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Research Article

Reprogramming responsiveness to checkpoint blockade in dysfunctional CD8 T cells

Christine E. Nelson, Lauren J. Mills, Jennifer L. McCurtain, Emily A. Thompson, Davis M. Seelig, Siddheshvar Bhela, Clare F. Quarnstrom, View ORCID ProfileBrian T. Fife, and Vaiva Vezys
PNAS February 12, 2019 116 (7) 2640-2645; first published January 24, 2019; https://doi.org/10.1073/pnas.1810326116
Christine E. Nelson
aDepartment of Microbiology and Immunology, University of Minnesota, Minneapolis, MN 55455;
bCenter for Immunology, University of Minnesota, Minneapolis, MN 55455;
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Lauren J. Mills
cMinnesota Supercomputing Institute, University of Minnesota, Minneapolis, MN 55455;
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Jennifer L. McCurtain
aDepartment of Microbiology and Immunology, University of Minnesota, Minneapolis, MN 55455;
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Emily A. Thompson
aDepartment of Microbiology and Immunology, University of Minnesota, Minneapolis, MN 55455;
bCenter for Immunology, University of Minnesota, Minneapolis, MN 55455;
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Davis M. Seelig
dDepartment of Veterinary Clinical Sciences, University of Minnesota, St. Paul, MN 55118;
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Siddheshvar Bhela
aDepartment of Microbiology and Immunology, University of Minnesota, Minneapolis, MN 55455;
bCenter for Immunology, University of Minnesota, Minneapolis, MN 55455;
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Clare F. Quarnstrom
aDepartment of Microbiology and Immunology, University of Minnesota, Minneapolis, MN 55455;
bCenter for Immunology, University of Minnesota, Minneapolis, MN 55455;
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Brian T. Fife
bCenter for Immunology, University of Minnesota, Minneapolis, MN 55455;
eDepartment of Medicine, University of Minnesota, Minneapolis, MN 55455
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  • ORCID record for Brian T. Fife
Vaiva Vezys
aDepartment of Microbiology and Immunology, University of Minnesota, Minneapolis, MN 55455;
bCenter for Immunology, University of Minnesota, Minneapolis, MN 55455;
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  • For correspondence: vvezys@umn.edu
  1. Edited by Rafi Ahmed, Emory University, Atlanta, GA, and approved December 20, 2018 (received for review June 14, 2018)

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Significance

Cancer immunotherapies, such as immune checkpoint blockade, work by stimulating immune cells to kill tumors. Unfortunately, not all patients respond to checkpoint treatment, which also causes autoimmune side effects due to self-reactive immune cell activation. This study uncovers immune subtypes that respond best to this immunotherapy and reveals methods to reinvigorate dysfunctional antitumor immune responses. We show that self-reactive CD8 T cells can be pathogenic or nonresponsive to checkpoint blockade therapy depending on their activation status. In addition, tolerant self-reactive CD8 T cells bear striking similarity to dysfunctional tumor-specific CD8 T cells. Finally, we demonstrate that previously tolerant self-specific CD8 T cells can eliminate aggressive tumors bearing self-antigens without concomitant autoimmunity after robust antigenic vaccination in concert with PD-L1 blockade.

Abstract

Established T cell dysfunction is a barrier to antitumor responses, and checkpoint blockade presumably reverses this. Many patients fail to respond to treatment and/or develop autoimmune adverse events. The underlying reason for T cell responsiveness remains elusive. Here, we show that susceptibility to checkpoint blockade is dependent on the activation status of T cells. Newly activated self-specific CD8 T cells respond to checkpoint blockade and cause autoimmunity, which is mitigated by inhibiting the mechanistic target of rapamycin. However, once tolerance is established, self-specific CD8 T cells display a gene signature comparable to tumor-specific CD8 T cells in a fixed state of dysfunction. Tolerant self-specific CD8 T cells do not respond to single or combinatorial dosing of anti-CTLA4, anti–PD-L1, anti–PD-1, anti–LAG-3, and/or anti–TIM-3. Despite this, T cell responsiveness can be induced by vaccination with cognate antigen, which alters the previously fixed transcriptional signature and increases antigen-sensing machinery. Antigenic reeducation of tolerant T cells synergizes with checkpoint blockade to generate functional CD8 T cells, which eliminate tumors without concomitant autoimmunity and are transcriptionally distinct from classic effector T cells. These data demonstrate that responses to checkpoint blockade are dependent on the activation state of a T cell and show that checkpoint blockade-insensitive CD8 T cells can be induced to respond to checkpoint blockade with robust antigenic stimulation to participate in tumor control.

