Immunoregulatory and lipid presentation pathways are upregulated in human face transplant rejection

Abstract

BACKGROUNDRejection is the primary barrier to broader implementation of vascularized composite allografts (VCAs), including face and limb transplants. The immunologic pathways activated in face transplant rejection have not been fully characterized.METHODSUsing skin biopsies prospectively collected over 9 years from 7 face transplant patients, we studied rejection by gene expression profiling, histology, immunostaining, and T cell receptor sequencing.RESULTSGrade 1 rejection did not differ significantly from nonrejection, suggesting that it does not represent a pathologic state. In grade 2, there was a balanced upregulation of both proinflammatory T cell activation pathways and antiinflammatory checkpoint and immunomodulatory pathways, with a net result of no tissue injury. In grade 3, IFN-γ-driven inflammation, antigen-presenting cell activation, and infiltration of the skin by proliferative T cells bearing markers of antigen-specific activation and cytotoxicity tipped the balance toward tissue injury. Rejection of VCAs and solid organ transplants had both distinct and common features. VCA rejection was uniquely associated with upregulation of immunoregulatory genes, including SOCS1; induction of lipid antigen-presenting CD1 proteins; and infiltration by T cells predicted to recognize CD1b and CD1c.CONCLUSIONOur findings suggest that the distinct features of VCA rejection reflect the unique immunobiology of skin and that enhancing cutaneous immunoregulatory networks may be a useful strategy in combatting rejection.Trial registrationClinicalTrials.gov NCT01281267.FUNDINGAssistant Secretary of Defense and Health Affairs, through Reconstructive Transplant Research (W81XWH-17-1-0278, W81XWH-16-1-0647, W81XWH-16-1-0689, W81XWH-18-1-0784, W81XWH-1-810798); American Society of Transplantation's Transplantation and Immunology Research Network Fellowship Research Grant; Plastic Surgery Foundation Fellowship from the American Society of Plastic Surgeons; Novo Nordisk Foundation (NNF15OC0014092); Lundbeck Foundation; Aage Bangs Foundation; A.P. Moller Foundation for the Advancement of Medical Science; NIH UL1 RR025758.

Keywords: Adaptive immunity; Cellular immune response; Immunology; Transplantation.

Conflict of interest statement

Conflict of interest: The authors have declared that no conflict of interest exists.

Figures

Figure 1. Human face transplant rejection has a distinct gene expression signature.

(A) Design of the study. Skin biopsies from 7 face transplant patients collected during episodes of acute cellular rejection (red) and nonrejection (green) were analyzed using histologic examination, multiplex gene expression profiling, and immunostaining. (B) Clinical photographs of a recipient of a full face transplant during nonrejection (grade 0) and severe acute cellular rejection (grade 3), demonstrating edema and erythema of the transplanted face. (C) Representative examples of H&E staining of a face transplant skin biopsy graded as nonrejection (grade 0, minimal inflammatory infiltrates), and a second biopsy graded as severe acute cellular rejection (grade 3, dermal inflammatory infiltrates with apoptotic keratinocytes). (D) Unsupervised principal component analysis clustered grade 3 rejection biopsies (n = 11) separately from grade 0 samples (n = 10). (E) Heatmap of the top 50 genes differentially expressed in grade 3 compared with grade 0 biopsies (log2 fold change >1; adjusted P value <0.05). Differentially expressed genes (DEGs) were obtained using normalized gene expression counts as input and the Wald significance test. Each column represents a facial allograft biopsy. Gene values are row scaled. The full list of differentially expressed genes and associated statistics are shown in Supplemental Table 3.

Figure 2. Effector T cell molecules, T cell cosignaling, and IFN-γ signaling molecules are upregulated in acute cellular rejection of face transplants.

