Analysis of CD4⁺ and CD8⁺ T cell phenotypes from face recipients over time.

Pie charts of the mean CD4⁺ (A) and CD8⁺ (B) naïve (CCR7⁺CD45RA⁺), central memory (TCMs: CCR7⁺CD45RA⁻), effector memory (TEMs: CCR7⁻CD45RA⁻), and effector memory RA (TEMRAs: CCR7⁻CD45RA⁺) cells at pretransplantation and 6 and 12 months posttransplantation. All six patients were included on this analysis. (C) Representative contour plots of T helper (Th)1 (CD4⁺CXCR3⁺CCR6⁻), Th2 (CD4⁺CXCR3⁻CCR6⁻), and Th17 (CD4⁺CXCR3⁻CCR6⁺) cells from patient 3. (D) Percentages of Th1, Th2, and Th17 cells from patients 1, 2, 3, 5, and 6, over time. (E) Representative contour plots of Th1, Th2, and Th17 cells from patient 4. (F) Percentages of Th1, Th2, and Th17 cells from patient 4, over time. (G) Interleukin (IL)-17A, interferon- γ, and IL-4 production by CD4⁺ T cells from patient 4 at 6 months posttransplantation after stimulation in vitro with phorbol myristate acetate plus ionomycin. Graphs displayed as mean ± SEM at each time point examined.

Despite Tfh cell expansion, development of de novo DSAs is uncommon

The development of DSAs and consequent endothelial injury is considered one of the major causes of late allograft loss in solid organ transplantation (22). Based on the high immunogenicity of the skin (7,8), one would expect a high rate of de novo anti-HLA antibody generation posttransplantation. First, we analyzed the kinetics of T follicular helper cells (Tfh) and B cells posttransplantation. Although antithymocyte globulin presumably depletes all T cells, we observed an unexpected initial sparing of circulating Tfh cells with a fourfold expansion at 12 months posttransplantation (Figure 3B).

Figure 3. Dynamics of B cells, Tfh cells, and anti-HLA antibodies post–face transplantation.

Percentages (A) and absolute numbers (B) of B cells (CD19⁺) and Tfh (CD4⁺CXCR5⁺PD-1⁺)cells from face recipients at following time points: pretransplantation, 24 h and 1 week, 3 months, 6 months, and 12 months posttransplantation. *p < 0.05 compared with pretransplantation (Mann–Whitney test). (C) Panel-reactive antibodies (PRAs) for class I and class II anti-HLA antibodies over time. All six patients were included on this analysis. (D) Number of circulating donor-specific antibodies and C1q-positivity of patient 4 at different time points posttransplantation. Graphs displayed as mean ± SEM at each time point examined.

To our surprise, no patient developed persistent de novo DSAs posttransplantation, and PRAs remained stable posttransplantation (Figure 3C). The highly sensitized patient 4, who had three DSAs at the time of transplantation (against HLA-A2, -A32, and -B57) and a positive CDC T cell crossmatch, had progressive reduction of her PRA and of the DSA numbers over time (Figure 3D) after active treatment for antibody-mediated rejection with plasmapheresis, bortezomib, alemtuzumab, and IVIG (23). Patient 5 developed CMV infection at 5 months posttransplantation, which led to reduction of immunosuppression. During that time, his PRA increased from 13% (3 months) to 79% (6 months posttransplantation) with concomitant detection of circulating de novo DSAs (against HLA-A2 antigen). Repeated analysis at 7 months revealed disappearance of the DSA. Patient 1 also had a transient detection of DSAs at 1 week post-transplantation and patient 6 had a pretransplantation DSA against HLA-A1 with negative CDC crossmatch, which disappeared by 6 months posttransplantation without any specific intervention. Among the DSAs detected, C1q positivity was only transiently positive on the highly sensitized patient 4 at 1 week posttransplantation (Figure 3D). Despite the abundance of keratinocytes on skin, we did not detect any circulating anti–MHC class I chain-related molecule A antibody posttransplantation in our cohort. In sum, despite the high alloimmunogenicity of the skin and the rise in Tfh cells over time, there was no evidence of de novo DSA development or increase in PRA posttransplantation.

