Clonal dominance and transplantation dynamics in hematopoietic stem cell compartments

Modelling post-chemotherapy stem cell dynamics in the bone marrow niche of AML patients

Acute myeloid leukemia (AML) is a stem cell-driven malignancy of the blood forming (hematopoietic) system. Despite of high dose chemotherapy with toxic side effects, many patients eventually relapse. The "7+3 regimen", which consists of 7 days of cytarabine in combination with daunorubicin during the first 3 days, is a widely used therapy protocol. Since peripheral blood cells are easily accessible to longitudinal sampling, significant research efforts have been undertaken to characterize and reduce adverse effects on circulating blood cells. However, much less is known about the impact of the 7+3 regimen on human hematopoietic stem cells and their physiological micro-environments, the so-called stem cell niches. One reason for this is the technical inability to observe human stem cells in vivo and the discomfort related to bone marrow biopsies. To better understand the treatment effects on human stem cells, we consider a mechanistic mathematical model of the stem cell niche before, during and after chemotherapy. The model accounts for different maturation stages of leukemic and hematopoietic cells and considers key processes such as cell proliferation, self-renewal, differentiation and therapy-induced cell death. In the model, hematopoietic (HSCs) and leukemic stem cells (LSCs) compete for a joint niche and respond to both systemic and niche-derived signals. We relate the model to clinical trial data from literature which longitudinally quantifies the counts of hematopoietic stem like (CD34+CD38-ALDH+) cells at diagnosis and after therapy. The proposed model can capture the clinically observed interindividual heterogeneity and reproduce the non-monotonous dynamics of the hematopoietic stem like cells observed in relapsing patients. Our model allows to simulate different scenarios proposed in literature such as therapy-related impairment of the stem cell niche or niche-mediated resistance. Model simulations suggest that during the post-therapy phase a more than 10-fold increase of hematopoietic stem-like cell proliferation rates is required to recapitulate the measured cell dynamics in patients achieving complete remission. We fit the model to data of 7 individual patients and simulate variations of the treatment protocol. These simulations are in line with the clinical finding that G-CSF priming can improve the treatment outcome. Furthermore, our model suggests that a decline of HSC counts during remission might serve as an indication for salvage therapy in patients lacking MRD (minimal residual disease) markers.

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

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.

Computational modeling reveals key factors driving treatment-free remission in chronic myeloid leukemia patients

Patients with chronic myeloid leukemia (CML) who receive tyrosine kinase inhibitors (TKIs) have been known to achieve treatment-free remission (TFR) upon discontinuing treatment. However, the underlying mechanisms of this phenomenon remain incompletely understood. This study aims to elucidate the mechanism of TFR in CML patients, focusing on the feedback interaction between leukemia stem cells and the bone marrow microenvironment. We have developed a mathematical model to explore the interplay between leukemia stem cells and the bone marrow microenvironment, allowing for the simulation of CML progression dynamics. Our proposed model reveals a dichotomous response following TKI discontinuation, with two distinct patient groups emerging: one prone to early molecular relapse and the other capable of achieving long-term TFR after treatment cessation. This finding aligns with clinical observations and underscores the essential role of feedback interaction between leukemic cells and the tumor microenvironment in sustaining TFR. Notably, we have shown that the ratio of leukemia cells in peripheral blood (PBLC) and the tumor microenvironment (TME) index can be a valuable predictive tool for identifying patients likely to achieve TFR after discontinuing treatment. This study provides fresh insights into the mechanism of TFR in CML patients and underscores the significance of microenvironmental control in achieving TFR.

