Dynamics of competing heterogeneous clones in blood cancers explains multiple observations - a mathematical modeling approach

Heterogeneity of stem cell clones provide a key ingredient in altered hematopoiesis and is of main interest in the study of predisease states as well as in the development of blood cancers such as chronic myeloid leukemia (CML) and the Philadelphia-negative myeloprofilerative neoplasms (MPNs). A mathematical model based on biological mechanisms and basic cell descriptors such as proliferation rates and apoptosis rates is suggested, connecting stem cell dynamics with mature blood cells and immune mediated feedback. The flexible approach allows for arbitrary numbers of mutated stem cell clones with perturbed properties. In particular, the stem cell niche provides a competition between wild type and mutated stem cells. Hence, the stem cell niche can mediate suppression of the wild type clones and up-regulation of one or more malignant clones. The model is parameterized using clinical data to show typical disease progression in several blood cancers and the hematological and molecular response to treatment. Intriguingly, occasional oscillatory cell counts observed during treatment of CML and MPNs can be explained by heterogeneous stem cell clone dynamics. Thus, the vital heterogeneous stem cell dynamics may be inferred from mathematical modeling in synergy with clinical data to elucidate hematopoiesis, blood cancers and the outcome of interventions

Mathematical Modeling of MPNs Offers Understanding and Decision Support for Personalized Treatment

(1) Background: myeloproliferative neoplasms (MPNs) are slowly developing hematological cancers characterized by few driver mutations, with JAK2V617F being the most prevalent. (2) Methods: using mechanism-based mathematical modeling (MM) of hematopoietic stem cells, mutated hematopoietic stem cells, differentiated blood cells, and immune response along with longitudinal data from the randomized Danish DALIAH trial, we investigate the effect of the treatment of MPNs with interferon-α2 on disease progression. (3) Results: At the population level, the JAK2V617F allele burden is halved every 25 months. At the individual level, MM describes and predicts the JAK2V617F kinetics and leukocyte- and thrombocyte counts over time. The model estimates the patient-specific treatment duration, relapse time, and threshold dose for achieving a good response to treatment. (4) Conclusions: MM in concert with clinical data is an important supplement to understand and predict the disease progression and impact of interventions at the individual level

Epigenetic changes in myelofibrosis:Distinct methylation changes in the myeloid compartments and in cases with <i>ASXL1</i> mutations

Abstract This is the first study to compare genome-wide DNA methylation profiles of sorted blood cells from myelofibrosis (MF) patients and healthy controls. We found that differentially methylated CpG sites located to genes involved in ‘cancer’ and ‘embryonic development’ in MF CD34+ cells, in ‘inflammatory disease’ in MF mononuclear cells, and in ‘immunological diseases’ in MF granulocytes. Only few differentially methylated CpG sites were common among the three cell populations. Mutations in the epigenetic regulators ASXL1 (47%) and TET2 (20%) were not associated with a specific DNA methylation pattern using an unsupervised approach. However, in a supervised analysis of ASXL1 mutated versus wild-type cases, differentially methylated CpG sites were enriched in regions marked by histone H3K4me1, histone H3K27me3, and the bivalent histone mark H3K27me3 + H3K4me3 in human CD34+ cells. Hypermethylation of selected CpG sites was confirmed in a separate validation cohort of 30 MF patients by pyrosequencing. Altogether, we show that individual MF cell populations have distinct differentially methylated genes relative to their normal counterparts, which likely contribute to the phenotypic characteristics of MF. Furthermore, differentially methylated CpG sites in ASXL1 mutated MF cases are found in regulatory regions that could be associated with aberrant gene expression of ASXL1 target genes