Tolerance induction is dose dependent

We have investigated the s.c. route for self-peptide immunotherapy in the Tg4 TCR transgenic model of EAE15, where >90% of CD4+ T cells recognize the nine-residue N-terminal peptide of MBP (MBP Ac1-9). The dose of a high-affinity major histocompatibility complex binding MBP peptide (MBP Ac1-9[4Y])24 required for effective tolerance induction by this route was determined. The proliferative capacity of CD4+ T cells was reduced in direct correlation to the MBP Ac1-9[4Y] dose administered in vivo (Fig. 1a). While proliferation of CD4+ T cells from animals treated with the lowest peptide dose (0.008 μg) remained unaltered, CD4+ T cells from mice treated at a higher (8 μg) dose displayed proliferative anergy. Abrogation of the secretion of Th1-associated cytokines, IL-2 (Fig. 1b) and interferon (IFN)-γ (Fig. 1c), was also observed among CD4+ T cells from mice treated with 8 μg MBP Ac1-9[4Y]. A direct correlation was noted between IL-10 secretion and peptide dose (Fig. 1d); IL-10 levels were negligible from control or 0.008 μg treatment groups, while CD4+ T cells from mice treated with 8 μg secreted the highest level. A dose-dependent effect on the development of a suppressive phenotype was observed in vitro (Fig. 1e). CD4+ T cells from animals treated with 0.8 and 8 μg doses suppressed responder cell proliferation by 85% and 95%, respectively. In vivo, treatment of Tg4 mice with repetitive 0.8 or 8 μg doses of MBP Ac1-9[4Y] delayed the onset and reduced the severity of myelin-induced EAE in a dose-dependent manner (Fig. 1f).

Figure 1: Peptide dose dictates regulatory CD4+ T-cell phenotype and protection from EAE. CD4+ T cells from Tg4 mice treated 10 times s.c. with different doses of MBP Ac1-9[4Y] were re-stimulated in the presence of irradiated antigen-presenting cells (APCs) and a titration of MBP Ac1-9[4K]. (a) After 3 days, proliferative responses were measured by 3[H] thymidine incorporation. (b–d) Cytokines detected in cultures described in a, measured by an enzyme-linked immunosorbent assay (ELISA). (e) In vitro-expanded CD4+ T cells from peptide-treated Tg4 mice were cultured at a ratio of 1:1 with responder CD4+ T cells from untreated Tg4 mice, irradiated APCs and 0.1 μg ml−1 MBP Ac1-9[4K]. After 3 days, proliferative responses were measured by 3[H] thymidine incorporation. Graph shows percentage suppression of responder CD4+ T-cell proliferation, relative to proliferation of responder cells cultured alone. Data (a–e) are representative of three similar experiments, error bars show s.e.m. of two independent biological replicates, each assayed in triplicate. (f) Onset and severity of EAE in Tg4 mice pre-treated with 10 doses of MBP Ac1-9[4Y] before immunization with spinal cord homogenate/Complete Freund's Adjuvant and Pertussis toxin. Results of two independent experiments are pooled, showing mean disease score±s.e.m. (n=7 PBS group, n=6 for each peptide-treated group). Full size image

Inflammatory cytokines are induced at high antigen doses

A higher dose of MBP Ac1-9[4Y] (80 μg) has been used to treat Tg4 mice by the i.n. route21. However, this dose was not tolerated when administered s.c. (Fig. 2a). Adverse effects (hunched posture, reduced mobility and responsiveness, piloerection and dyspnoea) developed between 2 and 24 h after the second and third injections. High concentrations of inflammatory cytokines were detected in the serum of treated mice, whereas Th2 cytokine concentrations remained low (Fig. 2b). Immunoglobulin E-mediated anaphylaxis has been reported to follow the administration of soluble myelin peptides after induction of EAE25,26. We noted, however, that adverse effects concomitant with high inflammatory cytokine levels developed similarly in the B-cell-deficient Tg4 Rag-1−/− mouse (Fig. 2c), suggesting that high-dose complications observed in the TCR transgenic Tg4 model were not antibody mediated, but a consequence of an excessive CD4+ T-cell response.