Somatic epimutations enable single-cell lineage tracing in native hematopoiesis across the murine and human lifespan

Current approaches to lineage tracing of stem cell clones require genetic engineering or rely on sparse somatic DNA variants, which are difficult to capture at single-cell resolution. Here, we show that targeted single-cell measurements of DNA methylation at single-CpG resolution deliver joint information about cellular differentiation state and clonal identities. We develop EPI-clone, a droplet-based method for transgene-free lineage tracing, and apply it to study hematopoiesis, capturing hundreds of clonal trajectories across almost 100,000 single-cells. Using ground-truth genetic barcodes, we demonstrate that EPI-clone accurately identifies clonal lineages throughout hematopoietic differentiation. Applied to unperturbed hematopoiesis, we describe an overall decline of clonal complexity during murine ageing and the expansion of rare low-output stem cell clones. In aged human donors, we identified expanded hematopoietic clones with and without genetic lesions, and various degrees of clonal complexity. Taken together, EPI-clone enables accurate and transgene-free single-cell lineage tracing at scale.

Tissue mosaicism following stem cell aging: blood as an exemplar

Loss of stem cell regenerative potential underlies aging of all tissues. Somatic mosaicism, the emergence of cellular patchworks within tissues, increases with age and has been observed in every organ yet examined. In the hematopoietic system, as in most tissues, stem cell aging through a variety of mechanisms occurs in lockstep with the emergence of somatic mosaicism. Here, we draw on insights from aging hematopoiesis to illustrate fundamental principles of stem cell aging and somatic mosaicism. We describe the generalizable changes intrinsic to aged stem cells and their milieu that provide the backdrop for somatic mosaicism to emerge. We discuss genetic and nongenetic mechanisms that can result in tissue somatic mosaicism and existing methodologies to detect such clonal outgrowths. Finally, we propose potential avenues to modify mosaicism during aging, with the ultimate aim of increasing tissue resiliency.

Capturing the unpredictability of stem cells

A new mathematical model that can be applied to both single-cell and bulk DNA sequencing data sheds light on the processes governing population dynamics in stem cells.

Stochastic fate decisions of HSCs after transplantation: early contribution, symmetric expansion, and pool formation

Hematopoietic stem cells (HSCs) are assumed to be rare, infrequently dividing, long-lived cells not involved in immediate recovery after transplantation. Here, we performed unprecedented high-density clonal tracking in nonhuman primates and found long-term persisting HSC clones to actively contribute during early neutrophil recovery, and to be the main source of blood production as early as 50 days after transplantation. Most surprisingly, we observed a rapid decline in the number of unique HSC clones, while persisting HSCs expanded, undergoing symmetric divisions to create identical siblings and formed clonal pools ex vivo as well as in vivo. In contrast to the currently assumed model of hematopoietic reconstitution, we provide evidence for contribution of HSCs in short-term recovery as well as symmetric expansion of individual clones into pools. These findings provide novel insights into HSC biology, informing the design of HSC transplantation and gene therapy studies.

A mixed-effects stochastic model reveals clonal dominance in gene therapy safety studies

BACKGROUND

Mathematical models of haematopoiesis can provide insights on abnormal cell expansions (clonal dominance), and in turn can guide safety monitoring in gene therapy clinical applications. Clonal tracking is a recent high-throughput technology that can be used to quantify cells arising from a single haematopoietic stem cell ancestor after a gene therapy treatment. Thus, clonal tracking data can be used to calibrate the stochastic differential equations describing clonal population dynamics and hierarchical relationships in vivo.

RESULTS

In this work we propose a random-effects stochastic framework that allows to investigate the presence of events of clonal dominance from high-dimensional clonal tracking data. Our framework is based on the combination between stochastic reaction networks and mixed-effects generalized linear models. Starting from the Kramers-Moyal approximated Master equation, the dynamics of cells duplication, death and differentiation at clonal level, can be described by a local linear approximation. The parameters of this formulation, which are inferred using a maximum likelihood approach, are assumed to be shared across the clones and are not sufficient to describe situation in which clones exhibit heterogeneity in their fitness that can lead to clonal dominance. In order to overcome this limitation, we extend the base model by introducing random-effects for the clonal parameters. This extended formulation is calibrated to the clonal data using a tailor-made expectation-maximization algorithm. We also provide the companion  package RestoreNet, publicly available for download at https://cran.r-project.org/package=RestoreNet .

