Multi-Antigen Spherical Nucleic Acid Cancer Vaccines

Abstract

Cancer vaccines must activate multiple immune cell types to be effective against aggressive tumors, but design considerations for these multi-targeted vaccines are underexplored. Herein, we demonstrate the impact of structural presentation of multiple antigenic peptides on immune responses at transcriptomic, cellular, and organismal levels. Spherical nucleic acid (SNA) nanoconstructs were used to investigate differences in antigen processing, cytokine production, and memory stemming from spatial distribution and nanoscale placement of two antigen classes to activate two T cell types. A single dual-antigen SNA (DA-SNA), compared to two single-antigen SNAs, elicited a 30% and two-fold increase in antigen-specific T cell activation and proliferation, respectively. Antigen placement within DA-SNAs changed immunological gene expression and tumor growth: encapsulating helper and externally-conjugating cytotoxic T cell antigens (termed DA-SNA 2) elevated antitumor gene pathways, stalling tumors in mice with lymphoma. When combined with anti-PD-1 checkpoint inhibitor in clinically relevant melanoma, DA-SNA 2 suppressed tumors and increased circulating T cell memory. This work highlights the importance of implementing structural control afforded by modular nanoscale architectures to synthesize multi-antigen vaccines with improved efficacy.

Introduction

Vaccination is an attractive strategy against cancers expressing targetable tumor-associated antigens and neoantigens. For melanoma, increasing efforts have been made to develop vaccines targeting identified tumor-associated proteins (e.g., gp100, MAGE-A3, MART-1, NY-ESO-1).^1–4 However, while these vaccines elicit some benefits (i.e., increasing activated melanoma-specific T cells), many are designed to primarily activate cytotoxic T cells. Tumors can have significant heterogeneity and high mutational burdens^{5, 6} that allow for easy escape of immune surveillance.⁷ Thus, vaccines that primarily rely on cytotoxic T cell activity are inadequate, necessitating vaccines containing antigens targeting multiple immune cell types to induce enhanced tumor remission.

Common approaches to elicit a multi-faceted immune response include administration of: 1) “long peptides” whose sequence covers multiple epitopes to activate both cytotoxic and helper T cells, or 2) multiple “minimal” peptide antigens each unique to T cell subclasses.^8–11 However, many of these ongoing efforts involve pools of peptides, with or without an adjuvant, delivered in saline as a mixture. Recently, simple changes to the delivery of vaccine components through the use of basic chemical linkages¹² or nanotechnology^13–16 have demonstrated the potential of structuring vaccines to improve potency. This concept, termed rational vaccinology, offers a path to structurally optimize the placement of antigens targeting multiple immune cell types within a vaccine for broad antitumor immunity.

This work explores the vaccine design space involving multiple cell-targeting antigens. By employing structural changes in antigen placement, we elucidate the impact of the resulting immune response and harness it to drive success in translational efforts. Antigens used activate cytotoxic (CD8⁺) T cells to effectively kill tumors, as well as helper (CD4⁺) T cells to synergize immune interactions for long-lasting tumor rejection.^{17, 18} CD4⁺ T cells maintain tumor-directed CD8⁺ functionality by recruiting them to the tumor site and enhancing their proliferation and effector functions.^19–23 Therefore, vaccines in this work consider precise structural placement of both major histocompatibility complex (MHC)-I and -II restricted antigen targets (CD8⁺- and CD4⁺-activating, respectively) to prime the immune system most effectively.

Herein, the spherical nucleic acid (SNA) platform is utilized to elucidate the effect of nanoscale structure on multi-antigen immunological processes. The SNA is comprised of a nanoparticle core (e.g., liposome) with a dense, radially arranged surface of oligonucleotides. SNAs are powerful tools to explore these complex relationships because of their biocompatibility,²⁴ ability to rapidly enter cells in high quantities,^{25, 26} potent immune activation when employing toll-like receptor 9 (TLR9) agonist DNA as the shell,²⁷ and modularity that enables the defined nanoscale placement of components using well-known chemistry.^28–30 In this work, we demonstrate how the structures of SNA vaccines carrying multiple immune cell targeting peptide antigens greatly influences immune activation. Changing the position of the antigen type within the SNA alters dendritic cell processing, upregulates immune cell pathways at the transcriptome level, enhances production and secretion of cytokines and memory markers at the cellular level, and slows tumor growth at the organismal level. Collectively, these changes define vaccine potency against an aggressive B16-F10 melanoma tumor model and, importantly, elucidate design insights regarding the placement of multiple peptide antigens that can translate to other therapeutics and guide their development.

Results and Discussion

We sought to determine the optimal antigen processing conditions for multi-antigen SNA vaccines to generate robust cytotoxic and helper T cell responses. In particular, we investigated how the delivery of peptides for two antigen classes (MHC-I and -II restricted) to dendritic cells (DCs) would change processing in vitro. DCs are critical professional antigen-presenting cells that induce signaling for effective T cell priming. Previous literature has demonstrated the potential to enhance DC activation through simultaneous delivery of both cytotoxic and helper antigens,^{31, 32} but none have had a platform capable of understanding the best way to present such antigens.¹⁴ We hypothesized that the simultaneous delivery of both antigen classes on the same nanoparticle, as opposed to their delivery on different nanoparticles, enhances the activation of both T cell types, and that the structural location of the antigens markedly impacts vaccine performance.

Processing of Multiple Antigens In Vitro Based on Antigen Distribution on SNAs

To test this theory, we designed and synthesized dual-antigen SNA vaccines (DA-SNAs) that contained both MHC-I and -II restricted antigens in different nanoscale locations (termed DA-SNA 1 and DA-SNA 2 based on placement of each antigen, Figure 1A). Due to the modularity of SNAs, there are multiple different locations within the SNA construct where antigens can be placed. For this work, encapsulation and hybridization arrangements were selected for antigen placement and compared to one another. To assess how the distribution of antigens and delivery on different nanoparticles affect immune activation, formulations containing two individual SNAs, each presenting only one antigen class in the same position as in the DA-SNA vaccine, were synthesized (Supplementary Figure 1). The formulations were termed “separate” for the individual SNAs delivering a single antigen and “combined” for the dual-antigen containing DA-SNA.

Figure 1. The delivery of two classes of antigen from spherical nucleic acid (SNA) vaccines alters how the antigens are processed in vitro.

a) Dual-antigen SNA (DA-SNA) vaccines synthesized to alter the placement of MHC-I and MHC-II restricted antigens within the same nanoparticle structure. b) The expression (measured through median fluorescence intensity (MFI)) of co-stimulatory markers CD80 (left) and CD86 (right) on CD11c⁺ DCs based on delivery of the two antigen classes on either separate nanoparticles (dashed, separate) or a singular DA-SNA (solid, combined). (left) Untreated versus Admix (P < 0.0001), Separate OVA1 Encapsulated & OVA2 Hybridized (P = 0.0433), and Separate and Combined OVA2 Encapsulated & OVA1 Hybridized (P < 0.0001 for both). Separate versus Combined OVA2 Encapsulated & OVA1 Hybridized (P = 0.0332). (right) Untreated versus Admix (P = 0.0163), and Separate and Combined OVA2 Encapsulated & OVA1 Hybridized (P = 0.0012 and 0.005, respectively). c) CD8⁺ T cells specific for the OVA1 antigen (left) or CD4⁺ T cells specific for the OVA2 antigen raised from a co-culture of treatment-pulsed DCs with naïve splenic T cells. (left) T cell versus Separate and Combined OVA1 Encapsulated & OVA2 Hybridized (P = 0.0025 and 0.0016, respectively) and Separate and Combined OVA2 Encapsulated & OVA1 Hybridized (P = 0.0017 and 0.0094, respectively). (right) T cell versus Combined OVA1 Encapsulated & OVA2 Hybridized (P = 0.0268) and Combined OVA2 Encapsulated & OVA1 Hybridized (P = 0.0285). d) MFI of CD69 activation marker signal within the population of antigen-specific CD8⁺ (left) or CD4⁺ (right) T cells. (right) T cell versus Combined OVA2 Encapsulated & OVA1 Hybridized (P = 0.0047). e) Fold-change in T cell proliferation from OT1 splenocytes specific for the OVA1 antigen after co-culture with treatment-pulsed DCs. (left) Separate versus Combined OVA1 Encapsulated & OVA2 Hybridized (P = 0.0036); (right) Separate versus Combined OVA2 Encapsulated & OVA1 Hybridized (P = 0.0306). For all panels, mean ± s.e.m. shown, along with statistical significance between relevant comparisons. Significance was calculated using a one-way ANOVA with Sidak’s multiple comparisons test, with n = 3–4 replicates per group. ns = non-significant; *p < 0.05; **p < 0.01; ****p < 0.0001.

To synthesize DA-SNAs, a peptide from one antigen class was encapsulated into 50 nm 1,2-dioleoyl-sn-glycero-3-phosphocholine (DOPC) liposomes during their formation (Supplementary Figures 2–3). In parallel, the peptide of the other antigen class was conjugated to a strand complementary to the CpG motif adjuvant DNA shell (“CpG complement”) of the SNA using disulfide bond formation (Supplementary Figure 4). DNA and peptide sequences used in this work can be found in Supplementary Tables 1–2. A hybridized duplex was formed by slow-cooling the CpG complement with an appended antigen to a complementary 3’-cholesterol-terminated CpG strand. The cholesterol anchors the duplex to the surface of the liposome. These two strands have been previously shown to effectively duplex at temperatures below ~56 °C.^{33, 34} This hybridized product was added to the liposomes to obtain an equimolar amount of each antigen. The liposome surface was backfilled with non-targeting T20 DNA that did not contain antigen to obtain 75 total DNA strands per liposome, equivalent to a density of 1.6 pmol/cm², at which properties associated with SNAs that make them useful in biology are observed.¹⁶ SNAs containing either a single encapsulated antigen or a single hybridized antigen (the “separate” formulations) were synthesized following previous protocols.¹⁶ SNA formation was confirmed using dynamic light scattering (Supplementary Figure 5), and stability of the nanostructures was maintained over 45 days (Supplementary Figure 6).