Figure 2: High peptide doses administered subcutaneously induce inflammatory cytokines in TCR transgenic mice. Tg4 mice were treated 10 times s.c. with 80 μg MBP Ac1-9[4Y]. (a) Shows the percentage of mice (n=15) free from adverse effects during the course of treatment. (b) Box-and-whisker plots show cytokine concentrations in serum (n=6), collected 2 h after successive 80 μg MBP Ac1-9[4Y] treatments as detected by a multiplex fluorescent bead immunoassay (MFBI). Box extends from 25th to 75th percentiles, horizontal line in boxes represents median value, error bars show minimum and maximum values. Data are representative of three independent experiments. (c) MFBI-detected serum cytokines from Tg4 Rag-1−/− mice 2 h after a second s.c. injection with 80 μg MBP Ac1-9[4Y]. Mean cytokine concentration+s.e.m. is shown for four individual animals. Full size image

Dose escalation is critical for effective immunotherapy

We determined whether escalating doses (0.08 μg→0.8 μg→8 μg→3 × 80 μg) would prevent the adverse effects associated with a high-dose regimen (Fig. 3a). No adverse effects were seen in EDI-treated animals despite the high dose of peptide given. Serum cytokine concentrations were measured at each stage of EDI (Fig. 3b) and were compared with mice treated with a constant 8 μg Ac1-9[4Y], the highest safe s.c. dose investigated. While an early peak in inflammatory cytokine levels was detected in mice treated with a constant 8 μg dose, the response was significantly lower (IFN-γ, IL-2 and IL-6) or much delayed (IL-17) in the EDI group. Levels of IL-10 were found to be similar at the end of both treatment courses, indicating that subversion of the initial inflammatory response did not compromise induction of the anti-inflammatory cytokine.

Figure 3: Peptide dose escalation desensitizes antigen-specific CD4+ T cells, allowing safe administration of high peptide doses subcutaneously. (a) MBP Ac1-9[4Y] dose escalation strategy. (b) Mean serum cytokine concentrations, detected by MFBI, 2 h after treatment of Tg4 mice with either six 8-μg MBP Ac1-9[4Y] doses or EDI (illustrated in a). Representative of three experiments, error bars show±s.e.m. of three biological replicates. *P≤0.05, **P≤0.01, ***P≤0.001, two-way analysis of variance with Bonferroni post-test, comparing 8-μg MBP Ac1-9[4Y]- and EDI-treated mice. Tg4 mice were treated s.c. with high antigen doses, with (+) or without (−) prior dose escalation (dosing strategy illustrated in c). CD4+ T-cell expression of Ki67, CD69 and CD62L 2 h after peptide challenge in vivo was determined by flow cytometric analysis (d). Scatter plots show the percentage of CD4+ cells from individual mice, which are Ki67+, CD69+ or CD62L+, horizontal lines show means for each column. Results of two independent experiments are pooled (n=6). **P≤0.01, ***P≤0.001, unpaired t-test. Full size image

Next we investigated the mechanism by which EDI permits s.c. administration of high, 80 μg, MBP Ac1-9[4Y] doses without adverse effects. Tg4 mice were treated with two high, 80 μg, MBP Ac1-9[4Y] doses, with or without prior dose escalation (Fig. 3c). The proliferative and activation status of antigen-specific CD4+ T cells was determined after the second 80-μg dose (Fig. 3d). CD4+ T cells from EDI-treated mice showed significantly lower expression of Ki67, a protein associated with cell division, than animals treated without dose escalation. Expression of the activation marker CD69 was also significantly suppressed in EDI-treated mice, while CD62L expression was significantly higher. These results demonstrate that dose escalation desensitises self-antigen-specific CD4+ T cells, suppressing activation and proliferation in response to cognate antigen, even at high doses.