CONCLUSIONS

Simulation studies show that our proposed method outperforms the state-of-the-art. The application of our method in two in-vivo studies unveils the dynamics of clonal dominance. Our tool can provide statistical support to biologists in gene therapy safety analyses.

HSC Niche Dynamics in Regeneration, Pre-malignancy, and Cancer: Insights From Mathematical Modeling

The hematopoietic stem cell (HSC) niche is a crucial driver of regeneration and malignancy. Its interaction with hematopoietic and malignant stem cells is highly complex and direct experimental observations are challenging. We here develop a mathematical model which helps relate processes in the niche to measurable changes of stem and non-stem cell counts. HSC attached to the niche are assumed to be quiescent. After detachment HSC become activated and divide or differentiate. To maintain their stemness, the progeny originating from division must reattach to the niche. We use mouse data from literature to parametrize the model. By combining mathematical analysis and computer simulations, we systematically investigate the impact of stem cell proliferation, differentiation, niche attachment, and detachment on clinically relevant scenarios. These include bone marrow transplantation, clonal competition, and eradication of malignant cells. According to our model, sampling of blood or bulk marrow provides only limited information about cellular interactions in the niche and the clonal composition of the stem cell population. Furthermore, we investigate how interference with processes in the stem cell niche could help to increase the effect of low-dose chemotherapy or to improve the homing of genetically engineered cells.

Understanding Hematopoietic Stem Cell Dynamics—Insights from Mathematical Modelling

Purpose of review

Hematopoietic stem cells (HSCs) drive blood-cell production (hematopoiesis). Out-competition of HSCs by malignant cells occurs in many hematologic malignancies like acute myeloid leukemia (AML). Through mathematical modelling, HSC dynamics and their impact on healthy blood cell formation can be studied, using mathematical analysis and computer simulations. We review important work within this field and discuss mathematical modelling as a tool for attaining biological insight.

Recent findings

Various mechanism-based models of HSC dynamics have been proposed in recent years. Key properties of such models agree with observations and medical knowledge and suggest relations between stem cell properties, e.g., rates of division and the temporal evolution of the HSC population. This has made it possible to study how HSC properties shape clinically relevant processes, including engraftment following an HSC transplantation and the response to different treatment.

Summary

Understanding how properties of HSCs affect hematopoiesis is important for efficient treatment of diseases. Mathematical modelling can contribute significantly to these efforts.

The Origin of Clonal Hematopoiesis and Its Implication in Human Diseases

Clonal expansion of hematopoietic cells is first observed in hematological malignancies where all the leukemic cells can be traced back to a single cell carrying oncogenic alterations. Interestingly, expansion of hematopoietic clones with defined genomic alterations, including single nucleotide variants (SNVs), small insertions and deletions (indels), and large structural chromosomal alterations (CAs), is also found in the healthy population. These genomic changes often affect leukemia driver genes. As a result, healthy individuals bearing such clonal hematopoiesis (CH) are at a higher risk of hematological malignancies. In addition to blood cancers, SNV/indel-related CH has been found associated with elevated cardiovascular and all-cause mortality, indicating adverse impacts of abnormalities in the blood on the normal functions of non-hematological tissues. In the past decade, much effort has been invested in understanding the origins of CH and its causal relationship with diseases in hematological and non-hematological tissues. Here, we review recent progress in these areas and discuss future directions that can be pursued to translate the acquired knowledge into better management of CH-related diseases.