CD4⁺, CD8⁺, and CD14⁺ cells are the predominant cells during face transplant rejection

After characterizing the kinetics of circulating immune cells over time, we analyzed these cells in relation to the rejection events both in the allograft and in the periphery compared with prerejection and postrejection time points to better characterize the rejection process in full face transplant recipients. For the rejection time points, skin biopsies with a Banff grading of II, II/III, or III (from all six patients) were selected with respective blood samples from the same time points. For the prerejection and postrejection time points, the samples used revealed either grade 0 or I. Rejection episodes were characterized by a significant accumulation of CD4⁺ and CD8⁺ cells in the allograft, while absolute numbers of total circulating CD4⁺ and CD8⁺ cells were not significantly different compared with prerejection and postrejection time points (Figures 4A–D). CD14⁺ cells also significantly increased in the allograft during rejection (Figure 4E) and were associated with a concomitant increase in the absolute numbers of CD14⁺ cells in peripheral blood (Figure 4F), although not statistically significant. Among 24 relevant cytokines/chemokines evaluated in the serum of rejecting recipients, monocyte chemotactic protein (MCP)-1 was the only cytokine that was clearly increased an average of 2.5-fold during rejection compared with prerejection time points (951 ± 338 vs. 387 ± 69, p = 0.01) (Figure 4G). Although high levels of chemokines such as CXCL-10 have been associated with rejection episodes in kidney transplantation (24–26), serum levels were no different during rejection or prerejection time points (Figure 4H). Other serum cytokines such as interleukin (IL)-6 and IL-8, also did not correlate with rejection episodes (Table S2). Last, when we analyzed circulating CD4⁺ and CD8⁺ T cell subsets during rejection episodes (naive, TCM, TEM, and TEMRA cells), we observed a nonsignificant reduction in TEMs (CD45RA⁻CCR7⁻; Figures S4A and B) and an increase in both CD4⁺ and CD8⁺ TEMRAs (CD45RA⁺CCR7⁻; Figures S4A and C) compared with pre-rejection time points. In sum, acute cellular rejection after full face transplantation is characterized by CD4⁺, CD8⁺, and CD14⁺ infiltrates and a trend toward increased circulating CD14⁺ cells. Serum MCP-1 was the only serum biomarker to be significantly associated with face cellular rejection.

Figure 4. Predominance of CD4⁺, CD8⁺, and CD14⁺ cells in skin grafts during face transplant rejection.

(A) Representative immunofluorescence of CD4 staining (green) of skin biopsy specimens from prerejection, rejection, and postrejection time points (4′, 6-diamidino-2-phenylindole [DAPI] in blue) (×400). (B) Absolute numbers of CD4⁺ cells in the allograft (upper graph) and in the blood (lower graph) at prerejection, rejection, and postrejection time points. Data from all six patients included. (C) Representative immunofluorescence of CD8 staining (pink) on skin grafts as in (A) (×400). (D) Absolute numbers of CD8⁺ cells in the allograft (upper graph) and in the blood (lower graph) at prerejection, rejection, and postrejection time points. (E) Representative immunofluorescence of CD14 staining (red) on skin grafts as in (A) (×400). (F) Absolute numbers of CD14⁺ cells in the allograft (upper graph) and in the blood (lower graph) at prerejection, rejection, and postrejection time points. (G) Serum MCP-1 and CXCL10 (H) mean concentrations with SD, measured by Luminex prerejection and during rejection episodes. *p < 0.05 (Mann–Whitney test); **p < 0.01; ***p < 0.001; ****p < 0.0001. All six patients were included on analyses above.

IFNγ- and IL-17–producing T cells codominate in acute cellular rejection both in the periphery and in the face allograft

