Autonomous metal-organic framework nanorobots for active mitochondria-targeted cancer therapy

Abstract

Nanorobotic manipulation to access subcellular organelles remains unmet due to the challenge in achieving intracellular controlled propulsion. Intracellular organelles, such as mitochondria, are an emerging therapeutic target with selective targeting and curative efficacy. We report an autonomous nanorobot capable of active mitochondria-targeted drug delivery, prepared by facilely encapsulating mitochondriotropic doxorubicin-triphenylphosphonium (DOX-TPP) inside zeolitic imidazolate framework-67 (ZIF-67) nanoparticles. The catalytic ZIF-67 body can decompose bioavailable hydrogen peroxide overexpressed inside tumor cells to generate effective intracellular mitochondriotropic movement in the presence of TPP cation. This nanorobot-enhanced targeted drug delivery induces mitochondria-mediated apoptosis and mitochondrial dysregulation to improve the in vitro anticancer effect and suppression of cancer cell metastasis, further verified by in vivo evaluations in the subcutaneous tumor model and orthotopic breast tumor model. This nanorobot unlocks a fresh field of nanorobot operation with intracellular organelle access, thereby introducing the next generation of robotic medical devices with organelle-level resolution for precision therapy.

Fig. 1.. Overall concept of active mitochondria-targeted cancer therapy and characterization of ZIF-67@DOX-TPP nanorobots.

(A) Schematic of the fabrication of ZIF-67@DOX-TPP nanorobots and their intracellular mitochondriotropic propulsion, enabling mitochondrial targeting drug delivery to effectively inhibit cancer growth and metastasis. (B) Transmission electron microscopy (TEM) and energy-dispersive x-ray images of ZIF-67@DOX-TPP nanorobots. Scale bars, 50 nm. (C) Size and zeta (ζ) potential (n = 3; means ± SD) and (D) P2p x-ray photoelectron spectroscopy (XPS) spectra of zeolitic imidazolate framework-67 (ZIF-67) nanoparticles (NPs), ZIF-67@DOX, and ZIF-67@DOX-TPP nanorobots. DOX, doxorubicin; TPP, triphenylphosphonium; a.u., arbitrary units.

Fig. 2.. Motion study, drug loading, and drug release profiles of ZIF-67@DOX-TPP nanorobots.

(A) Typical motion trajectories (over 20 s), (B) mean square displacement (MSD), (C) diffusion coefficient (D_eff), and (D) speed of ZIF-67@DOX-TPP nanorobots in phosphate-buffered saline (PBS) solution with different H₂O₂ concentrations (n = 15; means ± SEM). (E) Typical movement trajectories (over 20 s), (F) MSD, (G) D_eff, and (H) speed of ZIF-67@DOX-TPP nanorobots in the solution of cytoplasmic extracts with various H₂O₂ concentrations (n = 15; means ± SEM). Loading capacity of ZIF-67@DOX-TPP nanorobots upon various incubation time (I) and DOX-TPP input concentrations (J) (n = 3; means ± SD). The cumulative release of DOX-TPP from nanorobots upon different pH values (K) and H₂O₂ concentrations (L) (n = 3; means ± SEM).

Fig. 3.. Intracellular autonomous propulsion and mitochondrial targeting of ZIF-67@DOX-TPP nanorobots.

(A) Schematic of the mitochondria-targeted movement of nanorobots inside the tumor cell. Confocal laser scanning microscopy (CLSM) images of the merged optical and DOX channels showing intracellular motion trajectories of ZIF-67@DOX-TPP nanorobots inside the T24 bladder tumor cell (B), 4T1 breast tumor cell (C), and the SV- HUC-1 human uroepithelial cell (D). DOX fluorescence (red) represents ZIF-67@DOX-TPP nanorobots. Scale bars, 10 μm. (E) CLSM image showing intracellular motion trajectories of ZIF-8@DOX-TPP NPs inside the T24 cell. Scale bar, 10 μm. (F) Representative fluorescence images showing mitochondrial colocalization in T24 cells upon various incubations for 12 hours, including DOX, DOX-TPP, ZIF-8@DOX, ZIF-8@DOX-TPP, ZIF-67@DOX, and ZIF-67@DOX-TPP nanorobots. Nuclei were stained by Hoechst 33342 (blue). Mitochondria were labeled with MitoTracker Green FM (green). The red fluorescence represents the loaded DOX or DOX-TPP. The right columns show the calculated Pearson's correlation coefficients of the colocalization of mitochondria and nanorobots in T24 cells (n = 5; means ± SD). Scale bars, 10 μm.