What Is a Digital Twin? Experimental Design for a Data-Centric Machine Learning Perspective in Health

The idea of a digital twin has recently gained widespread attention. While, so far, it has been used predominantly for problems in engineering and manufacturing, it is believed that a digital twin also holds great promise for applications in medicine and health. However, a problem that severely hampers progress in these fields is the lack of a solid definition of the concept behind a digital twin that would be directly amenable for such big data-driven fields requiring a statistical data analysis. In this paper, we address this problem. We will see that the term 'digital twin', as used in the literature, is like a Matryoshka doll. For this reason, we unstack the concept via a data-centric machine learning perspective, allowing us to define its main components. As a consequence, we suggest to use the term Digital Twin System instead of digital twin because this highlights its complex interconnected substructure. In addition, we address ethical concerns that result from treatment suggestions for patients based on simulated data and a possible lack of explainability of the underling models.

Patient-specific molecular response dynamics can predict the possibility of relapse during the second treatment-free remission attempt in chronic myelogenous leukemia

In chronic myelogenous leukemia (CML), treatment-free remission (TFR) is defined as maintaining a major molecular response (MMR) without a tyrosine kinase inhibitor (TKI), such as imatinib (IM). Several studies have investigated the safety of the first TFR (TFR₁) attempt and suggested recommendation guidelines for such an attempt. However, the plausibility and predictive factors for a second TFR (TFR₂) have yet to be reported. The present study included 21 patients in chronic myeloid leukemia who participated in twice repeated treatment stop attempts. We develop a mathematical model to analyze and explain the outcomes of TFR₂. Our mathematical model framework can explain patient-specific molecular response dynamics. Fitting the model to longitudinal BCR-ABL1 transcripts from the patients generated patient-specific parameters. Binary tree decision analyses of the model parameters suggested a model based predictive binary classification factor that separated patients into low- and high-risk groups of TFR₂ attempts with an overall accuracy of 76.2% (sensitivity of 81.1% and specificity of 69.9%). The low-risk group maintained a median TFR₂ of 28.2 months, while the high-risk group relapsed at a median time of 3.25 months. Further, our model predicted a patient-specific optimal IM treatment duration before the second IM stop that could achieve the desired TFR₂ (e.g., 5 years).

Increased stem cell proliferation in atherosclerosis accelerates clonal hematopoiesis

Clonal hematopoiesis, a condition in which individual hematopoietic stem cell clones generate a disproportionate fraction of blood leukocytes, correlates with higher risk for cardiovascular disease. The mechanisms behind this association are incompletely understood. Here, we show that hematopoietic stem cell division rates are increased in mice and humans with atherosclerosis. Mathematical analysis demonstrates that increased stem cell proliferation expedites somatic evolution and expansion of clones with driver mutations. The experimentally determined division rate elevation in atherosclerosis patients is sufficient to produce a 3.5-fold increased risk of clonal hematopoiesis by age 70. We confirm the accuracy of our theoretical framework in mouse models of atherosclerosis and sleep fragmentation by showing that expansion of competitively transplanted Tet2^-/- cells is accelerated under conditions of chronically elevated hematopoietic activity. Hence, increased hematopoietic stem cell proliferation is an important factor contributing to the association between cardiovascular disease and clonal hematopoiesis.

Mathematical modelling of the hematopoietic stem cell-niche system: Clonal dominance based on stem cell fitness

Human blood cell production is maintained by hematopoietic stem cells (HSC) which give rise to all types of mature blood cells. Experimental observation of HSC in their physiologic bone-marrow microenvironment, the so-called stem cell niche, is challenging. Therefore, the details of HSC dynamics and the cellular interactions in the stem cell niche remain elusive. Mutations that lead to a competitive advantage are the cause of clinical challenges when treating HSC-derived malignancies such as acute myeloid leukemia or the myeloproliferative neoplasms (MPNs). To investigate the significance of the interaction between the HSC and the stem cell niche in these malignancies, we propose and analyse a mechanism-based mathematical model of HSC dynamics within the bone-marrow microenvironment. The model is based on the central hypothesis that HSC self-renewal depends on the niche. In the model, the interaction of HSC with specific niches located in the bone marrow are key to the indefinite HSC renewal necessary for long-term maintenance of blood cell production. We formulate a general model of n distinct clones that differ with respect to cell properties. We identify an attractive trapping region and compute and classify all steady states. A concept of HSC fitness naturally arises from the model analysis. HSC fitness is found to determine the asymptotic behaviour of the model, as the HSC clone with the highest fitness is related to the unique locally stable steady state. Based on biological assumptions about HSC, we propose two reduced models of different complexity. A thorough mathematical analysis reveals that both reduced models have the same asymptotic behaviour as the full model. We compare the simpler of the two models, a logistic equation of the disease burden, to clinical data of MPN-patients. The reduced model is found to agree well with data and suggests a simple interpretation and possible prediction of patient prognosis. The proposed mathematical model and the reduced forms have the potential to provide insights into the regulation of HSC dynamics and blood cell formation, and ultimately for future advances in treatment of hematologic malignancies.

