Mathematical modeling of the impact of cytokine response of acute myeloid leukemia cells on patient prognosis

• Verfasst von: Stiehl, Thomas [VerfasserIn]
• Verfasst von: Ho, Anthony Dick [VerfasserIn]
• Verfasst von: Marciniak-Czochra, Anna [VerfasserIn]
• Titel: Mathematical modeling of the impact of cytokine response of acute myeloid leukemia cells on patient prognosis
• Verf.angabe: Thomas Stiehl, Anthony D. Ho & Anna Marciniak-Czochra
• E-Jahr: 2018
• Jahr: 12 February 2018
• Umfang: 11 S.
• Fussnoten: Gesehen am 18.12.2018
• Titel Quelle: Enthalten in: Scientific reports
• Ort Quelle: [London] : Macmillan Publishers Limited, part of Springer Nature, 2011
• Jahr Quelle: 2018
• Band/Heft Quelle: 8(2018), Artikel-ID 2809
• ISSN Quelle: 2045-2322
• DOI: doi:10.1038/s41598-018-21115-4
• Datenträger: Online-Ressource
• Sprache: eng
• K10plus-PPN: 1585638439

Abstract

Acute myeloid leukemia (AML) is a heterogeneous disease. One reason for the heterogeneity may originate from inter-individual differences in the responses of leukemic cells to endogenous cytokines. On the basis of mathematical modeling, computer simulations and patient data, we have provided evidence that cytokine-independent leukemic cell proliferation may be linked to early relapses and poor overall survival. Depending whether the model of cytokine-dependent or cytokine-independent leukemic cell proliferation fits to the clinical data, patients can be assigned to two groups that differ significantly with respect to overall survival. The modeling approach further enables us to identify parameter constellations that can explain unexpected responses of some patients to external cytokines such as blast crisis or remission without chemotherapy.