  • CD8 T cells
  • tolerance
  • checkpoint
  • tumor
  • dysfunction

Self-specific CD8 T cells that escape negative selection undergo peripheral tolerance to prevent autoimmunity. Peripheral tolerance can induce a state of T cell hyporesponsiveness (1). Tolerant self-specific T cells up-regulate inhibitory receptors such as PD-1 (2). The importance of inhibitory receptors is highlighted by autoimmune pathology resulting from genetic manipulation or antibody blockade of inhibitory receptor interactions (3⇓⇓–6).

These inhibitory pathways are critical for T cell tolerance to self and are important in T cell dysfunction during cancer and chronic infections (7⇓⇓⇓⇓–12). Checkpoint blockade is an immunotherapy using antibodies blocking inhibitory pathways to stimulate antitumor immunity. This therapy has been approved for the treatment of many cancers; however, it also induces autoimmune adverse events and only one-third of patients benefit from this therapy (7, 13⇓–15). Only tumors with high mutation rates are thought to be amenable to checkpoint blockade (16⇓⇓⇓–20). This suggests that there are subsets of T cells that do, and do not, respond to inhibitory receptor blockade. Identification of such subsets would aid efforts to minimize autoimmune side effects and maximize clinical efficacy of checkpoint blockade.

Our previous work temporally divided the self-specific CD8 T cell response into two populations: recently activated T cells that respond to PD-L1 blockade, and tolerized or anergic cells that do not respond (21). This parallels the dysfunction seen during the differentiation of tumor-specific CD8 T cells (22, 23). These data suggested that susceptibility to checkpoint blockade within the self- and tumor-specific repertoire is linked to a T cell’s activation state and recent proliferation (24, 25). We hypothesized that if tolerized CD8 T cells could be induced to proliferate, this would renew checkpoint blockade responsiveness. Here, we show that newly primed self-specific T cells respond to anti-CTLA4 treatment, leading to organ-specific pathology. In contrast, tolerized self-specific T cells are refractory to all combinations of checkpoint blockade. Their transcriptional profile overlaps with tumor-specific CD8 T cells exhibiting a fixed dysfunctional state. However, robust restimulation with self-antigen induced phenotypic and genotypic changes, resulting in proliferation of self-specific CD8 T cells. This antigenic reeducation and reprogramming of tolerant T cells renewed susceptibility to PD-L1 blockade, leading to control of melanoma without concomitant autoimmunity. Ultimately, we show that dysfunctional CD8 T cells can be made amenable to checkpoint blockade with proper antigen stimulation to aid in the treatment of cancer.

Results

Recently Activated Self-Specific CD8 T Cells Respond to Checkpoint Blockade and Cause Pathology.

Using iFABP-Ova mice producing ovalbumin (Ova) in the small intestine, we have previously shown that transfer of naïve T cell receptor (TCR) transgenic Ova-specific OTI CD8 T cells results in activation, proliferation, and migration of OTI cells to many organs (21, 26⇓–28). Without additional stimulation, OTI cells become tolerized and are maintained long-term (21). Using this model, we tested whether anti-CTLA4 given at the time of cell transfer inhibits tolerance. With treatment, there is enhanced cytokine production and accumulation of OTI cells (Fig. 1 A and B) (21). When anti-CTLA4 or anti–PD-L1 is given at the time of OTI cell transfer, weight loss and intestinal pathology occur (SI Appendix, Fig. S1) (27, 28).

Fig. 1.
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Fig. 1.

Checkpoint blockade interferes with CD8 T cell tolerance induction but not does alter established T cell tolerance. (A–C) OTI cells were transferred to iFABP-Ova mice, which were untreated (−) or treated (+) with anti-CTLA4 (αCTLA4) starting at day of cell transfer or after 30 d. (A) Mice were given anti-CTLA4 starting at the day of OTI cell transfer. Enumeration of OTI cells 5 d after transfer in the small intestine intraepithelial lymphocyte compartment (IEL), mesenteric lymph node (mLN), or spleen (SPL). Open circles, untreated; filled circles, +anti-CTLA4. (B) Cytokine production from animals in A. Gated on OTI cells from treated (Right) and untreated (Left). (C) Mice were or were not given anti-CTLA4 starting at >day 30 after OTI cell transfer. Enumeration of OTI cells 14 d after start of treatment. Open circles, untreated; filled circles, +anti-CTLA4. (D) Expression of inhibitory receptors on OTI IEL in untreated mice >day 30 after OTI cell transfer. Gray filled, non-OTI cells; black outline, OTI cells. (E and F) RNA sequencing data from naïve CD44− OTI splenocytes, OTI cells from IEL of B6 mice 7 d after VSV-Ova infection (effector), OTI cells from IEL of B6 mice 30 d after VSV-Ova infection (memory), or tolerant OTI cells from IEL of iFABP-Ova mice 30 d after adoptive transfer (tolerant). (E) Principal component (PC) analysis of RNA sequencing data. (F, Left) Tolerance gene cluster derived from scaled transcripts per million (TPM) values and k-means clustering based on differentially expressed genes in tolerant OTI compared with the other groups. Average scaled TPM value (point) and SD (error bars). The cluster contains 928 genes. (F, Right) Gene set enrichment analysis (GSEA) of the tolerance gene cluster as it relates to the tolerant states 1 and 2, as described in ref. 23 for tumor-specific CD8 T cells. State 1 is plastic and state 2 is fixed. Of the 928 genes in our tolerance gene set, there were 743 shared genes with the dataset. Our tolerance gene set was enriched for genes most highly enriched in state 2. The enrichment score was −0.623406, with a normalized enrichment score of −2.009594 and a false discovery rate Q value of 0.0. Significance for A and C was calculated with a Mann–Whitney U test. Representative of two to four experiments with n = 2 to 5 per group. ***P ≤ 0.0008, **P ≤ 0.0097, *P ≤ 0.0373. ns, nonsignificant.

