Adaptive plasticity of IL-10⁺ and IL-35⁺ T_reg cells cooperatively promotes tumor T cell exhaustion

Abstract

Regulatory T cells (T_reg cells) maintain host self-tolerance but are a major barrier to effective cancer immunotherapy. T_reg cells subvert beneficial anti-tumor immunity by modulating inhibitory receptor expression on tumor-infiltrating lymphocytes (TILs); however, the underlying mediators and mechanisms have remained elusive. Here we found that the cytokines IL-10 and IL-35 (Ebi3–IL-12α heterodimer) were divergently expressed by T_reg cell subpopulations in the tumor microenvironment (TME) and cooperatively promoted intratumoral T cell exhaustion by modulating multiple inhibitory receptor expression and exhaustion-associated transcriptomic signature of CD8⁺ TILs. While expression of BLIMP1 (encoded by Prdm1) was a common target; IL-10 and IL-35 differentially affected effector T cell versus memory T cell fates, respectively, highlighting their differential, partially overlapping but non-redundant regulation of anti-tumor immunity. Our results reveal previously unappreciated cooperative roles for T_reg cell-derived IL-10 and IL-35 in promoting BLIMP1-dependent exhaustion of CD8⁺ TILs that limits effective anti-tumor immunity.

Regulatory T cells (T_reg cells) are a specialized suppressive CD4⁺ T cell population capable of limiting deleterious immune responses to self and foreign antigens that underlie autoimmune and chronic inflammation^1,2. Conversely, T_reg cells suppress beneficial anti-tumor immunity and thereby pose an impediment to effective immunotherapies^3,4. Indeed, increased T_reg cells frequencies and a reduced CD8⁺/T_reg cell-ratio in tumors are linked to poor prognosis in multiple cancers^3,5. Although T_reg cell depletion dramatically reduces tumor burden, the ensuing autoimmune sequelae limit the utility of this approach in the clinic^6,7. Hence, current trials are evaluating strategies targeting receptors preferentially enriched on intratumoral T_reg cells (CCR4, GITR, OX40, CTLA4)⁸. T_reg cells utilize a plethora of suppressive mechanisms – inhibitory cytokine secretion, metabolic disruption, modulation of antigen-presenting cell (APC) function, and cytolysis of effector cells; often in a target cell and tissue-specific manner¹. While targeting suppressive mechanisms selectively or predominantly employed by intratumoral T_reg cells would be efficacious, the precise mechanisms and predominant suppressive mediators that promote T cell exhaustion and dominant suppression in the tumor microenvironment (TME) remain poorly defined.

One of the major contact-independent modes of T_reg cell suppression is via secretion of inhibitory cytokines (IL-10, IL-35, and TGF-β)^1,9. The established suppressive cytokine duo (IL-10 and TGF-β) plays a critical role in steady-state immune homeostasis and taming exuberant responses at environmental interfaces. Perturbation of IL-10 and TGF-β signaling improved the function of exhausted T cells in chronic viral infections^10–12. Co-targeting T_reg cells or IL-10 along with the PD-1 immune checkpoint pathway resulted in a synergistic reversal of T cell exhaustion^13,14. IL-35 is required for maximal T_reg cell suppressor function and contributes to the regulatory milieu in numerous disease states^15,16. Previous work demonstrated enrichment of IL-35 expression on tumor-infiltrating T_reg cells in B16 tumors and a role of IL-35 in promoting inhibitory receptor expression (PD-1, TIM3, LAG3) on intratumoral T cells⁷. Thus, while T_reg cells and suppressive cytokines have been linked to T cell exhaustion in chronic settings, the molecular mechanisms and the relative contribution of T_reg cell-derived suppressive cytokines underlying T_reg cell-induced exhaustion remain obscure.

In this study, we report a divergent and largely non-overlapping IL-10 and IL-35 expression pattern on T_reg cells infiltrating both murine tumors as well as patients with non-small cell lung cancer (NSCLC). We further demonstrate that these IL-10⁺ and Ebi3⁺ T_reg cell populations are not distinct lineages, but rather transitory states with concordant transcriptional and T cell receptor (TCR) profiles. This transition is inducible via TCR stimulation of purified T_reg cell subpopulations in vitro, potentially reflecting plasticity in inhibitory cytokine expression in chronic environments. While the two cytokines target a common BLIMP1 axis to promote the exhausted intratumoral T cell state; IL-10 and IL-35 differentially impacted effector versus memory generation, respectively. Our results uncover the previously unappreciated adaptive plasticity of IL-10 and IL-35 inhibitory cytokine expression by T_reg cell subpopulations in the TME and how they cooperatively impinge on T cell function to promote exhaustion and limit anti-tumor immunity.

Results

Divergent IL-10 and IL-35 expression on T_reg cells in murine tumors and NSCLC patients

Intratumoral T_reg cells are more suppressive than their peripheral counterparts in both murine models and human tumors owing to their heightened activation status^3,4. Thus, we reasoned that the major suppressive mediators might be co-expressed on intratumoral Foxp3⁺ T_reg cells to maximize their functional impact. To address this hypothesis, we generated triple reporter mice (Il10^GFP.Ebi3^Tom.Foxp3^Cre-YFP; Il10 for IL-10, Ebi3 for IL-35, and Foxp3 for T_reg cells, respectively^7,17,18; Fig. 1a, Supplementary Fig. 1a). We observed largely segregated expression of IL-10 and Ebi3 by T_reg cells in various lymphoid and non-lymphoid organs, with minimal co-expression (Supplementary Fig. 1b); consistent with a previous report¹⁹. The only tissues with a notable (>5%) population of T_reg cells co-expressing IL-10 and Ebi3 at steady state were skin and lamina propria, likely due to elevated IL-10⁺ T_reg cells at these environmental interfaces (Supplementary Fig. 1b). Specifically, in the B16 TME, there was an approximately 4-fold and 2-fold intratumoral enrichment of IL-10⁺ (GFP⁺YFP⁺) and Ebi3⁺ (Tom⁺YFP⁺) T_reg cells, respectively, compared to the periphery (Fig. 1a-c).

Figure 1: Reciprocal expression of IL-10 and IL-35 on both mouse and human T_reg cells.

a, Representative flow plots depicting the expression and distribution of IL-10⁺ and Ebi3⁺ cells within Foxp3YFP⁺ T_reg cells, isolated from B16-tumor bearing Il10^GFP.Ebi3^Tom.Foxp3^Cre-YFP mice 14 days post tumor inoculation. The expression of IL-10 (GFP⁺) and IL-35 (Ebi3-Tomato⁺) assessed in the non-draining axillary and brachial lymph nodes (NDLN), draining inguinal lymph nodes (DLN) and B16 tumor-infiltrating lymphocytes (TIL).

b, SPICE plots depicting co-expression pattern of IL-10 and Ebi3 on TIL T_reg cells as in (a).

c, Scatter-bar plot depicting percent distribution of cytokine single- and double-positive T_reg cells as in (a) (n=11 mice). Bars represent mean values. Statistical significance was determined by Two-way ANOVA with Holm-Sidak multiple comparisons (p-values as indicated).

d, Representative flow plots depicting expression and distribution of IL-10⁺ and Ebi3⁺ cells within Foxp3-YFP⁺ T_reg cells, isolated from day 14 allergic inflammation induced Il10^GFP.Ebi3^Tom.Foxp3^Cre-YFP mice. NDLN, DLN, Lungs, and Bronchoalveolar lavage fluid (BAL).

e, SPICE plots depicting co-expression pattern of IL-10 and Ebi3 on T_reg cells as described in (d).

f, Scatter-bar plot depicting percentage of cytokine single- and double-positive T_reg cells as described in (d) (n=12 mice). Bars represent mean values. Statistical significance was determined by Two-way ANOVA with Holm-Sidak multiple comparisons (****p<0.0001 and other p-values as indicated).

g, Representative flow plots depicting the expression and distribution of IL-10 and IL-35 in human T_reg cells (CD4⁺CD25^HIFoxp3⁺) obtained from healthy donor (HD) PBMC (PBL), NSCLC PBL, or NSCLC TILs. Cells were stimulated overnight with plate-bound anti-CD3 and anti-CD28 in the presence of hIL2, followed by four hours of stimulation with PMA-ionomycin prior to surface and intracellular (IC)-staining for IL-10 and IL-35 (EBI3) expression analysis. Isotype control (black) and IC-stained (red) are overlaid. Data representative of three independent experiments.

h, SPICE plots depicting co-expression pattern of IL-10 and EBI3 on T_reg cells as described in (g).

i, Scatter-bar graph depicting percent distribution of inhibitory cytokines as in (g). Bars represent mean values HD PBL (n=9), NSCLC PBL (n=9), and NSCLC TIL (n=16). Statistical significance was determined by Two-way ANOVA with Holm-Sidak multiple comparisons (****p<0.0001).

