癌细胞
内吞作用
抗药性
癌症
药品
细胞
药物输送
流式细胞术
化学
癌症研究
材料科学
纳米技术
生物
药理学
分子生物学
生物化学
遗传学
微生物学
作者
Lingshan Liu,Qiurui Zhang,Chenglong Wang,Heze Guo,Vincent Mukwaya,Rong Chen,Yichun Xu,Xiaohui Wei,Xiaohong Chen,Sujiang Zhang,Min Zhou,Hongjing Dou
出处
期刊:ACS Nano
[American Chemical Society]
日期:2023-10-02
卷期号:17 (19): 19372-19386
被引量:9
标识
DOI:10.1021/acsnano.3c07030
摘要
Single-cell diagnosis of cancer drug resistance is highly relevant for cancer treatment, as it can be used to identify the subpopulations of drug-resistant cancer cells, reveal the sensitivity of cancer cells to treatment, and monitor the progress of cancer drug resistance. However, simple and effective methods for cancer drug resistance detection at the single-cell level are still lacking in laboratory and clinical studies. Inspired by the fact that nanoparticles with diverse physicochemical properties would generate distinct and specific interactions with drug-resistant and drug-sensitive cancer cells, which have distinctive molecular signatures, here, we have synthesized a library of fluorescent nanoparticles with various sizes, surface charges, and compositions (SiO2 nanoparticles (SNPs), organic PS-co-PAA nanoparticles (ONPs), and ZIF-8 nanoparticles (ZNPs)), thus demonstrating that the composition has a critical influence on the interaction of nanoparticles with drug-resistant cancer cells. Furthermore, the clathrin/caveolae-independent endocytosis of ZNPs together with the P-glycoprotein-related decreased cell membrane fluidity resulted in a lower cellular accumulation of ZNPs in drug-resistant cancer cells, consequently causing the distinct cellular accumulation of ZNPs between the drug-resistant and drug-sensitive cancer cells. This difference was further quantified by detecting the fluorescence signals generated by the accumulation of nanoparticles at the single-cell level via flow cytometry. Our findings provide another insight into the nanoparticle–cell interactions and offer a promising platform for the diagnosis of cancer drug resistance of various cancer cells and clinical cancer samples at the single-cell level.
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