Fig. 4.. In vitro evaluation of ZIF-67@DOX-TPP nanorobots for cancer cell death and metastasis inhibition.

(A) Fluorescence images of T24 cells stained with JC-1 dyes after incubated with various solutions for 8 hours, including PBS, ZIF-8@DOX-TPP, ZIF-67@DOX, and ZIF-67@DOX-TPP nanorobots. The right columns represent the calculated fluorescence ratio of J-aggregate (red) and J-monomer (green) (n = 5; means ± SD). Scale bars, 20 μm. (B) Viability of T24 cells after incubation with nanorobots and other control groups for 48 hours (n = 3; means ± SD). (C) Western blots for characteristic proteins involved in mitochondria-mediated apoptosis in T24 cells after treatment with nanorobots and other control groups. Bcl-2, B cell lymphoma 2. (D) Optical images showing in vitro wound healing assay and (E) corresponding wound closure percentages. The wound (cell gap) was built by a straight scratch across T24 cancer cells (0 hours). The wound closure rate was examined after incubation with nanorobots and other control groups for 12 hours (n = 5; means ± SD). Scale bar, 50 μm. (F) Schematic and images of invaded T24 cells across the Matrigel barrier after treatment with nanorobots and other control groups in the upper chamber of transwell assay and (G) corresponding invasive contents (n = 5; means ± SD). Scale bar, 100 μm. **P < 0.01; ****P < 0.0001; one-way analysis of variance (ANOVA).

Fig. 5.. In vivo evaluation of the antitumor effect of ZIF-67@DOX-TPP nanorobots using a subcutaneous tumor model.

(A) Schematic of the mouse model that bears subcutaneous T24 bladder tumor and the following treatment protocol. (B) The tumor growth kinetics of tumor-bearing mice that were treated with various intratumoral injections, including PBS, ZIF-67, DOX-TPP, ZIF-8@DOX-TPP, ZIF-67@DOX, and ZIF-67@DOX-TPP nanorobots, over the treatment process (n = 5; means ± SEM). (C) Excised tumor weights from mice at the end of treatment with nanorobots and other control groups (n = 5; means ± SD). (D) Body weight changes of tumor-bearing mice that were treated with nanorobots and other control groups over the treatment process (n = 5; means ± SEM). (E) Representative images of hematoxylin and eosin (H&E), terminal deoxynucleotidyl transferase–mediated deoxyuridine triphosphate nick end labeling (TUNEL), and Ki67 staining of resected tumor tissues from mice that were administrated with nanorobots and other control groups. Scale bars, 100 μm. *P < 0.05; **P < 0.01; ***P < 0.001; ****P < 0.0001; one-way ANOVA.

Fig. 6.. In vivo cancer treatment of ZIF-67@DOX-TPP nanorobots using an orthotopic breast tumor model.

(A) Schematic of the mouse model bearing orthotopic 4T1 breast cancer and the following treatment protocol. (B) The tumor growth kinetics of tumor-bearing mice that were intratumorally injected with PBS, ZIF-67, DOX-TPP, ZIF-8@DOX-TPP, ZIF-67@DOX, and ZIF-67@DOX-TPP nanorobots over the treatment process (n = 5; means ± SD). (C) Tumor images and (D) weights of excised primary tumors from mice at the end of treatment with nanorobots and other control groups (n = 5; means ± SD). (E) Representative images and H&E staining showing metastatic nodules (labeled with circles) in resected lungs from tumor-bearing mice at the end of treatment with nanorobots and other control groups and (F) quantified pulmonary metastatic nodules (n = 5; means ± SD). Scale bar, 1 mm. (G) Body weight changes of tumor-bearing mice treated with nanorobots and other control groups over the treatment process (n = 5; means ± SD). (H) H&E staining of histological sections from main organs, including the heart, liver, spleen, and kidney, resected from tumor-bearing mice that were intratumorally injected with PBS or nanorobots at the end of the treatment course. Scale bar, 100 μm. **P < 0.01; ***P < 0.001; ****P < 0.0001; one-way ANOVA.