A strong TCR signal is required for the development of IL-10-secreting CD4+ T cells17,27,28,29,30. The outcome of altering the end-point dose in EDI was investigated, using EDI with increasingly higher final doses (Fig. 4a). CD4+ T cells from all peptide-treated groups displayed a dose-dependent reduction in proliferative capacity (Fig. 4b), concomitant with an increase in the proportion of IL-10+IFN-γ+ T cells (Fig. 4c). Furthermore, the suppressive capacity of CD4+ T cells induced by EDI, either in vitro or in vivo, correlated with the magnitude of the final dose administered (Fig. 4d). These results reveal the direct correlation between peptide dose and the induction of a regulatory phenotype in auto-reactive T cells. Experiments were undertaken to determine whether the escalation phase of EDI itself enhances the induction of tolerance by EDI, in addition to reducing the risk of adverse effects in response to treatment. This was done by comparing the effects of repetitive 8-μg doses of MBP Ac1-9[4Y], with or without prior dose escalation (Supplementary Fig. 1a). The percentage of IL-10+ CD4+ T cells was higher in animals treated with prior dose escalation (Supplementary Fig. 1b); however, resistance to EAE was comparable in both of these treatment groups (Supplementary Fig. 1c). The robustness of tolerance induced by EDI was investigated in vivo using three disease models, testing both the prophylactic and therapeutic efficacy of EDI. Tg4 recipients pre-treated with EDI demonstrated reduced disease incidence following adoptive transfer of in vitro-differentiated MBP Ac1-9-specific Th1 cells (Fig. 5a). Tg4 Rag-1−/− mice lack FoxP3+ nTreg cells and develop EAE spontaneously19. EDI treatment of healthy 6-week-old Tg4 Rag-1−/− mice provided complete protection from spontaneous EAE, up to and beyond 20 weeks of age (Fig. 5b). Therapeutic treatment of Tg4 mice after EAE induction with Complete Freund's Adjuvant (CFA)/spinal cord homogenate and Pertussis toxin reduced disease incidence and mortality in EDI-treated mice, indicating that EDI is effective in both naive and primed settings (Fig. 5c).

Figure 4: Dose escalation to higher peptide doses improves induction of a regulatory CD4+ T-cell phenotype. (a) Treatment groups for EDI with increasingly higher final doses. (b) Proliferative responses of CD4+ T cells from EDI-treated Tg4 mice cultured with irradiated antigen-presenting cells (APCs) and MBP Ac1-9[4K] for 3 days, measured by 3[H] thymidine incorporation. Representative of three independent experiments each with two biological replicates assayed in triplicate. (c) Percentages of Vβ8+ T cells expressing IL-10 and IFN-γ after 6 days culture with 10 μg ml−1 MBP Ac1-9[4K], detected by flow cytometric analysis. Representative of two similar experiments, error bars show+s.e.m. of two biological replicates. (d) For in vitro suppression assay, in vitro-expanded CD4+ T cells from peptide-treated Tg4 mice cultured 1:1 with carboxyfluorescein succinimidyl ester (CFSE)-labelled responder CD4+ T cells, APCs and 10 μg ml−1 MBP Ac1-9[4K]. After 3 days, the proliferative response of CD4+CFSE+ responder cells was measured by flow cytometry. For in vivo suppression assay, 5 × 106 Cell Trace Violet (CTV)-labelled CD45.1+ Tg4 CD4+ T cells were transferred i.v. into EDI-treated Tg4 CD45.2+ mice. After 24 h, mice were injected s.c. with 80 μg of MBP Ac1-9[4Y]. Three days after peptide challenge, Cell Trace Violet-labelled CD45.1+ CD4+ cells were recovered from spleens for flow cytometric analysis. Data in each plot are representative of two biological replicates, offset histograms show proliferation dye dilution and division indexes. Full size image

Figure 5: Escalating dose immunotherapy reduces EAE susceptibility. (a) Tg4 mice were pre-treated s.c. with an escalating course of MBP Ac1-9[4Y], either 0.08 μg→0.8 μg→4 × 8 μg (esc. to 8 μg) or 0.08 μg→0.8 μg→8 μg→3 × 80 μg (esc. to 80 μg). In vitro-differentiated MBP Ac1-9-specific Th1 cells (107) were transferred i.v. to treated animals. (b) Six-week-old Tg4 Rag-1−/− mice, susceptible to spontaneous development of EAE, were EDI-treated (esc. to 80 μg, as above). (c) EAE was induced in Tg4 mice by s.c. injection of Complete Freund's Adjuvant (CFA)/spinal cord homogenate (SCH) with Pertussis toxin given on day 0 and day 2. Animals were then EDI-treated (arrows indicate day of treatment, dosing as above escalating to 80 μg). Animals were monitored daily for onset of EAE symptoms. Graphs show mean EAE score and s.e.m., summary panel shows incidence, mean maximum score and mortality for each experiment, n as shown in a–c. Full size image