Current Trends on Hemopoietic Stem Cells

Advances in single-cell technology and genetic mouse models have resulted in the identification of new types of hemopoietic stem cells (HSC), resulting in baffling observations, suggesting a reconsideration of the long-held notion that all hematopoietic cells in the adult are derived from HSCs. The existence of long-lived HSC-independent hematopoiesis has led to the conclusion that despite the single hierarchical differentiation route that generates functional blood types, other differentiation routes exist in-vivo. Heterogeneity in the HSC population and the evolving knowledge around HSC has translated to it's improved application as a therapeutic tool for various blood disorders. The reprogramming of non-hematopoietic somatic and mature blood cells to pluripotency with their subsequent differentiation into hematopoietic stem cells/progenitor cells and the introduction of new generation sequencing holds the potential for the resolution of ambiguities involved in HSC bone marrow transplantation. There is a change in the paradigm for HSC transplantation donor selection. Donor choice favors haploidentical HCT than cord blood. This review provides a general overview of the current events around hemopoietic stem cells, with emphasis on the rising trend of HSC transplantation, especially haploidentical stem cell transplantation.

A somatic evolutionary model of the dynamics of aneuploid cells during hematopoietic reconstitution

Aneuploidy is a feature of many cancers. Recent studies demonstrate that in the hematopoietic stem and progenitor cell (HSPC) compartment aneuploid cells have reduced fitness and are efficiently purged from the bone marrow. However, early phases of hematopoietic reconstitution following bone marrow transplantation provide a window of opportunity whereby aneuploid cells rise in frequency, only to decline to basal levels thereafter. Here we demonstrate by Monte Carlo modeling that two mechanisms could underlie this aneuploidy peak: rapid expansion of the engrafted HSPC population and bone marrow microenvironment degradation caused by pre-transplantation radiation treatment. Both mechanisms reduce the strength of purifying selection acting in early post-transplantation bone marrow. We explore the contribution of other factors such as alterations in cell division rates that affect the strength of purifying selection, the balance of drift and selection imposed by the HSPC population size, and the mutation-selection balance dependent on the rate of aneuploidy generation per cell division. We propose a somatic evolutionary model for the dynamics of cells with aneuploidy or other fitness-reducing mutations during hematopoietic reconstitution following bone marrow transplantation. Similar alterations in the strength of purifying selection during cancer development could help explain the paradox of aneuploidy abundance in tumors despite somatic fitness costs.

Mathematical Modeling Provides Evidence for Niche Competition in Human AML and Serves as a Tool to Improve Risk Stratification

Acute myeloid leukemia (AML) is a stem cell-driven malignant disease. There is evidence that leukemic stem cells (LSC) interact with stem cell niches and outcompete hematopoietic stem cells (HSC). The impact of this interaction on the clinical course of the disease remains poorly understood. We developed and validated a mathematical model of stem cell competition in the human HSC niche. Model simulations predicted how processes in the stem cell niche affect the speed of disease progression. Combining the mathematical model with data of individual patients, we quantified the selective pressure LSCs exert on HSCs and demonstrated the model's prognostic significance. A novel model-based risk-stratification approach allowed extraction of prognostic information from counts of healthy and malignant cells at the time of diagnosis. This model's feasibility was demonstrable based on a cohort of patients with ALDH-rare AML and shows that the model-based risk stratification is an independent predictor of disease-free and overall survival. This proof-of-concept study shows how model-based interpretation of patient data can improve prognostic scoring and contribute to personalized medicine. SIGNIFICANCE: Combining a novel mathematical model of the human hematopoietic stem cell niche with individual patient data enables quantification of properties of leukemic stem cells and improves risk stratification in acute myeloid leukemia.