Furthermore, this divergent inhibitory cytokine distribution in T_reg cells was not a characteristic limited to the somewhat T_H1-polarized TME, as we noted a similarly divergent expression pattern in a T_H2-polarized fungal protease (Aspergillus oryzae) model of allergic airway disease (Fig. 1d-f)²⁰. The enrichment of IL-10⁺ T_reg cells was more pronounced in the allergic environment than the B16 TME, resulting in an approximately 10-fold expansion compared to the periphery, supporting the notion of adaptive plasticity in the relative abundance of IL-10⁺ and IL-35⁺ subpopulations depending on the nature of the inflammatory microenvironment. T_reg cell-restricted deletion of Ebi3 in Il10^GFP.Ebi3^L/L-Tom.Foxp3^Cre-YFP mice did not result in a compensatory change in the distribution of these T_reg cell subpopulations in either T_H1- or T_H2-polarized inflammatory environment (Supplementary Fig. 1c-h). Importantly, human T_reg cells from healthy donors and non-small cell lung cancer (NSCLC) patients also showed a similar segregated IL-10 and IL-35 expression pattern with a minimal percentage of double cytokine positive T_reg cells (Fig. 1g-i). In this case, there was also an increased percentage of Ebi3⁺ intratumoral T_reg cells, highlighting the translational importance of understanding the developmental and functional relationship between these intratumoral T_reg cell-subpopulations. Collectively, these data highlight preferential enrichment and divergent inhibitory cytokine expression pattern on mouse and human intratumoral T_reg cells.

Adaptive plasticity of cytokine expression and comparable transcriptome of intratumoral IL-10⁺ and IL-35⁺ T_reg cell subpopulations

To dissect the divergent cytokine expression pattern and the preferential generation of single inhibitory cytokine positive T_reg cell subpopulations, we performed single-cell RNAseq (scRNAseq) comparing T_reg cells isolated from naive, unchallenged lymph nodes (LNs) or day 14 B16 tumors from Foxp3^Cre-YFP mice (Fig. 2a). IL-10⁺ and Ebi3⁺ T_reg cells exhibited comparable transcriptomic signatures (Fig. 2b-c). Although unsupervised K-means clustering identified six unique T_reg cell clusters (Supplementary Fig. 2a), the distribution ratio of IL-10⁺ versus Ebi3⁺ T_reg cell subpopulations among those clusters was comparable, especially for intratumoral T_reg cells (Supplementary Fig. 2b). Consistent with the scRNAseq analyses, T cell receptor beta chain (TCRβ)-sequencing of IL-10⁺ and Ebi3⁺ T_reg cell subpopulations isolated from non-draining LNs (NDLN) and B16 tumors from Il10^GFP.Ebi3^Tom.Foxp3^Cre-YFP mice showed a comparable clonal enrichment (Supplementary Fig. 2c). We did not observe any bias in TCR V_β-gene usage or CDR3-length, which can play a role in regulating T cell development and differentiation via TCR affinity and signaling strength^21,22 (Fig. 2d, Supplementary Fig. 2d). Furthermore, substantial TCR clonal overlap noted among intratumoral T_reg cell subpopulations is consistent with the lack of distinct transcriptomic signatures (Supplementary Fig. 2e). TCR signaling plays a crucial role in the production of both IL-10 and IL-35^[23]. Importantly, we noted that TCR-stimulation in vitro was sufficient to induce Il10 and Ebi3 expression in purified T_reg cell subpopulations (Fig. 2e), inferring extensive developmental plasticity. There was a preferential upregulation of Ebi3 expression observed during in vitro fate mapping, which is consistent with a progressive enrichment of Ebi3⁺ (either IL-10⁻Ebi3⁺ or IL-10⁺Ebi3⁺) T_reg cells revealed by diffusion pseudotime analysis (Fig. 2f-g). Furthermore, while it has been reported that the development and function of Ebi3⁺ T_reg cells are independent of BLIMP1 expression¹⁹, our results indicate that BLIMP1 may also play a key role in supporting the maintenance and functions of Ebi3⁺ T_reg cells as approximately 90% of TIL T_reg cells express BLIMP1 and 30–50% of which are Ebi3⁺ (Supplementary Fig. 2f, Fig. 1a-c). These observations suggest that TCR signaling, and perhaps the suppressive tumor milieu, might drive this adaptive plasticity and lead to the generation of T_reg cell subpopulations marked by transitory IL-10 and IL-35 expression.

Figure 2: Adaptive plasticity of IL-10⁺ and IL-35⁺ T_reg cells.

a, scRNAseq tSNE plots of bulk T_reg cells from naive LNs or 14 days post inoculation B16 tumors (TIL T_reg cells) from Foxp3^Cre-YFP mice.

b, scRNAseq tSNE plot depicting the expression of Il10 and Ebi3 in individual T_reg cells overlaid on the same tSNE plot as in (a).

c, Heat maps contrasting the top 30 genes selected based on the differential expression analysis of T_reg cells utilizing the two-sided Negative Binomial Exact test, demonstrating the lack of distinct transcriptional signatures. p-values were adjusted to control the false discovery rate (FDR) set at 0.05. Treg cells were first stratified into IL-10⁻Ebi3⁻, IL-10⁺Ebi3⁻, IL-10⁻Ebi3⁺, and IL-10⁺Ebi3⁺ as described in (b). (Naive LN): IL-10⁻Ebi3⁻ (n=717 cells), IL-10⁺Ebi3⁻ (n=3 cells), IL-10⁻Ebi3⁺ (n=83 cells), and IL-10⁺Ebi3⁺ (n=3 cells). (TIL): IL-10⁻Ebi3⁻ (n=491 cells), IL-10⁺Ebi3⁻ (n=88 cells), IL-10⁻Ebi3⁺ (n=491 cells), and IL-10⁺Ebi3⁺ (n=111 cells).

d, Bar graphs with overlaid scatter-dots depicting the TCR V_β gene usage, comparing the T_reg cells subpopulations and effector T cells. Three independent B16 tumor-bearing Il10^GFP.Ebi3^Tom.Foxp3^Cre-YFP mice were used to harvest T_reg cell subpopulations for sequencing without pooling. Bars represent mean values.

e, In vitro tracing of adaptive plasticity in cytokine expression by TCR-stimulation. (top): Naive T_reg cells from LN and spleens were double-sort purified and stimulated with anti-CD3/CD28-coated beads in the presence of hIL2 and CD11c⁺ cells for 72 hours, followed by FACS analysis. (bottom): Stacked bar graph summarizing four independent experiments. Statistical significance was determined by Two-way ANOVA with Holm-Sidak multiple comparisons (^#p=0.0073, *p=0.0016, **=P=0.0017, ***p=0.0002, ****p<0.0001).

f, Diffusion pseudo-time analysis depicting the stochastic oscillation of IL-10 and IL-35 (Ebi3) expression based on the transcriptomic features of sequenced T_reg cells from the scRNAseq experiment.

g, Stacked-bar graph demonstrating the distribution of indicated T_reg subpopulations along the Pseudotime projection as analyzed in (f). The Pseudotime projection was evenly divided into 10 fractions and the percent distribution of each T_reg cell subpopulation was calculated.