The mechanistic target of rapamycin pathway inhibitor, rapamycin, decreases TCR signal strength, limiting T cell differentiation (29, 30). We hypothesized that rapamycin would affect pathology caused by checkpoint blockade. Rapamycin mitigated PD-L1 blockade-induced weight loss and reduced OTI cell numbers, but not CCR9 or α4β7 expression (SI Appendix, Fig. S1) (29, 31, 32). We propose that rapamycin alleviates pathology through inhibition of metabolism important for T cell effector functions.

Tolerant Self-Specific CD8 T Cells Do Not Respond to Simultaneous Blockade of Multiple Inhibitory Pathways and Resemble Dysfunctional Tumor-Specific CD8 T Cells.

Our data are consistent with reports showing that the CTLA4 and PD-1 pathways are important for the induction of tolerance (3⇓⇓–6). However, this does not mean that these pathways are necessary to maintain tolerance after it is established. The maintenance of tolerance is temporally distinct from tolerance induction and likely results in T cells at discrete phases of differentiation. In fact, checkpoint blockade is unable to rescue anergic human CD8 T cells in vitro (33). However, it can be difficult to interrogate requirements for the maintenance phase of T cell tolerance in vivo, because tolerance often results in deletion of T cells or loss of T cell tolerance over time, or the timing of antigen encounter is unknown (34). In our model, antigen encounter is synchronized and OTI cells are maintained indefinitely (21). This allowed us to monitor antigen-specific T cells over time and eliminates the impact of recent thymic emigrants.

We have previously demonstrated that after 30 d in iFABP-Ova mice, OTI cells are tolerant and refractory to anti–PD-L1 (21). Here, we tested whether this is also true for anti-CTLA4. When mice with tolerant OTI cells were given anti-CTLA4, we found no difference in the number of OTI cells in treated or untreated mice (Fig. 1C). This was not due to lack of inhibitory molecule expression, because levels of CTLA4, PD-1, LAG-3, and TIM-3 were high (Fig. 1D). RNA sequencing data confirm that tolerant CD8 T cells are a distinct subset and up-regulate many more inhibitory receptors (Fig. 1E and SI Appendix, Fig. S2).

We identified gene clusters defining naïve, effector, memory, and tolerant CD8 T cells, as well as clusters that were coexpressed by tolerant and naïve or by tolerant and effector subsets (Fig. 1F and SI Appendix, Fig. S2). Tolerant T cells up-regulated genes in the tolerance gene cluster and down-regulated genes in the memory gene cluster (SI Appendix, Fig. S2 and Table S1). The tolerance gene cluster is highly enriched for genes in published datasets that are associated with dysfunctional tumor-specific CD8 T cells (Fig. 1F) (23). Philip et al. (23) described this transcriptional profile as a state of fixed T cell dysfunction. Indeed, tolerant OTI cells had high expression of CD30L and low CD5. Tolerant T cells also expressed genes associated with long-term survival, like bcl-2, but down-regulated genes associated with functionality: TNF-α, IFN-γ, and CD28 (SI Appendix, Fig. S2). These data indicate that tolerant self-specific CD8 T cells are very similar to dysfunctional tumor-specific CD8 T cells.