(A–J) Volcano plots showing genes differentially expressed in grade 3 rejection biopsies (n = 11) versus grade 0 nonrejection biopsies (n = 10). DEGs were obtained using normalized gene expression counts as input and the Wald significance test. Each dot represents an individual gene. Horizontal dashed lines represent an adjusted P value cutoff of –log10 (0.05); vertical dashed lines represent log2 fold change of –1 and +1. Synonymous gene symbols, according to NCBI Gene, are provided in parentheses. All volcano plots illustrate identical data, but each highlights selected genes associated with leukocyte trafficking (A); T cell infiltration (B); T cell costimulation (C); T cell coinhibition (D); IFN-γ signaling (E); Th1 chemokine receptors and their ligands (F); effector molecules (G); immunoregulation (H); antigen processing and presentation (I); or innate immunity (J). (K) The top 25 canonical pathways overrepresented in 202 DEGs in grade 3 rejection biopsies in relation to grade 0 are shown. The significance of the association between gene expression and canonical pathways was estimated by the P value (depicted in bar graphs; primary y axis), and the ratio value reflects its strength (depicted as line graphs; secondary y axis). P values were determined using Fisher’s exact test with multiple testing adjustments according to the Benjamini-Hochberg false discovery rate method.

Figure 3. Comparison of acute rejection stages demonstrates that distinct gene expression patterns develop in grade 2 and grade 3 rejections.

(A) Unsupervised principal component analysis clustered all grade 3 samples (n = 11) separately from grade 0 biopsies (n = 10), but grade 1 (n = 6) and grade 2 biopsies (n = 8) were molecularly heterogeneous. (B) Volcano plots showing DEGs in grade 1, 2, and 3 rejections in relation to grade 0 samples. DEGs were obtained using normalized gene expression counts as input and the Wald significance test. (C–I) Box plots of normalized expression values of genes associated with leukocyte trafficking (C); T cell infiltration (D); T cell costimulation (E); IFN-γ signaling (F); antigen presentation (G); Th1 chemokine receptors and their ligands (H); and effector molecules (I). Horizontal lines represent median values, with whiskers extending to the farthest data points. Adjusted *P ≤ 0.05, **P ≤ 0.01, ***P ≤ 0.001, ****P ≤ 0.0001. The full lists of DEGs and associated statistics are shown in Supplemental Tables 3 and 7.

Figure 4. Immune checkpoint molecules and immunoregulatory genes are upregulated in face transplant rejection.

Box plots of normalized expression values of genes associated with immune checkpoints (A) and genes associated with regulation of the immune response (B). Normalized gene expression values are shown for biopsies collected during grade 0 (n = 10), grade 1 (n = 6), grade 2 (n = 8), and grade 3 rejection (n = 11). Horizontal lines represent median values, with whiskers extending to the farthest data points. Adjusted *P ≤ 0.05, **P ≤ 0.01, ***P ≤ 0.001, ****P ≤ 0.0001. The full lists of DEGs and associated statistics are shown in Supplemental Tables 3 and 7.

Figure 5. Severe rejection is characterized by upregulation of cytotoxicity, antigen presentation, and immunoregulation genes and infiltration of skin by proliferating T cells expressing markers of antigen-specific activation and cytotoxic effector molecules.

(A) Venn diagram showing shared and unique DEGs in grade 2 (n = 8) and grade 3 (n =11) biopsies (when compared with grade 0 samples). DEGs were obtained using normalized gene expression counts as input and the Wald significance test. One hundred seven genes were exclusively differentially expressed in grade 3 rejection. (B) Heatmap of 107 genes that are uniquely differentially expressed in grade 3 rejection, which included genes associated with cytotoxicity, antigen processing and presentation, and immunoregulation. Each column represents a biopsy. Gene expressions values are row scaled. (C–H) Multiplex immunostaining of grade 0, 1, and 3 rejection demonstrates the infiltration of proliferative, activated, and cytotoxic T cells in grade 3 skin biopsies but no significant differences between grades 0 and 1. Bars represent individual donors, and error bars represent the mean and SEM of at least 3 separate measurements per donor. (C) The numbers of total (CD3+) and proliferative (CD3+Ki-67+) T cells per ×200 high-power field (HPF) are shown. (D–H) The relative percentages (left) and absolute numbers per HPF (right) of T cells expressing markers of antigen-specific activation (CD40L+CD107a+) (D), CD8 (E), granzyme B (F), perforin (G), and the Treg marker FOXP3 (H) are shown. Significance was determined by nested 1-way ANOVA and Tukey’s post hoc test for comparison between grades.

