条形码
材料科学
仿形(计算机编程)
单细胞分析
吞吐量
微流控
纳米技术
炸薯条
外体
细胞
生物
微泡
计算机科学
小RNA
遗传学
电信
基因
无线
操作系统
作者
Chao Wang,Yu Zhang,Jianbo Wang,Yunrui Han,Yihe Wang,Mingyuan Sun,Yanbo Liang,Miao Huang,Yang Yu,Huili Hu,Hong Liu,Lin Han
标识
DOI:10.1002/adma.202411259
摘要
Abstract Exosomes, functional biomarkers involved in cancer progression, have gained widespread attention for promoting tumor formation, growth, and metastasis. Current bulk exosome detections in bodily fluids enable cancer functional analysis, but average secretion levels from cell populations, losing parent cell information and ignoring exosome heterogeneity from diverse cell subgroups, necessitating an effective platform for analyzing single‐cell exosome functional heterogeneity. Here, a high‐throughput platform is presented, capable of efficient single‐cell isolation and multi‐color exosome phenotype analysis, as well as quantifying trace exosomes secreted by single cells. Photothermal‐driven single‐cell chips achieve significant single‐cell isolation efficiency (≈97%) within 5 min, facilitating the ultra‐high throughput single‐cell exosome analysis. By conducting mass spectrometry and protein interaction of breast cancer exosome phenotypic proteins, key exosome phenotypes are identified. Tens of thousands of single cells from breast cancer cell lines, and clinical tissues are analyzed, revealing various subgroup differences. The study finds more CD44 and EGFR co‐expressing exosome subgroups in breast cancer cell lines, while immune‐evasion PD‐L1 high‐phenotype exosome subgroups are primarily presented in complex tumor microenvironments, especially in HER2‐positive tissues. This platform offers powerful single‐cell isolation, exosome quantification, and phenotypic analysis capabilities, making it a powerful tool for advancing single‐cell exosome analysis in cancer research.
科研通智能强力驱动
Strongly Powered by AbleSci AI