Once these different structures were synthesized, their ability to prime DCs was assessed using MHC-I and -II restricted model antigens of ovalbumin (OVA), known as OVA1 and OVA2, respectively. The activation of DC cues and the ability to prime T cells was characterized using murine bone marrow-derived DCs (BMDCs) and antigens delivered as two separate SNA structures versus the combined DA-SNA vaccine. An overnight incubation of BMDCs with the different vaccine structural arrangements showed that the percentage of CD11c⁺ DCs expressing innate co-stimulation markers CD86 and CD80 did not significantly change (Supplementary Figure 7). This is likely attributed to the fact that an extended incubation can lead to equivalent levels of adjuvant delivery between the combined and separate formulations and indicates that hybridization to CpG does not interfere with TLR9 activation. To maximize differences and evaluate the impact of early kinetics on immunostimulatory activity and the expression of the co-stimulatory markers, we pulsed DCs with the various structural formulations for 30 min and replaced the media before allowing the DCs time to express co-stimulatory signals. These results (Figure 1B) illustrate that the arrangement of antigens with OVA1 hybridized and OVA2 encapsulated in either separate nanoparticles or one single DA-SNA construct leads to significant expression of CD80 and CD86. Upon analysis of a range of doses, elevated CD80 and CD86 expression occurs when higher concentrations are used, and it is not due to a preferred interaction of MHC-I with peptide that could lead to enhanced internalization. This trend is also exhibited, albeit to a lesser extent, when using SNAs containing a different set of peptides (Supplementary Figure 8). The presentation of antigens to naïve splenic T cells to raise antigen-specific T cells, an indicator of the immune system’s ability to recognize tumor antigens³⁵ was not impacted by the way antigens were arranged; naïve T cells were able to clonally expand into OVA1- and OVA2-specific T cells (Figure 1C; gating strategy in Supplementary Figure 9). Indeed, ca. 0.6 – 0.7 % of the live CD19⁻ population was double-positive for the OVA1-H-2k^b dimer and CD8⁺ marker. Similar trends were observed for OVA2-specific T cell differentiation, with ca. 0.9 – 1.1 % containing double-positive markers for the OVA2-H-2-Ia^d tetramer and CD4⁺ antibody. Only the DA-SNA structures, and not the separate formulations, were capable of significantly elevating the amount of antigen-specific T cells above that of the T cell control baseline; this suggests the combined delivery of both antigens to DCs leads to stronger T cell differentiation. This is more apparent when assessing expression of the early activation marker CD69 within either antigen-specific T cell populations. An increased amount of CD69 signal (as measured by median fluorescence intensity, MFI) is present when the antigens are delivered combined as one DA-SNA, with the DA-SNA 2 structure outperforming all tested groups (Figure 1D). Moreover, delivery of antigens in DA-SNA structures regardless of the antigen placement translates to a two-fold increase in T cell proliferation, an important step in antitumor responses, using OT1 splenocytes specific for the OVA1 antigen (Figure 1E).

In Vivo Activation via DA-SNAs

Based on these promising in vitro findings using DA-SNAs, we evaluated how the arrangement of the antigens delivered affected the in vivo immune responses. C57BL/6 mice were immunized to delineate how the formulation of antigen on separate or the same nanostructures and how different placement of MHC-I and -II restricted antigens within DA-SNA vaccines, affect immune activation. Mice were given three total injections (6 nmol by DNA and each peptide; Figure 2A and Supplementary Figure 10). On day 35, splenocytes were harvested to assess raised specific immune responses towards both peptide antigens. After the five-week period, CD8⁺ levels were significantly elevated for DA-SNA 2 immunization, reaching ca. 35% of the spleen population, compared to when a simple mixture containing both peptide antigens and adjuvant DNA (termed “admix”), DA-SNA 1, and the separate equivalents of both DA-SNAs were used (Figure 2B). CD4⁺ levels were only significantly changed when mice were treated with the separate equivalent of DA-SNA 1. Other treatment groups decreased the level of CD4⁺ splenic T cells with the DA-SNA 2 group at the lowest with ca. 11.4% of the spleen cell population (Figure 2B). DA-SNA 2 most significantly elevated the production of a key pro-inflammatory cytokine, IFN-γ, as well as degranulation marker, CD107a, upon restimulation with OVA1 peptide ex vivo. DA-SNA 2 immunization also generated the largest percentage of polyfunctional splenic CD8⁺ T cells (ca. 15%, Figure 2C, gating strategy can be found in Supplementary Figure 11). Moreover, this correlated with an increase in the percentage of effector memory CD8⁺ T cells (CD44⁺CD62L⁻, ca. 54%) (Figure 2D, left). The levels of pro-inflammatory markers produced in CD8⁺ T cells and the polyfunctionality of the population were significantly elevated for the combined DA-SNA 2 structure compared to its separate counterpart (Figure 2C). Ex vivo stimulation of CD4⁺ T cells with OVA2 peptide showed an overall increase in these same parameters for both DA-SNAs and the separate formulations compared to admix treatment, further demonstrating the importance of the combined delivery of antigen and adjuvant to an immune cell. There was no significant difference observed between the DA-SNA 1 structure and its separate equivalent. These two constructs induced the highest levels of these pro-inflammatory markers in CD4⁺ T cells, although a statistically significant decrease was not observed between the two DA-SNAs (Figure 2C). Moreover, the greatest elevation in OVA1 specific CD8⁺ T cells is observed for DA-SNA 2, ca. three-fold higher than its separate equivalent (Figure 2E). Ultimately, the contribution of the combined delivery of both antigen types in the DA-SNA structures led to greater IFN-γ secretion as measured through an enzyme-linked immune absorbent spot (ELISpot) assay. Levels of spot-forming cells (SFCs) upon ex vivo stimulation with the MHC-I restricted OVA1 antigen were greatest with DA-SNA 2, and DA-SNA 2 generated 2.3-fold higher SFCs than its separate counterpart upon either MHC-I or -II antigen (OVA2) ex vivo stimulation (Figure 2F). An elevation in SFCs was observed for both DA-SNA structures compared to the admix; the largest enhancement overall was seen for DA-SNA 2. Splenocytes raised by DA-SNA 2 immunization led to ca. 2.2-fold and ca. 1.7-fold more SFCs than DA-SNA 1 immunization when stimulated ex vivo with either OVA1 or OVA2, respectively, demonstrating the potency utilizing this arrangement of antigens on a DA-SNA to respond ex vivo to MHC-I or -II restricted antigen cues. The administration of OVA1 encapsulated and OVA2 hybridized antigens displayed differences between the separate and combined formulations, with the combined DA-SNA 1 structure elevating SFCs to a greater extent upon OVA1 ex vivo stimulation, and the separate formulation elevating SFCs to a greater extent upon OVA2 ex vivo stimulation. Taking this entire study holistically, and given the role of CD8⁺ T cells in antitumor activity and the importance of activating both subsets of T cell responses effectively, we harnessed the combined delivery of antigen in the DA-SNA structures in further experimentation. Overall, when evaluating the differences in immune responses between the DA-SNAs, the results highlight that positioning the MHC-I restricted antigen in the hybridized architecture optimizes DC presentation for CD8⁺ T cell responses, while encapsulating the MHC-II restricted antigen within the core induces modest enhancements in CD4⁺ activity while preserving cytotoxic function.

Figure 2. Antigen placement within SNAs impacts immune responses after immunization.

a) Schedule of fortnightly immunization for C57BL/6 mice. Various treatment groups in study. Dose: 6 nmol each antigen; 6 nmol adjuvant. b) Change of CD8⁺ (left) or CD4⁺ (right) cell populations in the spleen after vaccination scheme. (left) Admix, Separate 1 Encap. 2 Hyb., Separate 2 Encap. 1 Hyb. all versus DA-SNA 2 (P = 0.0369, 0.0142, 0.04182, respectively). (right) Admix versus Separate 1 Encap. 2 Hyb. (P = 0.0008), Separate 1 Encap. 2 Hyb. versus Separate 2 Encap. 1 Hyb., DA-SNA 1, and DA-SNA 2, respectively (P = 0.0032, 0.008, 0.0002). c) Intracellular production of IFN-γ pro-inflammatory cytokine (left) or CD107a degranulation marker (middle) was assessed upon ex vivo restimulation with peptide antigen. Polyfunctional T cells (double-positive for both markers) were quantified (right). DA-SNA 2 significantly elevated production of all markers in CD8⁺ T cells, whereas differences were more subtle amongst production in CD4⁺ T cells, with both DA-SNAs observably elevating levels above mice immunized with an admix vaccine. (top) (left) Admix versus Separate 2 Encap. 1 Hyb. and DA-SNA 2 (P = 0.0273 and 0.0003); Separate 1 Encap. 2 Hyb., DA-SNA 1 versus DA-SNA 2 (P = 0.0373 and 0.0006); (middle and right) Admix, Separate 1 Encap. 2 Hyb., Separate 2 Encap. 1 Hyb., DA-SNA 1 all versus DA-SNA 2, respectively (P = <0.0001, 0.0008, 0.0135, <0.0001; and 0.0001, 0.0021, 0.014, 0.0002); (bottom) (left) Admix versus Separate 1 Encap. 2 Hyb. and DA-SNA 1 (P = 0.0009 and 0.0149); Separate 1 Encap. 2 Hyb. versus Separate 2 Encap. 1 Hyb. and DA-SNA 2, respectively (P = 0.005 and 0.0098); (middle and right) Admix versus Separate 1 Encap. 2 Hyb., DA-SNA 1, respectively (P = 0.0252, 0.0074; and 0.0106, 0.0227). d) Effector memory phenotype, measured through CD44⁺CD62L⁻ markers, was increased by DA-SNA 2 for CD8⁺ T cells. CD4⁺ effector function was most elevated for Separate 1 Encap. 2 Hyb. immunization. (left) Admix versus Separate 2 Encap. 1 Hyb. and DA-SNA 2 (P = 0.002 and <0.0001); Separate 2 Encap. 1 Hyb versus DA-SNA 1 (P = 0.0394); Separate 1 Encap. 2 Hyb. and DA-SNA 1 versus DA-SNA 2 (P = 0.0136 and 0.0023, respectively). (right) Admix versus Separate 1 Encap, 2 Hyb. and DA-SNA 1 (P = <0.0001 and 0.0194); Separate 1 Encap, 2 Hyb. versus Separate 2 Encap. 1 Hyb., DA-SNA 1, and DA-SNA 2 (P = 0.0004, 0.0032, 0.0004, respectively) e) Percentage of CD8⁺ T cells that are OVA1-specific, measured through staining with an antigen-specific dimer. Admix, Separate 1 Encap. 2 Hyb., Separate 2 Encap. 1 Hyb., DA-SNA 1 all versus DA-SNA 2 (P = 0.0029, 0.0057, 0.0298, 0.0091, respectively). f) Representative counts and images (left) of IFN-γ-secreting splenic T cells upon different ex vivo stimulations along with total spot forming cells (SFCs) measured by ELISpot assay (right). For OVA1 ex vivo stimulation, Admix versus DA-SNA 1 and DA-SNA 2 (P = 0.242 and <0.0001); Separate 2 Encap. 1 Hyb. and DA-SNA 1 versus DA-SNA 2 (P = 0.0057 and 0.0011, respectively). For OVA2 ex vivo stimulation, Admix versus Separate 1 Encap. 2 Hyb. and DA-SNA 2 (P = 0.0028 and 0.0018, respectively). Mean ± s.e.m. shown. n = 3–6 mice per group. Statistical significance between relevant comparisons is shown. For all panels significance was calculated using a one-way ANOVA with Tukey’s (b, c, d, f) or Dunnett’s (e) multiple comparisons test. *p < 0.05; **p < 0.01; ***p < 0.001; ****p < 0.0001.

