Beijing Engineering Research Center for BioNanotechnology, CAS Key Laboratory of Standardization and Measurement for Nanotechnology, National Center for Nanoscience and Technology, Beijing 100190, China.
School of Future Technology, University of Chinese Academy of Sciences, Beijing 100049, China.
Anal Chem. 2023 Feb 14;95(6):3468-3475. doi: 10.1021/acs.analchem.2c05257. Epub 2023 Feb 1.
Circulating tumor cells (CTCs) have emerged as promising circulating biomarkers for non-invasive cancer diagnosis and management. Isolation and detection of CTCs in clinical samples are challenging due to the extreme rarity and high heterogeneity of CTCs. Here, we describe a poly(ethylene oxide) (PEO) concentration gradient-based microfluidic method for rapid, label-free, highly efficient isolation of CTCs directly from whole blood samples. Stable concentration gradients of PEO were formed within the microchannel by co-injecting the side fluid (blood sample spiked with 0.025% PEO) and center fluid (0.075% PEO solution). The competition between the elastic lift force and the inertial lift force enabled size-based separation of large CTCs and small blood cells based on their distinct migration patterns. The microfluidic device could process 1 mL of blood sample in 30 min, with a separation efficiency of >90% and an enrichment ratio of >700 for tumor cells. The isolated CTCs from blood samples were enumerated by immunofluorescence staining, allowing for discrimination of breast cancer patients from healthy donors with an accuracy of 84.2%. The concentration gradient-based microfluidic separation provides a powerful tool for label-free isolation of CTCs for a wide range of clinical applications.
循环肿瘤细胞 (CTCs) 已成为有前途的非侵入性癌症诊断和管理的循环生物标志物。由于 CTCs 的极端稀有性和高度异质性,临床样本中 CTCs 的分离和检测具有挑战性。在这里,我们描述了一种基于聚氧化乙烯 (PEO) 浓度梯度的微流控方法,用于直接从全血样本中快速、无标记、高效地分离 CTCs。通过共注入侧流(含有 0.025%PEO 的血液样本)和中流(0.075%PEO 溶液),在微通道内形成稳定的 PEO 浓度梯度。弹性升力和惯性升力之间的竞争使大 CTCs 和小血细胞能够根据其不同的迁移模式进行基于大小的分离。微流控装置可以在 30 分钟内处理 1 毫升血液样本,分离效率>90%,肿瘤细胞的富集倍数>700。通过免疫荧光染色对血液样本中的分离 CTCs 进行计数,能够以 84.2%的准确率区分乳腺癌患者和健康供体。基于浓度梯度的微流分离为广泛的临床应用提供了一种用于无标记分离 CTCs 的强大工具。