We also performed bulk RNAseq-based transcriptome analysis on purified LN and tumor (TIL) T_reg cell subpopulations defined by Il10 and Ebi3 reporter expression (Supplementary Fig. 3a), to further investigate the transcriptomic relationship between these T_reg cell subpopulations with greater sequencing depth. Principal component analysis (PCA) of differentially regulated genes clearly separated LN vs. TIL T_reg cells, irrespective of cytokine expression pattern (Supplementary Fig. 3a). Consistent with the scRNAseq data, bulk profiling revealed no striking transcriptomic differences between intratumoral T_reg cell subpopulations (Supplementary Fig. 3b). Modest differences were noted in expression patterns of genes encoding co-signaling molecules (Cd226, Tnfsf11, Cd2, Lag3, Cd27, Cd28), likely reflecting their relative suppressive capacity noted in vitro (Supplementary Fig. 3c-f). Collectively, the concordant transcriptional and TCR profiles highlight these IL-10⁺ and Ebi3⁺ T_reg cell subpopulations as plastic transitory states, rather than distinct subsets.

Cooperative regulation of anti-tumor immunity by IL-10⁺ and IL-35⁺ T_reg cells

It was previously shown that mice with a T_reg cell restricted Ebi3 deletion, and thus loss of IL-35 production, exhibit reduced tumor burden⁷. To assess the functional impact of IL-10- and IL-35-producing T_reg cell subpopulations on the TME, we compared the growth rate of three transplantable tumor models; B16 and BrafPten (clone 24) melanoma models and EL4 thymoma in mice with T_reg cells that are unable to produce IL-10 (Il10^L/L.Foxp3^Cre-YFP), IL-35 (Ebi3^L/L-Tom.Foxp3^Cre-YFP) or either cytokine (Il10^L/L.Ebi3^L/L-Tom.Foxp3^Cre-YFP). T_reg cell-restricted deletion of Il10 or Ebi3 resulted in a comparable reduction in tumor growth (Fig. 3a-c). Dual-deletion did not exhibit a significant additive or synergistic reduction in tumor burden in both the melanoma models and only a marginal effect on EL4, suggesting that T_reg cell-derived IL-10 and IL-35 might regulate anti-tumor immunity through a common, co-operative pathway.

Figure 3: Cooperative, redundant regulation of CD8⁺ TILs by T_reg cell-derived IL-10 and IL-35.

(a-c): Tumor growth curve of Foxp3^Cre-YFP, Il10^L/L.Foxp3^Cre-YFP, Ebi3^L/L-Tom.Foxp3^Cre-YFP, and Il10^L/L.Ebi3^L/L-Tom.Foxp3^Cre-YFP mice inoculated with 1.25×10⁵ tumor cells intradermally. (a) B16 (**p=0.0019, ***p=0.0004, ****p<0.0001), (b) BrafPten clone 24 (*p=0.0263, ****p<0.0001), (c) EL4 (^#p=0.0054, *P=0.0047, **p=0.0043, ***p=0.0003, ****p<0.0001). Data averaged from 3 independent experiments with an indicated total number of mice per genotype. Each measurement time point represents mean value with s.e.m. error bar. Statistical significance was determined by Two-way ANOVA with Holm-Sidak multiple comparisons.

d, Representative flow plots depicting the expression of inhibitory receptors (PD-1 versus other inhibitory receptors: TIM3, LAG3, TIGIT, and 2B4) on CD8⁺ T cells infiltrating d14 B16 tumor-bearing Foxp3^Cre-YFP (n=13), Il10^L/L.Foxp3^Cre-YFP (n=9), Ebi3^L/L-Tom.Foxp3^Cre-YFP (n=11), and Il10^L/L.Ebi3^L/L-Tom.Foxp3^Cre-YFP (n=10) mice. SPICE plots depict the co-expression of multiple inhibitory receptors.

e, Scatter-bar graphs tabulating the percent distribution of inhibitory receptor-negative (0 & 1 inhibitory receptor-expressing effector-like) and multi-inhibitory receptor⁺ (3-5 inhibitory receptor-expressing exhausted) CD8⁺ TILs as in (d). Bars represent mean values. Statistical significance was determined by One-way ANOVA with Holm-Sidak multiple comparisons (****p<0.0001 and other p-values indicated).

f, Representative flow plots depicting expression of inhibitory receptors (PD-1 versus the other inhibitory receptors – TIM3, LAG3, TIGIT and 2B4) on CD4⁺Foxp3⁻ T cells harvested from d14 B16 tumor-bearing Foxp3^Cre-YFP (n=13), Il10^L/L.Foxp3^Cre-YFP (n=9), Ebi3^L/L-Tom.Foxp3^Cre-YFP (n=11), and Il10^L/L.Ebi3^L/L-Tom.Foxp3^Cre-YFP (n=10) mice. SPICE plots depicting expression and co-expression of multiple inhibitory receptors on CD4⁺Foxp3⁻ TILs.

g, Bar graphs representing the percent distribution of inhibitory receptor-negative (0 & 1 inhibitory receptor-expressing effector-like) and multi-inhibitory receptor⁺ (4 & 5 inhibitory receptor-expressing exhausted) CD4⁺Foxp3⁻ T cells as in (f). Bars represent mean values. Statistical significance was determined by One-way ANOVA with Holm-Sidak multiple comparisons (****p<0.0001 and other p-values indicated).

(d-g) Data averaged from 3 independent experiments.

IL-35 can modulate inhibitory receptor expression on CD8⁺ and CD4⁺ TILs⁷. A substantial fraction of CD8⁺ and CD4⁺ TILs in B16 tumor-bearing control Foxp3^Cre-YFP mice were PD-1^hi and co-expressed multiple inhibitory receptors (TIM3, LAG3, TIGIT and 2B4, referred to as PD-1^himulti-inhibitory receptor⁺ TILs) (Fig. 3d-g, Supplementary Fig. 4a-b). Consistent with previous observations, Ebi3^L/L-Tom.Foxp3^Cre-YFP exhibited a drastic reduction of CD8⁺ PD-1^himulti-inhibitory receptor⁺ TILs on day 14. Interestingly, Il10^L/L.Foxp3^Cre-YFP mice also exhibited a reduction in the CD8⁺ PD-1^himulti-inhibitory receptor⁺ TILs, albeit to a lesser extent. Mice with T_reg cell-specific deletion of both II10 and Ebi3 (Il10^L/L.Ebi3^L/L-Tom.Foxp3^Cre-YFP) demonstrated a near complete loss of the PD-1^hi and multi-inhibitory receptor⁺ populations and significant enrichment of inhibitory receptor-negative and PD-1^int CD8⁺ T cells (Fig. 3d-e, Supplementary Fig. 4a-b). B16 TIL analysis at a later time point (day 20) revealed a less extensive reduction of inhibitory receptor expression on CD8⁺ TILs from Il10^L/L.Foxp3^Cre-YFP mice while CD8⁺ TILs from Ebi3^L/L-Tom.Foxp3^Cre-YFP and Il10^L/L.Ebi3^L/L-Tom.Foxp3^Cre-YFP mice still exhibited diminished inhibitory receptor-expression (Supplementary Fig. 4c-d). Although the overall extent of PD-1^hi and multi-inhibitory receptor expression was not as prominent on CD4⁺ TILs, T_reg cell-restricted deletion of Il10 and Ebi3 showed a comparable, substantial impact on PD-1^himulti-inhibitory receptor⁺ CD4⁺ TILs at both time points as their CD8⁺ counterparts (Fig. 3f-g, Supplementary Fig. 4e-f). These data suggest that while both T_reg cell-derived IL-10 and IL-35 function cooperatively in driving inhibitory receptor induction on TILs, IL-35 may play a more dominant role.

