鉴别器
差速器(机械装置)
人工智能
计算机科学
工程类
电信
航空航天工程
探测器
作者
Zhengwei Liu,Lu Zhang,Tingting Cui,Mengmeng Ma,Jinsong Ren,Xiaogang Qu
标识
DOI:10.1002/anie.202102286
摘要
Metabolic glycan labeling (MGL) followed by bioorthogonal chemistry provides a powerful tool for tumor imaging and therapy. However, selectively metabolic labeling of cells or tissues of interest remains a challenge. Particularly, owing to tumor heterogeneity including tumor subtypes and interpatient heterogeneity, it is far more difficult to realize tumor-cell-selective metabolic labeling for precise diagnosis. Inspired by nature, we designed azidosugar-functionalized metal-organic frameworks camouflaged with cancer cell membranes to accomplish cancer-cell-selective MGL in vivo. With abundant receptors, this biomimetic platform not only selectively targets homotypic cells but also realizes different breast cancer subtype-selective MGL. Moreover, the endo/lysosomal-escaped ZIF-8 can make azidosugar escape from lysosomes and accelerate its metabolic incorporation. This strategy also takes advantage of cancer-tissue-derived cell membranes, which may have huge potential for personalized diagnosis and therapy.
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