Mechanistic Understanding of DA-SNA induced Immune Activation and Propagation

To evaluate the possible factors driving these differences in in vivo activation, we evaluated the administration pathway for the structures upon immunization. We administered DA-SNAs subcutaneously with fluorophore labels for both peptide antigens and assessed biodistribution after 24 h (Supplementary Figure 12). No significant differences in organ accumulation between the two DA-SNAs were observed for the hybridized antigen. The encapsulated antigen was primarily concentrated in the lymph node with very little detected in other major organs, and importantly, a significant increase in accumulation was observed as a result of DA-SNA 2 immunization. We sought to assess if the lymph node trafficking could be explained by a difference in the release rate of the antigens from the DA-SNA structures (Supplementary Figure 13). Release profiles performed in physiologically relevant solutions (10% FBS) ex cellulo show relatively low levels of release for the hybridized antigen within 48 h, whereas the encapsulated antigen reached over 63 % release for DA-SNA 1 and just under 50 % release for DA-SNA 2. However, we have observed SNA uptake in as little as 30 min.²⁵ When looking at the release profiles of the DA-SNAs within the first few hours of exposure to the serum, the structures exhibit the same release rates, which are also <25 % of the total encapsulated antigen. The stability of the liposome shell, and hence the SNA, has been previously found to lead to differences in distribution.^{29, 36} We postulate that the liposome stability, influenced by the peptide cargo,^{37, 38} leads to the observed differences in DA-SNA encapsulated peptide distribution. Nonetheless, we emphasize that this parameter should be a design consideration for selecting peptide cargo, which varies based on antigen set, and this work illustrates important structural-based vaccine enhancements through multiple different antigen sets. We therefore conclude that the significant immune-wide changes observed in vivo cannot be attributed solely to differences in biodistribution or antigen release rates between the two nanoparticles. Moreover, when evaluating the trafficking of the antigens into splenic DCs (Supplementary Figure 14), no differences can be resolved between the two DA-SNAs, and importantly both successfully generate a significant double-positive antigen population of DCs compared to naïve mice and mice administered with a simple mixture of the components. As a result of the minimal variation between the DA-SNAs based on distribution and organ-level trafficking, we performed dendritic cell transcriptome analysis to evaluate how treatment with the differently-structured vaccines impacts pathway enrichment and overall gene expression (Supplementary Figure 15, Supplementary Data 1). The DA-SNA structures affect dendritic cell pathways very differently compared to admix treatment, where few significant pathways were enriched. Pathway enrichment analysis between DA-SNA 1 and 2 suggests that DA-SNA 2 affects the internalization and pathway processing of components to a greater extent than DA-SNA 1.

We sought to resolve the processing pathways of DA-SNA 1 and 2 within dendritic cells in an effort to elucidate this impact on signaling kinetics. Using confocal microscopy (Figure 3), we assessed the intracellular fate of DA-SNAs following uptake by BMDCs at pre-determined time points and compared colocalization of both the hybridized and encapsulated antigens with organelle markers for early endosome (early endosome antigen 1, EEA1), late endosome (Rab7), lysosome (lysosomal associated membrane protein 1, Lamp1), endoplasmic reticulum (protein disulfide isomerase, PDI), MHC-I, and MHC-II. The data highlight that substantial processing occurs at earlier time points (i.e., <1h). Processing within the early endosome demonstrates comparable kinetics between the two structures (Figure 3A). Significant differences between the two structures arise in the late endosome (Figure 3B), where there is enhanced processing and trafficking for both the hybridized and encapsulated antigens for the DA-SNA 2 structure compared to both antigens for DA-SNA 1. Evaluation of the lysosome revealed key differences; there is decreased colocalization for the hybridized antigen of DA-SNA 2 (MHC-I restricted) and increased colocalization for the encapsulated antigen for DA-SNA 2 (MHC-II restricted) (Figure 3C), which suggests optimization of MHC-II loading for DA-SNA 2. We observed that the hybridized antigen of DA-SNA 1 (MHC-II restricted) does exhibit increased colocalization with the lysosome at early time points, but this quickly subsides, and no significant increases are observed later in the study. This also suggests that any DA-SNA 1 optimized processing routes are more transient, as increased colocalization of the DA-SNA 1 hybridized antigen (MHC-II restricted) with MHC-II is also not observed. Analysis of processing at the endoplasmic reticulum (ER) showed no major differences between DA-SNA treatment for the hybridized antigens. This could be attributed to faster cross-presentation kinetics with the DA-SNA 2 structural arrangement for the hybridized antigen and thus less effective capturing of this process (Figure 3D). Conversely, decreases in the colocalization for the ER and DA-SNA 2 encapsulated antigen (MHC-II restricted), significant at the 1 h timepoint, could be attributable to decreased trafficking of the encapsulated MHC-II restricted antigen for DA-SNA 2 to the ER. Importantly, the hybridized antigen of DA-SNA 2 (MHC-I restricted) exhibited increased colocalization with MHC-I at early timepoints, as early as 30 min with significant increases observed up to 1 h (Figure 3E), translating to an increased DA-SNA 2-driven OVA1 surface presentation on MHC-I (Supplementary Figure 16). While not significant, there is a trending increase in the DA-SNA 2 encapsulated antigen (MHC-II restricted) with MHC-II at later time points (Figure 3F). As there is significant DA-SNA 2 encapsulated antigen (MHC-II restricted) colocalization with the late endosome and lysosome, we suggest that the loading of MHC-II by DA-SNA incubation is a slower process than MHC-I loading. Moreover, differences between the DA-SNA treatments generally subsided by 6 h, suggesting that the immunological differences observed are driven primarily by early kinetics and processing of these structures by DCs.

Figure 3. Time dependent antigen processing differences driven by vaccine structure.

Representative confocal microscope images of BMDCs incubated for 30 min with either DA-SNA 1 or DA-SNA 2 containing both Cy5-labeled hybridized antigen (red) and FITC-labeled encapsulated antigen (green). Nucleus was stained by DAPI (blue) and the following organelles were stained: a) EEA1 (early endosome), b) Rab7 (late endosome), c) Lamp1 (lysosome), d) PDI (endoplasmic reticulum), e) MHC-I, and f) MHC-II. All organelles shown in yellow. Mander’s overlap coefficient representing the fraction of Cy5 or FITC signal colocalized with respective organelles at 0.5, 1, 6 and 24 h is shown. Scale bar = 10 μm. g,i) Colocalization and h,j) flow cytometry analysis of DA-SNA 1 and DA-SNA 2 processing in BMDCs after a 1 h pulse and following 24 hour treatment with g-h) chloroquine and i-j) brefeldin A. OVA1 colocalization with g) MHC-1 and i) ER is shown. Colocalization of OVA2 with k) lysosome (LAMP 1) in the presence of leupeptin and l) MHC-II in the presence of chloroquine. For a: encapsulated DA-SNA 1 versus DA-SNA 2 at 24 h (P = 0.0004). For b: hybridized DA-SNA 1 versus DA-SNA 2 at 0.5 (P = 0.0099) and 24 h (P = 0.0313); encapsulated DA-SNA 1 versus DA-SNA 2 at 0.5 (P = 0.0175), 1 (P = 0.0370), 6 (P = 0.0125), and 24 h (P = 0.0326). For c: hybridized DA-SNA 1 versus DA-SNA 2 at 0.5 h (P = 0.0005); encapsulated DA-SNA 1 versus DA-SNA 2 at 0.5 (P = 0.0025) and 24 h (P = 0.0002). For d: encapsulated DA-SNA 1 versus DA-SNA 2 at 1 h (P = 0.0281). For e: hybridized DA-SNA 1 versus DA-SNA 2 at 0.5 (P = 0.0007) and 1 h (P = 0.0498); encapsulated DA-SNA 1 versus DA-SNA 2 at 24 h (P < 0.0001). For f: hybridized DA-SNA 1 versus DA-SNA 2 at 1 h (P = 0.0100). For g: DA-SNA 1 versus DA-SNA 2 (P < 0.0001). For h: untreated versus DA-SNA 1 (P < 0.0001) and DA-SNA 2 (P < 0.0001); DA-SNA 1 versus DA-SNA 2 (P = 0.0417). For i: DA-SNA 1 versus DA-SNA 2 (P = 0.0001). For j: untreated versus DA-SNA 1 (P = 0.0005) and DA-SNA 2 (P = 0.0038). For k: DA-SNA 1 versus DA-SNA 2 (P = 0.0180). For l: DA-SNA 1 versus DA-SNA 2 (P = 0.0084). The data show mean ± s.d. from 6–10 randomly selected field of views. For panels a-f, statistical significance was calculated using a two-way ANOVA with Sidak’s multiple comparisons test. For panels g,i,k,l, statistical significance was calculated using an unpaired T test with Welch’s correction while panels h,j used a one-way ANOVA with a Tukey multiple comparison test. *p < 0.05; **p < 0.01; ***p < 0.001; ****p < 0.0001.