We also analyzed the impact of inhibitory cytokine-driven multi-inhibitory receptor induction on CD8⁺ T cell differentiation as well as other cell types in the TME. Increased cellularity and cytokine production were noted in tumors of Il10^L/L.Foxp3^Cre-YFP mice (Fig. 4a-b, Supplementary Fig. 5a-b), while enhanced T_CM differentiation was noted in both Ebi3^L/L-Tom.Foxp3^Cre-YFP and Il10^L/L.Ebi3^L/L-Tom.Foxp3^Cre-YFP TMEs (Fig. 4c). We also examined myeloid populations and observed a comparable reduction of PD-L1 expression and increase in T cell stimulatory molecules such as MHC-II and CD80 following the loss of T_reg cell-derived IL-10 or IL-35 (Supplementary Fig. 5c-e). There was an increase in the M1-like tumor-associated macrophage (TAM) population in Il10^L/L.Foxp3^Cre-YFP mice which conversely was decreased in Ebi3^L/L-Tom.Foxp3^Cre-YFP and Il10^L/L.Ebi3^L/L-Tom.Foxp3^Cre-YFP mice (Supplementary Fig. 5f)^24,25. Collectively, these data point to the differential impact of T_reg cell-restricted deletion of these two cytokines on the TME, with an apparent greater impact of IL-10 in limiting effector function and proliferation, whereas IL-35 seems to limit memory differentiation.

Figure 4: Non-redundant regulation of anti-tumor immunity by IL-10⁺ and IL-35⁺ T_reg cells.

a, Representative flow plots depicting the expression of IFN-γ and TNF-α. Scatter-bar plots representing the percent distribution of CD8⁺ TILs expressing IFN-γ and/or TNF-α infiltrating d20 B16 tumor-bearing Foxp3^Cre-YFP (n=10), Il10^L/L.Foxp3^Cre-YFP (n=12), Ebi3^L/L-Tom.Foxp3^Cre-YFP (n=12), and Il10^L/L.Ebi3^L/L-Tom.Foxp3^Cre-YFP (n=9) mice.

b, Representative flow plots depicting the expression of IFN-γ and TNF-α. Scatter-bar plots representing the percent distribution of CD4⁺Foxp3⁻ TILs expressing of IFN-γ and/or TNF-α as in (a). Foxp3^Cre-YFP (n=10), Il10^L/L.Foxp3^Cre-YFP (n=12), Ebi3^L/L-Tom.Foxp3^Cre-YFP (n=12), and Il10^L/L.Ebi3^L/L-Tom.Foxp3^Cre-YFP (n=9).

c, Representative flow plots depicting gating strategy to identify CD8⁺ T_CM TILs (CD44⁺KLRG1⁻CD127⁺CD62L⁺TCF1⁺) (left). The percent distribution of CD8⁺ T_CM was tabulated in scatter-bar graphs (right), analyzed 14 days (Foxp3^Cre-YFP (n=8), Il10^L/L.Foxp3^Cre-YFP (n=9), Ebi3^L/L-Tom.Foxp3^Cre-YFP (n=10), and Il10^L/L.Ebi3^L/L-Tom.Foxp3^Cre-YFP (n=12) mice) and 18 days (Foxp3^Cre-YFP (n=12), Il10^L/L.Foxp3^Cre-YFP (n=13), Ebi3^L/L-Tom.Foxp3^Cre-YFP (n=16), and Il10^L/L.Ebi3^L/L-Tom.Foxp3^Cre-YFP (n=10) mice) post-B16 tumor inoculation.

(a-c) Data averaged from 3 independent experiments. Bars represent mean values. Statistical significance was determined by One-way ANOVA with Holm-Sidak multiple comparisons (****p<0.0001 and other p-values indicated).

T_reg cell-derived IL-35 and IL-10 can directly induce inhibitory receptor expression on intratumoral CD8⁺ T cells

We next investigated whether IL-10 and IL-35 were directly impacting CD8⁺ T cells in the TME or if this regulation required an intermediate or accessory cell. We created an experimental system in which only CD8⁺ T cells were unable to respond to IL-10 or IL-35 utilizing a Rag1^−/− reconstitution model (Fig. 5a). Reconstitution with IL-35 receptor-deficient (CD4^Cre.Il6st^L/L.IL12rb2^−/−; referred to as IL-35R^−/−)²⁶ or IL-10 receptor-deficient (Il10rb^−/−; referred to as IL-10R^−/−)²⁷ CD8⁺ T cells recapitulated the reduced B16 tumor growth observed in mice with T_reg cells that cannot make IL-35 and IL-10, respectively (Fig. 5b). Although inhibitory receptor expression was substantively reduced on IL-35R.KO CD8⁺ T cells, there was only a partial reduction on IL-10R.KO CD8⁺ T cells assessed at both d14 and d18 timepoints (Fig. 5c-d, Supplementary Fig. 5g-h). These results in the Rag1^−/− reconstitution model were consistent with our analysis of intact mice, showing a ‘weaker’ effect of T_reg cell-derived IL-10 relative to IL-35 on inhibitory receptor expression (Fig. 3d-e, Supplementary Fig. 4c-d), limiting the possibility that an accessory cell is involved in this process. These data further support the notion that both T_reg cell-derived IL-10 and IL-35 can directly regulate multi-inhibitory receptor expression on intratumoral CD8⁺ cells.

Figure 5: Direct impact of IL-10 and IL-35 signaling on CD8⁺ TILs.

a, Experimental schematic of adoptive transfer system to generate an environment in which only CD8⁺ T cells lack IL-10R or IL-35R.

b, Tumor growth curve of Rag1^−/− mice that were sequentially reconstituted with CD8-depleted splenocytes and CD8⁺ T cells from wild-type (WT) (n=11), IL-10R^−/− (Il10rb^−/−) (n=8), or IL-35R^−/−(CD4^Cre.Il6st^L/L.Il12rb2 KO) (n=7) mice followed by B16 intradermal inoculation. Each measurement time point represents mean value with s.e.m. error bar. Statistical significance was determined by Two-way ANOVA with Holm-Sidak multiple comparisons (****p<0.0001).

c, Representative flow plots depicting the expression of PD-1 against the other 4 inhibitory receptors (TIM3, LAG3, TIGIT, 2B4) and SPICE plots showing the multi-inhibitory receptor expression on the donor CD8⁺ T cells infiltrating B16 tumor-bearing reconstituted Rag1^−/− mice 18 days post-tumor inoculation as described in (a).

d, Scatter-bar graphs representing the percent distribution of donor CD8⁺ TILs based on the number of inhibitory receptors expressed. (WT: n=10, IL-10R^−/−: n=6, IL-35R^−/−: n=7). Bars represent mean values. Statistical significance was determined by One-way ANOVA with Holm-Sidak multiple comparisons (****p<0.0001 and other p-values indicated).

(a-d) Data averaged from 2 independent experiments.

T_reg cell-derived IL-10 and IL-35 co-opt the BLIMP1-regulated exhaustion module to drive T cell dysfunction

We next probed the mechanistic underpinnings of IL-10 and IL-35-driven multi-inhibitory receptor upregulation to assess if these T_reg cell subpopulations employed similar or distinct downstream mechanisms to drive T cell dysfunction. We performed RNAseq with CD8⁺ TIL-subsets based on the expression of PD-1 and TIM3: (i) PD-1^hiTIM3⁺ double positive (DP), (ii) PD-1^hiTIM3⁻ single positive (SP), (iii) PD-1^int, and (iv) PD-1^neg T cell subsets (Fig. 6a, Supplementary Fig. 6a). PCA of these subsets from control Foxp3^Cre-YFP mice segregated them into defined clusters based on location (NDLN vs. TIL) and state of exhaustion (NEG, INT, SP vs. DP), highlighting the distinct transcriptional signatures specific to each subset (Fig. 6a-b). Differential gene expression analysis comparing the CD8⁺ TIL subsets from single and dual T_reg cell cytokine-deficient mice to corresponding wild-type counterparts revealed that the alteration of the TME by T_reg cell-restricted deletion of IL-10 and/or IL-35 influenced the transcriptome of all the CD8⁺ subsets (Supplementary Fig. 6b-d). In particular, gene set enrichment analysis (GSEA) confirmed significant downregulation of an exhaustion signature in SP and DP CD8⁺ subsets from Il10^L/L.Foxp3^Cre-YFP, Ebi3^L/L-Tom.Foxp3^Cre-YFP, and Il10^L/L.Ebi3^L/L-Tom.Foxp3^Cre-YFP mice, relative to the control CD8⁺ T cells (Fig. 6c). This exhaustion gene signature of CD8⁺ TIL subsets displayed strong congruence to the published data from LCMV infection²⁸, indicative of a core molecular program that drives PD-1^int to PD-1^hi transition in chronic settings (Supplementary Fig. 6e). These results further support the ability of both IL-10⁺ and IL-35⁺ T_reg cell subpopulations to drive the PD-1^int to PD-1^hi transition thereby promoting the multi-inhibitory receptor⁺ TIL state (Fig. 6c).

