Hematopoietic stem cells (HSCs) retain the ability to maintain their own population while at the same time generating all cell types of the peripheral blood. In contrast to other somatic stem cells, HSCs undergo periods of extended quiescence, in which they do not proliferate but retain their stemness. However, malignant transformations can convert these cells into the drivers of leukemia and other hematological diseases. Advances in sequencing technologies and longitudinal clonal analysis have revealed a substantial intrinsic heterogeneity and dynamic regulation at the HSC level that can only be fully understood using appropriate mechanistic mathematical models.
It is an open conceptual question whether the common binary description of HSCs as either “active” or “quiescent” captures a real biological dichotomy or merely approximates a continuous spectrum of functional activity. In the latter view, individual HSCs may gradually shift their proliferative activity and differentiation potential in response to external cues such as spatial or metabolic conditions. A continuous formulation requires a state space (e.g. with respect to activation level, lineage propensity, metabolic fitness) and a set of deterministic or stochastic dynamics defined on that space. However, the relevant dimensions of this state space are problem-dependent and it is unclear how to model state-dependent division, differentiation and death rates. It is also not fully resolved how to relate the resulting continuum model to experimentally accessible markers, such as flow-cytometry or sequencing data, and how changes in rate parameters can shift the physiological system towards disease pathology.
Clinical investigations have revealed that clonal advantages often emerge early in life and drive gradual clonal expansion over decades, presenting significant challenges for detecting and monitoring initially rare clones that may eventually contribute to disease development. While the notion of clonality in the biological context is not always well defined, it can be more stringently captured at a formal level. Challenges arise from experimental practices that rely on arbitrary abundance thresholds or frequency counts, which are sensitive to sampling depth, PCR bias and stochastic fluctuations. At this end, a formal framework is needed to separate pre-leukemic clonal expansion from physiological fluctuations, to quantify uncertainty in clonal developments and to identify relevant competition parameters from realistic data sets.
Such advanced mechanistic models of HSC organization and leukemia progression introduce additional challenges for parameter estimation, identifiability and computational efficiency. However, addressing these open problems is essential for risk stratification in clonal hematopoiesis and for the development of targeted therapeutic interventions.
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