Skip to main content
NCBI home page
Molecular Therapy logoLink to Molecular Therapy
. 2013 Dec 17;22(1):206–218. doi: 10.1038/mt.2013.255

Immunotherapy-induced CD8+ T Cells Instigate Immune Suppression in the Tumor

A J Robert McGray 1, Robin Hallett 1, Dannie Bernard 1, Stephanie L Swift 1, Ziqiang Zhu 2, Florentina Teoderascu 1, Heather VanSeggelen 1, John A Hassell 1, Arthur A Hurwitz 2, Yonghong Wan 1, Jonathan L Bramson 1,*
PMCID: PMC3978796  PMID: 24196579

Abstract

Despite clear evidence of immunogenicity, cancer vaccines only provide a modest clinical benefit. To evaluate the mechanisms that limit tumor regression following vaccination, we have investigated the weak efficacy of a highly immunogenic experimental vaccine using a murine melanoma model. We discovered that the tumor adapts rapidly to the immune attack instigated by tumor-specific CD8+ T cells in the first few days following vaccination, resulting in the upregulation of a complex set of biological networks, including multiple immunosuppressive processes. This rapid adaptation acts to prevent sustained local immune attack, despite continued infiltration by increasing numbers of tumor-specific T cells. Combining vaccination with adoptive transfer of tumor-specific T cells produced complete regression of the treated tumors but did not prevent the adaptive immunosuppression. In fact, the adaptive immunosuppressive pathways were more highly induced in regressing tumors, commensurate with the enhanced level of immune attack. Examination of tumor infiltrating T-cell functionality revealed that the adaptive immunosuppression leads to a progressive loss in T-cell function, even in tumors that are regressing. These novel observations that T cells produced by therapeutic intervention can instigate a rapid adaptive immunosuppressive response within the tumor have important implications for clinical implementation of immunotherapies.

Introduction

The proven clinical immunogenicity of multiple cancer vaccine strategies suggest that active immunization should be a realistic approach to cancer therapy. However, after testing a broad range of vaccination strategies in clinical trials (reviewed in ref. 1) only modest clinical benefits have been realized.2,3 Nevertheless, encouraging outcomes from several large-scale clinical trials4,5,6,7 and the recent market approval of Sipuleucel-T8,9 support continued efforts to develop therapeutic cancer vaccines. Studies of adoptive T-cell transfer have confirmed that T cells, when properly activated and delivered at sufficiently high doses, can produce regression of large tumor masses in humans.3,10,11,12,13 Given the production and cost advantages that vaccine therapies offer over adoptive T-cell therapies, the community remains enthusiastic about the prospect of effective cancer vaccines; however, further refinement of the current strategies are clearly needed. Comparing and contrasting the antitumor response produced by vaccines and adoptive T-cell therapies should provide important insight into approaches to improving the efficacy of vaccination.

It is now widely accepted that the tumor presents an immunosuppressive environment capable of limiting effective immune attack by infiltrating T cells.14,15,16 Membrane-bound ligands, checkpoint receptors, soluble factors, as well as infiltrating suppressive and/or tolerogenic immune cell populations have been described that contribute to the complex immunosuppressive network within the tumor (reviewed in ref. 17). According to the Immunoediting Hypothesis,18 tumors only develop when cancerous cells have acquired the ability to evade immune-mediated destruction. In that context, the immune suppressive nature of the tumor reflects the history of immune-mediated attack on the cancerous cells. It has been shown that immunotherapies cause further editing of the tumor and promote the outgrowth of tumor escape variants;19,20 however, whether immunotherapies also influence the immune suppressive pathways in the tumor remains to be elucidated.

We have previously demonstrated that vaccine-induced T cells display functional defects within the tumor despite being fully functional in the periphery,21 presumably as a consequence of the immune suppressive nature of the tumor. Little is known, however, about the reciprocal impact of the vaccine-induced T-cell response on the tumor. The immune suppressive pathways within the tumor are typically described as static and unidirectional (tumor acting on T cell). In this article, we have investigated the reciprocal interactions between the tumor and the infiltrating tumor-specific T cells elicited by a potent recombinant adenovirus vaccine. We now demonstrate that CD8+ T cells activated by immunotherapies instigate an adaptive immunosuppressive response in the tumor, whereby a constellation of immune suppressive mechanisms are upregulated in direct and measured response to T-cell attack. These novel observations have important implications to the future clinical application of immunotherapies.

Results

Vaccination produces modest suppression of tumor growth despite a robust expansion of tumor-specific CD8+ T cells

Immunization of tumor-bearing mice with recombinant adenovirus vaccines expressing either dopachrome tautomerase (rHuAd5-hDCT) or gp100 (rHuAd5-hgp100) yielded a robust antigen-specific CD8+ T-cell response, which peaked around 2 weeks after immunization (Figure 1a). Tumor growth slowed in mice treated with rHuAd5-hDCT and was unaffected in mice treated with rHuAd5-hgp100 loss (Figure 1b). The modest growth inhibition produced by the rHuAd5-hDCT vaccine was mediated by CD8+ T cells (Figure 1c).

Figure 1.

Figure 1

Open in a new tab

CD8+ T cells and interferon (IFN)-γ mediate tumor growth suppression that is associated with the activity of CD8+ T cells that infiltrate the tumor early following vaccination. (a) DCT (square) and gp100 (triangle)-specific CD8+ peripheral blood lymphocytes (PBLs) were measured based on IFN-γ production following ex vivo peptide stimulation at different time points post-rHuAd5-hDCT or rHuAd5-hgp100 immunization (n = 5–12). (b) Tumor-bearing mice were immunized with either rHuAd5-hDCT (square), rHuAd5-hgp100 (triangle), or left untreated (circle). (c) Tumor-bearing mice were treated with rHuAd5-hDCT and depleted of CD4+ (filled square), CD8+ (inverted triangle), or both cell subsets (diamond) or left nondepleted (NT) (square). (d) Tumor-bearing mice were treated with rHuAd5-hDCT (square) or the vaccine in combination with IFN-γ neutralization (triangle). (e) Expression of IFN-γ in tumors from mice treated with either rHuAd5-hDCT (square), rHuAd5-hgp100 (triangle) or left untreated (circle) (n = 4). (f) Intratumoral tumor necrosis factor (TNF)-α expression as described in e. (g) DCT-specific CD8+ TIL were enumerated following rHuAd5-hDCT immunization (n = 8–19). Tumor volumes in b–d reflect individual representative experiments (n = 4–6). Data presented as mean ± SEM. *P < 0.05, **P < 0.01, ***P < 0.001. DCT, dopachrome tautomerase.

Vaccine-induced T cells within the tumor display a progressive loss of function

The modest effect on tumor growth resulting from immunization with rHuAd5-hDCT was inconsistent with the high level of tumor-specific CD8+ T cells in the periphery (>3% of circulating CD8+ T cells), suggesting that the DCT-specific T cells may not be active within the tumor. Experiments using antibody blockade and knock-out mice revealed that interferon (IFN)-γ was critical to the modest antitumor effect produced by rHuAd5-hDCT vaccination (Figure 1d and data not shown). Therefore, we reasoned that monitoring IFN-γ transcripts directly within the tumor following vaccination would provide a direct measure of the activity of vaccine-induced T cells, as IFN-γ is rapidly upregulated following T-cell receptor (TCR) stimulation and extinguished with equal rapidity when contact with the major histocompatibility complex/peptide complex is disrupted.22 Tumor-bearing mice were vaccinated with rHuAd5-hDCT, rHuAd5-hgp100, or left untreated, total RNA was prepared from their tumors at different time points, and IFN-γ expression was measured by quantitative real-time PCR. Expression of IFN-γ was relatively low in untreated tumors (Figure 1e, circles) whereas immunization with rHuAd5-hDCT led to a rapid, but transient, increase in intratumoral IFN-γ, which peaked 5 days after vaccination (Figure 1e, squares). Little expression of IFN-γ was measured in tumors from mice immunized with rHuAd5-hgp100 (Figure 1e, triangles), despite a robust gp100-specific CD8+ T-cell response (Figure 1a); expression was however significantly elevated relative to untreated mice at days 9–11, indicating some activation of gp100-specific T cells within these tumors. Antibody depletion studies confirmed that IFN-γ expression in the tumor was due to CD8+ T-cell activation (Supplementary Figure S1a).

