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Modulating active targeting nanoparticle design according to tumor progressions

Nie, Huifang, Huang, Rong, Jiang, Guangwei, Li, Wenshuai, Yang, Lan, Zhang, Meng, Qian, Min, Guo, Wei, Ye, Tao, Huang, Rongqin·2025·Acta Pharmaceutica Sinica B
DOI 10.1016/j.apsb.2024.12.016PMC PMC11959910
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Graphical abstract Graphical abstract The changes in pathophysiology characterizations with the tumor development influence the accumulation and permeation behavior of actively targeted nanoparticles with different sizes.
Graphical abstract Graphical abstract The changes in pathophysiology characterizations with the tumor development influence the accumulation and permeation behavior of actively targeted nanoparticles with different sizes.CC BY-NC-ND · PubMed Central
Figure 1 Schematic illustration of nanoparticles entering the blood circulation, passing through the blood vessel wall and tumor stroma, and entering the tumor tissues.
Figure 1 Schematic illustration of nanoparticles entering the blood circulation, passing through the blood vessel wall and tumor stroma, and entering the tumor tissues.CC BY-NC-ND · PubMed Central
Figure 2 Nanoparticle synthesis and characterizations. (A–D) TEM images, corresponding histograms, and Gaussian fits of the measured AuNP size distribution as determined from their TEM micrographs, high-resolution TEM image, and locally enlarged image of AuNP with sizes 7 nm (A), 15 nm (B), 45 nm (C) and 90 nm (D). Hydrodynamic diameter distribution (E) and UV–Vis spectra (F) of different-sized AuNPs dispersed in water.
Figure 2 Nanoparticle synthesis and characterizations. (A–D) TEM images, corresponding histograms, and Gaussian fits of the measured AuNP size distribution as determined from their TEM micrographs, high-resolution TEM image, and locally enlarged image of AuNP with sizes 7 nm (A), 15 nm (B), 45 nm (C) and 90 nm (D). Hydrodynamic diameter distribution (E) and UV–Vis spectra (F) of different-sized AuNPs dispersed in water.CC BY-NC-ND · PubMed Central
Figure 3 Physiological and pathological characterizations of tumor tissues during growth. (A) Schematic illustration of the establishment of the four stages of in-situ breast cancer mouse models by the time interval method. (B, C) Representative fluorescence images depicting the evolution of the expression of integrin αvβ3 (B) and vascular density (C) with tumor sizes. (D, E) Representative bright-field and polarized light images of sections stained with Picrosirius red describing the development of collagen with tumor sizes. (F) Immunofluorescence images of tumor section to analyze the expression of α-SMA, FAP, and S100A4 with tumor sizes. (G) Representative photographs of CD68/CD86/CD163 immunofluorescence staining depicting the change in the density of tumor-associated macrophages (CD68), M1 (CD68/CD86), and M2 (CD68/CD163) with tumor sizes. The white arrows indicate M1 or M2 cells. (H) Quantitative analysis of the amount of M1 and M2 macrophages in tumor tissues (left) and percentage of M1/M2 (right). (I) Representative photographs of VEGF immunofluorescence staining depicting the change of vascular permeability with tumor sizes. (J) Representative photographs of LYVE-1 immunofluorescence staining depicting the change of lymphatic permeability with tumor sizes. The yellow box is located at the edge of the tumor tissue, while the red box is located inside the tumor tissue. The lower panels are enlarged sections of the boxed regions from the upper panels. Dashed circles indicate lymphatic vessels. Data are mean ± SEM (n = 10).