It remained possible that inhibitory receptors compensated for one another during tolerance maintenance and that simultaneous blockade of multiple inhibitory pathways would result in activation. In fact, anti-CTLA4 and anti–PD-1 are combined clinically, resulting in increased antitumor efficacy, as well as autoimmune side effects (7, 35, 36). Mice with tolerant OTI cells were given both anti–PD-L1 and anti-CTLA4 antibodies. Tolerant OTI cells did not expand or increase cytokine production in response to dual treatment (Fig. 2 A and B and SI Appendix, Fig. S3). Inclusion of additional antibodies targeting LAG-3, TIM-3, and PD-1 did not result in activation of tolerant OTI cells, nor did it rescue IFN-γ production (Fig. 2C and SI Appendix, Fig. S3). This is likely due to the maintenance of the genetic signature associated with tolerance after treatment with checkpoint blockade (Fig. 2D and SI Appendix, Fig. S3 and Table S2). There were no differentially expressed genes between the tolerant and anti–PD-L1 treated cells (Fig. 2D). This is in line with tolerant self-specific CD8 T cells expressing a genetic signature similar to what has been defined as a fixed state of dysfunction for tumor-specific CD8 T cells (Fig. 1F) (23). These data suggest that tolerant self-specific CD8 T cells have an intrinsic block to activation with checkpoint blockade because of a stable genetic signature of tolerance/dysfunction.

Fig. 2.
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Fig. 2.

Combinations of inhibitory pathway blockade do not reverse established CD8 T cell dysfunction. OTI cells were transferred to iFABP-Ova mice and on >day 30 posttransfer, mice were untreated or given antibodies. Animals were killed at day 14 posttreatment. (A) Enumeration of OTI cells in untreated (open circles), anti-CTLA4–treated (filled circles), anti–PD-L1–treated (filled squares), or dual-treated (filled diamonds) mice. (B) IFN-γ production by OTI cells from A. Histograms gated on OTI cells. (C) Enumeration of OTI cells in untreated mice or mice treated with the indicated antibodies. (D) Differentially expressed genes from the indicated comparisons of RNA sequencing data. Log2 fold change of 1.5, up or down, with an adjusted P value of <0.05 were considered. The number of genes up- or down-regulated in “tolerant vs. αPD-L1” is 0. Representative of two to three experiments; n = 2 to 5 per group. Significance for A and C was calculated with a one-way ANOVA with a Kruskal–Wallis test; ns, nonsignificant (P > 0.05).

Exposure to Robust Antigenic Stimulation Reverses Tolerance in Self-Specific CD8 T Cells.

Tolerized self-specific CD8 T cells do not respond to checkpoint blockade and, therefore, do not rely on inhibitory receptor signaling for the maintenance of tolerance. However, previous work suggested that tolerance is not always a fixed state (24, 25, 37). Our data suggest that tolerant T cells maintain some of the genetic signatures of effector cells and actively down-regulate molecules associated with antigen sensing (SI Appendix, Fig. S2 and Table S1). We hypothesized that we could reprogram tolerant CD8 T cells to respond to activation via exposure to self-antigen in the context of infection. When iFABP-Ova mice with dysfunctional OTI cells were infected with vesicular stomatitis virus (VSV)-Ova, we saw increased numbers of OTI cells in all tissues (Fig. 3A and SI Appendix, Fig. S4). Reducing the number of OTI cells to better approximate endogenous numbers of antigen-specific CD8 T cells resulted in the same observations: PD-L1 blockade did not affect tolerant CD8 T cells, and VSV-Ova infection can induce cell proliferation (SI Appendix, Fig. S4F). Expansion was accompanied by an increase in Ki67 (Fig. 3C and SI Appendix, Fig. S4). Ex-tolerant OTI cells overcame their fixed dysfunctional state and were transcriptionally distinct after VSV-Ova infection (Fig. 3 B and D and SI Appendix, Fig. S4 and Table S3). Inclusion of Ova antigen in the vector was required for tolerance reversal; OTI cell proliferation was not seen with wild-type VSV (SI Appendix, Fig. S4).

Fig. 3.
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Fig. 3.