To further elucidate the pathways involved through DA-SNA 1 and 2 antigen presentation, we employed inhibitors to mechanistically assess antigen processing. The addition of a disrupter of endosomal acidification (chloroquine)³⁹ which has been shown to increase the extent of cross-presentation,^{39, 40} impacts the colocalization of OVA1 with MHC-1 complexes. Through this enhanced cross-presentation, we observe that DA-SNA 2 induces increased OVA1 colocalization with MHC-1 (Figure 3G). These data suggest that DA-SNA 2 can take advantage of enhanced cross-presentation more effectively than DA-SNA 1. This architectural advantage ultimately translates to a greater surface presentation of OVA1 on MHC-1 (Figure 3H). The addition of Brefeldin A, which inhibits transport of assembled peptide-MHC-I complexes from the ER to the cell membrane,⁴¹ and thus impedes cross-presentation, more negatively impacts DA-SNA 2. There is a significant decrease (4.7-fold) in colocalization of OVA1 peptide with the ER upon Brefeldin A treatment for DA-SNA 2 (Figure 3I), translating to a complete loss of OVA1 surface presentation on MHC-1 (Figure 3J). The impact of pathway inhibitors on OVA2 processing was also analyzed. The addition of leupeptin, an inhibitor of cysteine and serine proteases (e.g., cathepsins B, S, and L),⁴² leads to a drop in OVA2 colocalization with the lysosome (the site of MHC-II loading) for DA-SNA 2 (Figure 3K). The antigen presentation through DA-SNA 2 is therefore more negatively impacted in MHC-II processing upon inhibitor addition. Moreover, the use of chloroquine, known to block MHC II-dependent antigen processing,^43–45 hinders the ability of OVA2 in DA-SNA 2 to colocalize with MHC-II (Figure 3L). DA-SNA 2 is therefore more strongly impacted by the addition of inhibitors that disrupt MHC-I and –II processing, thus indicating that the presentation and kinetic profiles that DA-SNA 2 provides are more optimally suited for antigen processing.

To understand how the different DA-SNAs and admix treatments were inducing such varied downstream T cell responses, we collected and isolated splenic CD8⁺ and CD4⁺ T cells after immunization following the same schedule in Figure 2 and performed bulk RNA sequencing (RNAseq). Principal component analysis (PCA) revealed holistically that the CD8⁺ and CD4⁺ T cell gene expression profiles of mice immunized with admix formulations were most similar to those from naïve mice, suggesting this is the cause of low overall activation (Figure 4A). Mice immunized with DA-SNA 2 were most distinct from naïve mice in their CD8⁺ transcriptome, whereas both DA-SNA 1 and 2 differed from naïve mice in their gene expression profiles in CD4⁺ T cells in a similar way. This suggests a rationale for the significant increases in DA-SNA 2-induced CD8⁺ T cell function but similar levels of CD4⁺ T cell function between both DA-SNAs observed in Figure 2. Moreover, differentially regulated genes for DA-SNA 2 immunized mice exhibited greater absolute log fold changes (LFCs) in both T cell types compared to the other treatments, with at least double the number of differentially regulated genes as a result of DA-SNA 2 immunization compared to DA-SNA 1 (Figure 4B). Differentially regulated genes were enriched in pathways involving inflammatory responses and upregulation of pro-inflammatory cytokines, chemotaxis, and migration of key immune cell populations (Figure 4C and Supplementary Data 2). While some of the enriched pathways from DA-SNA 2 treatment were shared with admix treatment and others with DA-SNA 1 treatment, overall, the widespread activation induced at the transcriptome level for the DA-SNA 2 architecture correlated with enhanced immunological outputs.

Figure 4. Immunization of mice with differently structured vaccines induces specific differences in gene expression among CD8⁺ and CD4⁺ T cells.

a) Principal Component Analysis (PCA) plot from the full transcriptome of CD8⁺ (left) and CD4⁺ (right) T cells. b) Gene expression changes represented by subset of log-fold change (LFC) for CD8⁺ (left) and CD4⁺ (right) T cell populations as a result of different treatments. c) Selection of significantly enriched pathways calculated using GSEA analysis. Colors of squares correspond to the enrichment score for each pathway as a result of different treatment for CD8⁺ (left) and CD4⁺ (right) T cells. d) Gene signatures for CD8⁺ (top) and CD4⁺ (bottom) T cells. Colors refer to normalized (z-scored) gene expression levels. Selection of relevant genes labeled. e) Volcano plots of CD8⁺ (left) and CD4⁺ (right) T cells between a pairwise comparison of DA-SNA 2 and DA-SNA 1. Colored dots indicate significantly expressed genes; a positive LFC indicates an upregulation for DA-SNA 2 with respect to DA-SNA 1 (red) whereas a negative LFC indicates a downregulation for DA-SNA 2 with respect to DA-SNA 1 (blue).

Relevant gene signatures were identified for adaptive and innate immune activation and functioning across all treatments and include, for example, CXCR3, TNFSF9, and GZMK (Figure 4D and Supplementary Data 3). These genes have particular relevance in T cell effector function and trafficking, antigen presentation and generation of cytotoxic T cells, and helper T cell cytolytic function, respectively. A particular comparison of DA-SNA 2 versus DA-SNA 1 demonstrates unique nanoscale-induced genetic differences simply by altering the placement of antigen class (Figure 4E). A total of 452 and 229 overlapping significant genes in CD8⁺ and CD4⁺ T cells, respectively, were detected between both DA-SNAs. Specifically, DA-SNA 2 induced higher expression of IL2RA, CD44, XCL1 in CD8⁺ T cells and LAG3, CCR7, CCL9 in CD4⁺ T cells compared to DA-SNA 1. Ultimately, comparing gene signatures across all immunization treatments highlights the substantial impact that vaccine structure and in particular, nanoscale antigen placement, have on genome and expression patterns. These results underscore the immunological measurements that were detected, providing mechanistic rationale that highlighted pathways leading to T cell activation and durable responses, and detail a framework for vaccine design using purposeful structure considerations.

DA-SNA Structure-driven Tumor Inhibition and Immune Activation

To evaluate the therapeutic efficacy and immunological impact of DA-SNAs, we employed a murine E.G7-OVA lymphoma cancer model due to its stable expression of the OVA protein, expressing both the OVA1 and OVA2 epitopes used above.⁴⁶ Briefly, C57BL/6 mice were inoculated subcutaneously with E.G7-OVA cells and immunized weekly with either DA-SNA or admix formulations (6 nmol of each OVA1 and OVA2 antigen, 6 nmol of adjuvant DNA) (Figure 5A). Tumor-bearing mice immunized with DA-SNA 2 demonstrated a ca. 3-fold reduction in tumor growth compared to both control (saline-treated) and admix groups as soon as five days after the second immunization (day 15) and more than a 16-fold difference in tumor growth when compared to saline-treated mice 22 days post-tumor inoculation (Figure 5B and Supplementary Figure 17). Importantly, DA-SNA 1 treatment did not effectively halt tumor growth compared to admix, unlike DA-SNA 2 treatment. Compared to the admix and DA-SNA 1, DA-SNA 2 produced a ca. 7-fold reduction in tumor growth at day 24, highlighting the pronounced impact of antigen positioning and, ultimately, translating to a significant extension in animal survival (median survival in days: PBS = 27; Admix = 24; DA-SNA 1 = 28; DA-SNA 2 = 35) (Figure 5C). To further investigate the physical impact of treatment on tumor growth, tumors were excised from mice at day 15 following the same treatment regimen and subsequently weighed (Figure 5D and Supplementary Figure 18). Interestingly, at this point in the tumor growth curve, both SNA groups showcased a significant reduction in tumor weights when compared to PBS-treated mice, suggesting that DA-SNA 1 is capable of raising an antitumor immune response, but that it is not as durable as that raised from DA-SNA 2.

Figure 5. DA-SNA immune activation for enhanced tumor suppression.

a-c) C57BL/6 mice were subcutaneously inoculated with E.G7-OVA cells (5 × 10⁵) in the right flank and provided weekly immunizations beginning at day 3 for a total of four vaccinations (6 nmol adjuvant, 6 nmol of each antigen). Average tumor growth curves and animal survival is shown. Tumor volume at day 24 of DA-SNA 2 compared to DA-SNA 1 and Admix (P = 0.0121 and P = 0.0084, respectively). Animal survival comparing DA-SNA 1 versus DA-SNA 2 (P = 0.0219); DA-SNA 2 versus PBS and Admix (P = 0.0030 and P = 0.0029, respectively). d) Tumor weights following treatment schedule depicted in a (at day 15). Tumor weight comparing PBS versus DA-SNA 1 and DA-SNA 2 (P = 0.0064 and P = 0.0034, respectively) e) Evaluation of immune CD8⁺ T cells in the spleen at the conclusion of the experiment (left). Ratio of CD8⁺/CD4⁺ T cells (right). T cells in spleen of DA-SNA 2 versus PBS (P = 0.0297), Admix (P = 0.0013), and DA-SNA 1 (P = 0.0002). f-i) Flow cytometric analysis of PBMCs at day 15 isolated from tumor-bearing mice under the schedule depicted in a. f) CD8⁺ T cells specific for the OVA1 antigen. DA-SNA 2 versus Admix (P = 0.0401). g) Effector memory CD8⁺ T cells (CD44⁺/CD62L⁻) within this antigen-specific T cell subset. DA-SNA 2 versus Admix (P = 0.0020). h) CD4⁺ T cells specific for the OVA2 antigen. Admix versus DA-SNA 1 (P = 0.0229) and DA-SNA 2 (P = 0.0436). i) Effector memory CD4⁺ T cells (CD44⁺/CD62L⁻). DA-SNA 1 versus Admix (P = 0.0001) and DA-SNA 2 (P = 0.0012). The data show mean ± s.e.m. from two independent experiments (each experiment n=7–9). For panels b, d-g, i, significance was calculated using a one-way ANOVA with Tukey’s multiple comparisons test. Panel h used a Welch ANOVA followed by a Dunnett’s multiple comparisons test due to significant differences between groups in standard deviation. Panel c was analyzed using a Log-rank test. *p < 0.05; **p < 0.01; ***p < 0.001.