As a second measure of T-cell activity in the tumor, we monitored tumor necrosis factor (TNF)-α. Following rHuAd5-hDCT immunization, TNF-α expression displayed kinetics similar to IFN-γ, albeit delayed (Figure 1f). Again, the expression of TNF-α was found to be wholly dependent upon CD8+ T cells (Supplementary Figure S1b). It is notable that the period of heightened cytokine expression (Figure 1e,f) within the tumor corresponded to the period of rHuAd5-hDCT–mediated tumor growth suppression (Figure 1b).

The T-cell activity within the tumor, as measured by cytokine expression, did not parallel the expansion kinetics of the DCT-specific CD8+ T cells in the periphery. To confirm that vaccine-induced CD8+ T cells accumulate in the tumor in accordance with the expansion of the cells in the periphery, we measured the DCT-specific CD8+ T cells within the tumor at an early time point (5 days) and later time point (10 days) after rHuAd5-hDCT immunization. Consistent with the peripheral expansion of DCT-specific CD8+ T cells (Figure 1a), there were approximately four times the number of DCT-specific CD8+ T cells in the tumor at day 10 compared to day 5 (Figure 1g). In line with our previous observations,21 we observed that tumor infiltrating CD8+ T cells (CD8+ tumor infiltrating lymphocytes (TILs)) displayed reduced functionality compared to the peripheral blood lymphocytes (PBLs) (Supplementary Figure S1c). Interestingly, the TIL revealed a progressive loss of function where the TIL at day 5 displayed significantly greater functionality than the TIL at day 10 with regard to the production of multiple cytokines (IFN-γ/TNF-α) and the ability to degranulate (based on CD107a mobilization) (P < 0.05; Supplementary Figure S1c). When considered together, the cytokine expression studies combined with the ex vivo polyfunctional analysis suggested that DCT-specific T cells within the tumor grew progressively more dysfunctional with time following vaccination.

Early intratumoral immune attack elicits rapid adaptation by the tumor involving numerous immunosuppressive genes

Our observations that vaccine-induced CD8+ T cells within the tumor displayed evidence of acquired dysfunction and diminished antitumor activity suggested that the tumor environment was mediating this progressive immune suppression. We reasoned that the early T-cell attack might be triggering the tumor to adapt through upregulation of immunosuppressive pathways, thus impairing the function of T cells that arrived later in the response. We therefore interrogated the transcriptional profiles of whole tumors following immunization with rHuAd5-hDCT for the expression of well-characterized immunosuppressive processes. Our analysis revealed rapid induction of genes associated with immune suppression following rHuAd5-hDCT immunization, including PD-L1, PD-L2, galectin-9, arginase 1, iNOS, TGF-β1, as well as the checkpoint receptors PD-1, LAG-3, and TIM-3 beginning as early as 5 days after vaccination (Figure 2a). Depletion studies confirmed that the induction of these immunosuppressive processes in the tumor following vaccination was CD8+ T-cell dependent (Figure 2b and Supplementary Figure S2).

Figure 2.

Figure 2

Open in a new tab

Local immune activity instigates an adaptive immunosuppressive response in the tumor. (a) Heat Map displaying the relative expression of immunosuppressive genes in rHuAd5-hDCT or Untreated tumors (n = 4). (b) Expression of PD-L1, PD-L2, iNOS, and arginase 1 in tumors from mice treated with rHuAd5-hDCT and depleted of CD4+ (αCD4), CD8+ (αCD8), both cell subsets (αCD8/αCD4) or left nondepleted (NT) (n = 4). Data points correspond to peak expression of individual genes and grey areas correspond to the mean ± SEM for genes expressed in untreated tumors. (c) Expression of PD-L1, PD-L2, iNOS, and arginase 1 in tumors from wild type (WT) (day 5 or 9, corresponding to peak expression) or interferon (IFN)-γ−/− (day 5 and 8) mice treated with rHuAd5-hDCT (n = 4). (d) Expression of IFN-γ in tumors following treatment with rHuAd5-hDCT or rHuAd5-hDCT in combination with IFN-γ neutralization (n = 4–5). (e) Tumor-bearing mice were immunized with rHuAd5-hDCT and subsequently treated with αPD-1 or the combination of αPD-1/αTIM-3/αLAG3 beginning 3 days following immunization (n = 5). Data presented as mean ± SEM. *P < 0.05, **P < 0.01. DCT, dopachrome tautomerase; NS, not significant.

We noted that IFN-γ was required for the induction of many, but not all, of these immunosuppressive genes, (Figure 2c and data not shown). Interestingly, blockade of IFN-γ signaling using a monoclonal antibody reversed the immunosuppression and resulted in sustained T-cell activity within the tumor, based on prolonged IFN-γ expression (Figure 2d); however, IFN-γ blockade also suppressed the antitumor effect of the vaccine (Figure 1d). We also noted that expression of the immunosuppressive gene set diminished as local immune activity (measured by IFN-γ and TNF-α expression) declined (data not shown). These data demonstrate that early immune attack by CD8+ T cells instigates upregulation of numerous immunosuppressive processes in the tumor, which suppress local T-cell activity.

Combination blockade of multiple inhibitory receptors results in transient tumor regression followed by tumor relapse

Blockade of PD-1 signaling following rHuAd5-hDCT immunization leads to transient regression of B16F10 tumors.23 In light of the current data set, we reasoned that additional blockade of TIM-3 and LAG-3 would further enhance the antitumor activity of rHuAd5-hDCT. While the combined blockade of PD-1/TIM-3/LAG3 resulted in a modest improvement in the duration of tumor regression compared to PD-1 blockade alone, all treated tumors ultimately relapsed (Figure 2e), indicating that blockade of checkpoint receptors alone is not sufficient to overcome the adaptive immunosuppression in the tumor.

rHuAd5-hDCT immunization elicits global changes within the tumor

To better understand the full breadth of intratumoral changes elicited by rHuAd5-hDCT, we performed microarray analysis comparing untreated tumors to tumors treated with rHuAd5-hDCT or rHuAd5-hgp100. We selected to examine RNA isolated 7 days following vaccination because the transcriptional data revealed clear evidence of immune attack at this time point but we did not yet observe a difference in tumor growth as a result of treatment with rHuAd5-hDCT. We considered this day to be the “tipping point” where tumor growth begins to slow and, thus, should reveal important biological insights. The transcriptome analysis revealed that despite the modest effect of the rHuAd5-hDCT vaccine on tumor growth, the vaccine had a major effect on the tumor biology. On a global level, we observed 189 probes to be differentially expressed (fold change > 2.0, q value <0.1), of which 180 were upregulated and 9 were downregulated in the rHuAd5-hDCT treatment group (Figure 3a). Gene ontology analysis revealed that genes over expressed after rHuAd5-hDCT treatment were most enriched in immune system processes such as antigen processing and presentation as well as regulation of T-cell processes (Figure 3b). Using the NCI-Nature pathway interaction database, pathways showing highest enrichment corresponded to well-characterized immune pathways, including the IL-12 and IL-23 pathways (Figure 3c and Supplementary Table S1). When considered together, our data suggest that while rHuAd5-hDCT vaccination initiates a complex network of both immune and nonimmune changes within the tumor, these local changes ultimately attenuate the immune activity of the vaccine-induced CD8+ T cells, resulting in continued tumor growth.

Figure 3.

Figure 3

Open in a new tab

rHuAd5-hDCT immunization instigates global transcriptional changes in the tumor. (a) Hierarchical clustering of differentially expressed genes in tumors following treatment with rHuAd5-hDCT, rHuAd5-hgp100, or untreated tumors (n = 3). (b) Graphical representation of gene ontology (GO) analysis of genes differentially expressed in rHuAd5-hDCT treated tumors. (c) Positively enriched pathways in the tumor following treatment with rHuAd5-hDCT.

