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Wang, D. ; Rausch, C.* ; Buerger, S.A.* ; Tschuri, S.* ; Rothenberg-Thurley, M.* ; Schulz, M. ; Hasenauer, J. ; Ziemann, F.* ; Metzeler, K.H.* ; Marr, C.

Modeling early treatment response in AML from cell-free tumor DNA.

iScience 26:108271 (2023)
Verlagsversion DOI PMC
Open Access Gold
Creative Commons Lizenzvertrag
Monitoring disease response after intensive chemotherapy for acute myeloid leukemia (AML) currently requires invasive bone marrow biopsies, imposing a significant burden on patients. In contrast, cell-free tumor DNA (ctDNA) in peripheral blood, carrying tumor-specific mutations, offers a less-invasive assessment of residual disease. However, the relationship between ctDNA levels and bone marrow blast kinetics remains unclear. We explored this in 10 AML patients with NPM1 and IDH2 mutations undergoing initial chemotherapy. Comparison of mathematical mixed-effect models showed that (1) inclusion of blast cell death in the bone marrow, (2) transition of ctDNA to peripheral blood, and (3) ctDNA decay in peripheral blood describes kinetics of blast cells and ctDNA best. The fitted model allows prediction of residual bone marrow blast content from ctDNA, and its scaling factor, representing clonal heterogeneity, correlates with relapse risk. Our study provides precise insights into blast and ctDNA kinetics, offering novel avenues for AML disease monitoring.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Schlagwörter Biological Sciences ; Disease; Acute Myeloid-leukemia; Residual Disease; Chemotherapy; Mutations; Evolution; Diagnosis; Relapse; Risk
Sprache englisch
Veröffentlichungsjahr 2023
HGF-Berichtsjahr 2023
ISSN (print) / ISBN 2589-0042
e-ISSN 2589-0042
Zeitschrift iScience
Quellenangaben Band: 26, Heft: 12, Seiten: , Artikelnummer: 108271 Supplement: ,
Verlag Elsevier
Verlagsort Amsterdam ; Bosten ; London ; New York ; Oxford ; Paris ; Philadelphia ; San Diego ; St. Louis
Begutachtungsstatus Peer reviewed
Institut(e) Human-Centered AI (HCA)
Institute of Computational Biology (ICB)
POF Topic(s) 30205 - Bioengineering and Digital Health
Forschungsfeld(er) Enabling and Novel Technologies
PSP-Element(e) G-540007-001
G-553800-001
Förderungen European Research Council (ERC)
China Scholarship Council
DOI 10.1016/j.isci.2023.108271
WOS ID 001114965700001
Scopus ID 85176737850
PubMed ID 38047080
Erfassungsdatum 2023-11-28
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