Figure 6. T cells are the major source of cytotoxic injury in grade 3 rejection.

(A) T cells are a major but not exclusive source of granzyme B. Multiplex immunostaining demonstrated increased expression of granzyme B in grade 3 rejection, but not all granzyme-producing cells were CD3+ T cells (original magnification, ×100). (B–G) Quantitative multiplex immunostaining was carried out to evaluate the relative contributions of T cells versus NK cells to cytotoxic injury in grade 3 rejection. Bars represent individual donors, and error bars represent the mean and SEM of at least 3 separate measurements per donor. (B) There were significantly more T cells than NK cells in skin biopsies of grade 3 rejection. The numbers of CD3+ T cells and CD56+ NK cells per ×200 HPF are shown. (C) The majority of granzyme B was produced by T cells. The numbers of granzyme-positive CD56+ NK cells and CD3+ T cells per ×200 HPF are shown. (D) There were significantly more activated T cells than activated NK cells. The numbers of CD3+CD40L+ (activated T) cells and CD56+CD107a+ (activated NK) cells per ×200 HPF are shown. (E) NK cells had higher frequencies of activation. The percentages of total CD3+ T cells expressing CD40L (left) and CD56+ NK cells expressing CD107a (right) are shown. (F and G) T cells mediated significantly more cytotoxic events than NK cells. Cells undergoing cytotoxic cell death were identified by immunostaining for caspase-8, and the number (F) and relative frequency (G) of events in which T cells (left) or NK cells (right) were juxtaposed with dying cells were enumerated. Significance was determined by nested t tests.

Figure 7. Comparison between human face and solid organ transplant rejection.

(A) Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) flow diagram of selection of solid organ transplant studies. (B) Volcano plots showing DEGs between grade 3 rejection biopsies (n = 11) and grade 0 nonrejection biopsies (n = 10). DEGs were obtained using normalized gene expression counts as input and the Wald significance test. Genes shared with solid organ transplant rejection are shown in blue, and genes unique to face transplant rejection are shown in orange. A subset of genes is shown; the complete list of shared genes together with associated statistics is shown in Supplemental Table 12, and the complete list of unique genes together with associated statistics is shown in Supplemental Table 13. Each dot represents an individual gene. Horizontal dashed lines represent an adjusted P value cutoff of –log10 (0.05); vertical dashed lines represent log2 fold change of –1 and +1. (C) Genes unique to face transplant rejection. A subset of genes is shown; the complete list of unique genes and their expression are shown in Supplemental Figure 5 and Supplemental Table 13.

Figure 8. T cells expressing CD1b- and CD1c-associated TCRs are enriched in the skin but not blood during rejection episodes.

The antigen receptor (CDR3) sequences of T cells infiltrating face transplant rejection specimens were analyzed by high-throughput TCR sequencing. These CDR3 sequences were then clustered with known CD1b- and CD1c-specific sequences using the grouping of lymphocyte interactions by paratope hotspots (GLIPH) algorithm. Two hundred eighty-five CDR3 sequences from face transplant skin specimens that clustered with known CD1b-reactive TCRs and 88 sequences that clustered with known CD1c-specific TCRs were identified (Supplemental Table 14). (A and B) The absolute number (left) and relative frequency of total T cells (right) of CD1b-associated TCRs (A) and CD1c-associated TCRs (B) in blood and skin are shown. Seventeen skin biopsies and 12 skin samples from 3 donors were studied. (C and D) Local enrichment of multiple CD1b-associated (C) and CD1c-associated (D) TCRs occurred in some but not all episodes of rejection. Gd, grade; Pt, patient.