Figure 3 Physiological and pathological characterizations of tumor tissues during growth. (A) Schematic illustration of the establishment of the four stages of in-situ breast cancer mouse models by the time interval method. (B, C) Representative fluorescence images depicting the evolution of the expression of integrin αvβ3 (B) and vascular density (C) with tumor sizes. (D, E) Representative bright-field and polarized light images of sections stained with Picrosirius red describing the development of collagen with tumor sizes. (F) Immunofluorescence images of tumor section to analyze the expression of α-SMA, FAP, and S100A4 with tumor sizes. (G) Representative photographs of CD68/CD86/CD163 immunofluorescence staining depicting the change in the density of tumor-associated macrophages (CD68), M1 (CD68/CD86), and M2 (CD68/CD163) with tumor sizes. The white arrows indicate M1 or M2 cells. (H) Quantitative analysis of the amount of M1 and M2 macrophages in tumor tissues (left) and percentage of M1/M2 (right). (I) Representative photographs of VEGF immunofluorescence staining depicting the change of vascular permeability with tumor sizes. (J) Representative photographs of LYVE-1 immunofluorescence staining depicting the change of lymphatic permeability with tumor sizes. The yellow box is located at the edge of the tumor tissue, while the red box is located inside the tumor tissue. The lower panels are enlarged sections of the boxed regions from the upper panels. Dashed circles indicate lymphatic vessels. Data are mean ± SEM (n = 10).CC BY-NC-ND · PubMed Central
Figure 4 Analysis of the ability of nanoparticles to cross vascular endothelial HUVEC cell monolayers, fibroblast M 20 cell monolayers, and be taken up by tumor cells. (A) Diagrammatic sketch of the multivalent interactions between RGD and integrin αvβ3. (B, C) Flow cytometry analysis of endothelial cellular uptake of active AuNPs with different sizes. (D, E) Quantitative comparisons of endothelial cellular uptake of active AuNPs at 4 and 37 °C by flow cytometry (D) and ICP-OES (E). (F) Relative fluorescence intensity of active AuNPs taken up by endothelial cells incubated with endocytosis inhibitors such as colchicine, filipin, and PhAsO. Results were normalized to the fluorescence intensity of the control. (G) Schematic representations of the Transwell assay imitating the vascular wall or tumoral matrix barrier in vitro. (H) Transwell assay analysis of the ability of active AuNPs to cross vascular endothelial cells within 2 h at 4 and 37 °C. (I) Transwell assay analysis of the ability of active AuNPs to cross vascular endothelial cells within 24 h at 37 °C. (J) Transwell assay analysis of the ability of active AuNPs to pass through M 20 human embryonic fibroblast layers at 2, 4, and 24 h. (K) Recognition and uptake of active AuNPs by MCF-10A and MDA-MB-231 cells by ICP-OES. (L) ICP-OES analysis of MDA-MB-231 cellular uptake of active AuNPs with different sizes. Data are mean ± SEM. ∗P < 0.05; ∗∗P < 0.01; ∗∗∗P < 0.001; one-way ANOVA (C, I, J) and two-way ANOVA (D–F, H, K).
Figure 4 Analysis of the ability of nanoparticles to cross vascular endothelial HUVEC cell monolayers, fibroblast M 20 cell monolayers, and be taken up by tumor cells. (A) Diagrammatic sketch of the multivalent interactions between RGD and integrin αvβ3. (B, C) Flow cytometry analysis of endothelial cellular uptake of active AuNPs with different sizes. (D, E) Quantitative comparisons of endothelial cellular uptake of active AuNPs at 4 and 37 °C by flow cytometry (D) and ICP-OES (E). (F) Relative fluorescence intensity of active AuNPs taken up by endothelial cells incubated with endocytosis inhibitors such as colchicine, filipin, and PhAsO. Results were normalized to the fluorescence intensity of the control. (G) Schematic representations of the Transwell assay imitating the vascular wall or tumoral matrix barrier in vitro. (H) Transwell assay analysis of the ability of active AuNPs to cross vascular endothelial cells within 2 h at 4 and 37 °C. (I) Transwell assay analysis of the ability of active AuNPs to cross vascular endothelial cells within 24 h at 37 °C. (J) Transwell assay analysis of the ability of active AuNPs to pass through M 20 human embryonic fibroblast layers at 2, 4, and 24 h. (K) Recognition and uptake of active AuNPs by MCF-10A and MDA-MB-231 cells by ICP-OES. (L) ICP-OES analysis of MDA-MB-231 cellular uptake of active AuNPs with different sizes. Data are mean ± SEM. ∗P < 0.05; ∗∗P < 0.01; ∗∗∗P < 0.001; one-way ANOVA (C, I, J) and two-way ANOVA (D–F, H, K).CC BY-NC-ND · PubMed Central
