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- W2889393872 abstract "With the growing number of novel therapeutic approaches for liver diseases, significant research efforts have been devoted to the development of liquid biopsy tools for precision medicine. This can be defined as non-invasive reliable biomarkers that can supplement and eventually replace the invasive liver biopsy for diagnosis, disease stratification and monitoring of response to therapeutic interventions. Similarly, detection of liver cancer at an earlier stage of the disease, potentially susceptible to curative resection, can be critical to improve patient survival. Circulating extracellular vesicles, nucleic acids (DNA and RNA) and tumour cells have emerged as attractive liquid biopsy candidates because they fulfil many of the key characteristics of an ideal biomarker. In this review, we summarise the currently available information regarding these promising and potential transformative tools, as well as the issues still needed to be addressed for adopting various liquid biopsy approaches into clinical practice. These studies may pave the way to the development of a new generation of reliable, mechanism-based disease biomarkers." @default.
- W2889393872 created "2018-09-07" @default.
- W2889393872 creator A5053295611 @default.
- W2889393872 creator A5068344887 @default.
- W2889393872 creator A5081913103 @default.
- W2889393872 date "2018-09-03" @default.
- W2889393872 modified "2023-10-17" @default.
- W2889393872 title "Liquid biopsy for liver diseases" @default.
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- W2889393872 cites W1986971722 @default.
- W2889393872 cites W1987120610 @default.
- W2889393872 cites W1988547671 @default.
- W2889393872 cites W1998404710 @default.
- W2889393872 cites W2001034543 @default.
- W2889393872 cites W2002387613 @default.
- W2889393872 cites W2004867383 @default.
- W2889393872 cites W2010409072 @default.
- W2889393872 cites W2017857120 @default.
- W2889393872 cites W2022725154 @default.
- W2889393872 cites W2029900392 @default.
- W2889393872 cites W2047039797 @default.
- W2889393872 cites W2048452946 @default.
- W2889393872 cites W2052478346 @default.
- W2889393872 cites W2057341417 @default.
- W2889393872 cites W2059450204 @default.
- W2889393872 cites W2072342982 @default.
- W2889393872 cites W2079345276 @default.
- W2889393872 cites W2080840499 @default.
- W2889393872 cites W2087050120 @default.
- W2889393872 cites W2097118471 @default.
- W2889393872 cites W2111093604 @default.
- W2889393872 cites W2115556288 @default.
- W2889393872 cites W2118236274 @default.
- W2889393872 cites W2146229869 @default.
- W2889393872 cites W2151293178 @default.
- W2889393872 cites W2152593958 @default.
- W2889393872 cites W2157085831 @default.
- W2889393872 cites W2170852633 @default.
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- W2889393872 cites W2342986204 @default.
- W2889393872 cites W2344070586 @default.
- W2889393872 cites W2408402611 @default.
- W2889393872 cites W2412644869 @default.
- W2889393872 cites W2415831220 @default.
- W2889393872 cites W2419361198 @default.
- W2889393872 cites W2482972152 @default.
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- W2889393872 cites W2523755017 @default.
- W2889393872 cites W2529688469 @default.
- W2889393872 cites W2559279353 @default.
- W2889393872 cites W2572403213 @default.
- W2889393872 cites W2577044595 @default.
- W2889393872 cites W2582113473 @default.
- W2889393872 cites W2586679548 @default.
- W2889393872 cites W2593500728 @default.
- W2889393872 cites W2608190552 @default.
- W2889393872 cites W2610239039 @default.
- W2889393872 cites W2619076775 @default.
- W2889393872 cites W2619081498 @default.
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- W2889393872 cites W2746295288 @default.
- W2889393872 cites W2749718952 @default.
- W2889393872 cites W2759288796 @default.
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- W2889393872 cites W2764195238 @default.
- W2889393872 cites W2766653717 @default.
- W2889393872 cites W2767650616 @default.
- W2889393872 cites W2781345608 @default.
- W2889393872 cites W2783971456 @default.
- W2889393872 cites W2784490726 @default.
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- W2889393872 cites W2793965821 @default.
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- W2889393872 doi "https://doi.org/10.1136/gutjnl-2017-315846" @default.
- W2889393872 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/30177542" @default.
- W2889393872 hasPublicationYear "2018" @default.
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