Yuri Kheifetz; Prof. Dr. Markus Scholz
IMISE (Institut für Medizinische Informatik, Statistik und Epidemiologie), Leipzig University
Objectives:
Leukopenia and thrombocytopenia are among the major side-effects of cytotoxic cancer therapies. Maturation of different blood cell lines are interdependent and influenced from stem-cells-niches supporting osteoblasts. The development of individual therapy adaptations is a non-trivial task since thrombocytopenic and leukopenic risks depend on many therapy-associated and individual factors. To solve this task we revised our biomathematical model of average granulopoiesis under chemotherapy or growth factor treatments (Scholz et al. 2004, 2013), combined it with our novel individualized model of thrombopoiesis (Kheifetz et al. 2017; Kheifetz et al. 2018) as well as with a model of osteoblasts/osteoclasts dynamics of other group (Komarova et al. 2003) and our novel model of lymphopoiesis. We implemented it in a software-tool usable for therapy management.
Methods:
We performed bio-mechanistic modelling of the dynamics of bone marrow hematopoietic and mature circulating cells by ordinary differential equations. We introduced quiescent states for stem and progenitor cells, whose activation is mediated by interactions with osteoblasts, growth factors thrombopoietin (TPO) and granulocyte-colony stimulating factor (G-CSF). Attached mechanistic PK/PD models consider injections of growth factors as well as of cytotoxic drugs. Short-range treatment effects influence proliferating blood-cells precursors, while both chemotherapy and G-CSF induce a long-term depletion of osteoblasts reducing the supporting capacity of the bone marrow. Our novel lymphopoiesis model describes short- and long-living lymphocytes, circulating between blood and peripheral compartments and originating from hematopoietic stem cells. We fitted 33 individual and 50 population parameters using simultaneously data from 11 studies measuring 19 different biological outcomes (cell counts of platelets, neutrophils, lymphocytes, leukocytes, megakaryocytes of different ploidies, osteoblasts, banded and segmented granulocytes; concentration of granulocyte-colony-stimulating factor (G-CSF), thrombopoietin (TPO) and prednisone). These 11 studies contained either individual or averaged data on hematopoiesis under five different chemotherapy regimens (CHOEP, BEACOPP, docetaxel, paclitaxel, carboplatin) and stimulatory treatments by TPO, filgrastim, pegylated filgrastim (synthetic variants of G-CSF), prednisone and transfusion of platelets or stem cells. We applied our innovative parameters estimation methodology, which has been developed earlier during a versatile fitting of our individualized thrombopoiesis model (Kheifetz et al. 2018). This methodology is based on virtual participation of patients from clinical studies in other experiments measuring different biological features.
Results:
Our model qualitatively and quantitatively explains major mechanisms of hematopoiesis. We described a negative synergism between G-CSF and TPO competing on a choice between granulopoietic and thrombopoietic differentiation alternatives of progenitor cells. According to several independent studies, we upgraded our model by direct stimulating effects of G-CSF and TPO on quiescent stem and early progenitor cells. We have found that multi-cyclic chemotherapy significantly reduces transit times for megakaryocytes. The long-term decrease in average platelets and leukocytes levels during multi-cyclic chemotherapy was attributed to interactions between osteoblasts, quiescent and active progenitor cells compartments. These slow changes are responsible for strong intra-individual variability of blood cells’ nadirs and consequently of chemotoxicity through treatment cycles. Incorporation of mechanistic model of osteoblasts and osteoclasts improved significantly the predictive potential of the thrombopoiesis model (Kheifetz et al. 2018). Our model described well few regimens of high-doses chemotherapy accompanied by bone-marrow transplantant.
Conclusions:
We successfully established a comprehensive mechanistic model of human hemathopoiesis perturbed by a wide spectrum of chemotherapies as well as of supportive treatments. It allows individual simultaneous predictions of degrees of thrombopenia, neutropenia, lymphocytopenia as well as of bone marrow injury with superior accuracy compared to statistical or semi-mechanistic competitors. This model has been realized in a tool supporting individualized decision making and therapy adaptations by physicians during multi-cyclic cancer treatments.
References:
[1] Kheifetz, Y.; Loeffler M.; Scholz M. (2017): Model-based individual managing of thrombocytopenia during multi-cyclic chemotherapy. Oral presentation, PAGE Conference, Budapest.
[2] Kheifetz, Y.; Scholz M. (2018): Modeling individual time courses of thrombopoiesis during multi-cyclic chemotherapy. Submitted.
[3] Komarova, S.; Smith, R.; Dixon, S.; Sims, S.; Wahl, L. (2003): Mathematical model predicts a critical role for osteoclast autocrine regulation in the control of bone remodeling. In: Bone 33 (2), S. 206–215. DOI: 10.1016/S8756-3282(03)00157-1.
[4] Scholz, M.; Engel, C.; Loeffler, M. (2005): Modelling human granulopoiesis under poly-chemotherapy with G-CSF support. In: Journal of mathematical biology 50 (4), S. 397–439. DOI: 10.1007/s00285-004-0295-1.
[5] Scholz, M.; Schirm, S.; Wetzler, M.; Engel, C.; Loeffler M. (2012): Pharmacokinetic and -dynamic modelling of G-CSF derivatives in humans. In: Theoretical biology & medical modelling 9, S. 32. DOI: 10.1186/1742-4682-9-32.
Reference: PAGE 27 (2018) Abstr 8561 [www.page-meeting.org/?abstract=8561]
Poster: Drug/Disease Modelling - Oncology