The immunological differences resulting from multi-antigen delivery were further elucidated by harvesting spleens from E.G7-OVA-tumor-bearing mice and evaluating changes in splenic CD8⁺ and CD4⁺ T cells (Figure 5E). The spleens of DA-SNA 2-treated mice generated a significantly higher percentage of CD8⁺ T cells when compared to other treatment groups and also displayed an overall higher ratio of CD8⁺ to CD4⁺ T cells. To evaluate the immunological differences that contributed to tumor suppression, tumor-bearing C57BL/6 mice were assessed for circulating peripheral blood mononuclear cells (PBMCs) on day 15, when differences in tumor growth were first observed and when the impact of DA-SNA 2 treatment began to halt tumor growth while the other treatments had negligible impact. Notably, DA-SNA 2-treated mice showcased the highest level of circulating antigen-specific CD8⁺ T cells (Figure 5F, gating strategy in Supplementary Figure 19). This subset of CD8⁺ lymphocytes was further evaluated for their memory phenotype. In this case, DA-SNA 2 treatment significantly elevated the effector memory phenotype to over 60 % of OVA1-specific circulating CD8⁺ T cells (Figure 5G). Antigen-specific CD4⁺ T cells were also significantly elevated for mice treated with the DA-SNAs (Figure 5H). As expected, due to the transcriptome profiles and immunological parameters previously explored herein for CD4⁺ T cells, there were negligible differences between the two DA-SNA groups. While there were not enough OVA2-specific CD4⁺ T cells to accurately delineate the memory phenotype within this subpopulation, the entirety of CD4⁺ T cells demonstrated an enhanced effector memory state when treated with DA-SNA 1 (ca. 30 % of CD4⁺ T cells), compared to treatment with DA-SNA 2, which matured ca. 10 % of CD4⁺ T cells (Figure 5I).

To determine the versatility and translatability of the design rules to guide structural placement for multi-antigen vaccination, we employed the MC-38 colon carcinoma model known for its high mutational burden.⁴⁷ Briefly, C57BL/6 mice were inoculated subcutaneously with MC-38 cells and immunized weekly with DA-SNAs containing MHC-I neoantigen “Adpgk I”¹⁴ and “Adpgk II”, an antigen predicted to bind effectively to MHC-II^48–51 (6 nmol of each Adpgk I and Adpgk II antigen, 6 nmol of adjuvant DNA) (Supplementary Figure 20A-C). Tumor growth was similarly inhibited for mice immunized with DA-SNA 2 with a significant extension in survival conferred to these animals (median survival in days: PBS = 27; DA-SNA 2 = 38). These differences likely result from a combination of significant increases in the tumor microenvironment and amongst raised circulating immune cells. CD8⁺ and CD4⁺ T cells are increased in the tumor microenvironment (Supplementary Figure 20D-E; gating strategy in Supplementary Figure 21) and a significant reduction in Gr-1⁺CD11b⁺ myeloid-derived suppressor cells is observed (Supplementary Figure 20F). Moreover, DA-SNA 2 treatment increased the percentage of Adpgk I-specific CD8⁺ T cells and induced splenic adaptive T cell immunity. Upon ex vivo stimulation of Adpgk I and II, DA-SNA 2-treated splenocytes secreted the more interferon gamma than DA-SNA 1 or PBS-treated splenocytes (Supplementary Figure 20G-H).

Structural Impact of Antigen Placement in Clinically-relevant Melanoma Tumor Model

The findings learned regarding DA-SNA structure heretofore were utilized to assess the ability of dual-antigen placement to impact growth of B16-F10 melanoma tumors. This model has been established as highly aggressive with enhanced immunosuppressive properties.⁵² The recently reported⁵³ M27 and M30 neo-epitopes containing mutations present only in the tumor, were selected as MHC-I and -II antigens, respectively. Initially, C57BL/6 mice inoculated with B16-F10 tumor cells and receiving a weekly vaccination 3 days post-tumor inoculation of either DA-SNA 1 or DA-SNA 2 showcased an inhibition in tumor growth at day 17 compared to saline-treated mice (68 % and 48 %, respectively) (Figure 6A–B). Indeed, a statistically significant ca. 4-fold increase in circulating effector memory antigen-specific CD8⁺ T cells was observed for mice treated with either DA-SNA relative to saline treatment (Figure 6C, gating strategy in Supplementary Figure 19). Therefore, an antigen-specific immune response is produced, but the negligible impact this has on tumor growth indicates the likelihood of a highly immunosuppressive tumor environment that is inhibiting the therapeutic potential of these T cells.

Figure 6. Tumor inhibition utilizing dual antigen immunotherapy with immune checkpoint inhibitors.

a-b) C57BL/6 mice were subcutaneously inoculated with B16-F10 cells (10⁵) in the right flank and provided weekly subcutaneous immunizations beginning at day 3 for a total of four vaccinations (9 nmol adjuvant, 9 nmol of each antigen). Average tumor growth curves and animal survival is shown. c) CD8⁺ T cells specific for the M27 antigen and memory CD8⁺ T cell markers 44⁺/62⁻ in isolated PBMCs. PBS versus DA-SNA 1 (P = 0.0060) and DA-SNA 2 (P = 0.0001). d-e) B16-F10 tumor-bearing mice receiving weekly subcutaneous immunizations of DA-SNAs combined with an anti-PD-1 immune checkpoint inhibitor administered intraperitoneally 3 and 6 d post DA-SNA immunization. Average tumor growth curves and animal survival is shown. Tumor growth comparing anti-PD-1 versus DA-SNA 2 + anti-PD-1 at day 17 (P = 0.0354), 20 (P = 0.0319), and 22 (P = 0.0475). Animal survival comparing DA-SNA 2 + anti-PD-1 versus PBS (P < 0.0001) and anti-PD-1 (P < 0.0001). f-k) Flow cytometric analysis of PBMCs at day 17 isolated from tumor-bearing mice receiving the schedule indicated in d. f) Evaluation of circulating CD8⁺ T cells and g) total effector memory CD8⁺ T cells (CD44⁺/62L⁻). For f: DA-SNA 2 + anti-PD-1 versus PBS (P = 0.0001), anti-PD-1 (P = 0.0009)), and DA-SNA 1 + anti-PD-1 (P < 0.0001). For g: DA-SNA 2 + anti-PD-1 versus PBS (P = <0.0001), anti-PD-1 (P < 0.0001), and DA-SNA 1 + anti-PD-1 (P = 0.0090). DA-SNA 1 + anti-PD-1 versus PBS (P = 0.0023) and anti-PD-1 (P = 0.0203). h) M27-specific CD8⁺/CD19⁻ T cells. DA-SNA 2 + anti-PD-1 versus PBS (P = 0.0093), anti-PD-1 (P = 0.0138), and DA-SNA 1 + anti-PD-1 (P = 0.0052). i) Quantification of circulating CD4⁺ T cells and j) assessment of effector memory CD4⁺ T cells (CD44⁺/62L⁻). For i: DA-SNA 2 + anti-PD-1 versus DA-SNA 1 + anti-PD-1 (P = 0.0372). For j: PBS versus DA-SNA 1 + anti-PD-1 (P = 0.0268) and DA-SNA 2 + anti-PD-1 (P = 0.0349); anti-PD-1 versus DA-SNA 1 + anti-PD-1 (P = 0.0067) and DA-SNA 2 + anti-PD-1 (P = 0.0089). k) M30-specific CD4⁺/CD19⁻ T cells. The data show mean ± s.e.m. from two independent experiments (n=9–15). For all panels except b and e, significance was calculated using a one-way ANOVA with Tukey’s multiple comparisons test. Animal survival was analyzed using a Log-rank test. Asterisks in d indicate statistically significant differences between DA-SNA 2 and anti-PD-1 treatment group. n.s. = not significant; n.d = not detected; *p < 0.05, **p < 0.01, ***p < 0.001 and **** p < 0.0001.

Due to these observations and the inherent aggressiveness of this tumor model, DA-SNA treatments were combined with the immune checkpoint inhibitor anti-PD-1, an FDA-approved treatment for advanced melanoma, in an effort to overcome the tumor’s immunosuppression.^{54, 55} These treatments began 3 days after B16-F10 tumor inoculation. Notably, when anti-PD-1 was co-administered with DA-SNAs, a significant decrease in tumor growth was observed beginning as early as 17 days post-tumor inoculation for animals treated with the combination DA-SNA 2 + anti-PD-1 therapy, while no substantial decrease in tumor growth was observed for mice in the other treatment groups (Figure 6D, Supplementary Figure 22). This translated to a 40 % extension in median survival for these mice compared to those in the saline-treated or anti-PD-1 monotherapy-treated groups (Figure 6E). The importance and the role that nanoscale antigen placement plays in driving synergistic and enhanced immune responses can be drawn from these results. Importantly, a comparison between DA-SNA combination treatment groups revealed an improvement in overall median survival for combination DA-SNA 2 + anti-PD-1 animals (p = 0.0507). The evaluation of immune cells isolated from peripheral blood further highlights this structure-induced difference where DA-SNA 2 appears to work synergistically with the checkpoint inhibitor. A significant increase in circulating CD8⁺ T cells for animals receiving a combination DA-SNA 2 + anti-PD-1 treatment was observed compared to all other groups (Figure 6F). Interestingly, when the total CD8⁺ effector memory T cell population was evaluated amongst these circulating PBMCs, significant increases were detected for both combination DA-SNA + anti-PD-1 groups, with DA-SNA 2 + anti-PD-1 generating effector memory phenotypes in ca. 60% of circulating CD8⁺ T cells (Figure 6G). Moreover, only this combination DA-SNA 2 + anti-PD-1 treatment was able to induce a robust antigen-specific CD8⁺ T cell response (Figure 6H). Observations of CD4⁺ T cell circulation revealed a similarly high increase as a result of combination DA-SNA 2 + anti-PD-1 therapy (Figure 6I), although both combination DA-SNA + anti-PD-1 groups significantly elevated the effector memory phenotype to ca. 28% of the CD4⁺ T cell population (Figure 6J). The combination DA-SNA 2 + anti-PD-1 treatment increased levels of antigen-specific CD4⁺ T cell production along with anti-PD-1 monotherapy compared to DA-SNA 1 + anti-PD-1 treatment, although significant differences were not observed between groups (Figure 6K).

