Next-generation liquid biopsies: Embracing data science in oncology Review
| Authors: | Im, Y. R.; Tsui, D. W. Y.; Diaz, L. A. Jr; Wan, J. C. M. |
| Review Title: | Next-generation liquid biopsies: Embracing data science in oncology |
| Abstract: | Deeper and broader sequencing of circulating tumor DNA (ctDNA) has identified a wealth of cancer markers in the circulation, resulting in a paradigm shift towards data science-driven liquid biopsies in oncology. Although panel sequencing for actionable mutations in plasma is moving towards the clinic, the next generation of liquid biopsies is increasingly shifting from analyzing digital mutation signals towards analog signals, requiring a greater role for machine learning. Concomitantly, there is an increasing acceptance that these cancer signals do not have to arise from the tumor itself. In this Opinion, we discuss the opportunities and challenges arising from increasingly complex cancer liquid biopsy data. © 2020 Elsevier Inc. |
| Keywords: | oncology; cancer; circulating tumor dna; liquid biopsy; cell-free dna |
| Journal Title: | Trends in Cancer |
| Volume: | 7 |
| Issue: | 4 |
| ISSN: | 2405-8025 |
| Publisher: | Cell Press |
| Date Published: | 2021-04-01 |
| Start Page: | 283 |
| End Page: | 292 |
| Language: | English |
| DOI: | 10.1016/j.trecan.2020.11.001 |
| PUBMED: | 33317961 |
| PROVIDER: | scopus |
| PMCID: | PMC8408348 |
| DOI/URL: | |
| Notes: | Review -- Export Date: 1 April 2021 -- Source: Scopus |
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