Increasing the magnitude of early immune attack through adoptive T-cell transfer results in tumor regression

Our data suggested that immune attack on the tumor following vaccination is attenuated by early adaptive events in the tumor, resulting in the emergence of a complex immunosuppressive environment prior to the complete manifestation of the vaccine-mediated response. Therefore, the antitumor response may be limited by the rate at which vaccine-induced CD8+ T cells expand and infiltrate the tumor. To augment the magnitude of the T-cell response following vaccination, we adoptively transferred increasing numbers (104, 105, and 106) of naïve congenically marked (Thy1.1+) transgenic T cells that express a TCR specific for the immunodominant epitope of DCT (DCTT cells) immediately following immunization with rHuAd5-hDCT. Adoptive transfer of 104 DCTT cells did not improve the efficacy of the rHuAd5-hDCT vaccine, while a small improvement in tumor growth control and survival was observed following transfer of 105 DCTT cells (Figure 4a,b). Treatment with rHuAd-hDCT + 106 DCTT cells resulted in rapid tumor regression in all treated mice (Figure 4a) and durable cures in ~65% of treated animals (Figure 4b). To confirm that the tumor regressions observed following infusion of 106 DCTT cells required cognate interactions with the vaccine antigen, a set of control mice received 106 DCTT cells in combination with an irrelevant adenovirus vaccine, rHuAd5-LCMV-GP, which carries no tumor antigen (see Materials and Methods). Previous studies have determined that the rHuAd5-LCMV-GP vaccine has no impact on B16F10 tumor growth.21 Adoptive transfer of 106 DCTT cells following immunization with rHuAd5-LCMV-GP, had no impact on tumor growth or survival (Figure 4a,b) confirming that the antitumor activity of the DCTT cells requires the DCT antigen expressed by the rHuAd5-hDCT vaccine.

Figure 4.

Figure 4

Open in a new tab

Increasing the magnitude of the DCT-specific CD8+ T-cell response results in tumor regression and improved survival that correlates with the early CD8+ T-cell response. (a) Tumor-bearing mice were immunized with rHuAd5-hDCT + 104 (square), 105 (triangle), or 106 (circle) DCTT cells, rHuAd5-LCMV-GP + 106 DCTT cells (diamond), or rHuAd5-hDCT alone (filled square) (b) Survival data corresponding to the treatments outlined in a. (c) DCT-specific CD8+ peripheral blood lymphocytes (PBLs) were measured (based on interferon (IFN)-γ production in response to ex vivo peptide stimulation) following treatment with rHuAd5-hDCT, rHuAd5-hDCT + 104–106 DCTT cells, or rHuAd5-LCMV-GP + 106 DCTT cells (n = 7–14). (d) Analysis of the early (day 5) and late (day 10) frequencies of DCT-specific CD8+ PBL, clustered based on tumor regression versus tumor growth, for mice immunized with rHuAd5-hDCT ± transfer of DCTT cells (n = 14–35). Tumor volumes were calculated from a single representative experiment (n = 4–5) and survival data was compiled from independent experiments (n = 7–14). Data presented as mean ± SEM. *P < 0.05, ***P < 0.001. DCT, dopachrome tautomerase; NS, not significant.

Adoptive transfer of 104 DCTT cells following vaccination with rHuAd5-hDCT had no impact on the overall frequency of DCT-specific CD8+ T cells (endogenous and exogenous cells combined) compared to vaccination alone (Figure 4c). Infusion of 105 DCTT cells produced a small increase in the frequency of DCT-specific CD8+ T cells, consistent with the small impact on tumor growth (Figure 4c). In line with the potent antitumor effect, adoptive transfer of 106 DCTT cells following rHuAd5-hDCT produced a robust fivefold enhancement in the frequency of circulating DCT-specific CD8+ T cells (Figure 4c). Adoptive transfer of DCTT cells followed by vaccination with the control rHuAd5-LCMV-GP vaccine did not result in expansion of DCT-specific CD8+ T cells (Figure 4c).

Tumor regression correlates with the intensity of the early CD8+ T-cell response following vaccination, but cures require sustained antitumor immunity

CD8+ T-cell responses for each mouse at day 5 and day 10 after immunization were stratified based on whether tumors initially grew or regressed following treatment with rHuAd5-hDCT ± DCTT cells. (This analysis did not consider whether regressing tumors were completely cured or eventually relapsed.) Tumor regression was associated with a high frequency DCT-specific CD8+ T-cell response at early times (day 5) after vaccination whereas the frequencies of DCT-specific CD8+ T cells at later time point (day 10) were no different between the mice where tumors regressed versus those that continued to grow (Figure 4d). Nevertheless, durable cures were dependent upon sustained antitumor immunity as depletion of CD8+ T cells 10 days following treatment with rHuAd5-hDCT + 106 DCTT cells resulted in complete tumor relapse in all treated animals (Supplementary Figure S3). Thus, although initial control of tumor growth seemed to require a vigorous immune attack, the level of immune response produced by the vaccine alone was sufficient to ablate the tumor once its growth was under control.

Adoptive transfer does not reverse the TIL functional impairments, but greatly increases the magnitude of intratumoral immune attack

We questioned whether the tumor regression that followed the high dose adoptive transfer was related to improved functionality of the DCT-specific TIL. DCTT cells were monitored in the TIL using flow cytometric analyses gated on Thy1.1+ events. As mentioned previously, adoptive transfer of 104 Thy1.1+ DCTT cells in combination with vaccination had no impact on tumor growth compared to vaccine alone, whereas adoptive transfer of 106 DCTT cells resulted in robust tumor regression. (Figure 4a,b and Supplementary Figure S4). Nevertheless, we observed no difference in the functional status of the DCTT cells in tumors that were growing or regressing. The Thy1.1+ CD8+ T cells in the tumor displayed a progressive loss of function in both groups, as measured by the frequency of transferred cells able to produce IFN–γ (upper right quadrant) compared to the total frequency of transferred cells (upper and lower right quadrants) (Figure 5a). The endogenous DCT-specific CD8+ T cells (Thy1.1−) within the tumor displayed a similarly progressive functional impairment, confirming that this effect was not an artifact of the TCR-transgenic T cells (Figure 5a). The Thy1.1+ TIL also revealed progressive defects in their ability to produce TNF-α and degranulate (based on CD107a mobilization) (Figure 5b). Note that analysis of DCT-specific CD8+ TIL was only carried out at days 5 and 8 after treatment with rHuAd5-hDCT + 106 DCTT cells, as tumors had become too small beyond this point to reliably isolate TILs.

Figure 5.

Figure 5

Open in a new tab

DCT-specific CD8+ TIL display a progressive decline in functionality despite increased tumor infiltration over time. Representative FACs plots showing interferon (IFN)-γ production by transferred (Thy1.1+) and endogenous (Thy1.1−) DCT-specific CD8+ T cells in response to peptide stimulation following rHuAd5-hDCT immunization + DCTT-cell transfer (n = 5–9). (b) Representative FACs plots showing frequencies of Thy1.1+ CD8+ TIL able to produce multiple cytokines (IFN-γ/TNF-α) and degranulate (IFN-γ/CD107a) over time as described in a (n = 5–9). (c) Transferred DCT-specific CD8+ TIL (Thy1.1+CD8+) were enumerated following vaccination with rHuAd5-hDCT (n = 5–9). Data presented as mean ± SEM. **P < 0.01. DCT, dopachrome tautomerase; TIL, tumor infiltrating lymphocyte; TNF, tumor necrosis factor.

The number DCT-specific CD8+ T cells infiltrating the tumors of mice treated with rHuAd5-hDCT + 106 DCTT cells was markedly higher than those treated with the vaccine + 104 DCTT cells (Figure 5c), consistent with the elevated frequencies of DCT-specific CD8+ T cells in the periphery (Figure 4c). Furthermore, immunohistochemistry revealed that treatment with rHuAd5-hDCT + 106 DCTT cells resulted in not only a greater number of TIL, but also a more uniform distribution of T cells throughout the entire tumor than was observed at the 104 T-cell dose, where infiltrating T cells were located more within the peripheral margins of the tumor (Supplementary Figure S5).

