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.

中文翻译：

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CTC 和 ctDNA 分离、表征和分析新策略的进展。

在过去的十年中，循环肿瘤细胞 (CTC) 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着进展。它们因其在早期癌症检测、疾病监测和评估治疗反应方面的临床实用性而受到认可。液体活检的出现是一个有益的发展，因为它提供了微创、快速、实时监测，并且可能替代传统组织活检。在资源有限的环境中，理想的液体活检平台不仅应该从最小的样本量中提取更多的CTC或ctDNA，而且还应该准确地代表患者疾病的分子异质性。本综述涵盖了基于 CTC 和 ctDNA 的液体活检平台的新策略和进展，包括微流体应用和分子复杂性的综合分析。我们讨论这些系统的操作原理和性能效率，以及它们在临床环境中实施的未来机遇和挑战。此外，我们强调将机器学习和人工智能融入精确液体活检检测系统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确诊断。