Progressive CD4+ T-cell transcriptome changes during EDI

Whole-genome expression arrays were used to generate transcriptome data of CD4+ T cells at successive stages of EDI. On the basis of the expression matrix of 1,893 transcripts regulated across six stages of EDI (Supplementary Table 1), we applied a self-organizing map (SOM)-based method for gene clustering and visualization31. Treatment stage-specific transcriptome changes during EDI are illustrated using component plane presentations (CPPs)32 (Fig. 6a). Comparison of presentations reveals that, while dynamic changes occur during the initial stages of treatment, the transcriptional profile induced by extended high doses (between treatments 6 and 10) remains remarkably stable. A second phase of unbiased analysis was undertaken, yielding 12 clusters on a SOM-CPP grid along with the representative expression pattern of each (Fig. 6b; Supplementary Table 1). To elucidate the functional relevance of transcripts within these gene clusters (excluding cluster 2 with only nine transcripts), we performed enrichment analysis to identify gene ontology-biological process (GO-BP)33 terms that were significantly associated with these expression patterns (Fig. 6c; Supplementary Table 2). Genes that were repressed, either from baseline (cluster 1) or following induction (cluster 5), were enriched with GO-BP terms associated with the induction of an inflammatory response. Genes relating to regulatory immune processes were incrementally induced during EDI (patterns in clusters 3 and 8), including negative regulation of MAPK, NFκB and protein kinase signalling pathways. The genes of cluster 11, associated with the inflammatory response and cytokine production, were upregulated upon the first exposure to self-antigen and broadly maintained throughout the course of immunotherapy. Many genes (those in clusters 4, 6, 7, 9, 10 and 12) were upregulated during the escalation phase of treatment, then strongly repressed following extended high doses. Terms enriched within this pattern were strongly associated with cell cycle-related processes, such as mitosis, cytokinesis and microtubule regulation. Additional enrichments using Mouse Genome Informatics-Mammalian Phenotype34, Reactome35 and Disease Ontology (DO)36 terms (Supplementary Fig. 2; Supplementary Table 2) supported that clusters of genes sharing this expression pattern were related to cell cycle processes and diseases of abnormal cell division. Interrogation of the DO database also revealed significant association of terms describing inflammatory autoimmune diseases within cluster 5, where gene expression is repressed following initial exposure to the antigen.

Figure 6: Transcriptome analysis of CD4+ T cells at consecutive stages of escalating dose immunotherapy. Tg4 Rag-1−/−mice were EDI-treated s.c. with MBP Ac1-9[4Y]. CD4+ T-cell transcriptome analysis was undertaken at the indicated treatment stages (n=3 per time point, RNA pooled). (a) CPP-SOM of 1,893 regulated transcripts across six stages of EDI, illustrating treatment stage-specific transcriptional changes, relative to PBS-treated controls. Hexagons represent groups of co-clustered transcripts; colour changes show modulation of transcript expression (upregulation in red, downregulation in blue and moderate regulation in yellow and green). (b) Twelve gene clusters (colour-coded, labelled 1–12) obtained by two-phase SOM clustering. Bar graphs show the expression pattern of the seed unit used to derive each gene cluster. (c) Heatmaps showing expression patterns of clustered genes, and GO terms associated with each. Gene clusters are organized according to five dominant patterns; genes that are repressed from baseline, repressed following initial induction, incrementally induced, induced and then repressed and finally, induced and then maintained throughout the course of treatment. All GO terms are associated with at least three transcripts within a cluster, with a false-discovery rate (FDR) of <0.05. Full size image

On the basis of the expression patterns and their functional relevance revealed above, we selected genes characterizing the altered CD4+ T-cell state during the course of EDI (Fig. 7). Expression of negative co-stimulatory molecules including Lag3, Tigit and Havcr2 (TIM-3), were highly upregulated during treatments 1–6 of EDI and were maintained with extended treatment. Conversely, expression of Pdcd1 (PD-1) and Ctla4 remained largely unchanged during treatment, while expression of Btla and Cd274 (PD-L1) decreased with extended treatment. Icos, reported to promote IL-10 expression in CD4+ T cells37,38, was upregulated, while expression of the positive co-stimulatory molecule Cd226 decreased with treatment. As anticipated, expression of Il10 rose incrementally during EDI, a pattern shared with Il21, a cytokine previously shown to act as an autocrine growth factor of IL-10-secreting T cells38. The transcription factors c-Maf and NFIL3 (also known as E4BP4) are both implicated in regulation of IL-10 production by CD4+ T cells38,39; Maf and Nfil3 transcript expression was highly upregulated during EDI. Expression of Ahr, a transcription factor that interacts with c-Maf for transactivation of the IL-10 and IL-21 promoters40, followed this trend at a lower magnitude. Transcripts pertaining to cell cycle and genome integrity were induced during the escalation phase of treatment and then repressed with extended high doses. These included regulators of mitotic spindle dynamics and G2/M-phase transition, as well as spindle checkpoint components. Aurora kinase B (Aurkb), survivin (Birc5) and Incenp, previously associated with cell cycle progression in T cells41, were all repressed following extended high-dose treatment. In contrast to published studies42, both of the anergy-associated cyclin-dependant kinase inhibitors, p21Cip1 (Cdkn1a) and p27Kip1 (Cdkn1b), were repressed during the course of EDI. Together, these results highlight that each escalating dose of peptide treatment modifies the CD4+ T-cell transcriptome in a co-ordinated manner, resulting in a distinct EDI-induced phenotype characterized by the expression of specific transcription factors, negative co-stimulatory molecules and cytokines.