Outlook

Although extensive research has explored the importance of adjuvants and antigens in creating powerful new immunotherapies, to date, no body of work has explored the importance of structural presentation of multiple antigens within a specific construct and its role in eliciting a potent and desired immune response. Collectively, this work shows that antigen placement may be as critical as antigen choice in vaccine efficacy. Indeed, when altering the placement of MHC-I and -II restricted antigens in two compositionally nearly identical vaccines, the treatment benefit against tumors is dramatically changed; one vaccine is potent and the other is ineffective. The origins of these differences may be due to antigen positioning affecting the pathway of processing that it undergoes in an immune cell, as well as its residence time in different cellular compartments. By changing the processing pathway and these kinetics of signaling, this affects the resulting immune response at the genetic, cellular, and organismal levels. An encapsulated MHC-II and a hybridized MHC-I restricted antigen upregulate genes specific for inflammatory responses, chemotaxis, and migration of key immune cells, which together influence immune cell activity. These structurally-defined genetic differences translate through to immunological behavior upon repeated in vivo immunization, and ultimately define the tumor growth profiles in multiple tumor models, including E.G7-OVA lymphoma, and clinically-relevant MC-38 colon carcinoma and B16-F10 melanoma mouse tumor system. This is a key demonstration of the impact of vaccine antigen positioning across multiple cellular processes.

Vaccine development has focused on the composition, number and type of antigen, and the ratio of these components, with almost no attention paid to their structural presentation. It is clear that in addition to these important parameters, presentation of antigen must be a focus in future vaccine development. Having the power to optimize antigen presentation to match a desired signaling profile is critical to generate potent future vaccines, where small vaccine changes in antigen placement significantly elevate cell-cell communication, cross-talk, and cell synergy. This new insight can be harnessed for targets yet to be discovered, as well as to those already-in-use. Taken together, the developments made in this work provide a path forward to rethink the design of vaccines for cancer and other diseases.

Methods

Materials and Animals:

Unless otherwise noted, all reagents were purchased commercially and used as received. Oligonucleotides were synthesized as described below. Peptides were purchased from Genscript or Northwestern’s Peptide Synthesis core. Chemicals were purchased from suppliers listed in parentheses. C57BL/6 mice and C57BL/6-Tg(TcraTcrb)1100Mjb/J (OT-1, 003831) female mice, age 8–12 weeks old, were purchased from Jackson Laboratory. Mice were used in accordance with all national and local guidelines and regulations and protocols performed were approved by the institutional animal use committee at Northwestern University (IUCAC). E.G7-OVA and B16-F10 cells were purchased from ATCC. MC-38 cells were kindly provided by Dr. Bin Zhang. Antibodies were purchased and clones are provided in Supplementary Table 3.

Oligonucleotide Synthesis and Purification:

Oligonucleotides were synthesized on an ABI 394 synthesizer using standard phosphoramidite chemistry with phosphate or phosphorothioate backbones, as indicated (Supplementary Table 1). Following synthesis, the strands were deprotected using a 1:1 solution of 37 % ammonium hydroxide/40 % methylamine at 55 °C for 35 min, unless they contained a dye, in which case they were deprotected using 37 % ammonium hydroxide at room temperature (RT) overnight. The strands were then purified using a C18 or C4 (for strands containing dye or cholesterol) column on reverse phase HPLC, and the peaks were collected as fractions. The dimethoxytrityl (DMT) group was removed from the product strands by incubation in 20 % aqueous acetic acid at RT for 1 h, followed by three washes with ethyl acetate to remove DMT. The final product was lyophilized and resuspended in deionized water (diH₂O). The concentration was measured using UV-vis absorption at 260 nm with extinction coefficients calculated through the IDT OligoAnalyzer online tool (listed in Supplementary Table 1).

Oligonucleotide-peptide Conjugate Synthesis and Purification:

Thiol-functionalized oligonucleotides in diH₂O were reduced to generate a free thiol for future reactions. Reduction was done using dithiothreitol (100 mM, DTT, Sigma) dissolved in phosphate buffered saline (PBS) pH 8.5 at a final concentration of 100 mM at RT for 45 min. This solution was washed in a 3 kDa molecular weight cut off (MWCO) spin filter (Amicon) at least three times with diH₂O. For OVA peptide conjugates, peptide was purchased on resin and washed three times each with dimethylformamide (DMF) and acetone before reacting 5 μmol at RT overnight with a solution of succinimidyl 2-(2-pyridyldithio)ethyl carbonate (SDEC, made using previous protocols⁵⁶) dissolved in DMF (10 equivalents with respect to the initial peptide loading on the solid support), with N,N-diisopropylethylamine (5 equivalents). The beads were subsequently washed three times with DMF and acetone each and dried in air before being deprotected with 95 % Trifluoroacetic acid (2.5% Triisopropyl silane, 2.5% diH₂O) for 1 h at RT. The TFA was blown off using nitrogen, and the beads were redissolved in DMF and filtered through glass wool. The peptide product was precipitated by adding ~5–6 times diethyl ether and was left at −20 °C for 1–2 h to further precipitate. The solution was centrifuged (2,000 × g, 3 min) to pellet the peptide, which was collected, dried, and dissolved in DMF. Reduced DNA (0.5 μmol) was reacted overnight at RT with the dissolved peptide (5 μmol) in 70–75 % DMF in water for a total volume of reaction of ~1.5 mL. For MART-1 peptide conjugates, the peptides were activated using 2,2′-dithiodipyridine (150 μmol) dissolved in 10 equivalents DMF under gentle agitation for 30 min at RT. The activated peptide was then washed three times in diethyl ether, pelleted by centrifugation (2,000 × g, 3 min), and allowed to dry. Reduced DNA (0.3 μmol) was reacted overnight at RT with the dissolved peptide (1.5 μmol) in ~70 % DMF in water for a total volume of reaction of ~1.5 mL.

Following conjugation of the peptide, the solutions were centrifuged at 17,000 × g for 2 min to pellet any precipitated peptide, and the supernatant was transferred to 3 kDa MWCO spin filters for 3–4 washes with diH₂O. The volume was concentrated to <500 μL, and the solutions were purified by preparatory scale denaturing (8 M urea) 15 % PAGE gels (no more than 0.5 μmol by DNA loaded onto a single gel). The gels were run for 30 min at 175 V, then ~3 h at 350 V, and subsequently imaged using a UV lamp to cut out desired bands. Cut-out gel bands were crushed, and the product was collected by three washes with 1x Tris/Borate/EDTA (TBE) buffer every ~4 h. The product mass was confirmed by electrospray ionization mass spectrometry (ESI-MS), and the concentrations were measured by UV-vis at 260 nm assuming an extinction coefficient of the DNA.

SNA Synthesis:

SNAs were synthesized as reported previously with slight modifications.^{16, 57} Briefly, dried lipid films of 50 mg of 1,2-dioleoyl-sn-glycero-3-phosphocholine (DOPC, Avanti Polar Lipids) were hydrated with 3–4 mL of PBS or PBS-containing peptide, for encapsulated liposomes. (Note: solutions containing peptide included, OVA1: 1 mg/mL dissolved in PBS containing ~100 μL 1M NaOH; OVA2: 1 mg/mL dissolved in PBS containing ~60 μL 1M NaOH; M27: 2.25 mg/mL dissolved in PBS containing ~60 μL 1M NaOH; M30: 1 mg/mL dissolved in PBS containing ~100 μL 1M NaOH) The solutions were subjected to 20 freeze-thaws in liquid nitrogen and then sonication at 37–40 °C. The liposomes were extruded using sequential high-pressure extrusion (Northern Lipids Inc.) using polycarbonate filters with pore sizes of 200, 100, 80, and 50 nm; liposomes were passed through each pore size three times. Following extrusion, the liposomes were concentrated down to ~2–3 mL using 100 kDa MWCO spin filters and dialyzed overnight against 3.5 L of PBS to remove unencapsulated peptide. The liposome concentration was determined using a phosphatidylcholine (PC) assay kit (Sigma, MAK049–1KT), assuming a 50-nm liposome contains 18,140 lipids per liposome.²⁴ Peptide concentration, if liposomes encapsulated peptide, was determined using a Pierce^™ fluorescence assay kit (Thermofisher, 23290) adding 1 % sodium dodecyl sulfate (SDS) to rupture liposomes and release peptide for quantification, and using peptide dissolved in 1 % SDS as a standard curve. The loading of peptide per liposome was calculated by dividing the peptide concentration over the liposome concentration. The amounts of each antigen per particle ranged from ca. 25 – 40 depending on the encapsulation yield of each batch, which was tuned using different starting concentrations.

Purified oligonucleotide-peptide conjugates were mixed in a 1:1 molar ratio with complementary 3’-cholesterol-terminated CpG DNA and centrivapped overnight. The next day, ~20–40 μL of duplex buffer (IDT) was added and the solution was slow-cooled to duplex the strands following the program: 70 °C for 10 min, 23 °C for 1.5 h, 4 °C for ≥1 h. The duplex was added to a solution of synthesized liposomes at an equimolar amount to the peptide encapsulated within the liposome. To obtain the maximum 75 strands per liposome, the remaining space was filled with 3’cholesterol terminated T₂₀ DNA. This mixture was incubated at 37 °C overnight and subsequently stored at 4 °C.

