4.7 Review

Liquid biopsy technologies for hematological diseases

期刊

MEDICINAL RESEARCH REVIEWS
卷 41, 期 1, 页码 246-274

出版社

WILEY
DOI: 10.1002/med.21731

关键词

cardiovascular diseases; disease monitoring; liquid biopsy; multiomics; patient stratification

资金

  1. City University of Hong Kong, Research Grants Council (RGC) [9610430]

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Technological advances in liquid biopsy markers have made cancer diagnosis and disease detection more convenient, potentially influencing disease management and treatment dynamics. Researchers highlighted the importance of cell-based, gene-based, and protein-based liquid biopsy markers in disease detection and discussed the research progress in using these biomarkers in conjunction with liquid biopsy.
Since the discovery of circulating tumor cells in 1869, technological advances in studying circulating biomarkers from patients' blood have made the diagnosis of nonhematologic cancers less invasive. Technological advances in the detection and analysis of biomarkers provide new opportunities for the characterization of other disease types. When compared with traditional biopsies, liquid biopsy markers, such as exfoliated bladder cancer cells, circulating cell-free DNA (cfDNA), and extracellular vesicles (EV), are considered more convenient than conventional biopsies. Liquid biopsy markers undoubtedly have the potential to influence disease management and treatment dynamics. Our main focuses of this review will be the cell-based, gene-based, and protein-based key liquid biopsy markers (including EV and cfDNA) in disease detection, and discuss the research progress of these biomarkers used in conjunction with liquid biopsy. First, we highlighted the key technologies that have been broadly adopted used in hematological diseases. Second, we introduced the latest technological developments for the specific detection of cardiovascular disease, leukemia, and coronavirus disease. Finally, we concluded with perspectives on these research areas, focusing on the role of microfluidic technology and artificial intelligence in point-of-care medical applications. We believe that the noninvasive capabilities of these technologies have great potential in the development of diagnostics and can influence treatment options, thereby advancing precision disease management.

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