Global dynamics of healthy and cancer cells competing in the hematopoietic system

Stem cells in the bone marrow differentiate to ultimately become mature, functioning blood cells through a tightly regulated process (hematopoiesis) including a stem cell niche interaction and feedback through the immune system. Mutations in a hematopoietic stem cell can create a cancer stem cell leading to a less controlled production of malfunctioning cells in the hematopoietic system. This was mathematically modelled by Andersen et al. (2017) including the dynamic variables: healthy and cancer stem cells and mature cells, dead cells and an immune system response. Here, we apply a quasi steady state approximation to this model to construct a two dimensional model with four algebraic equations denoted the simple cancitis model. The two dynamic variables are the clinically available quantities JAK2V617F allele burden and the number of white blood cells. The simple cancitis model represents the original model very well. Complete phase space analysis of the simple cancitis model is performed, including proving the existence and location of globally attracting steady states. Hence, parameter values from compartments of stem cells, mature cells and immune cells are directly linked to disease and treatment prognosis, showing the crucial importance of early intervention. The simple cancitis model allows for a complete analysis of the long term evolution of trajectories. In particular, the value of the self renewal of the hematopoietic stem cells divided by the self renewal of the cancer stem cells is found to be an important diagnostic marker and perturbing this parameter value at intervention allows the model to reproduce clinical data. Treatment at low cancer cell numbers allows returning to healthy blood production while the same intervention at a later disease stage can lead to eradication of healthy blood producing cells. Assuming the total number of white blood cells is constant in the early cancer phase while the allele burden increases, a one dimensional model is suggested and explicitly solved, including parameters from all original compartments. The solution explicitly shows that exogenous inflammation promotes blood cancer when cancer stem cells reproduce more efficiently than hematopoietic stem cells.

The evolutionary dynamics and fitness landscape of clonal hematopoiesis

Somatic mutations acquired in healthy tissues as we age are major determinants of cancer risk. Whether variants confer a fitness advantage or rise to detectable frequencies by chance remains largely unknown. Blood sequencing data from ~50,000 individuals reveal how mutation, genetic drift, and fitness shape the genetic diversity of healthy blood (clonal hematopoiesis). We show that positive selection, not drift, is the major force shaping clonal hematopoiesis, provide bounds on the number of hematopoietic stem cells, and quantify the fitness advantages of key pathogenic variants, at single-nucleotide resolution, as well as the distribution of fitness effects (fitness landscape) within commonly mutated driver genes. These data are consistent with clonal hematopoiesis being driven by a continuing risk of mutations and clonal expansions that become increasingly detectable with age.

Replicative cellular age distributions in compartmentalized tissues

The cellular age distribution of hierarchically organized tissues can reveal important insights into the dynamics of cell differentiation and self-renewal and associated cancer risks. Here, we examine the effect of progenitor compartments with varying differentiation and self-renewal capacities on the resulting observable distributions of replicative cellular ages. We find that strongly amplifying progenitor compartments, i.e. compartments with high self-renewal capacities, substantially broaden the age distributions which become skewed towards younger cells with a long tail of few old cells. For several of these strongly amplifying compartments, the age distribution becomes virtually independent of the influx from the stem cell compartment. By contrast, if tissues are organized into many downstream compartments with low self-renewal capacity, the shape of the replicative cell distribution in more differentiated compartments is dominated by stem cell dynamics with little added variation. In the limiting case of a strict binary differentiation tree without self-renewal, the shape of the output distribution becomes indistinguishable from that of the input distribution. Our results suggest that a comparison of cellular age distributions between healthy and cancerous tissues may inform about dynamical changes within the hierarchical tissue structure, i.e. an acquired increased self-renewal capacity in certain tumours. Furthermore, we compare our theoretical results to telomere length distributions in granulocyte populations of 10 healthy individuals across different ages, highlighting that our theoretical expectations agree with experimental observations.

