Stem cell clonality -- theoretical concepts, experimental techniques, and clinical challenges

Measures of Clonal Hematopoiesis: Are We Missing Something?

Clonal Hematopoiesis (CH) is a common, age-related phenomenon of growing scientific interest, due to its association with hematologic malignancy, cardiovascular disease and decreased overall survival. CH is commonly attributed to the preferential outgrowth of a mutant hematopoietic stem cell (HSC) with enhanced fitness, resulting in clonal imbalance. In-depth understanding of the relation between HSC clonal dynamics, CH and hematologic malignancy requires integration of fundamental lineage tracing studies with clinical data. However, this is hampered by lack of a uniform definition of CH and by inconsistency in the analytical methods used for its quantification. Here, we propose a conceptual and analytical framework for the definition and measurement of CH. First, we transformed the conceptual definition of CH into the CH index, which provides a quantitative measure of clone numbers and sizes. Next, we generated a set of synthetic data, based on the beta-distribution, to simulate clonal populations with different degrees of imbalance. Using these clonal distributions and the CH index as a reference, we tested several established indices of clonal diversity and (in-)equality for their ability to detect and quantify CH. We found that the CH index was distinct from any of the other tested indices. Nonetheless, the diversity indices (Shannon, Simpson) more closely resembled the CH index than the inequality indices (Gini, Pielou). Notably, whereas the inequality indices mainly responded to changes in clone sizes, the CH index and the tested diversity indices also responded to changes in the number of clones in a sample. Accordingly, these simulations indicate that CH can result not only by skewing clonal abundancies, but also by variation in their overall numbers. Altogether, our model-based approach illustrates how a formalized definition and quantification of CH can provide insights into its pathogenesis. In the future, use of the CH index or Shannon index to quantify clonal diversity in fundamental as well as clinical clone-tracing studies will promote cross-disciplinary discussion and progress in the field.

Interdisciplinary approach to biomedical research: a panacea to efficient research output during the global pandemic

Biomedical research is rapidly growing due to inventions and developments in science and technology. Several interdisciplinary fields should be combined to find the remedy of diseases including pandemics. To accomplish this, interdisciplinary research is a prerequisite. Using improved techniques in microscopy and genetic engineering, the systemic perspective of the human body and related diseases can be found. Recent genetic-based inheritance studies of diseases, understanding various omics, stem cell systems, and gene editing tools including CRISPR relevant to biomedical research require multidisciplinary approach. Improvements in the field of bioinformatics and efficient use of model organisms in clinical testing including drug assessment are important disciplines common in different researches. The merging of different closely related areas of medical research will produce suitable changes in diagnosis and treatment. In the present scenario of increased global pandemic hits like COVID-19, an understanding on the interdisciplinary approach is needed for controlling the spread and finding vaccines.

The recent advances in the mathematical modelling of human pluripotent stem cells

Human pluripotent stem cells hold great promise for developments in regenerative medicine and drug design. The mathematical modelling of stem cells and their properties is necessary to understand and quantify key behaviours and develop non-invasive prognostic modelling tools to assist in the optimisation of laboratory experiments. Here, the recent advances in the mathematical modelling of hPSCs are discussed, including cell kinematics, cell proliferation and colony formation, and pluripotency and differentiation.

Seeding hESCs to achieve optimal colony clonality

Human embryonic stem cells (hESCs) and induced pluripotent stem cells (iPSCs) have promising clinical applications which often rely on clonally-homogeneous cell populations. To achieve this, it is important to ensure that each colony originates from a single founding cell and to avoid subsequent merging of colonies during their growth. Clonal homogeneity can be obtained with low seeding densities; however, this leads to low yield and viability. It is therefore important to quantitatively assess how seeding density affects clonality loss so that experimental protocols can be optimised to meet the required standards. Here we develop a quantitative framework for modelling the growth of hESC colonies from a given seeding density based on stochastic exponential growth. This allows us to identify the timescales for colony merges and over which colony size no longer predicts the number of founding cells. We demonstrate the success of our model by applying it to our own experiments of hESC colony growth; while this is based on a particular experimental set-up, the model can be applied more generally to other cell lines and experimental conditions to predict these important timescales.

Clonal approaches to understanding the impact of mutations on hematologic disease development

Interrogation of hematopoietic tissue at the clonal level has a rich history spanning over 50 years, and has provided critical insights into both normal and malignant hematopoiesis. Characterization of chromosomes identified some of the first genetic links to cancer with the discovery of chromosomal translocations in association with many hematological neoplasms. The unique accessibility of hematopoietic tissue and the ability to clonally expand hematopoietic progenitors in vitro has provided fundamental insights into the cellular hierarchy of normal hematopoiesis, as well as the functional impact of driver mutations in disease. Transplantation assays in murine models have enabled cellular assessment of the functional consequences of somatic mutations in vivo. Most recently, next-generation sequencing-based assays have shown great promise in allowing multi-"omic" characterization of single cells. Here, we review how clonal approaches have advanced our understanding of disease development, focusing on the acquisition of somatic mutations, clonal selection, driver mutation cooperation, and tumor evolution.

