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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)
Publ. Version/Full Text DOI PMC
Open Access Gold
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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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Publication type Article: Journal article
Document type Scientific Article
Keywords Biological Sciences ; Disease; Acute Myeloid-leukemia; Residual Disease; Chemotherapy; Mutations; Evolution; Diagnosis; Relapse; Risk
Language english
Publication Year 2023
HGF-reported in Year 2023
ISSN (print) / ISBN 2589-0042
e-ISSN 2589-0042
Journal iScience
Quellenangaben Volume: 26, Issue: 12, Pages: , Article Number: 108271 Supplement: ,
Publisher Elsevier
Publishing Place Amsterdam ; Bosten ; London ; New York ; Oxford ; Paris ; Philadelphia ; San Diego ; St. Louis
Reviewing status Peer reviewed
Institute(s) Institute of AI for Health (AIH)
Institute of Computational Biology (ICB)
POF-Topic(s) 30205 - Bioengineering and Digital Health
Research field(s) Enabling and Novel Technologies
PSP Element(s) G-540007-001
G-553800-001
Grants European Research Council (ERC)
China Scholarship Council
Scopus ID 85176737850
PubMed ID 38047080
Erfassungsdatum 2023-11-28