Figure 5 Permeation behavior of active AuNPs into tumor spheroids. (A) Representative confocal microscope images and (B) quantitative analysis of the pervasion distance of active and passive AuNPs into MDA-MB-231 tumor spheroids. (C) Representative confocal microscope images and (D) quantitative analysis of the pervasion distance of active AuNPs with different sizes into MDA-MB-231 tumor spheroids. (E) The analysis of the pervasion distance of active AuNPs with different sizes into 3D coculture of MDA-MB-231 with M 20 cells in a ratio of 10:1, 5:1, 2:1, and 1:1. (F) All the penetration distance in (E) was normalized to the mean of penetration distance in a ratio of 10:1. (G) The analysis of the penetration distance of active AuNPs with different sizes into 3D coculture of MDA-MB-231 with THP-1 cells in a ratio of 10:1, 5:1, 2:1, and 1:1. (H) All the penetration distance in (E) was normalized to the mean of penetration distance in a ratio of 10:1. Data are mean ± SEM (n = 3). ∗P < 0.05; ∗∗P < 0.01; ∗∗∗P < 0.001; two-way ANOVA (B) and one-way ANOVA (D–H).
Figure 5 Permeation behavior of active AuNPs into tumor spheroids. (A) Representative confocal microscope images and (B) quantitative analysis of the pervasion distance of active and passive AuNPs into MDA-MB-231 tumor spheroids. (C) Representative confocal microscope images and (D) quantitative analysis of the pervasion distance of active AuNPs with different sizes into MDA-MB-231 tumor spheroids. (E) The analysis of the pervasion distance of active AuNPs with different sizes into 3D coculture of MDA-MB-231 with M 20 cells in a ratio of 10:1, 5:1, 2:1, and 1:1. (F) All the penetration distance in (E) was normalized to the mean of penetration distance in a ratio of 10:1. (G) The analysis of the penetration distance of active AuNPs with different sizes into 3D coculture of MDA-MB-231 with THP-1 cells in a ratio of 10:1, 5:1, 2:1, and 1:1. (H) All the penetration distance in (E) was normalized to the mean of penetration distance in a ratio of 10:1. Data are mean ± SEM (n = 3). ∗P < 0.05; ∗∗P < 0.01; ∗∗∗P < 0.001; two-way ANOVA (B) and one-way ANOVA (D–H).CC BY-NC-ND · PubMed Central
Figure 6 Accumulation and permeation of active AuNPs in tumor tissues. (A) Schematic illustration for evaluating the accumulation and permeation of active AuNPs on orthotopic breast cancer mouse models. (B) Fluorescence distribution of active AuNPs with different sizes in tumors of different volumes at 24 h after intravenous administration. (C) Fluorescence distribution of active AuNPs depicting how tumoral accumulation of AuNPs with different sizes varies with tumor volume and the expression of integrin αvβ3 at 24 h after intravenous administration. Red: Cy5-labeled active AuNPs; green: FITC-marked integrin αvβ3. (D) Quantitative analysis of active AuNPs levels in tumors with different volumes as measured by ICP-OES at 24 h after intravenous administration. Results were normalized to injection dose per gram of tumor. Data are mean ± SEM (n = 3). ∗P < 0.05; ∗∗P < 0.01; ∗∗∗P < 0.001; two-way ANOVA. (E) Distribution of active AuNPs with different sizes away from tumor blood vessels at 24 h after intravenous administration. Red: Cy5-labeled active AuNPs; green: integrin αvβ3. (F, G) Representative TEM images of the transvascular (F) and tumor tissue permeability (G) of active AuNPs with different sizes in II tumors. Scale bars, 5 μm; insets, 500 nm.
