Optimized Fabrication of Dendritic Mesoporous Silica Nanoparticles as Efficient Delivery System for Cancer Immunotherapy

Abstract

In the past decade, cancer immunotherapy has revolutionized the field of oncology. Major immunotherapy approaches such as immune checkpoint inhibitors, cancer vaccines, adoptive cell therapy, cytokines, and immunomodulators have shown great promise in preclinical and clinical settings. Among them, immunomodulatory agents including cancer vaccines are particularly appealing; however, they face limitations, notably the absence of efficient and precise targeted delivery of immune-modulatory agents to specific immune cells and the potential for off-target toxicity. Nanomaterials can play a pivotal role in addressing targeting and other challenges in cancer immunotherapy. Dendritic mesoporous silica nanoparticles (DMSNs) can enhance the efficacy of cancer vaccines by enhancing the effective loading of immune modulatory agents owing to their tunable pore sizes. In this work, an emulsion-based method is optimized to customize the pore size of DMSNs and loaded DMSNs with ovalbumin (OVA) and cytosine-phosphate-guanine (CpG) oligodeoxynucleotides (CpG-OVA-DMSNs). The immunotherapeutic effect of DMSNs is achieved through controlled chemical release of OVA and CpG in antigen-presenting cells (APCs). The results demonstrated that CpG-OVA-DMSNs efficiently activated the immune response in APCs and reduced tumor growth in the murine B16-OVA tumor model.

Keywords: cancer vaccines; delivery platform; dendritic mesoporous silica nanoparticles; immunotherapy.

Figure 1.

Overview of the synthesis and immunotherapeutic application of CpG-OVA-DMSNs. (a) Synthetic strategy to fabricate CpG-OVA-DMSNs from regular DMSNs. (b) In vitro priming of APCs by using CpG-OVA-DMSNs. (c) In vivo testing of the immunotherapeutic effect of CpG-OVA-DMSNs in B16-OVA melanoma model.

Figure 2.

Characterization of DMSNs with different volume ratios of TMB/water. (a) Schematic representation of the transformation of regular pores to dendritic nanostructure based on tuning the volume ratio TMB/water and microemulsion stabilization time. (b) TEM images of regular and DMSNs at different TMB/water ratios depicting the change on the pore structure of the nanoparticles. Scale bar = 50 nm. (c) Pore size distribution of the MSN materials as determined by the N₂ sorption isotherms. (d) Hydrodynamic diameters and (e) ξ-potential measurements of the synthesized DMSNs. (f) Surface area and (g) pore volume determined by the BJH and BET methods based on the N₂ sorption isotherms.

Figure 3.

Schematic representation of the fabrication of CpG-OVA-DMSNs. (a) Hydrodynamic diameter and (b) ξ- potential values of the DMSN materials; DMSNs (purple), AP-DMSNs (blue), SPDP-DMSNs (green), OVA-DMSNs (orange), and CpG-OVA-DMSNs (red). (c) Evaluation of the loading percentage calculated by the total OVA and CpG conjugated per mg of DMSNs. (d) Determination of the available amines on the AP- and SPDP-DMSNs using the ninhydrin test. (e) Colloidal stability of CpG-OVA-DMSNs in PBS (pH=7.4) at 37 °C. (f) Release profile of OVA and CpG from CpG-OVA-DMSN material in the presence of DTT at 10 mM (pH=7.4 and room temperature).

Figure 4.

In vitro evaluation of DMSNs in murine macrophages and DCs. (a) Biocompatibility of DMSNs tested in murine immune cells; RAW 264.7 (a1) and DC2.4 (a2). (b) Flow cytometry data for the cellular uptake of T-DMSNs by RAW 264.7 and DC2.4 cells. (c) Confocal images of RAW 264.7 (c1) and DC2.4 (c2) after treatment with FT-DMSNs (Scale bar = 10 μm). CD86 (d) and CD40 (e) expression in RAW 264.7 cells. Production of IL-6 (f) and TNF-α (g) cytokines by RAW 264.7 cells. Expression of OVA-MHC (h) and CD40 (i) in DC2.4. Statistical significance: P values: ns = not significant, *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001).

Figure 5.

Therapeutic benefit of CpG-OVA-DMSNs in syngeneic B16/OVA melanoma model. (a) Treatment regimen followed to monitor the tumor progression, biochemistry and safety of CpG-OVA-DMSNs and immune analysis in different organs post-treatment. (b) Tumor volume measurements in control (PBS, black), DMSNs (dark purple), Free CpG/OVA (light purple) and OVA-CpG-DMSNs (red). (c) Tumor volumes of all treatment groups at day 16 post-treatment. (d) Kaplan-Meier survival curve of mice in; control (PBS, black), DMSNs (dark purple), Free CpG/OVA (light purple) and OVA-CpG-DMSNs (red). (e) Schematic representation of interaction of activated CTLs with the tumors cells in the TME post-treatment. (f) Representative flow plots depicting the gating of CD4 and CD8 T cells (top panel) and tetramer⁺ T cells in tumors post-treatment from mice in control (black), Free CpG/OVA (light purple) and OVA-CpG-DMSNs (red) treatment groups. Composition of immune cells (macrophages, DCs, CD4 T, CD8 T, and tetramer⁺ T cells) in tumors (g) and lymph nodes (h) from mice in control (black), Free CpG/OVA (light purple) and CpG-OVA-DMSNs (red) treatment groups. Statistical significance comparisons for survival P values were calculated by the log-rank (Mantel–Cox) test, for tumor inhibition were done using two-way ANOVA with Tukey’s multiple-comparison test, and for tumor weight two-tailed Mann–Whitney test was used.

Figure 6.

In vivo safety profile of nanoparticles. (a) Body weight loss (%). (b) Complete blood count (CBC) and blood chemistry analyses. (c) H&E stained representative images of major organs including liver, lungs and kidneys after the treatment with PBS, free CpG/OVA and CpG-OVA-DMSNs. Scale bar = 200 μm. RBC, red blood cells (10¹²/liter); WBC, white blood cells (10⁹/liter); PLT, platelets (10⁹/liter); Neutro, neutrophils (% in WBC); Mon, monocytes (% in WBC); Lym, lymphocytes (% in WBC); ALT, alanine aminotransferase (U/liter); AST, aspartate aminotransferase (U/liter); T.P., total protein (g/dl); BUN, blood urea nitrogen (mg/dl); Cr, creatinine (mg/dl). Data are reported as mean ± SD (N = 4). A statistically significant difference was observed between the treated mice and the control group. Ordinary one-way ANOVA followed by Dunnett’s multiple-comparisons test was applied for statistical analyses. P values: NS, not significant, *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001).