Transcriptional analysis revealed that rHuAd5-hDCT combined with transfer of 106 DCTT cells evoked significant increases in the magnitude of intratumoral immune activity compared to vaccination alone. The level of IFN-γ expression following rHuAd5-hDCT + 106 DCTT-cell treatment was fivefold greater than the level produced by vaccination alone (Figure 6a, left panel). TNF-α expression in the tumor was again delayed compared to IFN-γ with expression increasing over vaccine alone by greater than 19-fold at day 7 (Figure 6a, middle panel). As expected based on enumeration of DCT-specific CD8+ TIL, TCRα expression in the tumor also increased following high dose T-cell transfer, showing a nearly 12-fold increase over rHuAd5-hDCT alone (Figure 6a, right panel). When the IFN-γ transcripts were normalized to TCRα, we noted that immune activity on a per-cell basis peaked 5 days following vaccination and subsequently dropped at day 7, consistent with ex vivo analysis revealing a progressive loss of function among the TIL (Figure 6b).

Figure 6.

Figure 6

Open in a new tab

Transfer of high dose DCTT cells in combination with rHuAd5-hDCT results in a transient increase in local intratumoral immune activity, but is accompanied by increased expression of immunosuppressive genes in the tumor. (a) Intratumoral expression of interferon (IFN)-γ (left), TNF-α (middle), and TCR-α (right) in tumors following treatment with rHuAd5-hDCT (square), rHuAd5-hDCT + 106 DCTT cells (triangle), or rHuAd5-LCMV-GP + 106 DCTT cells (circle) (n = 4) (b) Relative IFN-γ expression normalized to relative TCR-α expression in tumors following treatment with rHuAd5-hDCT (square) or rHuAd5-hDCT + 106 DCTT cells (triangle) (n = 4). (c) Heat Map displaying the relative expression of immunosuppressive genes in tumors following treatment with rHuAd5-hDCT ± 106 DCTT cells and rHuAd5-LCMV-GP + 106 DCTT cells (n = 4). Data presented as mean ± SEM. DCT, dopachrome tautomerase; TCR, T-cell receptor; TNF, tumor necrosis factor.

Elevated T-cell attack results in a commensurate increase in the adaptive immunosuppression within the tumor

We determined that expression of the immunosuppressive genes described in Figure 2 were further upregulated in the tumors from mice receiving rHuAd5-hDCT + 106 DCTT cells compared to those receiving vaccine alone (Figure 6c). Note that transcriptional analysis could only be carried out until 7 days after vaccination for tumors treated with rHuAd5-hDCT + 106 DCTT cells, as tumors had become too small beyond this point to isolate high quality RNA.

To gain further insight into differences between the combination rHuAd5-hDCT + 106 DCTT-cell treatment and treatment with rHuAd5-hDCT alone, we compared global gene expression profiles of tumors 5 days following treatment, corresponding to the point of maximal local immune function (Figure 6b). When compared to untreated tumors, we observed a large number of differentially expressed genes associated with both rHuAd5-hDCT–based therapies (Figure 7a). Treatment with rHuAd5-hDCT resulted in differential expression of 329 genes relative to untreated tumors (316 upregulated, 13 downregulated), while rHuAd5-hDCT + 106 DCTT cells resulted in differential expression of 990 genes (880 upregulated, 110 downregulated) (fold change > 2.0, q value <0.1)) (Figure 7a). Interestingly, genes differentially expressed following vaccination alone showed nearly complete overlap with genes impacted by vaccination combined with high dose DCTT-cell transfer. (Figure 7b,c). Similar to the previous microarray analysis (Figure 3), transcripts induced by the rHuAd5-hDCT treatments were almost exclusively enriched in immune system processes, such as regulation of T-cell–mediated toxicity and antigen processing and presentation (Supplementary Table S2) and did not reveal unique attributes that could explain the additional benefit of the high dose DCTT-cell transfer. Upon further examination of the induced transcripts common to both treatments, we noted that whereas these genes were induced by an average of fourfold in the rHuAd5-hDCT group, the same transcripts were upregulated by an average of nearly eightfold by rHuAd5-hDCT + 106 DCTT cells (Figure 7d, red line). Similarly, genes displaying reduced expression (relative to the untreated tumors) by both vaccine treatments were reduced to a greater extent by rHuAd5-hDCT + 106 DCTT-cells treatment (Figure 7d, blue line). These results demonstrate that among the transcripts affected by both vaccine treatments, the overall changes instigated by rHuAd5-hDCT + 106 DCTT cells are more robust, similar to the observations described in Figure 6.

Figure 7.

Figure 7

Open in a new tab

Transfer of high dose DCTT cells in combination with rHuAd5-hDCT initiates similar global changes within the tumor as vaccination alone, but of greater magnitude. (a) Hierarchical clustering of differentially expressed genes in untreated tumors compared to tumors treated with rHuAd5-hDCT (left) or rHuAd5-hDCT + 106 DCTT cells (right) (n = 4). (b,c) Comparison of differentially expressed genes shown in a using Venn diagrams. (d) Comparison of average relative expression for all codifferentially expressed genes following treatment with rHuAd5-hDCT ± 106 DCTT cells (n = 4). Data presented as mean ± SEM. DCT, dopachrome tautomerase.

The difference in treatment outcomes may be explained by the >600 genes that were only differentially expressed following treatment with rHuAd5-hDCT + 106 DCTT cells. Further investigation, however, revealed that most of these genes were also upregulated by rHuAd5-hDCT alone, albeit at a level below our statistical cut-off (fold change > 2.0, q value <0.1). Notably, among the 572 transcripts uniquely induced by rHuAd5-hDCT + 106 DCTT-cell treatment, 90% (515/572) were upregulated by a factor of 1.2-fold by rHuAd5-hDCT. Similarly, among genes uniquely repressed by the rHuAd5-hDCT + 106 DCTT-cell treatment, many were also modestly repressed by rHuAd5-hDCT (data not shown). Thus, it appears that nearly all genes regulated by rHuAd5-hDCT + 106 DCTT-cell treatment are also impacted by rHuAd5-hDCT treatment alone. Taken together, these data indicate the difference in treatment efficacy is likely a result of the robustness of the local immune attack elicited by rHuAd5-hDCT + 106 DCTT-cells vaccination, rather than the induction of unique immunological processes that are absent following vaccination alone.

Discussion

Tumor adaptation following immunotherapy is most commonly considered in the context of immunoediting where tumor cells emerge which can evade the immune response,18 often as a consequence of loss of antigen expression.19,24,25,26 Our data reveal a novel form of adaptation, which is more rapid than the emergence of resistant tumor cells. The adaptation described in this manuscript is an immediate response by the tumor to immune attack, where a constellation of immunoinhibitory pathways is upregulated, which ultimately renders the infiltrating tumor-specific T cells nonfunctional. Based on our studies where the precursor frequencies of the responding T cells were increased through adoptive cell transfer, the adaptive immunosuppression escalates in direct response to the magnitude of the immune attack. Nevertheless, when sufficient numbers of T cells are present within the tumor, they can produce tumor regression despite functional defects that arise from the adaptive immunosuppression. These results offer a new perspective into the mechanisms that underpin the limited therapeutic efficacy of most vaccination therapies and may explain the impressive successes of adoptive transfer strategies.

With regard to the modest success of cancer vaccines in the clinic, our results suggest that the slow kinetics of the T-cell response may be a strong contributing factor. We suspect that the modest efficacy observed in clinical vaccine studies results from adaptive immunosuppression where T cells produced by the initial immunizations instigate tumor adaptation, which renders the tumor refractory to immune attack by T cells that arrive at later points in the therapy. Thus, by the time the patient has received the full cadre of immunizations and T-cell frequencies have achieved levels that investigators expect to be therapeutic, the tumor microenvironment has become highly immunosuppressive as a consequence of the earlier immunizations. The development of an immunoinhibitory microenvironment notwithstanding, vaccines can provide some therapeutic benefit. The tumors in our model do grow more slowly for a brief period following vaccination. More importantly, a recent phase III study of a gp100 vaccine did reveal a benefit to progression free survival and overall survival, albeit a modest one.5 We believe that the true potential of cancer vaccines will be realized in time, as we gain further understanding of the mechanisms of tumor adaptation and develop strategies to usurp them.