Figure 6: T_reg cell-derived IL-10 and IL-35 regulate CD8⁺ TILs through BLIMP1–inhibitory receptor axis.

(a-e) Data averaged from 5 independent RNASeq experiments: Foxp3^Cre-YFP (n=3), Il10^L/L.Foxp3^Cre-YFP (n=2), Ebi3^L/L-Tom.Foxp3^Cre-YFP (n=3), and Il10 ^L/L.Ebi3^L/L-Tom.Foxp3^Cre-YFP CD8s (n=4).

a, The gating strategy for double-sorted CD8⁺ subsets for RNAseq. (PD-1^negTIM3⁻, NEG; PD-1^intTIM3⁻, INT; PD-1^hiTIM3⁻, SP; and PD-1^hiTIM3⁺, DP). PCA plot depicting the NDLN and CD8⁺ TILs subsets from Foxp3^Cre-YFP. Each symbol represents an independently sequenced replicate.

b, Heat map of tumor-exhaustion gene signature mapped to the chronic LCMV exhaustion program, representing the NDLN and CD8⁺ TIL subsets from B16-tumor-bearing Foxp3^Cre-YFP mice.

c, GSEA of tumor-exhaustion gene signature derived from SP (left) and DP (right) subsets of Foxp3^Cre-YFP mice; p-values as indicated.

d, XY plots representing differentially expressed transcription factors (TFs) in SP subsets. X axis represents differentially expressed genes in the PD-1^hi (SP and DP) subsets relative to NEG subsets from control Foxp3^Cre-YFP mice; Y axis represents differentially expressed genes in the T_reg cell cytokine deficient environments relative to control Foxp3^Cre-YFP counterparts. Only significantly changed TFs are listed. We only considered TFs that were differentially expressed in exhausted cells (PD1hi, DP and SP) with a minimum log2 fold-change of 1.5, which was further filtered for ones that were differentially expressed across genotypes in the SP subset with the same cutoffs.

e, GSEA of BLIMP1 associated gene signature in SP (left) and DP (right) subsets of Foxp3^Cre-YFP mice; p-values as indicated.

(c, e) Statistical significance was determined by Rank Sum Test With Correlation test in the limma R package with correction for loss in degrees of freedom due to correlation among genes. All p-values are two sided. No correction for multiple hypothesis was performed.

f, Representative histograms for validation of BLIMP1 and its associated gene (TCF7 and IL-7R) at the protein level in the CD8⁺ TILs from B16 tumor-bearing Foxp3^Cre-YFP (n=6), Il10^L/L.Foxp3^Cre-YFP (n=4), Ebi3^L/L-Tom.Foxp3^Cre-YFP (n=5), and Il10^L/L.Ebi3^L/L-Tom.Foxp3^Cre-YFP (n=6) mice from two independent experiments.

g, Scatter-bar plots tabulating the expression levels of BLIMP1, IL-7R, and TCF7 as in (f). Statistical significance was determined by One-way ANOVA with Holm-Sidak multiple comparisons (****p<0.0001 and other p-values as indicated).

We next interrogated the transcription factors that were upregulated during the PD-1^int to PD-1^hi transition in control CD8⁺ T cells and assessed their expression in mice lacking IL-10 and/or IL-35 in T_reg cells. The transcription factor Prdm1 (encoding BLIMP1) was one of the top genes induced during this transition and was significantly reduced in SP and DP CD8⁺ T cells from Il10^L/L.Foxp3^Cre-YFP, Ebi3^L/L-Tom.Foxp3^Cre-YFP, and Il10^L/L.Ebi3^L/L-Tom.Foxp3^Cre-YFP mice (Fig. 6d). Reduced Prdm1 expression was accompanied by an upregulation of its target genes (many of which are characteristic of memory T cells: Tcf7, Id3, Il7r)²⁹ (Fig. 6d-g), which is in agreement with an increase in CD8⁺ central memory T cells (T_CM) (Fig. 4c). We also noted upregulation of a PD-1 blockade-responsive TCF-1⁺CXCR5⁺ memory gene signature³⁰ in CD8⁺ T cells from Il10^L/L.Foxp3^Cre-YFP, Ebi3^L/L-Tom.Foxp3^Cre-YFP, and Il10^L/L.Ebi3^L/L-Tom.Foxp3^Cre-YFP mice (Supplementary Fig. 6f). Collectively, these data suggest common modulation of the BLIMP1 axis by the T_reg cell-derived IL-10 and IL-35 for optimal induction of an exhaustion gene signature in intratumoral CD8⁺ T cells.

Direct regulation of BLIMP1 locus by T_reg cell-derived IL-10 and IL-35

BLIMP1 is a well-characterized regulator of terminal differentiation for both T and B cell lineages, and it has been reported to drive inhibitory receptor expression and exhaustion of CD8⁺ T cells in chronic viral infection³¹. However, its role in intratumoral T cell exhaustion and whether it links T_reg cell-derived cytokines with inhibitory receptor expression is unknown. Analysis of B16 tumor-bearing Prdm1^YFP reporter mice revealed that BLIMP1 expression was strongly correlated with PD-1^hi and multi-inhibitory receptor⁺ CD8⁺ TILs (Supplementary Fig. 7a-c) and BLIMP1 protein was significantly reduced in the TME that lacks T_reg cell-derived IL-10 or IL-35 (Supplementary Fig. 7d). Adoptively transferred OT-I.Prdm1^YFP transgenic CD8⁺ T cells failed to up-regulate high BLIMP1 expression in B16-OVA tumor-bearing Il10^L/L.Foxp3^Cre-YFP, Ebi3^L/L-Tom.Foxp3^Cre-YFP, and Il10^L/L.Ebi3^L/L-Tom.Foxp3^Cre-YFP mice compared to Foxp3^Cre-YFP counterparts, further corroborating the role of both T_reg cell-derived IL-10 and IL-35 to cooperatively promote the intratumoral multi-inhibitory receptor⁺ TIL state via BLIMP1 induction (Fig. 7a-c).

Figure 7: Direct and cooperative regulation of BLIMP1–inhibitory receptor axis in CD8⁺ TILs by IL-10 and IL-35.

a, Experimental design schematic of BLIMP1YFP (Prdm1^YFP)xOT1 adoptive transfer model.

b, Representative flow plots depicting expression of BLIMP1YFP on Prdm1^YFP.OT-I Thy1.1⁺ CD8⁺ T cells adoptively transferred into Foxp3^Cre-YFP (n=11), Il10^L/L.Foxp3^Cre-YFP (n=10), Ebi3^L/L-Tom.Foxp3^Cre-YFP (n=10), and Il10^L/L.Ebi3^L/L-Tom.Foxp3^Cre-YFP (n=6) mice B16-OVA tumors.

c, Stacked bar graph depicting BLIMP1 expression in the donor CD8⁺ T cells as in (b). Statistical significance was determined by Two-way ANOVA with Holm-Sidak multiple comparisons (****p<0.0001 and other p-values as indicated).

d, Representative flow and SPICE plots depicting the expression of inhibitory receptors (PD-1, TIM3, LAG3, TIGIT, and 2B4) on CD8⁺ TILs from B16-tumor-bearing E8I^Cre-GFP (n=9), Prdm1^L/+.E8I^Cre-GFP (n=12), and Prdm1^L/L.E8I^Cre-GFP (n=10)mice.

e, Representative histograms depicting expression levels of BLIMP1, IL-7R and TCF7 on CD8⁺ TILs from B16 tumor-bearing E8I^Cre-GFP (n=8), Prdm1^L/+.E8I^Cre-GFP (n=12), and Prdm1^L/L.E8I^Cre-GFP (n=6) mice (top). For PD1, E8I^Cre-GFP (n=12), Prdm1^L/+.E8I^Cre-GFP (n=12), and Prdm1^L/L.E8I^Cre-GFP (n=6) mice. Scatter plots tabulating the percent distributions (bottom). Statistical significance was determined by One-way ANOVA with Holm-Sidak multiple comparisons (****p<0.0001 and other p-values as indicated).

