Genetically engineered Magnesium/Manganese nanoparticles for cancer radioimmunotherapy

Abstract

Radiotherapy (RT) has great potential on activating antitumor immunity for combination therapy, yet this effect is limited by immunosuppressive tumor microenvironment (TME) and the potential toxicity in immune cells from high-dose radiation. Herein, we developed engineered nanoparticles (NPs) (CVs@MgMn) composed of genetically edited cellular vesicles (CVs), MnO₂ and MgCO₃ for enhanced radioimmunotherapy by remolding TME and activating the stimulator of the interferon genes (STING) pathway. In the TME, the efficiently enriched CVs@MgMn were decomposed to generate hydroxyl (‧OH) and oxygen (O₂) for radiosensitization. Subsequently, reduced Mn²⁺ activated the STING pathway to promote dendritic cell (DC) maturation, and the released Mg²⁺ boosted antitumor immunity by regulating CD8⁺ T cell metabolism and tumor-associated macrophage polarization. PD1-displayed CVs increased the targeting effect of NPs and mediated the PD-L1 blocking, all synergistically triggering antitumor immune responses. In both in situ and distant re-challenge models of melanoma, the combination of RT and nanocomposites demonstrated a strong radioimmunotherapy effect, resulting in an increased survival time and long-term immunological memory of tumor bearing mice. Moreover, MgCO₃ NPs synergistically promoted anti-PD-1 mAb immunotherapy. These findings highlight the importance of Mg/Mn combined supplementation and TME remolding during RT and immunotherapy, offered a simple and readily therapeutic strategy for patients with any type of solid tumor.

Keywords: Biomimetic nanoparticle; Cancer immunotherapy, Radiotherapy; Immune checkpoint blockade; cGAS-STING.

Fig. 1

Schematic depiction of engineered CVs@Mg/Mn NPs for cancer radioimmunotherapy. (A) Engineering strategy for CVs@MgMn NPs. (B) Schematic illustration of radiosensitization, DC activation, macrophage polarization and PD-L1 blockade mediated by CVs@Mg/Mn for radioimmunotherapy

Fig. 2

Preparation and characterization of CVs@MgMn. (A) Overexpression of PD1 protein on B16F10 cells detected using flow cytometry. (B) Immunofluorescence staining for stable expression of PD1 protein on B16F10 cells. Scale bar: 100 μm. (C) The stable presence of PD1 protein on the surface of B16F10 cells and its derived CVs detected using western blotting. (D, E) Nanoparticle tracking analysis (NTA) results (D) and TEM images (E) of CVs@MgMn and the PD1-CVs. Scale bar: 200 nm. (F) TEM morphological characteristics of the different NPs. Scale bar: 200 nm. (G) TEM and mapping analysis of CVs@MgMn. (H) EDX analysis of CVs@MgMn. (I, J) XPS analysis of MgMn: Mg1s (I), Mn2p spectrum (J). (K). XRD patterns of MgCO₃ NPs, MgMn and CVs@MgMn. (L). Zeta potential change of different NPs measured using DLS

Fig. 3

CVs@MgMn-mediated antitumor effect and radiosensitization in vitro. (A) Cytotoxicity of MgCO₃ NPs, MgMn, and CVs@MgMn against B16F10 cells in vitro. (B) Cell viability of B16F10 cells after X-ray irradiation for 24 h. (C) Cell viability of B16F10 cells after different treatments for 24 h. (D) Flow cytometry for the phagocytosis of cancer cells in different NPs. (E) Quantitative analysis for clone formation for B16F10 cells after different treatments (n = 3). (F) Quantitative analysis for apoptosis for B16F10 cells after different treatments (n = 3). (G) Expression level of apoptosis-related proteins in B16F10 cells after different treatments. (H) ROS level for B16F10 cells after different treatments. (I) Quantitative analysis of GSH level for B16F10 cells after different treatments (n = 3). (J) The representative JQ-1 staining for mitochondrial membrane potential for B16F10 cells after different treatments for 24 h. Scale bar: 200 μm. (K) Mitochondrial respiration profiles of B16F10 cells after different treatments (n = 5). All data are expressed as the mean ± s.d. Tukey-corrected two-way ANOVA were used for statistical analysis in (A, C, E, F, K). Tukey-corrected one-way ANOVA was used for statistical analysis in (I). Two-tailed unpaired t-test was used for statistical analysis in (B). (*, P < 0.05; **, P < 0.01; ***, P < 0.001)

