液体活检
循环肿瘤细胞
细胞外小泡
癌症生物标志物
活检
计算机科学
计算生物学
纳米技术
医学
癌症
病理
材料科学
生物
内科学
细胞生物学
转移
作者
Yuan Liu,Nana Lyu,Alison Rodger,Yuling Wang
出处
期刊:Elsevier eBooks
[Elsevier]
日期:2022-01-01
卷期号:: 225-280
被引量:1
标识
DOI:10.1016/b978-0-12-821121-2.00008-1
摘要
Liquid biopsy, involving the detection of cancer biomarkers in circulation, offers a promising noninvasive alternative for the diagnosis and real-time monitoring of tumor evolution and therapeutic response. Compared to the traditional tissue biopsy, which gives a static snapshot of a tumor, a liquid biopsy can not only simplify sample collection but also improve analytical quality, providing real-time information on disease burden, shedding light on tumor evolution over time and on tumor heterogeneity. Comprehensive tumor molecular analysis from liquid biopsies has the potential to enable clinicians to adopt an optimal personalized therapeutic strategy ultimately promoting precision oncology. Existing liquid biopsy analysis techniques do not provide reliable analyses on limited amounts of circulating tumor biomarkers. So the development of novel approaches is required to improve data quality and practical feasibility. Among the new proposed approaches, surface-enhanced Raman scattering (SERS) has considerable potential due to its ultrasensitive response and its multiplexing capability, and when it is combined with rigorous sample preparation and statistical data analysis approaches. This chapter summarizes the current state of SERS-based biosensing platforms for analyzing circulating biomarkers in liquid biopsy samples. The analytical targets include circulating tumor cells, circulating extracellular vesicles, circulating tumor DNA, circulating tumor RNA, and disease-associated proteins. For each type of these biomarkers, a summary of its biological significance and current main characterization techniques and a highlight of its analysis by SERS-based strategies and its potential application for clinical translational research are presented. The chapter concludes with challenges impeding translation of SERS-based biosensing.
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