f, Tumor growth curve of E8I^Cre-GFP (n=20), Prdm1^L/+.E8I^Cre-GFP (n=15), and Prdm1^L/L.E8I^Cre-GFP (n=9) mice inoculated with 1.25×10⁵ cells of B16 tumors intradermally. Data averaged from 2 independent experiments. Statistical significance was determined by Two-way ANOVA with Holm-Sidak multiple comparisons (*p=0.0165, **p=0.0008, ***p=0.0002, ****p<0.0001).

g, Depiction of locus surrounding mouse Prdm1. The annotated STAT-binding sites were investigated here.

h ChIP analysis of IL-10-mediated STAT3 binding and IL-35-mediated STAT1/STAT4 binding to Prdm1 locus of CD8⁺ T cells activated for 48 hrs with anti-CD3, anti-CD28, and IL-2, followed by 4 days expansion with IL-2, resting in serum-free media for 2 hrs, then stimulation with IL-10 or IL-35 for 30 mins at 37°C. Chromatin was immunoprecipitated with anti-STAT1, anti-STAT3, anti-STAT4, or monoclonal rabbit IgG isotype control for real-time RT-PCR. Fold enrichment was calculated based on the isotype controls, which was then normalized to the no-cytokine stimulation (No-Stim) controls. Data averaged from 5 independent experiments. Bars represent mean values. Statistical significance was determined by Two-way ANOVA with Holm-Sidak multiple comparisons (p-values as indicated).

We next assessed inhibitory receptor expression in mice with a CD8⁺ T cell-restricted Prdm1 deletion (Prdm1^L/L.E8I^CreGFP) to validate whether BLIMP1 has a cell-intrinsic role in inhibitory receptor-regulation in tumors. Bi-allelic deletion of BLIMP1 in CD8⁺ T cells resulted in a substantial loss of multi-inhibitory receptor⁺ CD8⁺ TILs, mirroring our observations in T_reg cell-mutant mice, while heterozygous Prdm1^L/+.E8I^CreGFP mice exhibited a substantive but intermediate inhibitory receptor reduction (Fig. 7d, Supplementary Fig. 7e). Consistent with the T_reg cell cytokine-deficient mice, expression of memory-associated genes (IL-7R and TCF7) were also upregulated in Prdm1^L/L.E8I^CreGFP mice (Fig. 7e). It has been reported previously that bi-allelic deletion of BLIMP1 results in a loss of effector functions in CD8⁺ T cells in the context of chronic viral infection despite diminished inhibitory receptor expression³². Indeed, no loss of tumor growth was observed in Prdm1^L/L.E8I^CreGFP mice (Fig. 7f). Induced BLIMP1-haploinsufficiency³² or double-deletion of BLIMP1 and c-Maf³³ in CD8⁺ T cells was required to reinvigorate the cytotoxic effector function and memory-potential, as c-Maf is highly upregulated in the absence of BLIMP1 and is capable of regulating a largely overlapping network of genes, maintaining the exhausted phenotype³³. Consistent with these observations, heterozygous Prdm1^L/+.E8I^CreGFP mice exhibited improved B16 tumor control comparable to T_reg cell cytokine-deficient mice (Fig. 7f).

Lastly, ChIP-qPCR revealed that IL-10-induced STAT3^[34] and IL-35-induced STAT1 and STAT4^[26] were differentially enriched at STAT-binding sites within the Prdm1 gene locus (Fig. 7g-h), suggesting that IL-10 and IL-35 may act directly on CD8⁺ T cells to modulate the BLIMP1-inhibitory receptor axis. Overall, these data confirm an intrinsic role of BLIMP1 in regulating inhibitory receptor expression of T cells in tumors and validate BLIMP1 as a direct downstream target of both T_reg cell-derived cytokines, IL-10 and IL-35, in their cooperative promotion of multi-inhibitory receptor expression on TILs (Supplementary Fig. 7f).

Discussion

Collectively, our data support a model in which different subpopulations of intratumoral T_reg cells produce IL-10 and IL-35 while exhibiting adaptive plasticity in their cytokine production, which seems to favor single rather than double inhibitory cytokine-secreting states. Although these two inhibitory cytokines cooperatively regulate the BLIMP1-inhibitory receptor axis in CD4⁺ and CD8⁺ TILs and exhibit largely overlapping functions such as induction of an inhibitory receptor module (including PD-1, LAG3, TIM3, TIGIT, 2B4), IL-35 appears to play a greater role in inhibitory receptor induction and limiting T_CM differentiation whereas IL-10 plays a greater role in regulating cytokine production and effector function. Cooperatively, they have a substantive impact on anti-tumor immunity. Loss of T_reg cell-derived IL-10 and IL-35 also results in (i) significant downregulation of the exhaustion gene signature, (ii) upregulation of a memory-associated transcriptional profile, and (iii) development of a CXCR5⁺ signature in CD8⁺ TILs that is observed following PD-1 checkpoint blockade³⁰. These data suggest that IL-10- or IL-35-targeted immunotherapy may have a broader therapeutic impact than previously appreciated.

The physiological requirement for inducible, transitional, divergent intratumoral T_reg cell subpopulations that shift between IL-10 and IL-35 single inhibitory cytokine expressing states remains unclear. Adaptive plasticity in T_reg cell function has been reported in a number of inflammatory scenarios². While expression of Foxp3 and TCR signaling drive the core suppressive module^23,35,36, T_reg cells retain developmental plasticity to adapt to their microenvironment leading to their acquisition of additional suppressive modules characterized by expression of transcription factors, miRNAs, chemokine receptors and suppressive mediators. The current study exemplifies this plasticity in T_reg cell fates in the context of the tumor microenvironment, wherein priming in response to tumor antigens and/or the suppressive tumor milieu leads to the generation of IL-10⁺ and Ebi3⁺ T_reg cells for optimal tumor-induced immune suppression. Reciprocal IL-10 and IL-35 expression on T_reg cells has also been reported to play a role in the maintenance of immune tolerance¹⁹. In this context, differential TCR signal strength led to the generation of distinct effector IL-10⁺ and IL-35⁺ T_reg cell subsets that function in a complimentary fashion in the control of autoimmunity. In fact, such heterogeneity in inhibitory cytokine expression expands beyond the T_reg cell lineage and has also been noted for regulatory plasma cells. During Salmonella enterica Typhimurium infection, different subsets of CD138^hi plasma cells, depending upon their maturation level, expressed either IL-10 or IL-35, and very few co-transcribed Il10, Ebi3, and Il12a together³⁷. This functional segregation may represent a unifying theme of regulatory cell subsets for maximizing immunoregulation offering a “last-resort” to subvert beneficial anti-tumor or detrimental autoreactive T cell responses while limiting collateral tissue damage. While the mechanism that limits the accumulation of dual inhibitory cytokine expressing T_reg cell subpopulations will require further analysis, it is possible that IL-10 and IL-35 cooperatively limit T_reg cell development and expansion in a cell-intrinsic manner limiting the abundance of IL-35/IL-10-dual expressing T_reg cells.