Robust stimulation with cognate antigen induces proliferation in dysfunctional CD8 T cells. OTI cells were transferred to iFABP-Ova mice, which were or were not infected with VSV-Ova at >day 30 posttransfer. (A) Expansion of OTI cells at day 7 after VSV-Ova infection. Gated on CD8 T cells. (B) Principal component (PC) analysis of RNA sequencing data of OTI IEL from control B6 7 d (effector) or 35 d (memory) after VSV-Ova infection, or from iFABP-Ova mice that received OTI cells 35 d prior and were left untreated (tolerant) or given VSV-Ova and analyzed day 7 after infection (ex-tolerant). (C, Top) Expression of Ki67, PD-1, and CTLA4 on OTI IEL at day 4 or 7 after VSV-Ova infection. Gated on OTI or non-OTI CD8+ IEL. Gray filled, non-OTI CD8+ cells; dotted outline, tolerant OTI cells; black outline, OTI cells + VSV-Ova infection. (C, Bottom) Granzyme B and IFN-γ production by OTI cells at day 7 after VSV-Ova infection. Gated on OTI or non-OTI IEL. For granzyme B histogram: gray filled, non-OTI CD8+ cells; dotted outline, tolerant OTI cells; black outline, OTI cells + VSV-Ova infection. For IFN-γ histogram: dark gray filled, control B6 d 7 VSV-Ova effector CD8+ cells; light gray filled, OTI IEL with no peptide stimulation; dotted outline, tolerant OTI cells; black outline, OTI cells + VSV-Ova infection. (D) Heat map of scaled transcripts per million for the tolerant cluster for the indicated groups. (E) Expression of TCR-associated cell surface molecules on OTI IEL at day 7 after VSV-Ova infection. Gray filled, non-OTI IEL; dotted outline, tolerant OTI cells; black outline, +VSV-Ova infection, ex-tolerant. Representative of at least four experiments with n = 2 to 5 per group.

Despite robust proliferation and vast transcriptional changes after VSV-Ova infection, there was no change in granzyme B or IFN-γ production (Fig. 3C). Ex-tolerant OTI cells down-regulated CD103 expression at the protein and transcript level, consistent with T cell proliferation (SI Appendix, Fig. S4) (38). Increased expression of CD28, CD3, and TCR was seen in ex-tolerant OTI cells (Fig. 3E and SI Appendix, Fig. S4). Importantly, ex-tolerant T cells significantly down-regulated gene signatures associated with tolerance and fixed T cell dysfunction (Fig. 3D and SI Appendix, Fig. S4 and Table S3). The DNA methyltransferase Dnmt3b is up-regulated in ex-tolerant OTI cells, suggesting active de novo DNA methylation and epigenetic reprogramming (SI Appendix, Fig. S4). Certain molecules, like CD101 and CD30L, thought to be associated with cells refractory to rescue, are down-regulated with VSV-Ova infection (23). Finally, ex-tolerant OTI cells increased PD-1 and CTLA4, indicative of antigen-induced proliferation (Fig. 3C and SI Appendix, Fig. S4). Together, our data show that ex-tolerant self-specific CD8 T cells proliferate, have enhanced antigen-sensing capabilities, increase inhibitory receptor expression, and display a distinct transcriptional profile, suggesting that they would now be amenable to checkpoint blockade treatment.

Robust Antigenic Stimulation of Tolerant CD8 T Cells Renews Susceptibility to Checkpoint Blockade and Augments Antitumor Responses.

We hypothesized that ex-tolerant OTI cells would have renewed responsiveness to checkpoint blockade. iFABP-Ova mice with tolerant OTI cells received either VSV-Ova, anti–PD-L1, anti-CTLA4, or a combination of VSV-Ova infection and checkpoint blockade. Responsiveness to anti–PD-L1 was rescued when robust antigenic stimulation was given in combination with checkpoint blockade (Fig. 4A). Greater numbers of OTI cells were induced with VSV-Ova infection and anti–PD-L1 than with either treatment alone (Fig. 4A). Combination treatment rescued IFN-γ production (Fig. 4B and SI Appendix, Fig. S5). IFN-γ production by ex-tolerant OTI T cells was not necessary to induce OTI cell proliferation (SI Appendix, Fig. S5). While synergistic effects of antigenic stimulation and blockade were seen with anti–PD-L1 treatment, synergy was not observed with anti-CTLA4 (Fig. 4A and SI Appendix, Fig. S5).

Fig. 4.
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Fig. 4.

