Abstract
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.
| Original language | English |
|---|---|
| Pages (from-to) | 246-274 |
| Journal | Medicinal Research Reviews |
| Volume | 41 |
| Issue number | 1 |
| Online published | 14 Sept 2020 |
| DOIs | |
| Publication status | Published - Jan 2021 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Research Keywords
- cardiovascular diseases
- disease monitoring
- liquid biopsy
- multiomics
- patient stratification
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