Organoid-Based Assessment of Metal-Organic Framework (MOF) Nanomedicines for Ex Vivo Cancer Therapy.
Abstrak
Nanomaterials have been extensively exploited in tumor treatment, leading to numerous innovative strategies for cancer therapy. While nanomedicines present immense potential, their application in cancer therapy is characterized by significant complexity and unpredictability, especially regarding biocompatibility and anticancer efficiency. These considerations underscore the essential need for the development of ex vivo research models, which provide invaluable insights and understanding into the biosafety and efficacy of nanomedicines in oncology. Fortunately, the emergence of organoid technology offers a novel approach to the preclinical evaluation of the anticancer efficacy of nanomedicines in vitro. Hence, in this study, we constructed intestine and hepatocyte organoid models (Intestine-orgs and Hep-orgs) for assessing intestinal and hepatic toxicity at the microtissue level. We utilized three typical metal-organic frameworks (MOFs), ZIF-8, ZIF-67, and MIL-125, as nanomedicines to further detect their interactions with organoids. Subsequently, the MIL-125 with biocompatibility loaded methotrexate (MTX), forming the nanomedicine (MIL-125-PEG-MTX), indicated a high loading efficiency (82%) and a well-release capability in an acid microenvironment. More importantly, the anticancer effect of the nanomedicine was investigated using an in vitro patient-derived organoids (PDOs) model, achieving inhibition rates of 48% and 78% for PDO-1 and PDO-2, respectively, demonstrating that PDOs could predict clinical response and facilitate prospective therapeutic selection. These achievements presented great potential for organoid-based ex vivo models for nano theragnostic evaluation in biosafety and function.
Topik & Kata Kunci
Penulis (10)
Dan Li
Rui Zhang
Yinpeng Le
Ting Zhang
Dandan Luo
Han Zhang
Jun Li
Ruibo Zhao
Yeting Hu
Xiangdong Kong
Akses Cepat
- Tahun Terbit
- 2024
- Bahasa
- en
- Total Sitasi
- 19×
- Sumber Database
- Semantic Scholar
- DOI
- 10.1021/acsami.4c05172
- Akses
- Open Access ✓