Fluorescence-Reporting-Guided Tumor Acidic Environment-Activated Triple Photodynamic, Chemodynamic, and Chemotherapeutic Reactions for Efficient Hepatocellular Carcinoma Cell Ablation.
Mengyu YaoXiaojie WangKunshan HuangXiao JiaJinping XueBing GuoJuan-Juan ChenPublished in: Langmuir : the ACS journal of surfaces and colloids (2022)
Tumor acidic environment-activated combination therapy holds great promise to significantly decrease side effects, circumvent multiple drug resistance, and improve therapeutic outcomes for cancer treatment. Herein, Sorafenib/ZnPc(PS) 4 @Fe III -TA nanoparticles (SPFT) are designed with acid-environment turned-on fluorescence to report the activation of triple therapy including photodynamic, chemodynamic, and chemotherapy on hepatocellular carcinoma. The SPFT are composed of SP cores formulated via self-assembly of sorafenib and ZnPc(PS) 4 , with high drug loading efficiency, and Fe III -TA shells containing FeCl 3 and tannic acid. Importantly, the nanoparticles suppress reactive oxygen species (ROS) generation of ZnPc(PS) 4 due to their formation in nanoparticles, while assisting simultaneous uptake of the uploaded drugs in cancer cells. The tumor acidic environment initiates Fe III -TA decomposition and accelerates a chemodynamic reaction between Fe II and H 2 O 2 to generate toxic • OH. Then, the SP core is decomposed to separate ZnPc(PS) 4 and sorafenib, which leads to fluorescence turning-on of ZnPc(PS) 4 , expedited photodynamic reactions, and burst release of sorafenib. Notably, SPFT shows low dark cytotoxicity to normal cells but exerts high potency on hepatocellular carcinoma cells under near-infrared light irradiation, which is much more potent than either sorafenib or ZnPc(PS) 4 alone. This research offers a facile nanomedicine design strategy for cancer therapy.
Keyphrases
- quantum dots
- cancer therapy
- energy transfer
- reactive oxygen species
- combination therapy
- drug delivery
- single molecule
- ionic liquid
- metal organic framework
- induced apoptosis
- stem cells
- cell death
- single cell
- visible light
- cell cycle arrest
- machine learning
- radiation therapy
- type diabetes
- big data
- metabolic syndrome
- deep learning
- adipose tissue
- bone marrow
- weight loss
- anti inflammatory
- locally advanced
- catheter ablation
- pi k akt
- replacement therapy