A selenium-based NIR-II photosensitizer for a highly effective and safe phototherapy plan.
Xiangqian ZhangChonglu LiXiaofang GuanYu ChenQingqing ZhouHuili FengYun DengCheng FuGanzhen DengJunrong LiShuang LiuPublished in: The Analyst (2024)
High efficiency, stability, long emission wavelength (NIR-II), and good biocompatibility are crucial for photosensitizers in phototherapy. However, current Food and Drug Administration (FDA)-approved organic fluorophores exhibit poor chemical stability and photostability as well as short emission wavelength, limiting their clinical usage. To address this, we developed Se-IR1100, a novel organic photosensitizer with a photostable and thermostable benzobisthiadiazole (BBTD) backbone. By incorporating selenium as a heavy atom and constructing a D-A-D structure, Se-IR1100 exhibits a maximum fluorescence emission wavelength of 1100 nm. Compared with FDA-approved indocyanine green (ICG), DSPE-PEGylated Se-IR1100 nanoparticles exhibit prominent photostability and long-lasting photothermal effects. Upon 808 nm laser irradiation, Se-IR1100 NPs efficiently convert light energy into heat and reactive oxygen species (ROS), inducing cancer cell death in cellular studies and living organisms while maintaining biocompatibility. With salient photostability and a photothermal conversion rate of 55.37%, Se-IR1100 NPs hold promise as a superior photosensitizer for diagnostic and therapeutic agents in oncology. Overall, we have designed and optimized a multifunctional photosensitizer Se-IR1100 with good biocompatibility that performs NIR-II fluorescence imaging and phototherapy. This dual-strategy method may offer novel approaches for the development of multifunctional probes using dual-strategy or even multi-strategy methods in bioimaging, disease diagnosis, and therapy.
Keyphrases
- photodynamic therapy
- fluorescence imaging
- drug administration
- cell death
- reactive oxygen species
- high efficiency
- drug delivery
- cancer therapy
- palliative care
- squamous cell carcinoma
- dna damage
- artificial intelligence
- high resolution
- papillary thyroid
- solid state
- stem cells
- mass spectrometry
- cell proliferation
- heat stress
- machine learning
- high speed
- deep learning
- childhood cancer