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Curvature-mediated rapid extravasation and penetration of nanoparticles against interstitial fluid pressure for improved drug delivery

Jiang, Xiaohe, Xu, Sai, Miao, Yunqiu, Huang, Kang, Wang, Bingqi, Ding, Bingwen, Zhang, Zhuan, Zhao, Zitong, Zhang, Xinxin, Shi, Xinghua, Yu, Miaorong, Tian, Falin, Gan, Yong·2024·Proceedings of the National Academy of Sciences

Abstract

Elevated interstitial fluid pressure (IFP) within pathological tissues (e.g., tumors, obstructed kidneys, and cirrhotic livers) creates a significant hindrance to the transport of nanomedicine, ultimately impairing the therapeutic efficiency. Among these tissues, solid tumors present the most challenging scenario. While several strategies through reducing tumor IFP have been devised to enhance nanoparticle delivery, few approaches focus on modulating the intrinsic properties of nanoparticles to effectively counteract IFP during extravasation and penetration, which are precisely the stages obstructed by elevated IFP. Herein, we propose an innovative solution by engineering nanoparticles with a fusiform shape of high curvature, enabling efficient surmounting of IFP barriers during extravasation and penetration within tumor tissues. Through experimental and theoretical analyses, we demonstrate that the elongated nanoparticles with the highest mean curvature outperform spherical and rod-shaped counterparts against elevated IFP, leading to superior intratumoral accumulation and antitumor efficacy. Super-resolution microscopy and molecular dynamics simulations uncover the underlying mechanisms in which the high curvature contributes to diminished drag force in surmounting high-pressure differentials during extravasation. Simultaneously, the facilitated rotational movement augments the hopping frequency during penetration. This study effectively addresses the limitations posed by high-pressure impediments, uncovers the mutual interactions between the physical properties of NPs and their environment, and presents a promising avenue for advancing cancer treatment through nanomedicine.

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Crossref · 10.1073/pnas.2319880121