Antigenic stimulation induces responsiveness to PD-L1 blockade in tolerant CD8 T cells, leading to tumor control. OTI cells were transferred to iFABP-Ova mice and on >day 30 post-OTI cell transfer, mice were left untreated, were treated with either anti–PD-L1 or anti-CTLA4, were infected with VSV-Ova, or were given a combination of anti–PD-L1 or anti-CTLA4 and VSV-Ova infection. (A) Enumeration of OTI cells at day 7. (B) IFN-γ production in OTI cells at day 7. Dark gray filled, control OTI cells from B6 d 7 VSV-Ova effector CD8+; light gray filled, OTI cells with no peptide stimulation; red outline, iFABP-Ova + VSV-Ova infection OTI cells; blue outline, iFABP-Ova + VSV-Ova infection + anti–PD-L1 OTI cells. (C) Principal component (PC) analysis of RNA sequencing data. (D and E) Mice were challenged with B16-Ova either prophylactically or therapeutically. Black line, OTI cells only (tolerant); green line, +anti–PD-L1; red line, +VSV-Ova infection; blue line, +VSV-Ova infection + anti–PD-L1. (D) On >day 30 in mice with tolerant OTI cells only or 2 d after indicated treatment, B16-Ova cells were injected. Statistical analysis OTI cells only (tolerant) vs. VSV-Ova infection + anti–PD-L1. (D, Bottom) Weight loss from baseline at day 0 in indicated groups. (E) Mice were inoculated with B16-Ova cells at >day 30 in mice with tolerant OTI cells. When tumors were palpable (∼day 7 to 10), the indicated treatment occurred. Statistical analyses: tolerant untreated (black line) vs. VSV-Ova + anti–PD-L1 (blue line). Significance for A was calculated with a one-way ANOVA using the Holm–Sidak multiple comparison test. Significance for D was calculated with a Mantel–Cox test comparing treatments to tolerant control (Top); a 2-way ANOVA using a Tukey’s multiple comparison test (Middle); and a two-way ANOVA using Dunnett’s multiple comparison test comparing treatments to tolerant control (Bottom). Significance for E was calculated with a two-way ANOVA using Dunnett’s multiple comparison test, comparing each treatment group to untreated controls (Left) and a Mantel–Cox test comparing treatment group to untreated controls (Right). Representative of two to four experiments with n = 2 to 5 per group. ***P ≤ 0.0001, **P ≤ 0.01 to >0.0001, *P < 0.05 to >0.01. ns, nonsignificant.

The pattern of gene expression with combined VSV-Ova infection and anti–PD-L1 treatment (rescued) was similar to that observed with VSV-Ova infection alone (ex-tolerant), suggesting a reversal of the fixed state of tolerance (Fig. 4C and SI Appendix, Fig. S6 and Table S4). Compared with tolerant cells, rescued T cells down-regulated genes associated with the tolerance gene cluster (SI Appendix, Table S4). Up- and down-regulated genes in the rescued subset significantly overlapped with differentially expressed genes within the ex-tolerant group (SI Appendix, Fig. S6). However, there was also a unique subset of differentially expressed genes in the combination treatment group (SI Appendix, Figs. S5 and S6). Ingenuity Pathway Analysis was performed on differentially expressed genes in the combination treatment group, compared with tolerant OTI cells, and predicted that induction of CSF-2 (GM-CSF) and IL-2 and inhibition of TCF3 were responsible (SI Appendix, Fig. S6).

Because rescued self-specific OTI cells overcame their fixed dysfunctional state typically associated with tumor-specific CD8 T cells, we next investigated whether reprogrammed self-specific CD8 T cells could kill tumors expressing self-antigen. iFABP-Ova mice with tolerant OTI cells were treated with anti–PD-L1, VSV-Ova infection, or both, and were challenged with B16-Ova melanoma. Single treatment (anti–PD-L1 or VSV-Ova infection alone) did not result in tumor control over untreated mice (Fig. 4D). However, combinatorial treatment with VSV-Ova infection and anti–PD-L1 resulted in delayed tumor growth and control of tumor size (Fig. 4D). Despite this, the mice in this group did not lose weight or exhibit intestinal pathology, as seen with early checkpoint blockade treatment (Fig. 4D and SI Appendix, Figs. S1 and S6D). When the combinatorial treatment was given to mice with established B16 tumors, this resulted in control of further tumor growth, compared with other treatments, and had a positive impact on survival (Fig. 4E). Thus, tolerant self-specific CD8 T cells can be induced to control tumors, but this is not at the expense of healthy, self-antigen–bearing tissue.

Discussion

We show that checkpoint blockade responsiveness is dependent on the activation state of CD8 T cells. Newly primed self-specific CD8 T cells respond to checkpoint blockade, but tolerant populations have a cell-intrinsic block to treatment. Furthermore, simultaneous blockade of multiple inhibitory pathways does not induce responsiveness in a T cell that does not respond to inhibition of an individual pathway. However, nonpermissive T cells can be reprogrammed to respond to checkpoint blockade through proliferation brought on by antigen-specific activation.

Our previous work illustrated that the induction of tolerance is temporally distinct from the maintenance of tolerance and that self-specific T cells at these stages are disparate (21). Here, we show that when anti-CTLA4 or anti–PD-L1 is given at the time of OTI cell transfer to iFABP-Ova mice, tolerance is not induced, resulting in intestinal pathology (SI Appendix, Fig. S1 A–C). Patients receiving checkpoint blockade often experience autoimmune side effects (15, 39). We propose that these on-target, off-tissue effects are due to potentiation of nontolerized T cells that have recently encountered self-antigen.

