Mesoporous Doxorubicin-Loaded Polydopamine Nanoparticles Coated with a Platelet Membrane Suppress Tumor Growth in a Murine Model of Human Breast Cancer.
Dandan RenGareth R WilliamYanyan ZhangRong RenJiadong LouLi-Min ZhuPublished in: ACS applied bio materials (2021)
Bringing together photothermal therapy and chemotherapy (photothermal-chemotherapy, PT-CT) is a highly promising clinical approach but requires the development of intelligent multifunctional delivery vectors. In this work, we prepared mesoporous polydopamine nanoparticles (MPDA NPs) loaded with the chemotherapeutic drug doxorubicin (DOX). These NPs were then coated with the platelet membrane (PLTM). The coated MPDA NPs are spherical and clearly mesoporous in structure. They have a particle size of approximately 184 nm and pore size of ca. 45 nm. The NPs are potent photothermal agents and efficient DOX carriers, with increased rates of drug release observed in vitro in conditions representative of the tumor microenvironment. The NPs are preferentially taken up by cancer cells but not by macrophage cells, and while cytocompatible with healthy cells are highly toxic to cancer cells. An in vivo murine model of human breast cancer revealed that the NPs can markedly slow the growth of a tumor (ca. 9-fold smaller after 14 days' treatment), have extended pharmacokinetics compared to free DOX (with DOX still detectable in the bloodstream after 24 h when the NPs are applied), and are highly targeted with minimal off-site effects on the heart, liver, spleen, kidney, and lungs.
Keyphrases
- drug delivery
- cancer therapy
- drug release
- oxide nanoparticles
- photodynamic therapy
- induced apoptosis
- endothelial cells
- cell cycle arrest
- heart failure
- induced pluripotent stem cells
- emergency department
- adipose tissue
- computed tomography
- magnetic resonance imaging
- magnetic resonance
- metal organic framework
- highly efficient
- endoplasmic reticulum stress
- pluripotent stem cells
- cell proliferation
- atrial fibrillation
- pi k akt
- breast cancer risk