The concept that immune suppression within the tumor may be instigated by T-cell attack is supported by a recent report from Taube et al.27 where they described a positive association of PD-L1 (B7-H1) expression in human melanomas with T-cell infiltration and the local expression of IFN-γ. The authors suggested a model where PD-L1 expression in the tumor is the result of local immune attack. Interestingly, in their dataset for metastatic melanoma, the presence of PD-L1 was associated with good outcome, representing a measure of immune attack and, presumably, active IFN-γ production by infiltrating T cells. However, not all studies support T-cell–mediated induction of PD-L1. In fact, a study of ovarian carcinoma observed that PD-L1 expression was inversely related to CD8+ T-cell infiltration.28 Nevertheless, the results from Taube et al. provide clinical support for the model proposed in this manuscript. Our data go further to demonstrate that tumor-specific CD8+ TIL orchestrate a complex network of immunosuppressive processes, which raises the concern that targeting individual immunosuppressive pathway (e.g., checkpoint receptors) may not be sufficient to completely overcome local immune suppression. Indeed, while the therapeutic efficacy of rHuAd5-hDCT could be improved by blocking multiple checkpoint receptors (PD-1, LAG-3, and TIM-3), all of the tumors ultimately relapsed demonstrating that other mechanisms of immune suppression ultimately prevail. When considered together, these data indicate that the redundancy in the immunosuppressive pathways instigated by immune attack on the tumor may confound efforts to overcome the immune suppression.

It is interesting to note that tumor-specific T cells isolated from tumors treated with therapeutic doses of T cells (106 DCTT cells in our model) displayed similar functional impairments as tumor-specific T cells isolated from tumors treated with sub-therapeutic doses. Thus, the benefit of the high doses of T cells does not appear to arise from the presence of T cells with increased functionality. Our data argue that the rate and magnitude of immune attack is a key factor in determining the outcome of T-cell–based immunotherapy. This is further illustrated when considering adoptive cell transfer therapies, where high doses of ex vivo expanded and preconditioned T cells are infused into patients and have shown promising clinical response rates.3,10,11,12,13,29 It is tempting to speculate that the rapid immune attack achieved in clinical adoptive cell transfer treatments may be effective in outpacing the ability of the tumor to upregulate adaptive immunosuppressive mechanisms, resulting in a more pronounced antitumor effect than has been observed following vaccine delivery.

We, and others, have previously reported that tumor-specific TIL display a number of functional impairments, while T cells with similar specificity in the periphery are typically highly polyfunctional.21,30,31,32,33 While the development of functional impairments in the TILs may reflect an intrinsic property of the tumor, our study has revealed that the impairment is progressive and is worsened by the adaptive immunosuppression such that T cells present in the tumor at later time points after treatment are more impaired than those present at earlier time points. This is manifest in experiments both through ex vivo analysis of the TIL and through direct monitoring of T-cell activity within the tumor. In a recent report, we demonstrated that, following immunization with rHuAd5-hDCT, T-cell activity in the tumor could be restored by treating with a combination of antibodies against 4-1BB and PD-1.23 Consistent with the evidence of increased immune attack in the tumor, the combination treatment resulted in regression of all treated tumors. Notably, the increased local immune attack elicited through the combination therapy was also accompanied by increased intratumoral expression of the suppressive ligands PD-L1 and PD-L2, further demonstrating the ability of the tumor environment to adapt to local immunological assault. Importantly, the combination treatment did not correct the functional impairments within the tumor-infiltrating T cells, suggesting that it may not be necessary to reverse the “exhausted” phenotype of the TIL but rather relieve the encumbrances within the tumor that prevent them from becoming fully engaged.

Our current study was focused on adoptive transfer of tumor-specific CD8+ T cells to augment the immune response produced by the rHuAd5-hDCT vaccine. It has been reported that CD4+ T cells can improve the antitumor effect of CD8+ T cells in adoptive transfer settings.34,35 Thus, further investigation is required to determine whether additional CD4+ T cell help may overcome the adaptive immunosuppression instigated by the CD8+ T cells. CD4+ T cells can also mediate direct antitumor effects.36,37,38 Whether CD4+ T cells would elicit a similar adaptive response or display similar loss of functionality remains to be determined. Further research is required to understand the reciprocal interactions between the tumor and the various T-cell subsets.

The global analysis of gene expression within the tumor has provided important new insight into the complexity and rapidity of the tumor adaptation to immune attack. We noted that many, but not all, of the immunosuppressive genes upregulated during this adaptation were induced by IFN-γ. As a consequence, blockade of IFN-γ signaling actually enhanced local T-cell activity (measured as IFN-γ transcription). Despite the improvement in local T-cell activity following IFN-γ blockade, the tumors actually grew more rapidly because we also blocked the desirable antitumor effects of IFN-γ. Isolation of T cells from the tumor allowed us to directly confirm IFN-γ transcription by TIL (AJR McGray and JL Bramson, unpublished data). In contrast, other transcripts, such as TNF-α and PD-L1, were expressed by multiple infiltrating populations, including T cells and myeloid cells. Given the complexity of cells that make up the growing tumor, the source of specific immunosuppressive genes cannot be confirmed at this time and we have reason to believe that the cell populations within the tumor change during the adaptive response. A number of the genes that were upregulated in tumors treated with rHuAd5-hDCT were consistent with a change in the monocyte/macrophage/dendritic cell compartment, so it is quite likely that infiltrating cells are also contributing to the suppression of T cells, including myeloid derived suppressor cells. Interestingly, pathway analysis of genes induced in the tumor following rHuAd5-hDCT immunization revealed changes associated with IL-12 family members, IL-12, IL-23, and IL-27. It is noteworthy that recent studies have demonstrated that T cells engineered to express IL-12 display more potent tumor regression due to IL-12 signaling on myeloid cells.39 It is tempting to speculate that these myeloid cells were not present within the tumor at the time of treatment but were recruited into the tumor in response to immune attack and the IL-12 produced by the T cells promoted tumoricidal differentiation and overcame the adaptive response. In that regard, it is equally interesting to note an enrichment in genes associated with GM-CSF signaling and amb2 integrin signaling following rHuAd5-hDCT vaccination, both of which are indicative of activation of myeloid cells. The lack of efficacy of the rHuAd5-hDCT suggests that the activity of these pathways must either reach a certain threshold to trigger tumor destruction or be sustained for longer periods to influence the suppressive qualities of infiltrating myeloid cells. Further investigation is therefore required to determine how chemokines and cytokines released in the tumor environment following immune attack influences the recruitment and activity of immune inhibitory cell populations.

Overall, our findings highlight a critical limitation of cancer vaccines, namely the ability of the local tumor environment to rapidly adapt to early low-level immune attack prior to maximal induction of the targeted immune response. These findings have important implications in the future design of vaccination strategies for clinical use and provide important rationale for investigating local events within the tumor as a means of understanding the impact of immunotherapeutic treatments. Importantly, profiling of the tumor environment may allow for a better understanding of suppressive mechanisms within the tumor that lead to poor vaccine performance and may assist in addressing likely hurdles for future cancer vaccine treatment.

Materials and Methods

Mice. Female C57BL/6 mice were purchased from Charles River Breeding Laboratory (Wilmington, MA). IFN-γ-deficient mice were purchased from Jackson Laboratories (Bar Harbor, ME). TCR-transgenic mice bearing a high-avidity TCR transgene specific for the H-2Kb–restricted epitope DCT180–188 were kindly provided by Dr Arthur Hurwitz (National Cancer Institute, Frederick, MD). All of our investigations have been approved by the McMaster Animal Research Ethics Board.

Recombinant adenoviruses. The E1,E3-deleted recombinant human adenovirus serotype 5 (rHuAd5) vectors40 used in this study have been described previously.41,42 rHuAd5-hDCT expresses the full-length human DCT gene. rHuAd5-hgp100 expresses the full-length human gp100 gene. rHuAd5-LCMV-GP encodes the dominant CD8+ and CD4+ T-cell epitopes of the lymphocytic choriomeningitis virus glycoprotein.

