Up-Conversion Luminescent Nanoparticles for Molecular Imaging, Cancer Diagnosis and Treatment - Li S (Dove Medical Press, 2020)
Shuihong Li,1,* Xiaodan Wei,2,* Sisi Li,1 Cuiming Zhu,1 Chunhui Wu2 1Institution of Pathogenic Biology, Hengyang Medical College, University of South China, Hengyang 421001, Hunan, People’s Republic of China; 2School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, Sichuan, People’s Republic of China*These authors contributed equally to this workCorrespondence: Shuihong LiInstitution of Pathogenic Biology, Hengyang Medical College, University of South China, Hengyang 421001, Hunan, People’s Republic of ChinaTel/Fax +86 734 8282907Email zhoubaoxi520@163.comChunhui WuSchool of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, Sichuan, People’s Republic of ChinaTel/Fax +86 28 83203353Email wuchunhui@uestc.edu.cnAbstract: In the past few years, we have witnessed great development and application potential of various up-conversion luminescent nanoparticles (UCNPs) in the nanomedicine field. Based on the unique luminescent mechanism of UCNPs and the distinguishable features of cancer biomarkers and the microenvironment, an increasing number of smart UCNPs nanoprobes have been designed and widely applied to molecular imaging, cancer diagnosis, and treatment. Considerable technological success has been achieved, but the main obstacles to oncology nanomedicine is becoming an incomplete understanding of nano–bio interactions, the challenges regarding chemistry manufacturing and controls required for clinical translation and so on. This review highlights the progress of the design principles, synthesis and surface functionalization preparation, underlying applications and challenges of UCNPs-based probes for cancer bioimaging, diagnosis and treatment that capitalize on our growing understanding of tumor biology and smart nano-devices for accelerating the commercialization of UCNPs.Keywords: multimodal imaging, cancer biomarkers, tumor microenvironment