Chemiluminescent Conjugated Polymer Nanoparticles for Deep-Tissue Inflammation Imaging and Photodynamic Therapy of Cancer.
Ling LiXinyi ZhangYuxin RenQiong YuanYuze WangBenkai BaoMeiqi LiYanli TangPublished in: Journal of the American Chemical Society (2024)
Deep-tissue optical imaging and photodynamic therapy (PDT) remain a big challenge for the diagnosis and treatment of cancer. Chemiluminescence (CL) has emerged as a promising tool for biological imaging and in vivo therapy. The development of covalent-binding chemiluminescence agents with high stability and high chemiluminescence resonance energy transfer (CRET) efficiency is urgent. Herein, we design and synthesize an unprecedented chemiluminescent conjugated polymer PFV-Luminol, which consists of conjugated polyfluorene vinylene (PFV) main chains and isoluminol-modified side chains. Notably, isoluminol groups with chemiluminescent ability are covalently linked to main chains by amide bonds, which dramatically narrow their distance, greatly improving the CRET efficiency. In the presence of pathologically high levels of various reactive oxygen species (ROS), especially singlet oxygen ( 1 O 2 ), PFV-Luminol emits strong fluorescence and produces more ROS. Furthermore, we construct the PFV-L@PEG-NPs and PFV-L@PEG-FA-NPs nanoparticles by self-assembly of PFV-Luminol and amphiphilic copolymer DSPE-PEG/DSPE-PEG-FA. The chemiluminescent PFV-L@PEG-NPs nanoparticles exhibit excellent capabilities for in vivo imaging in different inflammatory animal models with great tissue penetration and resolution. In addition, PFV-L@PEG-FA-NPs nanoparticles show both sensitive in vivo chemiluminescence imaging and efficient chemiluminescence-mediated PDT for antitumors. This study paves the way for the design of chemiluminescent probes and their applications in the diagnosis and therapy of diseases.
Keyphrases
- photodynamic therapy
- energy transfer
- high resolution
- fluorescence imaging
- drug delivery
- reactive oxygen species
- sensitive detection
- quantum dots
- oxidative stress
- cell death
- machine learning
- molecularly imprinted
- stem cells
- squamous cell carcinoma
- mesenchymal stem cells
- big data
- small molecule
- lymph node metastasis
- oxide nanoparticles