The activity of CTLA4 or PD-L1 blockade early during T cell differentiation does not predict a positive response to treatment after tolerance has been established. After single or combined treatment with anti-CTLA4 and anti–PD-L1, tolerant CD8 T cells do not proliferate or alter their functional profile (Figs. 1 and 2 and SI Appendix, Fig. S3). Inclusion of additional checkpoint blockade, such as anti–LAG-3, anti–TIM-3, and anti–PD-1, did not result in activation (Fig. 2 and SI Appendix, Fig. S3). These data indicate that tolerant CD8 T cells have an intrinsic block to activation via multiple pathways of checkpoint blockade. Because we found that tolerant self-specific OTI cells are transcriptionally similar to dysfunctional tumor-specific CD8 T cells, our data suggest a similar mechanistic defect for tumor-specific T cells (23). This could explain why patients fail to respond to, or develop resistance to, checkpoint blockade, even when their tumors and/or tumor-infiltrating lymphocytes express inhibitory receptors/ligands (40).

We found that tolerant T cells had a distinct transcriptional profile distinguishing them from naïve, effector, or memory CD8 T cells. Our tolerance gene cluster is enriched for genes associated with fixed T cell dysfunction in tumor-specific CD8 T cells and identifies T cells that are nonresponsive to checkpoint blockade (Figs. 1 and 2). Tolerant T cells have a phenotypic and genotypic signature indicating that they are in contact with antigen and are actively suppressing activation: down-regulation of CD28, CD11a, CD2, CD3, CD5, CD8β, and TCR and up-regulation of inhibitory receptors. This suggests that they may be maintained via tonic signaling similar to CD4 regulatory T cells (41).

The lack of response to checkpoint blockade of tolerant CD8 T cells does not preclude terminal differentiation. Robust stimulation with self-antigen induced significant phenotypic and genotypic changes in the tolerant OTI cells, leading to their expansion (Fig. 3 and SI Appendix, Fig. S4). This was paired with a decrease in the tolerant transcriptional profile associated with the fixed state of dysfunction (23). VSV-Ova infection increased inhibitory receptor expression and antigen-sensing machinery on ex-tolerant OTI cells. VSV-Ova is a live replicating vector that delivers exogenous self-antigen. This type of vector may be critical for inducing a high density of MHC–peptide complexes and inflammatory sequelae to optimally activate tolerant T cells with suboptimal antigen-sensing capabilities. Other studies have shown that actA-deficient Listeria monocytogenes, which is severely attenuated, is insufficient to alter tolerance (22, 25). Production of exogenous self-antigen by VSV was required here, suggesting that self-replicating antigen is key for tolerance reversal (SI Appendix, Fig. S4). We conclude that increases in antigenic stimulation and inflammatory signals are required for tolerant CD8 T cell rescue. Because our data show overlap between tolerant self-specific CD8 T cells and dysfunctional tumor-specific CD8 T cells, it is possible that a similar vaccination strategy targeting tumor-specific T cells, whether they are neoantigen-specific or of another specificity, may reverse tolerance.

Antigenic reprogramming and activation of tolerant OTI cells led to renewed responsiveness to PD-L1 blockade (Fig. 4). The combination of anti–PD-L1 and VSV-Ova infection rescued IFN-γ production, compared with VSV-Ova infection alone (Fig. 3). We predict that there are differential requirements for inducing proliferation versus functionality in tolerant T cells. Our data show that the threshold for rescue of cytokine production can be achieved by the synergistic effects of antigenic reeducation plus PD-L1 blockade. While activation of tolerant OTI cells renewed susceptibility to anti–PD-L1, responsiveness to anti-CTLA4 was not restored (Fig. 4A). This implies that the reversal of CD8 T cell tolerance and augmentation with PD-L1 blockade with VSV-Ova infection may occur via antigen recognition on nonhematopoietic cells. Our data are in line with the concept that CTLA4 is important in the induction of tolerance, whereas PD-1 is important in the induction and maintenance of CD8 T cell tolerance when coupled with immunization (42).

Importantly, dual treatment with VSV-Ova infection and PD-L1 blockade induced control of B16 melanoma growth, which was not seen with either infection or anti–PD-L1 alone (Fig. 4). We propose that antitumor responses in patients could be induced with checkpoint blockade when combined with proper antigenic stimulation. Our data suggest that this type of combinatorial therapy could improve response rates to checkpoint blockade by mobilizing cancer-specific T cells which would have remained quiescent to checkpoint therapy alone. Combination therapy could increase the percent of patients benefiting from checkpoint blockade and increase overall efficacy. Interestingly, iFABP-Ova animals undergoing OTI-driven tumor rejection do not exhibit autoimmunity (Fig. 4D and SI Appendix, Fig. S6D). This may be due to elevated expression of self-antigen on tumor cells. Thus, T cell therapies targeting tumors with overexpressed self-antigens need not necessarily lead to damage of healthy tissue.

