Yaghoubi Naei Vahid, Bordhan Pritam, Mirakhorli Fatemeh, Khorrami Motahare, Shrestha Jesus, Nazari Hojjatollah, Kulasinghe Arutha, Ebrahimi Warkiani Majid
School of Biomedical Engineering, University of Technology Sydney, Sydney, Australia.
Faculty of Medicine, Frazer Institute, The University of Queensland, Brisbane, QLD, Australia.
Ther Adv Med Oncol. 2023 Sep 7;15:17588359231192401. doi: 10.1177/17588359231192401. eCollection 2023.
Over the past decade, the detection and analysis of liquid biopsy biomarkers such as circulating tumor cells (CTCs) and circulating tumor DNA (ctDNA) have advanced significantly. They have received recognition for their clinical usefulness in detecting cancer at an early stage, monitoring disease, and evaluating treatment response. The emergence of liquid biopsy has been a helpful development, as it offers a minimally invasive, rapid, real-time monitoring, and possible alternative to traditional tissue biopsies. In resource-limited settings, the ideal platform for liquid biopsy should not only extract more CTCs or ctDNA from a minimal sample volume but also accurately represent the molecular heterogeneity of the patient's disease. This review covers novel strategies and advancements in CTC and ctDNA-based liquid biopsy platforms, including microfluidic applications and comprehensive analysis of molecular complexity. We discuss these systems' operational principles and performance efficiencies, as well as future opportunities and challenges for their implementation in clinical settings. In addition, we emphasize the importance of integrated platforms that incorporate machine learning and artificial intelligence in accurate liquid biopsy detection systems, which can greatly improve cancer management and enable precision diagnostics.
在过去十年中,循环肿瘤细胞(CTCs)和循环肿瘤DNA(ctDNA)等液体活检生物标志物的检测和分析取得了显著进展。它们在癌症早期检测、疾病监测和治疗反应评估方面的临床实用性得到了认可。液体活检的出现是一项有益的进展,因为它提供了一种微创、快速、实时监测的方法,并且可能是传统组织活检的替代方法。在资源有限的环境中,理想的液体活检平台不仅应能从最小样本量中提取更多的CTCs或ctDNA,还应能准确反映患者疾病的分子异质性。本综述涵盖了基于CTCs和ctDNA的液体活检平台的新策略和进展,包括微流控应用和分子复杂性的综合分析。我们讨论了这些系统的工作原理和性能效率,以及它们在临床环境中实施的未来机遇和挑战。此外,我们强调了在精确的液体活检检测系统中纳入机器学习和人工智能的集成平台的重要性,这可以极大地改善癌症管理并实现精准诊断。