Despite the differential inhibitory cytokine expression pattern, comprehensive profiling of IL-10⁺ and Ebi3⁺ T_reg cells did not reveal striking transcriptional and TCR differences between these sub-populations. These results differ from previous observations wherein differences were noted in transcription factor dependency, chemokine receptor expression, and activation status of IL-10⁺ and IL-35⁺ T_reg cells isolated from secondary lymphoid organs¹⁹. In this study, BLIMP1 expression marked the IL-10⁺ T_reg cell subset while IL-35⁺ T_reg cells were predominantly BLIMP1-independent. In contrast, we noted that over 90% of T_reg cells express BLIMP1 in B16 tumors, indicating that BLIMP1 may also play a role in regulating the development and function of IL-35⁺ T_reg cells as approximately 30–50% of these intratumoral T_reg cells express IL-35. It is conceivable that following priming in response to tumor antigens, the T_reg cell repertoire that migrates to the tumor is fixed in its core transcriptional identity, while still retaining plasticity in inhibitory cytokine expression. Interestingly, T_reg cell-restricted IL-35 depletion did not lead to a compensatory increase in IL-10⁺ T_reg cells. While we were unable to assess the effect of T_reg cell-restricted IL-10 loss on IL-35⁺ T_reg cells, it has been suggested that mice with BLIMP1-deficient T_reg cells (unable to produce IL-10) exhibited a 2-fold enrichment of IL-35⁺ T_reg cells¹⁹. Thus it is possible that if T_reg cell-restricted IL-10 deficiency led to a compensatory increase in IL-35⁺ T_reg cells in our B16 tumor model, that may explain multiple aspects: (i) the less dramatic loss of multi-inhibitory receptor-positive TILs in Il10^L/L.Foxp3^Cre-YFP as well as Rag1^−/− reconstitution studies with IL-10R^−/− CD8⁺ T cells, (ii) consistent and more dramatic loss of multi-inhibitory receptor⁺ TILs in Ebi3^L/L-Tom.Foxp3^Cre-YFP and Il10^L/L.Ebi3^L/L-Tom.Foxp3^Cre-YFP mice, respectively, and (iii) lack of synergy or additivity in B16 tumor control in Il10^L/L.Ebi3^L/L-Tom.Foxp3^Cre-YFP mice. This may in part also underlie the non-overlapping regulation of effector versus memory responses by the two cytokines, with relatively low BLIMP1 protein reduction in Il10^L/L.Foxp3^Cre-YFP mice compared to Ebi3^L/L-Tom.Foxp3^Cre-YFP and Il10^L/L.Ebi3^L/L-Tom.Foxp3^Cre-YFP mice, recapitulating BLIMP1 haploinsufficiency³² and translating to increased effector responses and decreased memory generation. Although BLIMP1 is well-established as a driver of inhibitory receptor expression, a recent report demonstrated that another transcription factor, c-MAF, sufficiently promoted inhibitory receptor expression in the absence of BLIMP1, by impacting overlapping transcriptional networks. However, our RNAseq dataset did not reveal significant modulation of Maf expression in CD8⁺ TILs from T_reg cell cytokine-deficient mice relative to Foxp3^Cre-YFP counterparts, highlighting specific modulation of the BLIMP1-axis by IL-35 and IL-10 in cooperative regulation of T cell exhaustion.

In summary, the adaptive plasticity and cooperative regulation of anti-tumor immunity by IL-10⁺ and IL-35⁺ T_reg cells pose another tumor-immune evasive strategy and potential resistance mechanism to immunotherapy. Understanding this complex T_reg cell-driven regulatory circuitry in the TME may inform the rational design of combinatorial modalities targeting T_reg cells and their downstream mediators that promote T cell exhaustion to maximize responsiveness to checkpoint blockade and other immunotherapies while limiting adverse events and the risk of inflammatory or autoimmune complications.

Data availability

Bulk RNAseq and single-cell RNAseq data will be deposited in the Gene Expression Omnibus (GEO), and the accession codes will be provided. The RNAseq data sets reported by other studies used to cross-examine with our sequencing data in this study were obtained from GSE9650 and GSE84105. The main data supporting the findings of this study are available within the article and its supplementary figures. Data are available from the corresponding authors upon appropriate and reasonable request.

Methods

Mice

Unless otherwise specified, all experimental procedures were performed on 5–8 week old laboratory mice housed in Helicobacter/MNV free SPF facilities at the University of Pittsburgh in accordance with the current National Institutes of Health guidelines and with the approval and guideline of the Institutional Animal Care and Use Committee (IACUC) of the University of Pittsburgh. Female mice were used for tumor growth and RNA sequencing experiments, while both male and female mice were used for tumor-infiltrating lymphocyte flow cytometry analysis.

Il10^GFP.Ebi3^Tom.Foxp3^Cre-YFP mice were generated by crossing Il10^GFP (Vert-X¹⁷; Jackson Laboratory) to Ebi3^Tom.Foxp3^Cre-YFP (developed in our laboratory⁷). Ebi3^L/L-Tom mice were developed in our laboratory and have been previously described⁷. Il10^L/L (provided by Werner Muller (Germany))³⁸ and Ebi3^L/L-Tom were crossed to Foxp3^Cre-YFP mice¹⁸ to generate T_reg cell-specific cytokine deletion strains. Prdm1^YFP and Prdm1^L/L strains were provided by Amanda Poholek at University of Pittsburgh. E8I^Cre mice (provided by Dan R. Littman, New York University; previously described³⁹) and OT-I transgenic mice (obtained from Jackson Laboratory) were crossed to Prdm1^L/L and Prdm1^YFP strains, respectively, to generate E8I^Cre.Prdm1^L/L and Prdm1^YFP.OT-I mice. Rag1^−/− and IL-10R^−/− (Il10rb^−/−) mice were purchased from Jackson Laboratory. IL-35R^−/− (CD4^Cre.Il6st^L/L.IL12rb2^−/−) mice were generated as described previously²⁶.

Human specimen collection and processing

All specimens were acquired under University of Pittsburgh approved Institutional Review Board (IRB) protocol, and informed consent was obtained from all patients. All lung tumors were processed to single-cell suspension by a combination of mechanical and enzymatic digestion. For enzymatic digestion, Liberase (Sigma Aldrich) was used at 50 μg/mL for 15 minutes at 37°C in RPMI medium (Lonza) to release tumor infiltrating lymphocytes (TIL). For healthy donor peripheral blood samples, Ficoll Paque Plus (GE Healthcare) was used to separate peripheral blood leukocytes (PBL) and lysis buffer (BD Biosciences) was used to remove red blood cells when necessary.

Staining for EBI3 and IL-10 in human specimens

Lung TIL and HD PBL were incubated in complete RPMI (cRPMI) medium (10% FBS (Atlanta Biologicals), non-essential amino acids (Sigma Aldrich), L-glutamine (Lonza) and penicillin/streptomycin (Corning) and sodium pyruvate (Sigma Aldrich)) with TCR stimulation: plate-bound anti-CD3 (0.5 μg/mL, Invitrogen, clone: OKT3) and soluble anti-CD28 (1 μg/mL Invitrogen, clone: CD28.2) and 200U/ml rhIL-2 overnight followed by four hours of stimulation with PMA/ionomycin and GolgiStop. The cells were then harvested and stained with viability dye and fluorochrome-conjugate antibodies. For intracellular staining, fixation/permeabilization kit (eBiosciences) was used according to manufacturer’s protocol.

Cell lines and tumor processing

B16-F10 cells (referred to as B16) and EL4 cells were purchased from ATCC (Manassas, Virginia) and cultured in cRPMI. BrafPten (clone24) and B16-OVA cells were kindly provided by Greg Delgoffe (University of Pittsburgh) and cultured in cDMEM (Lonza) and G418-supplemented cRPMI (1mg/mL), respectively. BrafPten (clone 24) was originally generated by A.V. Menk and G.M. Delgoffe by cloning a cell line from a tumor harvested from BRaf^CA.Pten^L/L.Tyr^CreERT2 mice induced with 4-OHT administration.

Mice received an intradermal inoculation (i.d.) of tumor cells (1.25×10⁵) on day 0. Tumors were measured every 3 days in two dimensions using a digital caliper and expressed as tumor volume (mm³; defined as the Square of Smaller diameter x Larger diameter/2).

Tumors were excised on day 14 or d20 for end-point experimental analyses. Excised solid tumors were minced into small pieces and digested with Collagenase type IV (200 U/mL) and Dispase (1 U/mL) in cDMEM for 30 minutes at 37°C. Digested cell suspension was then processed through 70 μm cell-strainer and washed with cDMEM. Isolated cells were then used in various assays. Red blood cells were lysed with Gey’s solution when appropriate.