Tumor challenge and immunization. Mice were challenged intradermally with 105 B16F10 cells in 30 μl phosphate-buffered saline as previously described.21 108 pfu of Ad vector was prepared in 100 μl phosphate-buffered saline and injected in both rear thighs (50 μl/thigh) 5 days after tumor challenge. Tumor growth was monitored daily and measured with calipers every other day or daily as tumors approached endpoint. Tumor volume was calculated as width × length × depth. For experiments involving adoptive transfer of naïve TCR-transgenic DCT-specific T cells (referred to as DCTT cells), cells were isolated from the spleen and lymph nodes of naïve mice and subjected to ammonium-chloride-potassium-mediated lysis of red blood cells. Cells were then enumerated and viability confirmed to be greater than 80% by trypan blue exclusion. Following this, cells were prepared as to allow for delivery of the indicated number of viable cells in 200 μl phosphate-buffered saline. DCTT cells were administered within 2–3 hours of vaccination by intravenous injection.

Isolation of TILs. TIL were isolated as previously described.21 Briefly, tumors were digested in a mixture of 0.5 mg/ml collagenase type I (Gibco, Life Technologies, Grand Island, NY), 0.2 mg/ml DNase (Roche, Indianapolis, IN) and 0.02 mg/ml hyalorunidase (Sigma, St Louis, MO) prepared in Hank's buffered saline (Sigma; 10 ml/250 mg of tumor). The digested material was passed successively through 70 μm and 40 μm nylon cell strainers (BD Biosciences, San Jose, CA) and lymphocytes were purified using either mouse CD90.2 or CD45.2 positive selection by magnetic separation (EasySep, Stemcell Technologies, Vancouver, Canada). Prior to staining of TIL samples for analysis by flow cytometry, cells were stained using LIVE/DEAD fixable dead cell stain (Invitrogen, Carlsbad, CA) to permit the discrimination of viable cells.

Monoclonal antibodies. In all cases, monoclonal antibodies were delivered to mice by intraperitoneal injection in 500 μl phosphate-buffered saline. For depletion and neutralization experiments, CD4 (clone GK1.5), CD8 (clone 2.43), and IFN-γ (clone R4-6A2) antibodies were produced in our laboratory from hybridomas obtained from the American Type and Culture Collection (Manassas, VA). Depletion or neutralization was commenced 3 days following vaccination. For CD4+ and CD8+ T-cell depletion, 200 μg of the indicated antibody was delivered on 2 consecutive days, then every second (GK1.5) or third (2.43) day. Depletion of the desired T-cell population(s) was confirmed to be greater than 98% in the spleen by flow cytometry (data not shown). For IFN-γ neutralization, 250 μg–1 mg of antibody was delivered every other day. Successful neutralization of IFN-γ signaling at administered doses was confirmed based on the ability of antibody treatment to successfully block PD-L1 induction in the tumor following vaccination to similar levels as observed in IFN-γ−/− mice (data not shown). For blockade of immune checkpoint receptors, 250 μg each of αPD-1 (RMP1-14), αLAG-3 (C9B7W), and αTIM-3 (RMT3-23) (purchased from Bio X Cell, West Lebanon, NH) was delivered, every 3rd day beginning 3 days following immunization with rHuAd5-hDCT for a total of four doses. All flow cytometry antibodies (anti-CD16/CD32, anti-CD28, anti-CD4-PE-Cy7, anti-CD8α-PerCP-Cy5.5, anti-Thy1.1-PE, anti-CD107a-FITC, anti-IFN-γ-APC and anti-TNF-α-FITC) were purchased from BD Biosciences (San Jose, CA).

Intracellular cytokine staining. CD8+ T-cell epitope peptides (DCT180–188, hDCT342–351, hDCT363–371, LCMV-GP31–43 and LCMV-GP34–41) were purchased from Biomer Technologies (Pleasanton, CA) dissolved in dimethyl sulfoxide and stored at −20 °C. CD8+ T-cell epitope peptides specific for gp100 were identified from epitope mapping assays (data not shown) and pooled for intracellular cytokine staining analysis. The intracellular cytokine staining method has been described previously.21 Briefly, lymphocytes were stimulated with pooled DCT, LCMV-GP, or gp100 peptides (1 μg/ml) for 5 hours at 37 °C in the presence of 8 μg/ml anti-CD28 and GolgiPlug protein transport inhibitor (1:1,000 v/v, BD Pharmingen, San Jose, CA). The CD107a mobilization assay was performed by adding anti-CD107a-FITC at the beginning of the peptide stimulation as described.21 Data were acquired on a FACSCanto (BD Biosciences) and analyzed using FlowJo software (TreeStar, Ashland, OR).

Immunohistochemistry. Tumors were excised from mice and fixed in 10% Neutral Buffered Formalin for a period of 5 days and then paraffin embedded, sectioned and stained at the Core Histology Facility, McMaster Immunology Research Centre. Tumors were sectioned at a thickness of 3 μm and stained for CD3 using an anti-CD3 rabbit monoclonal antibody (Clone SP7; Fisher Scientific, Pittsburgh, PA) using a pretreatment of EDTA buffer pH = 9 and Envision plus-rabbit detection (Dako Cytomation, Carpinteria, CA). Slides were developed using AEC chromogen and visualized with a Leica DMRA microscope using the 5× optical lens. Images were captured using a QImaging MicroPublisher 5.0 RTV camera and Openlab imaging software (PerkinElmer, Foster City, CA).

RNA extraction from solid tumors and quantitative real-time PCR. Tumors were excised, snap-frozen in liquid nitrogen and stored at −80 °C. Tumors were homogenized in Trizol (Invitrogen, Life Technologies, Grand Island, NY) using a Polytron PT 1200C (Kinematica, Bohemia, NY) and total RNA was extracted according to the manufacturer's specifications. RNA samples were further purified using an RNeasy mini kit (Qiagen, Valencia, CA) and treated with Ambion's DNA-free kit (Ambion, Austin, TX). Reverse transcription was performed with Superscript III First-Strand (Invitrogen) according to the manufacturer's instructions. Quantitative PCR was carried out on an ABI PRISM 7900HT Sequence Detection System (Applied Biosystems, Foster City, CA) using Perfecta SYBR Green SuperMix, ROX (Quanta Biosciences, Gaithersburg, MD). Reaction efficiency was determined for individual primer sets using a minimum of 5 serial dilutions to ensure similar efficiency between target and endogenous control reactions. Data for target genes of interest were analyzed via the delta/delta CT method using GAPDH as an endogenous control. Analysis was performed using Sequence Detector Software version 2.2 (Applied Biosystems, Life Technologies, Grand Island, NY). Primer sequences used for the detection of all genes are given in Table 1.

Table 1. Primer sequences used for the detection of all genes.

graphic file with name mt2013255t1.jpg

Open in a new tab

Gene expression analysis by microarray. RNA from B16F10 melanoma tumors was isolated (as described above) 5 or 7 days after vaccination for each treatment as indicated and prepared for profiling on either MouseRef-8_V2 beadchips (Illumina, San Diego, CA) (day 5 tumors) or Affymetrix (Santa Clara, CA) MoGene 1.0 ST gene chips (day 7 tumors) according to the manufacturer's protocol. Affymetrix array expression files were created from raw.CEL files and normalized using Robust multiarray analysis.43 Illumina expression files were created using the IlluminaExpressionFileCreator module available on Gene Pattern (http://genepattern.broadinstitute.org/gp/pages/index.jsf), similar to Illumina BeadStudio, from raw.IDAT files. Genes were considered differentially expressed if the fold change was >2.0 and q value <0.1. Gene ontology analysis was carried out using the DAVID Functional Annotation Resource,44 and pathway analysis was carried out using the NCI-Nature pathway interaction database resource.45 All datasets were filtered such that when multiple probes recognized the same gene transcripts, only the probe with the highest mean intensity was used.

Statistical analysis. Two-tailed, unpaired Student's t-tests were used to compare two treatment groups. One and two-way analysis of variances were used for data analysis of more than two groups and a Bonferroni posttest was utilized to determine significant differences between treatment groups. Survival data was compared using a logrank test. Results were generated using GraphPad Prism 4.0b software (GraphPad Software, San Diego, CA). Differences between means were considered significant at P < 0.05: *P < 0.05, **P < 0.01, ***P < 0.001.