Clonal selection and asymmetric distribution of human leukemia in murine xenografts revealed by cellular barcoding

Genetic and phenotypic heterogeneity of human leukemia is thought to drive leukemia progression through a Darwinian process of selection and evolution of increasingly malignant clones. However, the lack of markers that uniquely identify individual leukemia clones precludes high-resolution tracing of their clonal dynamics. Here, we use cellular barcoding to analyze the clonal behavior of patient-derived leukemia-propagating cells (LPCs) in murine xenografts. Using a leukemic cell line and diagnostic bone marrow cells from 6 patients with B-progenitor cell acute lymphoblastic leukemia, we demonstrate that patient-derived xenografts were highly polyclonal, consisting of tens to hundreds of LPC clones. The number of clones was stable within xenografts but strongly reduced upon serial transplantation. In contrast to primary recipients, in which clonal composition was highly diverse, clonal composition in serial xenografts was highly similar between recipients of the same donor and reflected donor clonality, supporting a deterministic, clone-size-based model for clonal selection. Quantitative analysis of clonal abundance in several anatomic sites identified 2 types of anatomic asymmetry. First, clones were asymmetrically distributed between different bones. Second, clonal composition in the skeleton significantly differed from extramedullary sites, showing similar numbers but different clone sizes. Altogether, this study shows that cellular barcoding and xenotransplantation providea useful model to study the behavior of patient-derived LPC clones, which provides insights relevant for experimental studies on cancer stem cells and for clinical protocols for the diagnosis and treatment of leukemia.

Bistable Epigenetic States Explain Age-Dependent Decline in Mesenchymal Stem Cell Heterogeneity

The molecular mechanisms by which heterogeneity, a major characteristic of stem cells, is achieved are yet unclear. We here study the expression of the membrane stem cell antigen-1 (Sca-1) in mouse bone marrow mesenchymal stem cell (MSC) clones. We show that subpopulations with varying Sca-1 expression profiles regenerate the Sca-1 profile of the mother population within a few days. However, after extensive replication in vitro, the expression profiles shift to lower values and the regeneration time increases. Study of the promoter of Ly6a unravels that the expression level of Sca-1 is related to the promoter occupancy by the activating histone mark H3K4me3. We demonstrate that these findings can be consistently explained by a computational model that considers positive feedback between promoter H3K4me3 modification and gene transcription. This feedback implicates bistable epigenetic states which the cells occupy with an age-dependent frequency due to persistent histone (de-)modification. Our results provide evidence that MSC heterogeneity, and presumably that of other stem cells, is associated with bistable epigenetic states and suggest that MSCs are subject to permanent state fluctuations. Stem Cells 2017;35:694-704.

Model Based Analysis of Clonal Developments Allows for Early Detection of Monoclonal Conversion and Leukemia

The availability of several methods to unambiguously mark individual cells has strongly fostered the understanding of clonal developments in hematopoiesis and other stem cell driven regenerative tissues. While cellular barcoding is the method of choice for experimental studies, patients that underwent gene therapy carry a unique insertional mark within the transplanted cells originating from the integration of the retroviral vector. Close monitoring of such patients allows accessing their clonal dynamics, however, the early detection of events that predict monoclonal conversion and potentially the onset of leukemia are beneficial for treatment. We developed a simple mathematical model of a self-stabilizing hematopoietic stem cell population to generate a wide range of possible clonal developments, reproducing typical, experimentally and clinically observed scenarios. We use the resulting model scenarios to suggest and test a set of statistical measures that should allow for an interpretation and classification of relevant clonal dynamics. Apart from the assessment of several established diversity indices we suggest a measure that quantifies the extension to which the increase in the size of one clone is attributed to the total loss in the size of all other clones. By evaluating the change in relative clone sizes between consecutive measurements, the suggested measure, referred to as maximum relative clonal expansion (mRCE), proves to be highly sensitive in the detection of rapidly expanding cell clones prior to their dominant manifestation. This predictive potential places the mRCE as a suitable means for the early recognition of leukemogenesis especially in gene therapy patients that are closely monitored. Our model based approach illustrates how simulation studies can actively support the design and evaluation of preclinical strategies for the analysis and risk evaluation of clonal developments.

Tracing dynamics and clonal heterogeneity of Cbx7-induced leukemic stem cells by cellular barcoding

Accurate monitoring of tumor dynamics and leukemic stem cell (LSC) heterogeneity is important for the development of personalized cancer therapies. In this study, we experimentally induced distinct types of leukemia in mice by enforced expression of Cbx7. Simultaneous cellular barcoding allowed for thorough analysis of leukemias at the clonal level and revealed high and unpredictable tumor complexity. Multiple LSC clones with distinct leukemic properties coexisted. Some of these clones remained dormant but bore leukemic potential, as they progressed to full-blown leukemia after challenge. LSC clones could retain multilineage differentiation capacities, where one clone induced phenotypically distinct leukemias. Beyond a detailed insight into CBX7-driven leukemic biology, our model is of general relevance for the understanding of tumor dynamics and clonal evolution.