Ex Cellulo Release Study:

DA-SNAs containing fluorophore-labeled antigens (2 μM in 1.5 mL volume) were placed into Slide-A-Lyzer^™ MINI Dialysis Device 50 mL falcon tubes with a 10K MWCO. The falcon tube solution was prepared to be 10% fetal bovine serum in PBS. Samples were loaded and left on a rotator, and at specified time points, 200 μL of sample was collected and frozen at −20 °C until analysis using a BioTek plate reader.

Cell culture:

All cells were maintained at 37 °C in a 5 % CO₂ incubator. E.G7-OVA, MC-38 and DCs were cultured with RPMI 1640 media (Gibco, 11875093) containing 10 % heat-inactivated fetal bovine serum (HI-FBS) and 1 % Penicillin-Streptomycin, referred to herein as RPMI +/+. B16-F10 were handled using DMEM media (Gibco, 11965092) containing 10 % HI-FBS and 1 % Penicillin-Streptomycin.

Bone marrow-derived dendritic cell (BMDC) collection:

Bone marrow cells were collected from mice following a previous protocol;⁵⁶ briefly, red blood cells were lysed with 2–3 mL of ACK lysis buffer (Gibco, A1049201) for ~4 min and plated on 10-cm² cell culture dishes with 40 ng/mL GM-CSF (BioLegend, 576304) for 5–7 days prior to use to differentiate DCs from the population.

BMDC Activation and Cross-priming of T cells In vitro:

The cells were collected from 10-cm² cell culture dishes, and DCs were isolated from the mixture using a magnetic biotin positive selection kit (Stemcell Technologies, 17665). A CD11c⁺ biotin-labeled antibody was used to select DCs (BioLegend) and, after separation, purified DCs were counted using a Vi-CELL BLU Cell Viability Analyzer. For DC activation, 6 × 10⁴ DCs were cultured with SNA treatment in a final volume of 200 μL for a 30 min pulse. Cells were then washed twice with RPMI +/+ and left for 22 h in an incubator, after which cells were washed with PBS to end treatment, stained for 15 min at 4 °C using 0.5 μL of each antibody per tube (L/D, CD11c, CD86 and CD80), washed with PBS, and fixed with 100 μL of fixation buffer (BioLegend, 420801). For studies utilizing an MHC-I blocker, cells were incubated first for 30 min in 100 μL volume with 25 μg/mL of anti-MHC-I (BioXCell, E0077) Subsequently, SNAs in 100 μL volume were added to the cell and blocker solution and the samples were pulsed for 30 min. The remaining steps follow the protocol above. To assess T cell specificity and activation, 1.6 × 10⁵ purified DCs were pulsed with SNA treatment for 30 min in the incubator in a final volume of 200 μL. After the 30 min pulse, the cells were washed twice with RPMI +/+ to remove any residual SNAs from the cell solution, and the cells were resuspended in 500 μL RPMI +/+. Concurrently, splenocytes were isolated from a naïve mouse. After dissociation of the spleen and lysis of the red blood cells, the cells were counted and resuspended to a concentration of 3 × 10⁶ cells/mL in warmed RPMI +/+, and 100 μL of this cell solution was transferred to each well in a 96-well round bottom plate. To each well, 100 μL of treated DCs (3.3 × 10⁴ cells) were added so that the ratio of DC:splenocytes was 1:9. The cells were co-cultured for three days in the incubator, after which cells were washed with PBS and stained following the manufacturer’s instructions for either the DimerX Mouse H-2Kb:Ig Fusion Protein (BD, 552944) or OVA2 Tetramer (ProImmune). Staining antibodies in addition to the peptide-specific TCR markers included L/D, either CD8 or CD4, CD19, and CD69. After staining, the cells were fixed with 100 μL of fixation buffer. To assess T cell proliferation, 2.6 × 10⁵ of purified DCs were pulsed with SNA treatment for 30 min in the incubator in a final volume of 200 μL. After the 30 min pulse, the cells were washed twice with RPMI +/+ to remove any residual SNA from the cell solution, and the cells were resuspended in 266.6 μL RPMI +/+. Concurrently, splenocytes were isolated from a C57BL/6-Tg(TcraTcrb)1100Mjb/J (OT-1) mouse (Jackson, 003831). After dissociation of the spleen and lysis of the red blood cells, the cells were counted and resuspended to a concentration of 4 × 10⁷ cells/mL in PBS for staining with Cell Proliferation Dye eFluor^™ 450 (eBioscience, 65-0842-85), following the manufacturer’s instructions. After staining, the cells were washed, counted, and resuspended in RPMI +/+ to a concentration of 3 × 10⁶ cells/mL; 100 μL of this cell solution was transferred to each well in a 96-well round bottom plate. To each well, 33.3 μL of treated DCs (3.3 × 10⁴ cells) were added so that the ratio of DC:splenocytes was 1:9, and each well was brought up to 200 μL final volume with media. The cells were co-cultured for three days in the incubator, after which cells were washed with PBS, stained for CD8 (0.5 μL antibody per tube), washed, and immediately analyzed on flow cytometry using dilution of eFluor^™ 450 as a measure of T cell proliferation. All samples were analyzed using a BD A3 Symphony flow cytometer with data analyzed on FlowJo.

In Vivo Immunization to Measure Five-week Built-up Immune Responses:

Female C57BL/6 mice were subcutaneously immunized fortnightly three times with different treatments. Treatments included: simple mixture (admix, 6 nmol each peptide and 6 nmol CpG 1826 DNA), either DA-SNA (6 nmol by each OVA peptide and CpG 1826), or equivalent separate formulations of either DA-SNA (6 nmol by each OVA peptide and CpG 1826) or a double hybridized DA-SNA (termed “HH”; 6 nmol by each OVA peptide and 12 nmol CpG 1826). Volume of treatment injected was kept at 100 μL. One week after the final immunization, mice were sacrificed, and spleens were harvested for subsequent immune assessment.

Harvest Procedure:

Removed spleens were collected and held temporarily in 3–5 mL of RPMI +/+ until all spleens were collected, when they were passed through a 70 μm cell strainer with a constant flow of PBS. The cells were centrifuged at 1,200 rpm for 5 min, after which supernatant was removed, and the cells were resuspended in 2–3 mL ACK lysing buffer (Gibco, A1049201) for 4 min. To dilute the lysing buffer, PBS was then added to a final volume of 30 mL, and the cells were counted prior to centrifugation to resuspend in RPMI +/+ media at a concentration of 1×10⁸ cells mL⁻¹.

Ifn-γ Cytokine Production:

T cells were restimulated ex vivo to assess antigen-specific intracellular IFN-γ production. 4 × 10⁶ splenocytes were cultured for 4 h at 37 °C in a 5 % CO₂ incubator with 450 μL of RPMI +/+ media containing: either OVA1 or OVA2 peptide (10 μg/mL), monensin (2 μM), brefeldin A (5 μg/mL), and CD107a antibody (0.5 μL). After the 4 h incubation, cells were centrifuged at 1,200 rpm for 5 min, aspirated, and washed with 600 μL of PBS, prior to 15 min of staining with surface antibodies (0.5 μL per sample each of: L/D, CD8, CD4) at 4 °C. The cells were washed with 600 μL PBS, centrifuged at 1,200 rpm for 5 min, aspirated, and resuspended in 100 μL of Cytofix Fixation and Permeabilization solution (BD, 554722) for 20 min at 4 °C. After, the cells were washed with 600 μL of Perm/Wash Buffer (BD, 554723), centrifuged at 1,200 rpm for 5 min, aspirated, and resuspended in 100 μL of Perm/Wash Buffer containing the intracellular antibody IFN-γ (0.5 μL per sample). The samples were stored at 4 °C prior to flow cytometry analysis.

T cell Memory Phenotyping:

T cells were assessed for effector memory phenotype. 3 × 10⁶ splenocytes were washed with 600 μL PBS, and stained for 15 min with surface antibodies (0.5 μL per sample each of: L/D, CD8, CD4, CD44, and CD62L) at 4 °C. The cells were washed with 600 μL PBS, centrifuged at 1,200 rpm for 5 min, aspirated, and resuspended in 100 μL of Fixation buffer (BioLegend, 420801), and stored at 4 °C prior to flow cytometry analysis.

ELISpot Assay:

ELISpot analysis was performed using the commercially available Mouse INF-γ ELISPOT Set (BD, 551083) following the manufacturer’s instructions. Briefly, the provided clean plate was coated overnight at 4 °C with capture antibody. After, the plate was washed with RPMI+/+ media and then blocked for 2 h at room temperature with 200 μL of RPMI +/+ media. The blocking buffer was removed by pipetting, being mindful not to let wells dry out, and quickly replaced with 2 × 10⁵ splenocytes in 100 μL RPMI +/+. To each well, an additional 100 μL of either antigen, non-specific peptide, media (negative control), or positive control solutions were added (antigen and non-specific peptide were added to a final concentration of 5 μg/mL; positive control was prepared as a mixture of anti-CD3 and anti-CD28 antibodies at a final concentration of 2 μg/mL each). The solutions were left in an incubator at 37 °C in 5 % CO₂ for 48 h. After this incubation, the plate was washed, and detection antibody, enzyme conjugate, and chromogenic substrate were added according to the manufacturer’s instructions. The dried plate was imaged and analyzed using a CTL Immunospot imager.

