@article{oai:repo.qst.go.jp:00085194,
 author = {Shi, Xiumin and Qing, Li and Lulu, Zhang and Masayuki, Hanyu and Lin, Xie and Kuan, Hu and Kotaro, Nagatsu and Chuan, Zhang and Zhengcan, Wu and WANG, Feng and Zhang, Ming-Rong and Kai, Yang and Ran, Zhu and Masayuki, Hanyu and Lin, Xie and Kuan, Hu and Kotaro, Nagatsu and WANG, Feng and Zhang, Ming-Rong},
 issue = {8},
 journal = {Bioconjugate Chemistry},
 month = {Jul},
 note = {Targeted radionuclide therapy (TRT) provides new and safe opportunities for cancer treatment and management with high precision and efficiency. Here we have designed a novel semiconducting polymer nanoparticle (SPN)-based
radiopharmaceutical (211At-MeATE-SPN-GIP) for TRT against glucose-dependent insulinotropic polypeptide receptor (GIPR)-positive cancers to further explore the applications of nano-engineered TRT. 211At-MeATE-SPN-GIP was engineered
via nanoprecipitation, followed by its functionalization with a glucose-dependent insulinotropic polypeptide (GIP) to target
GIPR and deliver 211At for α therapy. The therapeutic effect and biological safety of 211At-MeATE-SPN-GIP were investigated using GIPR-overexpressing human pancreatic cancer CFPAC-1 cells and CFPAC-1-bearing mice. In this work, 211At-MeATE-SPN-GIP was produced with a radiochemical yield of 43% and radiochemical purity of 98%, which exhibited a specifically high uptake in CFPAC-1 cells, inducing cell cycle arrest at G2/M phase and extensive DNA damage. In the
CFPAC-1-bearing tumor model, 211At-MeATE-SPN-GIP exhibited high therapeutic efficiency, with no obvious side effects. The GIPR-specific binding of 211At-MeATE-SPN-GIP combined with effective inhibition of tumor growth, and fewer side effects compared to control suggest that 211At-MeATE-SPN-GIP TRT holds great potential as a novel nano-engineered TRT strategy for patients with GIPR-positive cancer.},
 pages = {1763--1772},
 title = {211At-Labeled Polymer Nanoparticles for Targeted Radionuclide Therapy of Glucose-Dependent Insulinotropic Polypeptide Receptor (GIPR)-Overexpressed Cancer},
 volume = {32},
 year = {2021}
}