期刊
BIOSENSORS & BIOELECTRONICS
卷 102, 期 -, 页码 372-382出版社
ELSEVIER ADVANCED TECHNOLOGY
DOI: 10.1016/j.bios.2017.11.049
关键词
Circulating cancer stem cells; Metastasis; Circulating tumor cells; Raman-active nanoprobes; Raman imaging
类别
资金
- Leading Foreign Research Institute Recruitment Program, through the National Research Foundation of Korea (NRF) - Ministry of Science, ICT and Future Planning (MSIP) [2013K1A4A3055268]
- Basic Science Research Program through the National Research Foundation of Korea (NRF) - Ministry of Education [2016R1A6A1A03012845]
- Bio & Medical Technology Development Program of the NRF - Korean government [2017M3A9B4042581]
- National Research Foundation of Korea [22A20150013275, 2017M3A9B4042581, 2016R1A6A1A03012845, 2013K1A4A3055268] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)
Circulating cancer stem cells (CCSCs), a rare circulating tumor cell (CTC) type, recently arose as a useful resource for monitoring and characterizing both cancers and their metastatic derivatives. However, due to the scarcity of CCSCs among hematologic cells in the blood and the complexity of the phenotype confirmation process, CCSC research can be extremely challenging. Hence, we report a nanoparticle-mediated Raman imaging method for CCSC characterization which profiles CCSCs based on their surface marker expression phenotypes. We have developed an integrated combinatorial Raman-Active Nanoprobe (RAN) system combined with a microfluidic chip to successfully process complete blood samples. CCSCs and CTCs were detected (90% efficiency) and classified in accordance with their respective surface marker expression via completely distinct Raman signals of RANs. Selectively isolated CCSCs (93% accuracy) were employed for both in vitro and in vivo tumor phenotyping to identify the tumorigenicity of the CCSCs. We utilized our new method to predict metastasis by screening blood samples from xenograft models, showing that upon CCSC detection, all subjects exhibited liver metastasis. Having highly efficient detection and noninvasive isolation capabilities, we have demonstrated that our RAN based Raman imaging method will be valuable for predicting cancer metastasis and relapse via CCSC detection. Moreover, the exclusion of peak overlapping in CCSC analysis with our Raman imaging method will allow to expand the RAN families for various cancer types, therefore, increasing therapeutic efficacy by providing detailed molecular features of tumor subtypes.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据