Our data indicate that once tolerance is established, blocking multiple inhibitory pathways will not rescue nonfunctional CD8 T cells. In the clinic, combinatorial checkpoint blockade results in better antitumor immunity. We postulate that this would not be due to tolerance reversal of nonrescuable T cells, but instead be due to increased numbers of responding T cells. Tolerant CD8 T cells have a unique transcriptional profile, but are not necessarily terminally differentiated. As summarized in SI Appendix, Fig. S7, dysfunctional CD8 T cells refractory to checkpoint blockade can be induced to proliferate and produce cytokines under the right conditions. Robust TCR and coreceptor stimulation predicts response to checkpoint blockade therapy and promotes tumor control (43).

Materials and Methods

Mice and Treatments.

C57BL/6J mice were purchased from The Jackson Laboratory. OTI and iFABP-Ova mice were bred in-house. All mice were used in accordance with the University of Minnesota Institutional Animal Care and Use Committee guidelines. Two hundred micrograms of antibodies were injected i.p. every 3 d for five treatments. Mice were infected i.v. with 1 × 106 pfu VSV-Ova or VSV.

Adoptive Transfers.

OTI/CD45.1 splenocytes (5 × 105) were transferred i.v. to adult iFABP-Ova/CD45.2 mice. For low OTI cell transfers, 5 × 103 OTI/CD45.1 splenocytes were transferred. Mice were either treated upon adoptive transfer or were maintained for ≥30 d before treatment or infection (21).

Isolation of Lymphocytes, Flow Cytometry, and Histology.

Cell isolation and flow cytometry occurred as previously described (21, 38). Tissues were fixed in formalin and stained with H&E.

Cytokine Assays.

Lymphocytes were incubated with 1 μg/mL GolgiPlug ± 1 μg/mL SIINFEKL for 4 h at 37 °C.

Tumor Challenge.

Mice were challenged with 1 × 105 B16-Ova cells administered s.c., and tumor size was measured with calipers daily.

RNA Sequencing and Analysis.

OTI cells were flow sorted from indicated animals, and RNA was prepared and sequenced using standard protocols. Data were analyzed as outlined in SI Appendix, Materials and Methods.

Statistical Analysis.

Unpaired two-tailed Student’s t test, Welch’s t test, Mann–Whitney U test, or ANOVA was used. P < 0.05 was considered significant. Error bars indicate mean ± SEM.

Acknowledgments

We thank Rachel Davis for expert technical assistance. This work was supported by the NIH Grant DP2OD006472 (to V.V.), the Randy Shaver Cancer Research Fund (V.V.), and the NIH Grant T32AI007313 (to C.E.N. and E.A.T.).

Footnotes

  • ↵1To whom correspondence should be addressed. Email: vvezys{at}umn.edu.
  • Author contributions: C.E.N. and V.V. designed research; C.E.N., J.L.M., E.A.T., S.B., and C.F.Q. performed research; B.T.F. contributed new reagents/analytic tools; C.E.N., L.J.M., J.L.M., E.A.T., D.M.S., S.B., C.F.Q., and V.V. analyzed data; and C.E.N., E.A.T., C.F.Q., B.T.F., and V.V. wrote the paper.

  • The authors declare no conflict of interest.

  • This article is a PNAS Direct Submission.

  • This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10.1073/pnas.1810326116/-/DCSupplemental.

Published under the PNAS license.

View Abstract

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Reprogramming responsiveness to checkpoint blockade in dysfunctional CD8 T cells
Christine E. Nelson, Lauren J. Mills, Jennifer L. McCurtain, Emily A. Thompson, Davis M. Seelig, Siddheshvar Bhela, Clare F. Quarnstrom, Brian T. Fife, Vaiva Vezys
Proceedings of the National Academy of Sciences Feb 2019, 116 (7) 2640-2645; DOI: 10.1073/pnas.1810326116

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Reprogramming responsiveness to checkpoint blockade in dysfunctional CD8 T cells
Christine E. Nelson, Lauren J. Mills, Jennifer L. McCurtain, Emily A. Thompson, Davis M. Seelig, Siddheshvar Bhela, Clare F. Quarnstrom, Brian T. Fife, Vaiva Vezys
Proceedings of the National Academy of Sciences Feb 2019, 116 (7) 2640-2645; DOI: 10.1073/pnas.1810326116
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