Liquid biopsies beyond mutation calling: genomic and epenomic features of cell-free DNA in cancer

Cell-free DNA (cfDNA) analysis using liquid biopsies is a non-invasive method to gain insights into the biology, therapy response, mechanisms of acquired resistance and therapy escape of various tumors. While it is well established that individual cancer treatment options can be adjusted by panel ne...

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Hauptverfasser: Angeles, Arlou Kristina J. (VerfasserIn) , Janke, Florian (VerfasserIn) , Bauer, Simone (VerfasserIn) , Christopoulos, Petros (VerfasserIn) , Riediger, Anja Lisa (VerfasserIn) , Sültmann, Holger (VerfasserIn)
Dokumenttyp: Article (Journal)
Sprache:Englisch
Veröffentlicht: 10 November 2021
In: Cancers
Year: 2021, Jahrgang: 13, Heft: 22, Pages: 1-20
ISSN:2072-6694
DOI:10.3390/cancers13225615
Online-Zugang:Verlag, lizenzpflichtig, Volltext: https://doi.org/10.3390/cancers13225615
Verlag, lizenzpflichtig, Volltext: https://www.mdpi.com/2072-6694/13/22/5615
Volltext
Verfasserangaben:Arlou Kristina Angeles, Florian Janke, Simone Bauer, Petros Christopoulos, Anja Lisa Riediger and Holger Sültmann

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520 |a Cell-free DNA (cfDNA) analysis using liquid biopsies is a non-invasive method to gain insights into the biology, therapy response, mechanisms of acquired resistance and therapy escape of various tumors. While it is well established that individual cancer treatment options can be adjusted by panel next-generation sequencing (NGS)-based evaluation of driver mutations in cfDNA, emerging research additionally explores the value of deep characterization of tumor cfDNA genomics and fragmentomics as well as nucleosome modifications (chromatin structure), and methylation patterns (epigenomics) for comprehensive and multi-modal assessment of cfDNA. These tools have the potential to improve disease monitoring, increase the sensitivity of minimal residual disease identification, and detection of cancers at earlier stages. Recent progress in emerging technologies of cfDNA analysis is summarized, the added potential clinical value is highlighted, strengths and limitations are identified and compared with conventional targeted NGS analysis, and current challenges and future directions are discussed. 
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