Figure 6 Accumulation and permeation of active AuNPs in tumor tissues. (A) Schematic illustration for evaluating the accumulation and permeation of active AuNPs on orthotopic breast cancer mouse models. (B) Fluorescence distribution of active AuNPs with different sizes in tumors of different volumes at 24 h after intravenous administration. (C) Fluorescence distribution of active AuNPs depicting how tumoral accumulation of AuNPs with different sizes varies with tumor volume and the expression of integrin αvβ3 at 24 h after intravenous administration. Red: Cy5-labeled active AuNPs; green: FITC-marked integrin αvβ3. (D) Quantitative analysis of active AuNPs levels in tumors with different volumes as measured by ICP-OES at 24 h after intravenous administration. Results were normalized to injection dose per gram of tumor. Data are mean ± SEM (n = 3). ∗P < 0.05; ∗∗P < 0.01; ∗∗∗P < 0.001; two-way ANOVA. (E) Distribution of active AuNPs with different sizes away from tumor blood vessels at 24 h after intravenous administration. Red: Cy5-labeled active AuNPs; green: integrin αvβ3. (F, G) Representative TEM images of the transvascular (F) and tumor tissue permeability (G) of active AuNPs with different sizes in II tumors. Scale bars, 5 μm; insets, 500 nm.CC BY-NC-ND · PubMed Central
Figure 7 Effect of integrin αvβ3 expression on tumor cellular uptake and tumor tissue accumulation of active AuNPs. Confocal microscopy (A) and flow cytometric analysis (B) of the internalization of active AuNPs by MDA-MB-231 cells pretreated with RGD at concentrations of 1, 5, and 10 μmol/L. (C) Quantitative analysis of flow cytometric results. Data are mean ± SEM (n = 3). ∗∗P < 0.01; ∗∗∗P < 0.001; one-way ANOVA. (D) Confocal microscopy images of tumor tissue distribution of active AuNPs depicting the distribution of active AuNPs with the expression of integrin αvβ3 in the tumor. Right: quantitative analysis of fluorescence intensity of integrin αvβ3 and active AuNPs in cyan and yellow circles by Image J.
Figure 7 Effect of integrin αvβ3 expression on tumor cellular uptake and tumor tissue accumulation of active AuNPs. Confocal microscopy (A) and flow cytometric analysis (B) of the internalization of active AuNPs by MDA-MB-231 cells pretreated with RGD at concentrations of 1, 5, and 10 μmol/L. (C) Quantitative analysis of flow cytometric results. Data are mean ± SEM (n = 3). ∗∗P < 0.01; ∗∗∗P < 0.001; one-way ANOVA. (D) Confocal microscopy images of tumor tissue distribution of active AuNPs depicting the distribution of active AuNPs with the expression of integrin αvβ3 in the tumor. Right: quantitative analysis of fluorescence intensity of integrin αvβ3 and active AuNPs in cyan and yellow circles by Image J.CC BY-NC-ND · PubMed Central

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Metadata

Authors
Nie, H., Huang, R., Jiang, G., Li, W., Yang, L., Zhang, M., Qian, M., Guo, W., Ye, T., & Huang, R.
Venue
Acta Pharmaceutica Sinica B
Publisher
Elsevier BV
Published
2025-02
Volume
15
Issue
2
Pages
1143-1158
ISSN
2211-3835
DOI
10.1016/j.apsb.2024.12.016
PMC
PMC11959910
Cited by
15
References
2
Language
en
Licence
Funders
National Natural Science Foundation of China (82172746, 82473342)

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Nie, H., Huang, R., Jiang, G., Li, W., Yang, L., Zhang, M., Qian, M., Guo, W., Ye, T., & Huang, R. (2025). Modulating active targeting nanoparticle design according to tumor progressions. Acta Pharmaceutica Sinica B. https://doi.org/10.1016/j.apsb.2024.12.016