Mathematical Modeling of Leukemogenesis and Cancer Stem Cell Dynamics

Stiehl, Thomas; Marciniak-Czochra, Anna

doi:10.1051/mmnp/20127199

Cited by 100 publications

(119 citation statements)

References 62 publications

Supporting

Mentioning

111

Contrasting

Order By: Relevance

“…These cells, that have been identified in many cancers (see [1,4,5,7,11,12]), are practically immortal and are pluripotent, in the sense that after mitosis they can generate new CSC (a relatively rare event) or non-stem cancer cells (CC). 1 On the contrary, CC can only generate CC.…”

Section: Introductionmentioning

confidence: 99%

Tumours with cancer stem cells: A PDE model

Fasano

Mancini

Primicerio

2016

Mathematical Biosciences

View full text Add to dashboard Cite

a b s t r a c tThe role of cancer stem cells (CSC) in tumour growth has received increasing attention in the recent literature. Here we stem from an integro-differential system describing the evolution of a population of CSC and of ordinary (non-stem) tumour cells formulated and studied in a previous paper, and we investigate an approximation in which the system reduces to a pair of nonlinear coupled parabolic equation. We prove that the new system is well posed and we examine some general properties. Numerical simulations show more on the qualitative behaviour of the solutions, concerning in particular the so-called tumour paradox, according to which an increase of the mortality rate of ordinary (non-stem) tumour cells results asymptotically in a faster growth.

show abstract

Section: Introductionmentioning

confidence: 99%

Tumours with cancer stem cells: A PDE model

Fasano

Mancini

Primicerio

2016

Mathematical Biosciences

View full text Add to dashboard Cite

show abstract

“…In this work, we have applied a combination of mathematical models established by our group (5,27). In conjunction with clinical parameters, we have studied the impact of LSC proliferation and self-renewal rates, compared with proliferation and self-renewal of less primitive leukemia blast cells or leukemia progenitor cells (LPC), on clinical outcome.…”

Section: Introductionmentioning

confidence: 99%

Cell Division Patterns in Acute Myeloid Leukemia Stem-like Cells Determine Clinical Course: A Model to Predict Patient Survival

et al. 2015

View full text Add to dashboard Cite

Acute myeloid leukemia (AML) is a heterogeneous disease in which a variety of distinct genetic alterations might occur. Recent attempts to identify the leukemia stem-like cells (LSC) have also indicated heterogeneity of these cells. On the basis of mathematical modeling and computer simulations, we have provided evidence that proliferation and self-renewal rates of the LSC population have greater impact on the course of disease than proliferation and self-renewal rates of leukemia blast populations, that is, leukemia progenitor cells. The modeling approach has enabled us to estimate the LSC properties of 31 individuals with relapsed AML and to link them to patient survival. On the basis of the estimated LSC properties, the patients can be divided into two prognostic groups that differ significantly with respect to overall survival after first relapse. The results suggest that high LSC self-renewal and proliferation rates are indicators of poor prognosis. Nevertheless, high LSC self-renewal rate may partially compensate for slow LSC proliferation and vice versa. Thus, model-based interpretation of clinical data allows estimation of prognostic factors that cannot be measured directly. This may have clinical implications for designing treatment strategies. Cancer Res; 75(6); 940-9. Ó2015 AACR.

show abstract

“…Glauche et al (2007); Marciniak-Czochra et al (2009); Foo et al (2009); Stiehl and Marciniak-Czochra (2012); Goyal et al (2015). There are several mathematical papers focusing on MPN and related disorders.…”

Section: Introductionmentioning

confidence: 99%

Determining the role of inflammation in the selection of JAK2 mutant cells in myeloproliferative neoplasms

Zhang

Fleischman²,

Wodarz

et al. 2017

Journal of Theoretical Biology

View full text Add to dashboard Cite

Myeloproliferative neoplasm (MPN) is a hematologic malignancy characterized by the clonal outgrowth of hematopoietic cells with a somatically acquired mutation most commonly in JAK2 (JAK2V617F). This mutation endows upon myeloid progenitors cytokine independent growth and consequently leads to excessive production of myeloid lineage cells. It has been previously suggested that inflammation may play a role in the clonal evolution of JAK2V617F mutants. In particular, it is possible that one or more cellular kinetic parameters of hematopoietic stem cells (HSCs) are affected by inflammation, such as division or death rates of cells, and the probability of HSC differentiation. This suggests a mechanism that can steer the outcome of the cellular competition in favor of the mutants, initiating the disease. In this paper we create a number of mathematical evolutionary models, from very abstract to more concrete, that describe cellular competition in the context of inflammation. It is possible to build a model axiomatically, where only very general assumptions are imposed on the modeling components and no arbitrary (and generally unknown) functional forms are used, and still generate a set of testable predictions. In particular, we show that, if HSC death is negligible, the evolutionary advantage of mutant cells can only be conferred by an increase in differentiation probability of HSCs in the presence of inflammation, and if death plays a significant role in the dynamics, an additional mechanism may be an increase of HSC’s division-to-death ratio in the presence of inflammation. Further, we show that in the presence of inflammation, the wild type cell population is predicted to shrink under inflammation (even in the absence of mutants). Finally, it turns out that if only the differentiation probability is affected by the inflammation, then the resulting steady state population of wild type cells will contain a relatively smaller percentage of HSCs under inflammation. If the division-to-death rate is also affected, then the percentage of HSCs under inflammation can either decrease or increase, depending on other parameters.

show abstract

Mathematical Modeling of Leukemogenesis and Cancer Stem Cell Dynamics

Cited by 100 publications

References 62 publications

Tumours with cancer stem cells: A PDE model

Tumours with cancer stem cells: A PDE model

Cell Division Patterns in Acute Myeloid Leukemia Stem-like Cells Determine Clinical Course: A Model to Predict Patient Survival

Determining the role of inflammation in the selection of JAK2 mutant cells in myeloproliferative neoplasms

Contact Info

Product

Resources

About