SUPPLEMENTARY MATERIAL Figure S1. Dependence of intratumoral IFN-γ and TNF-α expression on CD8+ T cells and the polyfunctionality of DCT-specific CD8+ T cells over time following vaccination. Figure S2. Induction of additional suppressive genes within the tumor following rHuAd5-hDCT immunization is dependent on CD8+ T cells. Figure S3. Complete tumor regression following treatment with rHuAd5-hDCT + 106 DCTT cells requires persistent activity of CD8+ T cells. Figure S4. Transfer of 104 DCTT cells in combination with vaccination does not significantly alter tumor growth. Figure S5. Treatment with rHuAd5-hDCT + 106 DCTT cells results in tumor infiltration by a greater number of DCT-specific CD8+ T cells which distribute throughout the tumor. Table S1. Top 30 positively enriched pathways in the tumor following treatment with rHuAd5-hDCT Table S2. Comparison of top 10 GO terms associated with the differentially expressed genes following treatment with rHuAd5-hDCT ± 106 DCTT cells.

Acknowledgments

This work was supported by funds from the Terry Fox Foundation. D.B. was supported by a scholarship from the Canadian Institutes for Health Research. The authors declared no conflict of interest.

Supplementary Material

Supplementary Information
Click here for additional data file. (6.1MB, pdf)

