Wong Jodie, Muralidhar Rohit, Wang Liang, Huang Chiang-Ching
Department of Tumor Microenvironment and Metastasis, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA.
Nova Southeastern University, Kiran C. Patel College of Osteopathic Medicine, Davie, FL, USA.
Biomed J. 2025 Feb;48(1):100718. doi: 10.1016/j.bj.2024.100718. Epub 2024 Mar 23.
This review provides a comprehensive overview of the latest advancements in the clinical utility of liquid biopsy, with a particular focus on epigenetic approaches aimed at overcoming challenges in cancer diagnosis and treatment. It begins by elucidating key epigenetic terms, including methylomics, fragmentomics, and nucleosomics. The review progresses to discuss methods for analyzing circulating cell-free DNA (cfDNA) and highlights recent studies showcasing the clinical relevance of epigenetic modifications in areas such as diagnosis, drug treatment response, minimal residual disease (MRD) detection, and prognosis prediction. While acknowledging hurdles like the complexity of interpreting epigenetic data and the absence of standardization, the review charts a path forward. It advocates for the integration of multi-omic data through machine learning algorithms to refine predictive models and stresses the importance of collaboration among clinicians, researchers, and data scientists. Such cooperative efforts are essential to fully leverage the potential of epigenetic features in clinical practice.
本综述全面概述了液体活检临床应用的最新进展,特别关注旨在克服癌症诊断和治疗挑战的表观遗传学方法。它首先阐明了关键的表观遗传学术语,包括甲基组学、片段组学和核苷组学。该综述进而讨论了分析循环游离DNA(cfDNA)的方法,并重点介绍了最近的研究,这些研究展示了表观遗传修饰在诊断、药物治疗反应、微小残留病(MRD)检测和预后预测等领域的临床相关性。在承认存在诸如解释表观遗传数据的复杂性以及缺乏标准化等障碍的同时,该综述规划了前进的道路。它主张通过机器学习算法整合多组学数据以完善预测模型,并强调临床医生、研究人员和数据科学家之间合作的重要性。这种合作努力对于在临床实践中充分利用表观遗传特征的潜力至关重要。