ReviewPharmacogenomics
Liquid biopsy: an essential tool for metastatic breast cancer's follow-up.
Review in Pharmacogenomics. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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0 citing papers in PubMed.
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Breast cancer is the most common malignancy in women worldwide. While personalized treatment options are obstructed by the limitations of conventional biopsy follow-up, the liquid biopsy could detect the tumor's characteristics in order to reach a more targeted therapy for metastatic breast cancer patients. The aim of this article is to review the characteristics of the liquid biopsy in the follow-up of metastatic breast cancer patients. A comprehensive literature search was conducted using the PubMed literature to retrieve topic-related articles using keywords 'metastatic breast cancer,' 'liquid biopsy' and 'follow up.' A descriptive analysis was undertaken, and 29 original articles were retained. The study of blood biomarkers is being used in the monitoring and follow-up of metastatic breast cancer. It is used to determine the survival rate based on different biomarkers and monitor the response to treatment through the status of the tumor. This review describes the latest findings on breast cancer's circulating tumor cells, circulating cell-free DNA, circulating tumor DNA, proteomes, and extracellular vesicles (exosomes) in the plasma. Our literature review revealed that the liquid biopsy is capable of detecting breast cancer biomarkers in order to monitor breast cancer patients, improve their treatment choices and predict their prognosis more accurately.
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