Diverse Th cell subtypes may emerge after transplantation depending on the microenvironment and additional signals provided by antigen-presenting cells on T cell activation (27). Among alloantigen-specific CD4⁺ T cells, Th1 cells are the predominant Th subset during acute cellular rejection in kidney transplantation (28,29). Little is known about the Th phenotype during rejection in human face transplantation. We observed that IL-17–producing T cells infiltrated the face allograft during rejection (Figures 5A and C) with a concomitant increase in IFNγ-producing T cells compared with prerejection time points (Figures 5B and D). In the peripheral blood, we found an increase in IL-17 production by CD4⁺ T cells (Figures 5E and F) and IFNγ production by CD8⁺ T cells (Figures 5G and H) during rejection compared with prerejection. We also observed a non-significant reduction of IL-4 production of CD4⁺ T cells (Th2) cells during rejection (Figure S5). Tregs significantly accumulated in the graft during rejection (Figures 6A and B), while absolute numbers of circulating Tregs were reduced at rejection time points compared with prerejection (Figure 6C). Among regulatory markers, we also observed a trend toward lower expression of programmed cell death-1 and cytotoxic T-lymphocyte antigen 4 on CD4 cells at the time of rejection compared with prerejection (Figures 6D and E). Together, the rejection process of face allografts was characterized by a codominant IFNγ- and IL-17–driven immune response with simultaneous infiltration of Tregs into the allograft and a decrease of Th2 and Tregs in the blood.

Figure 5. Increased infiltration of interleukin (IL)-17– and interferon (IFN)γ-producing T cells in skin grafts during face transplant rejection.

(A) Representative triple-color immunofluorescence images taken from skin biopsy specimens from prerejection, rejection, and postrejection time points are stained with antibodies to CD3 (red) and IL-17 (green) and a nuclear stain 4′,6-diamidino-2-phenylindole (DAPI) (blue) (×200). (B) Representative triple-color immunofluorescence images taken from skin biopsy specimens from prerejection, rejection, and postrejection time points are stained with antibodies to CD3 (red) and IFNγ (green) and a nuclear stain DAPI (blue) (9200). (C) CD3⁺ and IL-17⁺ cells were counted using 8–10 high-powered fields (×200) from skin biopsies of six patients, and the absolute numbers of CD3⁺ and CD3⁺IL-17⁺ cells are shown with the mean (horizontal bar). **p < 0.02, ***p < 0.01 using Mann–Whitney test. (D) CD3⁺ and IFNγ⁺ cells were counted and displayed as described in (C). **p < 0.02 compared with the prerejection time point. (E) Representative contour plot of IL-17A production in blood CD4⁺ T cells at prerejection and rejection time points. (F) IL-17A mean fluorescence intensity in CD4⁺ T cells at prerejection, rejection, and postrejection time points. (G) Flow contour plots of IFNγ-producing CD8⁺ T cells as in (E). Data from all six patients are included. (H) IFNγ mean fluorescence intensity in CD8⁺ T cells at prerejection, rejection, and postrejection time points. Graphs displayed as mean ± SEM at each time point examined. *p < 0.05 compared with prerejection (Mann–Whitney test). Data from all six patients are included.

Figure 6. Characterization of circulating and graft infiltrating regulatory T cells posttransplantation.

(A) Representative immunofluorescence of CD4 (green) and Foxp3 (red) stainings of skin biopsy specimens from prerejection, rejection, and postrejection time points (4′,6-diamidino-2-phenylindole [DAPI] in blue) (×400). (B) CD4⁺Foxp3⁺ cells were counted using 8–10 high-powered fields (×200) from skin biopsies of 8–11 patients, and the absolute numbers of CD4⁺Foxp3⁺ cells are shown with the mean (horizontal bar). **p < 0.01 using Mann–Whitney test. (C) Absolute number of CD4⁺Foxp3⁺ cells from patients’ peripheral blood mononuclear cell (PBMCs) at prerejection, rejection and postrejection. *p < 0.05 compared with prerejection (Mann–Whitney test). (D) Representative contour plots, perce (lower left) and absolute numbers (lower right) of CD4⁺programmed cell death-1 (PD-1⁺) cells from patients’ PBMCs at prerejection, rejection, and postrejection. (E) Representative contour plots, percentages (lower left), and absolute numbers (lower right) of CD4⁺cytotoxic T-lymphocyte antigen 4 (CTLA-4⁺) cells from patients’ PBMCs at prerejection, rejection, and postrejection. Graphs displayed as mean ± SEM at each time point examined. Data from all six patients are included.

Discussion

Here, we characterize the immune response in a cohort of full facial transplant recipients. Face allografts are unique in their composition because they contain skin, muscle, bone, vessels, and lymph nodes. Each compartment has differing immunogenicity, although the predominant target and the most immunogenic component is the skin (5–8).