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Figures

Fig. 1. Characterization of pathological extravasation and penetration environment in tumor. (A) Schematic diagram representing distinct IFP region and the IFP values of tumor interstitium, with 0 mm indicating the starting position of the blood vessel. (B) Representative Masson trichrome stained clinical specimen of human tumor vasculature of hepatic cancer. Yellow line: blood vessel wall; red line: boundary between extravasation and penetration. (Scale bar, 50 μm.) (C) Collagen content and (D) Porosity of extravasation and penetration region. (P > 0.05, ns; *P < 0.05; **P < 0.01; ***P < 0.001, ****P < 0.0001)
Fig. 1. Characterization of pathological extravasation and penetration environment in tumor. (A) Schematic diagram representing distinct IFP region and the IFP values of tumor interstitium, with 0 mm indicating the starting position of the blood vessel. (B) Representative Masson trichrome stained clinical specimen of human tumor vasculature of hepatic cancer. Yellow line: blood vessel wall; red line: boundary between extravasation and penetration. (Scale bar, 50 μm.) (C) Collagen content and (D) Porosity of extravasation and penetration region. (P > 0.05, ns; *P < 0.05; **P < 0.01; ***P < 0.001, ****P < 0.0001)CC BY-NC-ND · PubMed Central
Fig. 2. Characterization of NPs of different curvatures. (A) Left: TEM images; Middle: Scheme of NPs; Right: Curvature distribution. a for the apical endpoint, b for the blunt endpoint. (Scale bar, 100 nm.) (B) Apical mean curvatures, (C) Blunt mean curvatures. (P > 0.05, ns; *P < 0.05; **P < 0.01; ***P < 0.001, ****P < 0.0001)
Fig. 2. Characterization of NPs of different curvatures. (A) Left: TEM images; Middle: Scheme of NPs; Right: Curvature distribution. a for the apical endpoint, b for the blunt endpoint. (Scale bar, 100 nm.) (B) Apical mean curvatures, (C) Blunt mean curvatures. (P > 0.05, ns; *P < 0.05; **P < 0.01; ***P < 0.001, ****P < 0.0001)CC BY-NC-ND · PubMed Central
Fig. 3. NP extravasation against IFP in tumor environment in vitro. (A) Schematic illustration of a microfluidic model to simulate the tumor environment with high IFP. (B) Photographic images of NP extravasation in vitro using the in vivo imaging system (IVIS) system. The images are representative of the average at each time point. (C) The cumulative extravasation percentage obtained by the in vitro modeling of extravasation at distinct time points. (D) Heat map of sedimentation depths of NPs overcoming pressure differentials. (P > 0.05, ns; *P < 0.05; **P < 0.01; ***P < 0.001, ****P < 0.0001).
Fig. 3. NP extravasation against IFP in tumor environment in vitro. (A) Schematic illustration of a microfluidic model to simulate the tumor environment with high IFP. (B) Photographic images of NP extravasation in vitro using the in vivo imaging system (IVIS) system. The images are representative of the average at each time point. (C) The cumulative extravasation percentage obtained by the in vitro modeling of extravasation at distinct time points. (D) Heat map of sedimentation depths of NPs overcoming pressure differentials. (P > 0.05, ns; *P < 0.05; **P < 0.01; ***P < 0.001, ****P < 0.0001).CC BY-NC-ND · PubMed Central
Fig. 4. NP penetration against ECM in tumor environment in vitro. (A and B) MSD of NPs in ECM of low and high IFP, respectively. (C and D) Diffusion coefficient of NPs in ECM of low and high IFP, respectively. (E) 3D motion snapshots of NPs in high IFP. (F) 3D motion trajectories of NPs in high IFP. (P > 0.05, ns; *P < 0.05; **P < 0.01; ***P < 0.001, ****P < 0.0001)
Fig. 4. NP penetration against ECM in tumor environment in vitro. (A and B) MSD of NPs in ECM of low and high IFP, respectively. (C and D) Diffusion coefficient of NPs in ECM of low and high IFP, respectively. (E) 3D motion snapshots of NPs in high IFP. (F) 3D motion trajectories of NPs in high IFP. (P > 0.05, ns; *P < 0.05; **P < 0.01; ***P < 0.001, ****P < 0.0001)CC BY-NC-ND · PubMed Central
Fig. 5. The mechanism underneath curvature-mediated NP extravasation against IFP in tumors from finite element simulation. (A) Schematics of the model used in the finite element simulations. (B and C) The moving distance and resistance of the NPs in the PG-induced flow field.
Fig. 5. The mechanism underneath curvature-mediated NP extravasation against IFP in tumors from finite element simulation. (A) Schematics of the model used in the finite element simulations. (B and C) The moving distance and resistance of the NPs in the PG-induced flow field.CC BY-NC-ND · PubMed Central
Fig. 6. The diffusivity of NPs in ECM-like polymer network from MD simulation. (A) The typical coarse-grained model used in the simulation. (B and C) The representative MSD and diffusivities of the four types of NP in a polymer network with a mesh size of 12σ, respectively. (D) The diffusivities for four types of NPs when the mesh size of the polymer network was tuned from 9σ to 15σ gradually.
