组学
液体活检
工作流程
蛋白质组学
仿形(计算机编程)
疾病
生物信息学
医学
癌症
计算机科学
数据科学
病理
生物
内科学
数据库
基因
操作系统
生物化学
作者
Geng Chen,Jing Zhang,Qiaoting Fu,Valérie Taly,Fei Tan
标识
DOI:10.1038/s41416-022-02048-2
摘要
The innovation of liquid biopsy holds great potential to revolutionise cancer management through early diagnosis and timely treatment of cancer. Integrative analysis of different tumour-derived omics data (such as genomics, epigenetics, fragmentomics, and proteomics) from body fluids for cancer detection and monitoring could outperform the analysis of single modality data alone. In this review, we focussed on the discussion of early cancer detection and molecular residual disease surveillance based on multi-omics data of blood. We summarised diverse types of tumour-derived components, current popular platforms for profiling cancer-associated signals, machine learning approaches for joint analysis of liquid biopsy data, as well as multi-omics-based early detection of cancers, molecular residual disease monitoring, and treatment response surveillance. We also discussed the challenges and future directions of multi-omics-based liquid biopsy. With the development of both experimental protocols and computational methods dedicated to liquid biopsy, the implementation of multi-omics strategies into the clinical workflow will likely benefit the clinical management of cancers including decision-making guidance and patient outcome improvement.
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