Our study demonstrates that face recipients with a stable graft (no significant rejection on protocol biopsy) are characterized by edominance of Th2 cells in the periphery, while cellular rejection is associated with a shift toward Th1 and Th17 cells. This Th2/Th1 balance is consistent with observations in preclinical transplant models (30–33) as well as in solid organ transplantation in humans such as in rejecting kidney allografts (28) and cardiac allografts (34) with the exception of Th17 cells that were most predominant in the face allografts during rejection. The predominance of IL-4–secreting Th cells has been previously shown to be associated with graft stability in kidney recipients (35). While Th1 cells are well accepted as dominant players during solid organ allograft rejection, the role of Th17 cells is less well defined (36). Few studies reported the presence of IL-17 in rejecting kidneys by immunofluorescence staining and revere transcription–polymerase chain reaction (37,38) as well as in the bronchoalveolar lavage fluid of rejecting lung transplant recipients (39). However, neutralization of IL-17 in murine transplant models only modestly delayed acute rejection (40,41). Interestingly, in a humanized mouse skin model in which human skin was transplanted into severe combined immunodeficiency disease mice followed by infusion of human peripheral blood mononuclear cells, skin rejection was clearly associated with infiltration of IL-17–producing T cells (42). Similarly, certain inflammatory skin conditions such as psoriasis shared a similar pattern of Th1/Th17 dominance, indicating that possibly signals derived from dermal dendritic cells may be important in favoring this phenotype (43,44). In regard to the antibody-mediated rejection that occurred with patient 4, it is premature to draw strong conclusions based on a single patient. However, the pattern of Th17 phenotype dominance over time was completely different than that of the other five patients. This state is consistent with data demonstrating that Th17 can provide help to B cells, inducing its proliferation and triggering antibody production with class switch recombination (45,46). Further studies will be needed to confirm this initial observation. The importance in identifying Th phenotypes that lead to rejection is related to variable resistance of subsets such as Th17 cells to certain immunosuppressive drugs. As an example, Th17 cells were shown to be resistant to B7:CD28 blockade with belatacept in vitro and acute rejection episodes in kidney transplant recipients treated with belatacept were associated with expansion of Th17 cells (47). Therefore, determination of functional pathological T cell subsets during face rejection will allow better personalization and wiser choice of potential agents to modulate the alloimmune response.

Our findings also demonstrate that acute cellular rejection in face allografts is characterized by graft infiltration of monocytes/macrophages and CD4⁺ and CD8⁺ T cells that starts in the dermal perivascular space with progressive involvement of skin adnexal structures and epidermis in the absence of treatment. This pattern of cellular rejection is similar to that observed in other solid transplant organs such as kidneys with differences pertaining to the specific targeted antigenic cells on specific organs such as tubular cells in the kidney and epithelial cells in the face (48). Analogous to our findings, an analysis of hand biopsy specimens during rejection revealed predominance of CD3⁺ lymphocytes and CD68⁺ cells (histiocytic/macrophage lineage) (49). MCP-1 was the predominant cytokine that peaked during rejection of face recipients, confirming the important role of macrophages in cellular rejection. This is in agreement with prior studies that also detected high MCP-1 levels in the serum and urine of patients at the time of kidney allograft rejection (50,51). The lack of rejection signal among other relevant chemokines such as CXCL10 may suggest that either rejections are being caught earlier (compared with kidneys, in which creatinine elevation is a late biomarker), and therefore not allowing the full blown presentation and/or that a more local immune response is occurring that not necessarily reflects the status on peripheral blood. Our findings with donor alloreactivity using ELISPOT indicates similar discrepancy between local and systemic responses, in particular because this assay has been clearly validated in multiple cohorts of solid organ transplants to accurately prognosticate rejection episodes (17,52–54).