Fig. 6. The diffusivity of NPs in ECM-like polymer network from MD simulation. (A) The typical coarse-grained model used in the simulation. (B and C) The representative MSD and diffusivities of the four types of NP in a polymer network with a mesh size of 12σ, respectively. (D) The diffusivities for four types of NPs when the mesh size of the polymer network was tuned from 9σ to 15σ gradually.CC BY-NC-ND · PubMed Central
Fig. 7. Simulation study of the mechanism underneath curvature-mediated NP penetration in ECM of tumors. (A) The variation of displacement (along the Y direction) and the rotational angle (around the Z-axis) for a typical ENP5 during a period of simulation time. The two green regions indicated the “rotation-hopping” of the ENP5 during the diffusion processes. Inset is the schematic of the rotation angle. (B) A significant change in the position and orientation of ENP5 during the simulation. (C) Distributions of the angular velocity of NPs within a period of simulation time. (D) The time proportion for NPs in the rotation-hopping states.
Fig. 7. Simulation study of the mechanism underneath curvature-mediated NP penetration in ECM of tumors. (A) The variation of displacement (along the Y direction) and the rotational angle (around the Z-axis) for a typical ENP5 during a period of simulation time. The two green regions indicated the “rotation-hopping” of the ENP5 during the diffusion processes. Inset is the schematic of the rotation angle. (B) A significant change in the position and orientation of ENP5 during the simulation. (C) Distributions of the angular velocity of NPs within a period of simulation time. (D) The time proportion for NPs in the rotation-hopping states.CC BY-NC-ND · PubMed Central
Fig. 8. NP extravasation against IFP in tumor environment in vivo. (A and B) The fluorescence images of NPs extravasating from blood vessels in tumors with volumes of 100 and 500 mm3, respectively. (Scale bar, 5 μm.) (C and D) Changes of the accumulation of NPs extravasating from blood vessels over time in tumors with volumes of 100 and 500 mm3, respectively. (E) Quantification of NP fluorescent signal in tumor tissues in three-dimensional immunofluorescence images (n = 3 independent experiments; mean ± SD). (P > 0.05, ns; *P < 0.05; **P < 0.01; ***P < 0.001, ****P < 0.0001)
Fig. 8. NP extravasation against IFP in tumor environment in vivo. (A and B) The fluorescence images of NPs extravasating from blood vessels in tumors with volumes of 100 and 500 mm3, respectively. (Scale bar, 5 μm.) (C and D) Changes of the accumulation of NPs extravasating from blood vessels over time in tumors with volumes of 100 and 500 mm3, respectively. (E) Quantification of NP fluorescent signal in tumor tissues in three-dimensional immunofluorescence images (n = 3 independent experiments; mean ± SD). (P > 0.05, ns; *P < 0.05; **P < 0.01; ***P < 0.001, ****P < 0.0001)CC BY-NC-ND · PubMed Central
Fig. 9. NP penetration in tumor environment. (A and B) CLSM images of RITC-labeled NPs penetration ex vivo in tumors with volumes of 100 and 500 mm3, respectively. (Scale bar, 3 mm.) (C and D) Quantification of the fluorescence intensity in the inside area of tumors in A and B. (E and F) Three-dimensional images along z-direction showing the penetration and distribution of NPs in vivo in tumor tissues with volume of 500 and 100 mm3 at 4 h. (Scale bar, 50 μm.) (P > 0.05, ns; *P < 0.05; **P < 0.01; ***P < 0.001, ****P < 0.0001)
Fig. 9. NP penetration in tumor environment. (A and B) CLSM images of RITC-labeled NPs penetration ex vivo in tumors with volumes of 100 and 500 mm3, respectively. (Scale bar, 3 mm.) (C and D) Quantification of the fluorescence intensity in the inside area of tumors in A and B. (E and F) Three-dimensional images along z-direction showing the penetration and distribution of NPs in vivo in tumor tissues with volume of 500 and 100 mm3 at 4 h. (Scale bar, 50 μm.) (P > 0.05, ns; *P < 0.05; **P < 0.01; ***P < 0.001, ****P < 0.0001)CC BY-NC-ND · PubMed Central

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Metadata

Authors
Jiang, X., Xu, S., Miao, Y., Huang, K., Wang, B., Ding, B., Zhang, Z., Zhao, Z., Zhang, X., Shi, X., Yu, M., Tian, F., & Gan, Y.
Venue
Proceedings of the National Academy of Sciences
Published
2024-05-20
Volume
121
Issue
22
ISSN
  • 0027-8424
  • 1091-6490
Cited by
57
References
6
Language
en
Funders
  • MOST | NSFC | National Science Fund for Distinguished Young Scholars (82025032)
  • MOST | National Natural Science Foundation of China (82073773, 12272101)
  • MOST | National Key Research and Development Program of China (2022YFA1203200)
  • &quot;Open Competition to Select the Best Candidates&quot; Key Technology Program for Nucleic Acid Drugs of NCTIB (NCTIB2022HS01006)
  • Key Research Program of Chinese Academy of Sciences (ZDBS-ZRKJZ-TLC005)
  • Young Elite Scientists Sponsorship Program by CAST (2022QNRC001)

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