Clonal hematopoiesis of indeterminate potential and its impact on patient trajectories after stem cell transplantation

Clonal hematopoiesis of indeterminate potential (CHIP) is a recently identified process where older patients accumulate distinct subclones defined by recurring somatic mutations in hematopoietic stem cells. CHIP's implications for stem cell transplantation have been harder to identify due to the high degree of mutational heterogeneity that is present within the genetically distinct subclones. In order to gain a better understanding of CHIP and the impact of clonal dynamics on transplantation outcomes, we created a mathematical model of clonal competition dynamics. Our analyses highlight the importance of understanding competition intensity between healthy and mutant clones. Importantly, we highlight the risk that CHIP poses in leading to dominance of precancerous mutant clones and the risk of donor derived leukemia. Furthermore, we estimate the degree of competition intensity and bone marrow niche decline in mice during aging by using our modeling framework. Together, our work highlights the importance of better characterizing the ecological and clonal composition in hematopoietic donor populations at the time of stem cell transplantation.

The global clonal complexity of the murine blood system declines throughout life and after serial transplantation

Although many recent studies describe the emergence and prevalence of "clonal hematopoiesis of indeterminate potential" in aged human populations, a systematic analysis of the numbers of clones supporting steady-state hematopoiesis throughout mammalian life is lacking. Previous efforts relied on transplantation of "barcoded" hematopoietic stem cells (HSCs) to track the contribution of HSC clones to reconstituted blood. However, ex vivo manipulation and transplantation alter HSC function and thus may not reflect the biology of steady-state hematopoiesis. Using a noninvasive in vivo color-labeling system, we report the first comprehensive analysis of the changing global clonal complexity of steady-state hematopoiesis during the natural murine lifespan. We observed that the number of clones (ie, clonal complexity) supporting the major blood and bone marrow hematopoietic compartments decline with age by ∼30% and ∼60%, respectively. Aging dramatically reduced HSC in vivo-repopulating activity and lymphoid potential while increasing functional heterogeneity. Continuous challenge of the hematopoietic system by serial transplantation provoked the clonal collapse of both young and aged hematopoietic systems. Whole-exome sequencing of serially transplanted aged and young hematopoietic clones confirmed oligoclonal hematopoiesis and revealed mutations in at least 27 genes, including nonsense, missense, and deletion mutations in Bcl11b, Hist1h2ac, Npy2r, Notch3, Ptprr, and Top2b.

Stem cell homeostasis by integral feedback through the niche

Hematopoiesis is a paradigm for tissue development and renewal from stem cells. Experiments show that the maintenance of hematopoietic stem cells (HSCs) relies on signals from niche cells. However, it is not known how the size of the HSC compartment is set. Competition by HSCs for niche access has been suggested, yet niche cells in the bone marrow outnumber HSCs. Here we propose a cooperative model of HSC homeostasis in which stem and niche cells mutually interact such that niche cells function as negative feedback regulators of HSC proliferation. This model explains puzzling experimental findings, including homeostatic recovery of the HSC compartment after irradiation versus apparent lack of recovery after HSC ablation. We show that bidirectional niche-stem cell regulation has properties of a proportional-integral feedback controller. Moreover, we predict that the outflux of differentiated cells from HSCs can be regulated by the affinity of HSCs for niche cells. Much effort has been devoted to elucidating niche cell signaling to stem cells; our theoretical insights indicate that studying the effect of stem cells on the niche may be equally important for understanding stem cell homeostasis.