Mathematical modelling of stem and progenitor cell dynamics during ruxolitinib treatment of patients with myeloproliferative neoplasms

被引:1
作者
Boklund, Tobias Idor [1 ]
Snyder, Jordan [1 ]
Gudmand-Hoeyer, Johanne [1 ]
Larsen, Morten Kranker [2 ]
Knudsen, Trine Alma [2 ]
Eickhardt-Dalboge, Christina Schjellerup [2 ]
Skov, Vibe [2 ]
Kjaer, Lasse [2 ]
Hasselbalch, Hans C. [2 ]
Andersen, Morten [1 ]
Ottesen, Johnny T. [1 ]
Stiehl, Thomas [1 ,3 ]
机构
[1] Roskilde Univ, Ctr Math Modeling Human Hlth & Dis, Dept Sci & Environm, IMFUFA, Roskilde, Denmark
[2] Zealand Univ Hosp, Dept Hematol, Roskilde, Denmark
[3] Rhein Westfal TH Aachen, Inst Computat Biomed & Dis Modeling, Aachen, Germany
来源
FRONTIERS IN IMMUNOLOGY | 2024年 / 15卷
关键词
mathematical modelling; ordinary differential equations; myeloproliferative neoplasms (MPN); parameter estimation; JAK2; V617F; ruxolitinib; blood cancer; stem cells; HEMATOPOIETIC-STEM; POLYCYTHEMIA-VERA; AVAILABLE THERAPY; ALLELE BURDEN; IFN-ALPHA; DIVISION;
D O I
10.3389/fimmu.2024.1384509
中图分类号
R392 [医学免疫学]; Q939.91 [免疫学];
学科分类号
100102 ;
摘要
Introduction The Philadelphia chromosome-negative myeloproliferative neoplasms are a group of slowly progressing haematological malignancies primarily characterised by an overproduction of myeloid blood cells. Patients are treated with various drugs, including the JAK1/2 inhibitor ruxolitinib. Mathematical modelling can help propose and test hypotheses of how the treatment works.Materials and methods We present an extension of the Cancitis model, which describes the development of myeloproliferative neoplasms and their interactions with inflammation, that explicitly models progenitor cells and can account for treatment with ruxolitinib through effects on the malignant stem cell response to cytokine signalling and the death rate of malignant progenitor cells. The model has been fitted to individual patients' data for the JAK2 V617F variant allele frequency from the COMFORT-II and RESPONSE studies for patients who had substantial reductions (20 percentage points or 90% of the baseline value) in their JAK2 V617F variant allele frequency (n = 24 in total).Results The model fits very well to the patient data with an average root mean square error of 0.0249 (2.49%) when allowing ruxolitinib treatment to affect both malignant stem and progenitor cells. This average root mean square error is much lower than if allowing ruxolitinib treatment to affect only malignant stem or only malignant progenitor cells (average root mean square errors of 0.138 (13.8%) and 0.0874 (8.74%), respectively).Discussion Systematic simulation studies and fitting of the model to the patient data suggest that an initial reduction of the malignant cell burden followed by a monotonic increase can be recapitulated by the model assuming that ruxolitinib affects only the death rate of malignant progenitor cells. For patients exhibiting a long-term reduction of the malignant cells, the model predicts that ruxolitinib also affects stem cell parameters, such as the malignant stem cells' response to cytokine signalling.
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页数:17
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