References

  1. Schlom J. Therapeutic cancer vaccines: current status and moving forward. J Natl Cancer Inst. 2012;104:599–613. doi: 10.1093/jnci/djs033. [DOI] [PMC free article] [PubMed] [Google Scholar]
  2. Klebanoff CA, Acquavella N, Yu Z, Restifo NP. Therapeutic cancer vaccines: are we there yet. Immunol Rev. 2011;239:27–44. doi: 10.1111/j.1600-065X.2010.00979.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  3. Rosenberg SA. Raising the bar: the curative potential of human cancer immunotherapy. Sci Transl Med. 2012;4:127ps8. doi: 10.1126/scitranslmed.3003634. [DOI] [PMC free article] [PubMed] [Google Scholar]
  4. Kantoff PW, Schuetz TJ, Blumenstein BA, Glode LM, Bilhartz DL, Wyand M, et al. Overall survival analysis of a phase II randomized controlled trial of a Poxviral-based PSA-targeted immunotherapy in metastatic castration-resistant prostate cancer. J Clin Oncol. 2010;28:1099–1105. doi: 10.1200/JCO.2009.25.0597. [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. Schwartzentruber DJ, Lawson DH, Richards JM, Conry RM, Miller DM, Treisman J, et al. gp100 peptide vaccine and interleukin-2 in patients with advanced melanoma. N Engl J Med. 2011;364:2119–2127. doi: 10.1056/NEJMoa1012863. [DOI] [PMC free article] [PubMed] [Google Scholar]
  6. Schuster SJ, Neelapu SS, Gause BL, Janik JE, Muggia FM, Gockerman JP, et al. Vaccination with patient-specific tumor-derived antigen in first remission improves disease-free survival in follicular lymphoma. J Clin Oncol. 2011;29:2787–2794. doi: 10.1200/JCO.2010.33.3005. [DOI] [PMC free article] [PubMed] [Google Scholar]
  7. Odunsi K, Matsuzaki J, Karbach J, Neumann A, Mhawech-Fauceglia P, Miller A, et al. Efficacy of vaccination with recombinant vaccinia and fowlpox vectors expressing NY-ESO-1 antigen in ovarian cancer and melanoma patients. Proc Natl Acad Sci USA. 2012;109:5797–5802. doi: 10.1073/pnas.1117208109. [DOI] [PMC free article] [PubMed] [Google Scholar]
  8. Kantoff PW, Higano CS, Shore ND, Berger ER, Small EJ, Penson DF, et al. IMPACT Study Investigators Sipuleucel-T immunotherapy for castration-resistant prostate cancer. N Engl J Med. 2010;363:411–422. doi: 10.1056/NEJMoa1001294. [DOI] [PubMed] [Google Scholar]
  9. Sims RB. Development of sipuleucel-T: autologous cellular immunotherapy for the treatment of metastatic castrate resistant prostate cancer. Vaccine. 2012;30:4394–4397. doi: 10.1016/j.vaccine.2011.11.058. [DOI] [PubMed] [Google Scholar]
  10. Galluzzi L, Vacchelli E, Eggermont A, Fridman WH, Galon J, Sautès-Fridman C, et al. Trial Watch: Adoptive cell transfer immunotherapy. Oncoimmunology. 2012;1:306–315. doi: 10.4161/onci.19549. [DOI] [PMC free article] [PubMed] [Google Scholar]
  11. Porter DL, Levine BL, Kalos M, Bagg A, June CH. Chimeric antigen receptor-modified T cells in chronic lymphoid leukemia. N Engl J Med. 2011;365:725–733. doi: 10.1056/NEJMoa1103849. [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. Kochenderfer JN, Dudley ME, Feldman SA, Wilson WH, Spaner DE, Maric I, et al. B-cell depletion and remissions of malignancy along with cytokine-associated toxicity in a clinical trial of anti-CD19 chimeric-antigen-receptor-transduced T cells. Blood. 2012;119:2709–2720. doi: 10.1182/blood-2011-10-384388. [DOI] [PMC free article] [PubMed] [Google Scholar]
  13. Rosenberg SA, Yang JC, Sherry RM, Kammula US, Hughes MS, Phan GQ, et al. Durable complete responses in heavily pretreated patients with metastatic melanoma using T-cell transfer immunotherapy. Clin Cancer Res. 2011;17:4550–4557. doi: 10.1158/1078-0432.CCR-11-0116. [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Malyguine AM, Strobl SL, Shurin MR. Immunological monitoring of the tumor immunoenvironment for clinical trials. Cancer Immunol Immunother. 2012;61:239–247. doi: 10.1007/s00262-011-1148-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
  15. Gajewski TF, Fuertes M, Spaapen R, Zheng Y, Kline J. Molecular profiling to identify relevant immune resistance mechanisms in the tumor microenvironment. Curr Opin Immunol. 2011;23:286–292. doi: 10.1016/j.coi.2010.11.013. [DOI] [PMC free article] [PubMed] [Google Scholar]
  16. Gajewski TF. Cancer immunotherapy. Mol Oncol. 2012;6:242–250. doi: 10.1016/j.molonc.2012.01.002. [DOI] [PMC free article] [PubMed] [Google Scholar]
  17. Stewart TJ, Smyth MJ. Improving cancer immunotherapy by targeting tumor-induced immune suppression. Cancer Metastasis Rev. 2011;30:125–140. doi: 10.1007/s10555-011-9280-5. [DOI] [PubMed] [Google Scholar]
  18. Schreiber RD, Old LJ, Smyth MJ. Cancer immunoediting: integrating immunity's roles in cancer suppression and promotion. Science. 2011;331:1565–1570. doi: 10.1126/science.1203486. [DOI] [PubMed] [Google Scholar]
  19. Landsberg J, Kohlmeyer J, Renn M, Bald T, Rogava M, Cron M, et al. Melanomas resist T-cell therapy through inflammation-induced reversible dedifferentiation. Nature. 2012;490:412–416. doi: 10.1038/nature11538. [DOI] [PubMed] [Google Scholar]
  20. Kaluza KM, Thompson JM, Kottke TJ, Flynn Gilmer HC, Knutson DL, Vile RG. Adoptive T cell therapy promotes the emergence of genomically altered tumor escape variants. Int J Cancer. 2012;131:844–854. doi: 10.1002/ijc.26447. [DOI] [PMC free article] [PubMed] [Google Scholar]
  21. Grinshtein N, Ventresca M, Margl R, Bernard D, Yang TC, Millar JB, et al. High-dose chemotherapy augments the efficacy of recombinant adenovirus vaccines and improves the therapeutic outcome. Cancer Gene Ther. 2009;16:338–350. doi: 10.1038/cgt.2008.89. [DOI] [PubMed] [Google Scholar]
  22. Slifka MK, Rodriguez F, Whitton JL. Rapid on/off cycling of cytokine production by virus-specific CD8+ T cells. Nature. 1999;401:76–79. doi: 10.1038/43454. [DOI] [PubMed] [Google Scholar]
  23. McGray AJ, Bernard D, Hallett R, Kelly R, Jha M, Gregory C, et al. Combined vaccination and immunostimulatory antibodies provides durable cure of murine melanoma and induces transcriptional changes associated with positive outcome in human melanoma patients. Oncoimmunology. 2012;1:419–431. doi: 10.4161/onci.19534. [DOI] [PMC free article] [PubMed] [Google Scholar]
  24. Bernal M, Ruiz-Cabello F, Concha A, Paschen A, Garrido F. Implication of the ß2-microglobulin gene in the generation of tumor escape phenotypes. Cancer Immunol Immunother. 2012;61:1359–1371. doi: 10.1007/s00262-012-1321-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
  25. Zhang B, Karrison T, Rowley DA, Schreiber H. IFN-gamma- and TNF-dependent bystander eradication of antigen-loss variants in established mouse cancers. J Clin Invest. 2008;118:1398–1404. doi: 10.1172/JCI33522. [DOI] [PMC free article] [PubMed] [Google Scholar]
  26. Khong HT, Restifo NP. Natural selection of tumor variants in the generation of “tumor escape” phenotypes. Nat Immunol. 2002;3:999–1005. doi: 10.1038/ni1102-999. [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. Taube JMJ, Anders RAR, Young GDG, Xu HH, Sharma RR, McMiller TLT, et al. Colocalization of inflammatory response with B7-h1 expression in human melanocytic lesions supports an adaptive resistance mechanism of immune escape. Sci Trans Med. 2012;4:127ra37. doi: 10.1126/scitranslmed.3003689. [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. Hamanishi J, Mandai M, Iwasaki M, Okazaki T, Tanaka Y, Yamaguchi K, et al. Programmed cell death 1 ligand 1 and tumor-infiltrating CD8+ T lymphocytes are prognostic factors of human ovarian cancer. Proc Natl Acad Sci USA. 2007;104:3360–3365. doi: 10.1073/pnas.0611533104. [DOI] [PMC free article] [PubMed] [Google Scholar]
  29. Robbins PF, Morgan RA, Feldman SA, Yang JC, Sherry RM, Dudley ME, et al. Tumor regression in patients with metastatic synovial cell sarcoma and melanoma using genetically engineered lymphocytes reactive with NY-ESO-1. J Clin Oncol. 2011;29:917–924. doi: 10.1200/JCO.2010.32.2537. [DOI] [PMC free article] [PubMed] [Google Scholar]
  30. Ahmadzadeh M, Johnson LA, Heemskerk B, Wunderlich JR, Dudley ME, White DE, et al. Tumor antigen-specific CD8 T cells infiltrating the tumor express high levels of PD-1 and are functionally impaired. Blood. 2009;114:1537–1544. doi: 10.1182/blood-2008-12-195792. [DOI] [PMC free article] [PubMed] [Google Scholar]
  31. Harlin H, Meng Y, Peterson AC, Zha Y, Tretiakova M, Slingluff C, et al. Chemokine expression in melanoma metastases associated with CD8+ T-cell recruitment. Cancer Res. 2009;69:3077–3085. doi: 10.1158/0008-5472.CAN-08-2281. [DOI] [PMC free article] [PubMed] [Google Scholar]
  32. Baitsch L, Baumgaertner P, Devêvre E, Raghav SK, Legat A, Barba L, et al. Exhaustion of tumor-specific CD8? T cells in metastases from melanoma patients. J Clin Invest. 2011;121:2350–2360. doi: 10.1172/JCI46102. [DOI] [PMC free article] [PubMed] [Google Scholar]
  33. Gajewski TF. Failure at the effector phase: immune barriers at the level of the melanoma tumor microenvironment. Clin Cancer Res. 2007;13 18 Pt 1:5256–5261. doi: 10.1158/1078-0432.CCR-07-0892. [DOI] [PubMed] [Google Scholar]
  34. Bos R, Sherman LA. CD4+ T-cell help in the tumor milieu is required for recruitment and cytolytic function of CD8+ T lymphocytes. Cancer Res. 2010;70:8368–8377. doi: 10.1158/0008-5472.CAN-10-1322. [DOI] [PMC free article] [PubMed] [Google Scholar]
  35. Shafer-Weaver KA, Watkins SK, Anderson MJ, Draper LJ, Malyguine A, Alvord WG, et al. Immunity to murine prostatic tumors: continuous provision of T-cell help prevents CD8 T-cell tolerance and activates tumor-infiltrating dendritic cells. Cancer Res. 2009;69:6256–6264. doi: 10.1158/0008-5472.CAN-08-4516. [DOI] [PMC free article] [PubMed] [Google Scholar] [Retracted]
  36. Corthay A, Skovseth DK, Lundin KU, Røsjø E, Omholt H, Hofgaard PO, et al. Primary antitumor immune response mediated by CD4+ T cells. Immunity. 2005;22:371–383. doi: 10.1016/j.immuni.2005.02.003. [DOI] [PubMed] [Google Scholar]
  37. Perez-Diez A, Joncker NT, Choi K, Chan WF, Anderson CC, Lantz O, et al. CD4 cells can be more efficient at tumor rejection than CD8 cells. Blood. 2007;109:5346–5354. doi: 10.1182/blood-2006-10-051318. [DOI] [PMC free article] [PubMed] [Google Scholar]
  38. Muranski P, Boni A, Antony PA, Cassard L, Irvine KR, Kaiser A, et al. Tumor-specific Th17-polarized cells eradicate large established melanoma. Blood. 2008;112:362–373. doi: 10.1182/blood-2007-11-120998. [DOI] [PMC free article] [PubMed] [Google Scholar]
  39. Kerkar SP, Goldszmid RS, Muranski P, Chinnasamy D, Yu Z, Reger RN, et al. IL-12 triggers a programmatic change in dysfunctional myeloid-derived cells within mouse tumors. J Clin Invest. 2011;121:4746–4757. doi: 10.1172/JCI58814. [DOI] [PMC free article] [PubMed] [Google Scholar]
  40. Ng P, Parks RJ, Cummings DT, Evelegh CM, Graham FL. An enhanced system for construction of adenoviral vectors by the two-plasmid rescue method. Hum Gene Ther. 2000;11:693–699. doi: 10.1089/10430340050015590. [DOI] [PubMed] [Google Scholar]
  41. Leitch J, Fraser K, Lane C, Putzu K, Adema GJ, Zhang QJ, et al. CTL-dependent and -independent antitumor immunity is determined by the tumor not the vaccine. J Immunol. 2004;172:5200–5205. doi: 10.4049/jimmunol.172.9.5200. [DOI] [PubMed] [Google Scholar]
  42. Bernard D, Ventresca MS, Marshall LA, Evelegh C, Wan Y, Bramson JL. Processing of tumor antigen differentially impacts the development of helper and effector CD4+ T-cell responses. Mol Ther. 2010;18:1224–1232. doi: 10.1038/mt.2010.30. [DOI] [PMC free article] [PubMed] [Google Scholar]
  43. Irizarry RA, Hobbs B, Collin F, Beazer-Barclay YD, Antonellis KJ, Scherf U, et al. Exploration, normalization, and summaries of high density oligonucleotide array probe level data. Biostatistics. 2003;4:249–264. doi: 10.1093/biostatistics/4.2.249. [DOI] [PubMed] [Google Scholar]
  44. Huang DW, Sherman BT, Lempicki RA. Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat Protoc. 2009;4:44–57. doi: 10.1038/nprot.2008.211. [DOI] [PubMed] [Google Scholar]
  45. Schaefer CF, Anthony K, Krupa S, Buchoff J, Day M, Hannay T, et al. PID: the Pathway Interaction Database. Nucleic Acids Res. 2009;37 Database issue:D674–D679. doi: 10.1093/nar/gkn653. [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplementary Information
Click here for additional data file. (6.1MB, pdf)

Articles from Molecular Therapy are provided here courtesy of The American Society of Gene & Cell Therapy

RESOURCES