Figure 7: Modulated expression of select genes associated with regulatory T-cell phenotype during escalating dose immunotherapy. Tg4 Rag-1−/− mice were EDI-treated s.c. with MBP Ac1-9[4Y]. CD4+ T-cell transcriptome analysis was undertaken at the indicated treatment stages (n=3 per time point, RNA pooled) and transcripts were grouped by two-phase SOM clustering (see Fig. 6). Heatmaps are used to illustrate the fold changes in mRNA expression of individual genes during EDI. The cluster from which individual genes are derived (illustrated in Fig. 6b) is indicated by a colour identifier. Genes that were not included in clustering analysis (did not demonstrate a two-fold or greater change at ⩾4 treatment points, compared with the PBS-treated control) are indicated by a hyphen. Full size image

Incremental induction of a regulatory CD4+ T-cell phenotype

Expression of selected genes characterizing the CD4+ T-cell transcriptional state induced by EDI was confirmed by real-time PCR (Fig. 8a). This supports the incremental induction of transcripts for transcription factors and negative co-stimulatory molecules commonly associated with T-cell tolerance, as well as IL-10. CD4+ T-cell expression of these markers at the protein level was confirmed (Fig. 8b; Supplementary Fig. 3). Similar patterns of protein expression were observed in resting (Supplementary Fig. 4) and recently activated cells (Fig. 8b), although expression was higher in activated T cells. Indeed, a gradual increase in NFIL3 expression was detected only in activated cells. The percentage of CD4+ T cells expressing IL-10, c-Maf or LAG-3 expanded sequentially during EDI, culminating in at least 50% of activated cells expressing these markers. A rising percentage of TIGIT+ cells also accumulated during EDI (20% of activated CD4+ T cells). The proportion of cells expressing TIM-3 remained relatively stable throughout EDI, while the percentage of PD-1+ cells increased upon initial CD4+ T-cell activation and further increased during the later stages of EDI. An early peak in the percentage of FoxP3+ cells was detected, following low-dose treatment, but the percentage of FoxP3+ cells did not correlate with effective tolerance induction. Although expression of Il21 messenger RNA (mRNA) increased sequentially throughout the course of EDI, no change in CD4+ T-cell expression of IL-21 at the protein level was detected (Supplementary Fig. 5). We generated Tg4Il10/GFP reporter mice by crossing Tg4 mice with B6.129S6-Il10tm1Flv/J mice, originally generated and characterized by Kamanaka et al.43 Tg4Il10/GFP reporter mice were then used to determine the correlation between negative co-stimulatory molecule expression and IL-10. CD4+ T cells from treated mice were divided on the basis of green fluorescent protein (GFP) (IL-10) expression (Fig. 9a). Levels of LAG-3, TIGIT, PD-1 and TIM-3 correlated positively with IL-10 in CD4+ T cells, as did expression of CD49b, a marker recently used in combination with LAG-3 for the detection of IL-10-secreting Tr1 cells44. However, GFP−(IL-10−) cells were also detected among populations demonstrating high-level expression of these markers (Fig. 9b).

Figure 8: CD4+ T-cell signature induced by dose escalation immunotherapy. Tg4 mice were treated s.c. with an escalating dose of MBP Ac1-9[4Y] (0.08 μg→0.8 μg→8 μg→3 × 80 μg). (a) Real-time PCR analysis of mRNA of select genes expressed by CD4+ T cells, 2 h after peptide challenge in vivo, at the indicated stages of treatment. Graphs show mean expression values+s.e.m. for three replicate experiments, pooled (n=3 total). (b) Flow cytometric staining of IL-10, c-Maf, NFIL3, FoxP3, LAG-3, TIGIT, PD-1 and TIM-3 by CD4+ T cells at the indicated stages of treatment. Cells were harvested 2 h after peptide challenge in vivo. Data are representative of two to three independent experiments. Full size image