A major difference between face transplant and other solid organ transplants was the frequency of acute cellular rejections, which was present in 100% of face recipients in this cohort while it occurs in only 10–15% of kidney or heart recipients using a similar immunosuppressive regimen during the first year posttransplantation (55). This high rate of rejection has been documented by other groups performing vascularized composite allotransplantation transplants, including hand and face (2,56,57). The higher rate of rejection after face transplantation compared with kidney transplantation could be primarily related to the higher immunogenicity of the skin based on the high content of antigen-presenting cells (7). Further, the skin and mucosa are colonized by microorganisms, and there is accumulating literature suggesting an important crosstalk of the commensal microbiota with epithelial immunity, with evidence of microbiota tuning the function of resident T lymphocytes (58–60). Whether microbial dysbiosis lowers the threshold for rejection in face transplant recipients remains to be determined. Additional factors that may have contributed to the high rate of rejection include our immunosuppression protocol with early steroid withdrawal and the younger age of the recipients (mean 37 years) and therefore a stronger immunity (61). Despite that, all cellular rejections were successfully treated and did not lead to graft loss. One of the advantages of skin grafts compared with other transplants is the capability of earlier detection of rejection based on its prompt visual findings, which may permit timely intervention and prevention of chronic changes. Indeed, we have not observed any chronic rejection in our cohort so far. In the literature, only one case of a face transplant recipient developing chronic rejection has been reported, and this occurred in the setting of significant reduction of immunosuppression due to concomitant malignancy (62).

Development of de novo DSAs occurs in about 5% of unsensitized transplant recipients and is significantly associated with long-term graft loss (63,64). However, different transplanted organs may have diverse sensitivities to antibody-mediated injury (65–68). Based on the high immunogenicity of the skin, one would expect a high rate of DSA development after full facial transplantation. However, we did not observe any de novo DSAs in our cohort despite the expansion of T follicular cells over time. There are three potential explanations: (1) similar to liver (69), de novo DSAs formed could be completely absorbed in the skin and is therefore undetectable in the serum. This is unlikely because there is little evidence of active antibody deposition in the surveillance biopsies using C4d staining (2). De novo DSAs may develop later after transplantation and a longer follow-up in a larger cohort would be required to detect it (limitation in our study) (3). The unique composition of full face graft may promote immune regulation and prevent DSA formation in combination with immunosuppressive drugs. Further studies are needed to investigate these hypotheses.

Our study has a few limitations, including the small number of patients and the single-center nature. This reflects in part the novelty of this procedure and limited number of face transplantations performed worldwide since 2005. Validation of our rejection phenotype in other face transplant cohorts will be important as well as assessment of current findings in a cohort receiving a different regimen of immunosuppression. Despite that, we believe our unique biobank with 51 time points involving both surveillance and rejection episodes has permitted a thorough evaluation of the effector immune function of face recipients. Last, the skin contains a large resident pool of lymphocytes (70,71), and the presence of donor T cells during rejection has been previously documented during face rejection (72). Additional studies will be required to elucidate the role of donor T cells in the rejection process and differentiation of pathological infiltrates from nonpathological ones.

Overall, face transplantation is now a clinically feasible strategy for patients with facial deformities, and the use of an immunosuppressive regimen similar to those used in solid organ transplants has yielded good short- and medium-term graft outcomes. Nonetheless, the high frequency of cellular rejection is concerning, and the development of novel biomarkers and organ-specific immunosuppression strategies based on the known difference between transplanted organs will be critical to further advance the field.

Supplementary Material

Supplemental Mats

Data S1: Supplementary Methods.

Figure S1: Photographs of the six patients before transplantation and several months after surgery.

Figure S2: Gating strategy of the cell populations from peripheral blood analyzed in this study.

Figure S3:Direct and indirect donor-specific T cell alloreactivity posttransplantation.

Figure S4: CD4 and CD8 effector and effector memory RA T cells at prerejection, rejection, and postrejection time points.

Figure S5: Interleukin-4 production by CD4 T cells at rejection time points.

Table S1: Cell phenotypes analyzed in this study.

Table S2: Serum cytokine levels measured by Luminex assay according to rejection or prerejection time points (n = 8; Mann–Whitney nonparametric test).

Abbreviations

CMV

cytomegalovirus

DSA

donor-specific antibody

IFN

interferon

IL

interleukin

IVIG

intravenous immunoglobulin

MCP-1

monocyte chemotactic protein-1

PBMC

peripheral blood mononuclear cell

POD

postoperative day

PRA

panel reactive antibody

TCM

central memory T cell

TEM

effector memory T cell

TEMRA

effector memory RA T cell

Tfh

T follicular helper cell

Th

T helper cell

Treg

regulatory T cell