Qureshi Zaheer, Altaf Faryal, Khanzada Mikail, Safi Adnan, Asghar Zoha, Warraich Daniyal, Shah Shivendra
The Frank H. Netter M.D. School of Medicine at Quinnipiac University, Bridgeport, Connecticut, USA.
Department of Internal Medicine, Icahn School of Medicine at Mount Sinai/BronxCare Health System, New York, USA.
Ann Med Surg (Lond). 2025 May 21;87(6):3244-3253. doi: 10.1097/MS9.0000000000002776. eCollection 2025 Jun.
The article offers an extensive survey of the progressions, problems, and future trends of liquid biopsies in the early discovery and surveillance of cancer. Liquid biopsies can detect signals associated with cancer by looking at biological fluids like cerebrospinal fluid, blood, or urine, making them a less invasive alternative to traditional tissue biopsies.
The review explores the molecular biology and techniques behind liquid biopsy, including circulating tumor DNA, circulatory tumor cells, and exosomes. It evaluates clinical applications of liquid biopsy across different cancer types, showing their potential for early diagnosis, monitoring disease progression, and therapy response prediction.
The article identifies several critical issues with liquid biopsies, including achieving a balance between high sensitivity and specificity, standardizing protocols, addressing technological heterogeneity, and ensuring cost-effectiveness and accessibility. Also, ethical issues about informed consent, data privacy, incidental findings management, and equal testing access have been examined in this context.
Finally, this article sheds light on future developments in liquid biopsies, such as enhanced specificity, sensitivity, and integration with artificial intelligence methods.
本文对液体活检在癌症早期发现和监测中的进展、问题及未来趋势进行了广泛综述。液体活检可通过检测脑脊液、血液或尿液等生物流体来发现与癌症相关的信号,使其成为传统组织活检的一种侵入性较小的替代方法。
本综述探讨了液体活检背后的分子生物学和技术,包括循环肿瘤DNA、循环肿瘤细胞和外泌体。它评估了液体活检在不同癌症类型中的临床应用,展示了其在早期诊断、监测疾病进展和预测治疗反应方面的潜力。
本文指出了液体活检的几个关键问题,包括在高灵敏度和特异性之间取得平衡、规范检测方案、解决技术异质性以及确保成本效益和可及性。此外,还在此背景下探讨了有关知情同意、数据隐私、偶然发现管理和平等检测机会的伦理问题。
最后,本文阐明了液体活检的未来发展方向,如提高特异性、灵敏度以及与人工智能方法相结合。