Fungal protease-induced allergic airway disease

Mice received 7 intranasal challenges with a mixture comprised of a fungal protease derived from Aspergillus oryzae and Ovalbumin, every alternate day for two weeks. On day 14, mice were intubated, tracheas were cannulated and flushed with PBS (twice) for isolation of broncho-alveolar lavage (BAL) fluid, prior to isolation of lungs and the draining (mediastinal) and non-draining (inguinal) lymph nodes. Lungs were perfused with 10 mL PBS injected through the right ventricle of the heart using a 20 gauge needle immediately after BAL fluid collection. Harvested lungs were minced into small pieces and digested in 5 mL capped polystyrene tube with 1 mg/mL Collagenase D (Roche) in 2 mL PBS for 45 minutes at 37°C. Digested cell suspension was then processed through 70 μm cell-strainer and washed with cDMEM. Isolated cells were then used in flow cytometry analysis. Red blood cells were lysed with Gey’s solution when appropriate.

Flow cytometry

Single-cell suspensions from mouse or human specimens were stained with live/dead exclusion dye, followed by fluorochrome-conjugated antibodies in the presence of 5% normal mouse serum. TruNuclear transcription factor staining kit (Biolegend) was used for intracellular staining. Flow cytometry data were acquired on BD Fortessa and analyzed by FlowJo (Treestar, Inc.). Pie charts were created using the SPICE program⁴⁰.

Processing and analysis of scRNAseq data

We used Cell Ranger (v2.0) (10X Genomics) to analyze sequencing data generated from Chromium Single Cell 3’ RNA-seq libraries⁴¹. We first ran “cellranger mkfastq” on the Illumina BCL output folder to generate fastq files. We next generated the UMI count matrix with “cellranger count” for each library. The data were normalized with R package cellrangerRkit and visualized via t-distributed stochastic neighbor embedding (t-SNE). The diffusion pseudo-time analysis was run with R package Destiny^42,43. Briefly, we built a transition matrix for all cells based on their adjacency using a locally-scaled Gaussian kernel and determined the diffusion components according to the eigenvectors of the matrix. Then, a new matrix M was generated by removing the first eigenvalue of the original transition matrix and the diffusion pseudo-time was calculated as a distance metric between the rows of M. Lastly, we plotted the trajectory lines, which were fitted by the locally weighted scatterplot smoothing (LOESS) regression using the previously calculated values. For the differential expression analyses between the IL-10 and Ebi3 gene-expressing cells in LN and Tumor T_reg cells, we used the “sseq” method from the standard R package CellrangerRkit. Additionally, top expressed genes from differential expression analysis were determined by performing the two-sided Negative Binomial Exact test⁴⁴ and the p-values were adjusted to control the false discovery rate (FDR)⁴⁵.

RNASeq profiling and data analysis

T_reg cell fractions and NDLN Foxp3YFP CD4⁺ T_eff control were FACS sorted from day 14 B16 tumor-bearing Il10^GFP.Ebi3^Tom.Foxp3^Cre-YFP mice. CD8⁺ T cell subsets were FACS sorted from day 14 B16-bearing WT control and T_reg cell cytokine-deficient mice.

Each cell fraction was double-sorted to ensure high purity (>95%) and directly lysed using the Clontech SMART-Seq v4 (T_reg cells) or v3 (CD8) kit for cDNA synthesis. Libraries were prepared using Nextera XT DNA Library Preparation kit (Illumina), normalized at 2nM using Tris-HCl (10mM, pH 8.5) with 0.1% Tween20, diluted and denatured to a final concentration of 1.8nM. Cluster generation and 75bp paired-end dual-indexed sequencing were performed on Illumina NextSeq 500 system.

RNASeq data were aligned to the mm10 genome using the STAR aligner⁴⁶ and quantified against the Refseq gene models⁴⁷ using featureCounts⁴⁸. The number of uniquely aligned reads ranged from 10 to 12 million. The raw data counts were processed for differential expression using the “voom” function⁴⁹ in the limma R package^50,51 with the robust model option. Gene set enrichment testing was performed using the “Rank Sum Test With Correlation” function in the limma R package, which automatically corrects enrichment statistic inflation due to correlation among genes. We used the GSEA-style enrichment score for visualization of pathway enrichment results⁵².

We defined the tumor-specific exhaustion signature to be the set of genes that are overexpressed in the PD-1^hi state (both DP and SP) when compared to PD-1^neg state in Foxp3^Cre-YFP mice at fold change of 4 and q-value FDR of 0.05. Tumor exhaustion signature was aligned with the chronic LCMV exhaustion profile dataset (GEO accession number: GSE9650)²⁸. The CXCR5⁺ PD-1-responsive CD8⁺ T cell signature was derived from GEO accession number: GSE84105^[30].

Code availability

Computational and mathematical codes utilized in the RNAseq analyses supporting the findings of this study are available within the article. Additional information is available from corresponding author upon reasonable and appropriate request.

In vitro micro-suppression assay

Sorted T_reg cell subpopulations from NDLN and B16 tumors were co-cultured with CellTrace Violet (Life Technologies)-labeled CD4⁺Foxp3⁻ responder T cells (T_responders) in the presence of mitomycin-C-treated TCRβ-depleted splenocytes and anti-CD3ε (1 μg/mL) for 72 hrs at 37°C as previously described⁷.

TCRseq and data analysis

T_reg cell fractions and IL-10⁻Ebi3⁻Foxp3YFP⁻ CD4⁺ T_eff control were purified by FACS from day 14 B16-bearing Il10^GFP.Ebi3^Tom.Foxp3^Cre-YFP mice. DNA was purified using QIAamp DNA Micro Kit (QIAGEN), and TCRbeta-enriched library was generated with TCRbeta immunoSeq (Adaptive Biotechnologies), following the manufacturer’s protocol. Cluster generation and sequencing were performed on Illumina high output NextSeq 500 system. The data were analyzed using immunoSeq Analyzer (Adaptive Biotechnologies).

Adoptive transfer experiments

BLIMP1YFP.OT-1 transfer experiment: Recipient mice received intravenous injections of 0.5×10⁶ BLIMP1YFP CD8⁺ T cells isolated by negative selection from spleen and lymph nodes of Prdm1^YFP.OT-I.Thy1.1 mice, followed by i.d. injection of 2.5×10⁵ B16-OVA cells two days following adoptive transfer. Tumors and NDLN were harvested at day 14 post-tumor inoculation for assessment of BLIMP1YFP induction.

Rag1 KO reconstitution experiment: Rag1 KO recipient mice received intravenous injections of CD8-depleted splenocytes isolated from Foxp3^Cre-YFP.Thy1.1 mice containing 1×10⁶ T_reg cells day −8, followed by injection of 6×10⁶ WT, IL-10R.KO, or IL-35R KO.CD8⁺ T cells on day −1 and i.d. B16 tumor inoculation (1.25×10⁵ cells/mouse) on day 0. Tumor size was measured every 3 days until day 18 post-tumor inoculation. Tumors were harvested on day 14 or day 18 for end-point experimental analysis.

ChIP-qPCR

Naive CD8⁺ T cells were purified and activated for 2 days with plate-bound anti-CD3 (3 μg/mL) and anti-CD28 (5 μg/mL) supplemented with 50 U/mL hIL2, followed by expansion for 4 days in hIL2-containing cRPMI. Following serum-deprivation for 3 hours, cells were pulsed with recombinant IL-10 or IL-35 for 30 mins prior to fixation with 1% formaldehyde. 15×10⁶ cells per sample were sonicated with Bioruptor Pico in shearing buffer. ChIP was performed overnight for STAT1 (D1K9Y), STAT3 (124H6), STAT4 (C46B10), and IgG (Cell Signaling Technology) using Protein A Dynabeads (Thermo Fisher). EvaGreen-based qPCR was performed using primers previously described³⁴.

Statistical analysis

Except for RNAseq and scRNAseq data analysis, GraphPad Prism software was used to determine the statistical significance. Group means were compared with two-tailed Student’s t-test when only two experimental groups were involved. Tumor growth was analyzed using Two-way ANOVA with multiple comparisons correction with sequential time point measurements. For other analysis, One-way or Two-way ANOVA with multiple comparison correction. All p-values were two-sided, and statistical significance assessed at or below 0.05.

Reporting summary

Additional experimental design detail of this study is available in the Life Sciences Reporting Summary linked to this article.