Confocal Microscopy:

To evaluate the uptake and intracellular trafficking of DA-SNAs, BMDCs were harvested from murine femurs and purified for CD11c⁺ (as described above) and subsequently seeded on 8-chambered slides (Lab-Tek, 155409) at 50,000 cells/well. Following overnight incubation, cells were treated with DA-SNAs (2.5 μM) containing fluorophore-labeled OVA 1 and OVA2 antigens for either 0.5, 1, 6, or 24 h. For 6 and 24 h, cells were pulsed for 2 h with DA-SNAs and replaced with fresh media for the remaining time. After incubation at the indicated time points, cells were then fixed for 15 min (BioLegend) and blocked with 5% BSA (Thermo) in PBS containing 0.1% Triton-X for 1 h. Cells were then stained for organelle markers using primary antibodies for EEA1 (ratio 1:700, Abcam), Rab7 (1:500, Abcam), LAMP1 (1:200, ABclonal), PDI (1:50, Cell Signaling), MHC-I (1 μg/mL, BioXCell), and MHC-II (1 μg/mL, BioXCell) overnight at 4°C before secondary labeling with Alexa Fluor 555 (EEA1, Rab7, LAMP1, and PDI; Abcam ab150078) and Alexa Fluor 594 (MHC-I and MHC-II; Thermo A48264) for 1 h at 4°C. Cell nuclei were stained with DAPI for 1 min and stored in PBS until imaging. Imaging was performed using a Zeiss LSM 800 microscope maintaining the same parameters for all images. Mander’s overlap coefficient was calculated using ZEN software (Zeiss). For inhibitor studies (including those done via flow), cells were seeded at 150,000 cells/well. Following overnight incubation, cells were incubated with chloroquine (5 μM, Sigma), Brefeldin A (2 μg/mL, BioLegend), or leupeptin (100 μM, Sigma) for 1 h. Following 1 h incubation, media containing DA-SNA (2.5 μM) and indicated inhibitors was added and pulsed for an additional 1 h. After pulse with DA-SNAs, wells were washed with media and subsequently replaced with media containing inhibitors for a total incubation time of 24 h. Organelle staining was performed as described above.

Bulk RNA Sequencing:

Dendritic cells, CD4⁺ and CD8⁺ T cells were isolated from whole splenocytes from individual treatment groups following three fortnightly subcutaneous immunizations using magnetic positive selection kits (Stemcell Technologies, 17665, 18952, and 18953). From these isolated cell populations, RNA extraction was performed using an RNeasy^® Plus Mini Kit (Qiagen) in combination with QIAshredders (Qiagen) following manufacturer’s specifications. RNA concentration was quantified using a NanoDrop 8000 (Thermo Scientific), and RNA samples were stored in −80 °C until further use. Sequencing was conducted at the Northwestern University NUSeq Core Facility. Briefly, total RNA examples were checked for quality using RNA integrity numbers (RINs) generated from Agilent Bioanalyzer 2100. RNA quantity was confirmed with a Qubit fluorometer. The Illumina TruSeq Stranded mRNA Library Preparation Kit was used to prepare sequencing libraries from 125 ng of high-quality RNA samples (RIN>7). The kit procedure, including mRNA purification and fragmentation, cDNA synthesis, 3’ end adenylation, Illumina adapter ligation, library PCR amplification and validation, was performed without modifications. Libraries were sequenced using an Illumina HiSeq 4000 sequencer to generate 50 bp single reads at the depth of 20–25 million reads per sample. The quality of reads, in FASTQ format, was evaluated using FastQC. Reads were trimmed to remove Illumina adapters from the 3’ ends using cutadapt.⁵⁸ Trimmed reads were aligned to the Mus musculus genome (mm10) using STAR.⁵⁹ Read counts for each gene were calculated using htseq-count⁶⁰ in conjunction with a gene annotation file for mm10 obtained from Ensembl (http://useast.ensembl.org/index.html). Normalization and differential expression were calculated using DESeq2 that employed the Wald test.⁶¹ The cutoff for determining significantly differentially expressed genes was an FDR-adjusted p-value less than 0.05 using the Benjamini-Hochberg method.

Gene set enrichment analysis (GSEA):

GSEA⁶² was performed to understand whether differentially expressed genes were connected to differentially enriched pathways. Genes detected with RNA sequencing were ranked based on log₁₀-transformed nominal P values obtained from DeSeq2 analysis and were compared to naïve T cells. Pathway enrichment analysis was performed using the GSEA software (v4.0.3) and following the protocol of Reimand, et al.⁶³ Gene sets were obtained from the Molecular Signatures Database and included Reactome, KEGG. The ranked list was remapped using a CHIP platform from the Molecular Signatures Database that used the Mouse Gene Symbol to remap to Human Orthologs (v7.1). A term was defined as differentially enriched if it had an FDR < 0.05. A subset of strongly enriched pathways was selected for visualization in R using pheatmap package (v1.0.12). This selection included all pathways with an FDR < 0.05 and were of relevance to immune responses in dendritic, CD8⁺ and CD4⁺ T cells.

Gene expression profiles:

Genes whose expression were significantly altered in both SNA treatment groups, as defined by FDR p-value < 0.05, were selected for visualization as heatmaps. Gene expression scores in FPKM were converted to z-scores across treatment groups and gene expression values clustered using K-means clustering. Pairwise combinations were performed between two conditions of interest, setting naive CD4⁺ or CD8⁺ T cells as controls. Genes up or down regulated between groups as defined by FDR p-value < 0.05 and log₂ fold-change of > 0.5 (up-regulated) or log₂ fold-change < 0.05 (down-regulated) were visualized using a volcano plot.

In vivo efficacy studies:

Female C57BL/6 mice aged 8–12 weeks were acquired from The Jackson Laboratory. Tumor inoculation was performed by subcutaneously (s.c.) injecting animals with either 5 × 10⁵ E.G7-OVA, 10⁵ B16-F10, or 10⁵ MC-38 cells in the right flank. Immunizations were administered at a dose of either 6 nmol (OVA1/2 & Adpgk I/II) or 9 nmol (M27/30) of each antigen and CpG by s.c. injection in the abdomen. Immunizations were administered as listed in the treatment schedule provided in respective figures by s.c. injection in the abdomen. For combination therapy with the immune checkpoint inhibitor anti-PD-1, mice were administered 100 μg anti-mouse PD-1 (clone RMP1–14, BioXCell) via intraperitoneal injection. Tumor growth was measured on pre-determined days and volume was calculated using the following equation: tumor volume = length × width² × 0.5. Animals were euthanized when tumor volumes reached either 2,000 mm³ (E.G7-OVA) or 1,500 mm³ (B16-F10, MC-38) or when the animal became moribund.

In vivo Biodistribution and splenic uptake:

Biodistribution of DA-SNAs to major organs was performed in female C57BL/6 mice (n=3) using fluorophore-labeled OVA peptides and a single dose at 6 nmol administered subcutaneously (s.c.). Following 24 h, whole organs were harvested and stored briefly in PBS until imaged. Imaging was performed using an In Vivo Imaging System (IVIS) with excitation/emission filters set for 500/540 (FITC) and 640/680 (Cy5). Hybridized antigens were labeled using Cy5 fluorescent dye while encapsulated antigens were labeled using FITC fluorescent dye. Data was quantified by measuring with the Living Image software v4.5. Spleens collected from biodistribution analysis were mashed after imaging through a 70 μm cell strainer. Cells were pelleted at 1200 rpm for 5 min, and cells were resuspended in ACK lysing buffer (Gibco) for 4–5 min. Cells were diluted in PBS up to ~25–30 mL and counted. Three million cells were put into flow tubes and washed with PBS. Cells were incubated with staining solution containing 0.5 μL each of: fixable live/dead - UV and CD11c (clone N418, PE) for 15 min at 4 °C in 100 μL PBS. Supernatant was removed following a wash and centrifugation and cells were fixed in 100 μL of fixation buffer (BioLegend, 420801) and stored at 4 °C prior to flow cytometry.

Immunoactivation of PBMCs:

For collection of peripheral blood mononuclear cells (PBMCs), animals were inoculated with cancer cells as described above. Treatment was performed following the same schedule and animals were euthanized on day 15 (E.G7-OVA), day 16 (MC38), or day 17 (B16-F10). Blood was collected via cardiac puncture into EDTA-lined collection tubes (BD) and briefly mixed by inverting. Red blood cells were lysed using ACK lysing buffer (Gibco) and washed, and the remaining cells were subsequently stained using the methods described above with antibodies for L/D, CD4, CD8, CD19, CD44, CD62L, and antigen-specific dimer or pentamer, and tetramer (E.G7-OVA, B16-F10) or L/D, CD8, CD19, and antigen-specific pentamer (MC38).

Whole organ Immune Assessment:

Tumor weights and splenocyte evaluation was performed on C57BL/6 mice bearing an E.G7-OVA tumor in the right flank. Three days after tumor inoculation, the first immunization was administered followed by an additional dose 7 days later (day 10). The tumors and spleens were excised from the animals at day 15 and subsequently analyzed. Tumor microenvironment evaluation was performed on C57BL/6 mice bearing an MC-38 tumor in the right flank. Three days after tumor inoculation, the first immunization was administered followed by an additional dose 7 days later (day 10). Tumors were excised from the animals at day 16 and subsequently analyzed. To generate single-cell solutions, the spleens or tumors were mechanically forced through a 70 μm cell strainer while maintaining hydration in PBS solution. The cells were subsequently centrifuged at 1200 rpm for 5 min. The spleen pellet was resuspended in ACK lysing buffer (Thermo) for 4 min to lyse red blood cells and subsequently neutralized in PBS prior to centrifugation. Following centrifugation, the cells were labeled using the following antibodies: (E.G7-OVA) CD4, CD8, and CD19, L/D; (MC-38) CD4, CD8, CD45, CD11b, Gr-1, L/D.

Statistical Analysis:

Statistics were calculating using GraphPad Prism 8 software, and specific statistical analyses used are highlighted in the respective figure captions. Comparisons between multiple groups were analyzed with a one-way ANOVA with a Šidák or Tukey’s multiple comparison test, or a Welch ANOVA with a Dunnett multiple comparison test due to the lack of assumptions that could be made based on large differences in standard deviation between groups. Statistics for animal survival were calculated using a Log-rank test. Outliers for Figure 5e–f and Figure 6h,j were identified using the ROUT method with a Q set to 10% or 1%, respectively. For all cases, p-value was depicted as follows: *p < 0.05; **p < 0.01; ***p < 0.001; ****p < 0.0001; n.s. indicated that no significance was determined and n.d. indicates values were not detected. The allocation of animals to each group, administered immunizations, and measurements for tumor studies were performed blind. Values in graphs are depicted as the mean ± s.e.m. or s.d., and this, as well as sample size, is indicated in the respective figure caption.

Data availability

The data that support the findings of this study are available within the paper and its Supplementary Information. All data generated in this study are available from the corresponding author upon reasonable request.