Fig. 4

Immune activation roles of NPs in vitro. (A) Schematic illustration of the STING pathway activated by CVs@MgMn. (B) Representative figures of PD1-CVs modified NPs binding to the receptor. Red fluorescence is the cell membrane of B16F10 cells labeled by WGA^{Alexa Fluor 647}, green fluorescence is the DiO-labeled NPs. Scale bar: 100 μm. (C) Flow cytometry for PD-1 Amb binding after B16F10 cells pretreated with CVs@MgMn. (D) Cytotoxicity effect of CD8⁺ T cells on B16F10 cells in the presence of CVs or MgCO₃ NPs (n = 5). (E) Glucose metabolism capacity of mCD8⁺ T cells in the presence of MgCO₃ or PD1-CVs NPs (n = 5). (F) Representative flow cytometry plots and quantitative statistics of CD11c⁺CD80⁺CD86⁺ BMDCs after different treatments (n = 3). (G) Protein expression of STING pathway in BMDCs after different treatments. (H) The IFN-β and CXCL10 secretion in supernatant of BMDCs after different treatments (n = 5). (I) Quantitative statistics of M1-like (CD80⁺CD86⁺) RAW264.7 cells after treatments with B16F10 cell supernatant containing LPS or different NPs (n = 3). (J) Quantitative statistics of M2-like (CD206⁺) RAW264.7 cells after treatment with B16F10 cell supernatant containing IL-4 or IL-4 + NPs (n = 3). (K) Cytokine levels of TNF-α and IFN-γ isolated from RAW264.7 cells in vitro after treatment with LPS or different NPs. Data are expressed as the mean ± s.d. (*, P < 0.05; **, P < 0.01; ***, P < 0.001 by one-way ANOVA with Tukey’s multiple comparison test)

Fig. 5

The tumor targeting and radiosensitization effects of CVs@MgMn in vivo. (A, B) Fluorescence imaging and corresponding statistics of the tumor-bearing mice after nanoparticle i.v. injection (n = 3). (C, D) Fluorescence imaging and corresponding fluorescence intensities of major organs and tumors after nanoparticle i.v. injection for 24 h (n = 3). (E) Fluorescence imaging and corresponding fluorescence statistics for tumors after different treatments (n = 3). (F) Hemolysis assay of CVs@MgMn with different concentrations in vitro (n = 3). (G) Tumor growth curves with time for different groups (n = 5). (H) Statistics of tumor weights at the end of the experiment (n = 5). (I) Schematic illustration of the in vivo experimental design for B16F10 tumors. (J) Tumor growth curves with time for different groups (n = 5). (K) Body weights of tumor-bearing mice with different treatment (n = 5). (L) Statistics for tumor weights at the end of the experiment (n = 5). Tukey-corrected two-way ANOVA were used for statistical analysis in (A), (C), (E), (F), (K). Tukey-corrected one-way ANOVA was used for statistical analysis in (G, J, K). Two-tailed unpaired t-test was used for statistical analysis in (E). The log-rank (Mantel-Cox) test was used for statistical analysis in (H, L). (*, P < 0.05; **, P < 0.01; ***, P < 0.001)

Fig. 6

Radiosensitization and immune activation effects of CVs@MgMn in vivo. (A, B) Representative flow cytometry plots of DCs (A) and CD8⁺ T cell (B) in tumor tissues after different treatments. (C-E) Quantitative statistics of immune cells for DCs (C), CD8⁺ T cell (D) and M1-like macrophages (E) in tumor tissues after different treatments (n = 4). (F) Transcriptomic alteration in tumors between PD1-CVs and PBS group after two-way cluster analysis (n = 3). (G) Heatmap of representative genes with significant changes between the CVs@MgMn, PD1-CVs and PBS groups (n = 3). (H) GSEA enrichment analysis for upregulated genes in tumors between the CVs@MgMn and PBS treatment groups (n = 3). Data are expressed as the mean ± s.d. Two-tailed Student’s t-test was performed for statistical analysis. (*, P < 0.05; **, P < 0.01; ***, P < 0.001)

Fig. 7

The enhanced in situ vaccine effects of RT by CVs@MgMn (A) In vivo schematic illustration of the experimental design for bilateral tumor model. (B) Primary tumor growth curves with time for different groups (n = 5). (C) Distal tumor growth curves with time for different groups (n = 5). (D) Distal tumor volume for different groups at the end of the experiments (n = 5). (E-G) Quantitative statistics for CD8⁺ T cells (G), CD8⁺IFN-γ⁺ T cells (F) and CD8⁺GramB⁺ T cells in tumor tissues after different treatments (n = 4). (H-J) Representative flow cytometry plots (H) and quantitative statistics of effective memory T cells (I, CD44⁺CD62L⁻) or central memory T cells (J, CD44⁺CD62L⁺) in distant tumor tissues after different treatments (n = 4). (K) Quantitative statistics of Tregs (Foxp3⁺CD4⁺CD3⁺) cells in distant tumor tissues after different treatments (n = 4). Data are expressed as the mean ± s.d. Two-tailed Student’s t-test was used to determine statistical significance. (*, P < 0.05; **, P < 0.01; ***, P < 0.001)