Abstract | The search for genes that regulate stem cell self-renewal and differentiation has been hindered by a paucity of markers that uniquely label stem cells and early progenitors. |
Abstract | We have applied this marker-free approach to screen for transcription factors that regulate mammary stem cell differentiation in a 3D model of tissue morphogenesis and identified RUNX1 as a stem cell regulator. |
Abstract | Inhibition of RUNX1 expanded bipotent stem cells and blocked their differentiation into ductal and lobular tissue rudiments. |
Author Summary | The discovery of stem cell regulators is a major goal of biological research, but progress is often limited by a lack of definitive markers capable of distinguishing stem cells from early progenitors. |
Author Summary | PEACS t0 mammary stem cells resulted in the identification of RUNXI as a key regulator of eXit from the bipotent state. |
Introduction | Adult stem cells are functionally defined based on their ability to regenerate tissues. |
Introduction | This unique regenerative ability can be recapitulated in culture models, Where single stem cells , but not differentiated cells, form tissue rudiments in three-dimensional extracellular matrices. |
Introduction | For example, mammary stem cells form ducts and lobules in collagen matrices that resemble structures present in the breast [1—3] , While colon stem cells form mini-crypts in Matrigel that resemble analogous structures in the small intestine [4]. |
Abstract | We develop a cellular automaton model that tracks the temporal evolution of the malignant subpopulation of so-called cancer stem cells (CSC), as these cells are exclusively able to initiate and sustain tumors. |
Abstract | We explore orthogonal cell traits, including cell migration to facilitate invasion, spontaneous cell death due to genetic drift after accumulation of irreversible deleterious mutations, symmetric cancer stem cell division that increases the cancer stem cell pool, and telomere length and erosion as a mitotic counter for inherited non-stem cancer cell proliferation potential. |
Abstract | The subpopulation of cancer stem cells in itself becomes highly heterogeneous dictating population level dynamics that vary from longterm dormancy to aggressive progression. |
Author Summary | We present an in silico computational model of tumor growth and evolution according to the cancer stem cell hypothesis. |
Author Summary | Phenotypic evolution yields aggressive tumors with large heterogeneity, prompting the notion that the cancer stem cell population per se is highly heterogeneous. |
Author Summary | Within aggressive tumors cancer stem cells With low tumorigenic potential may be isolated. |
Introduction | Repopulation of the tissue is assured by tissue stem cells that sit on top of a cellular hierarchy [5,6]. |
Introduction | In a physiological setting, stem cells are predominantly non-mitotic to prevent malignant transformation [7] and only enter the mitotic cycle when tissue repopulation is required [8—10]. |
Introduction | The transit-amplifying offspring of a stem cell may undergo multiple divisions to produce a population of cells that differentiate into tissue-specific cells with determined function and lifespan. |
Author Summary | While it is generally accepted that the immune system plays a key role in HPV clearance, we investigate here a mechanism which could be equally important: the stochastic division dynamics of stem cells in the infected tissues. |
Introduction | One potential contributor in the clearing of HPV that has received little attention is chance itself, or more precisely, the stochasticity of the stem cell dynamics in the infected epithelia. |
Introduction | Several mouse studies have used fluorescent labeling to observe lineage dynamics over time, and have concluded that while 8 cell division is prominently asymmetric (yielding one 8 and one D cell), a small fraction of 8 cell divisions are symmetric, yielding either two stem cells or two differentiated daughter cells [18, 19]. |
Introduction | By explicitly accounting for the stochasticity in stem cell proliferation, as well as cytotoxic T-cell mediated elimination of infected basal cells, we investigate the potential role of chance in the viral clearing process. |
Model | Nevertheless, the bottom-up renewal dynamics (as explained below) of the affected epithelia are very similar, and the parametric model developed here can be applied to different tissue types by virtue of adjusting the relevant parameters, such as density of stem cells in the basal layer and regeneration time of the epithelium. |
Model | In addition, it has been shown that there are regulatory mechanisms for stem cell fate [19, 28], and it is conceivable that similar mechanisms prevent the total number of 8 cells to fluctuate significantly. |
Model | The underlying premise for the following replacement rules is conservation (on average) of basal stem cells . |
Abstract | The cancer stem cell hypothesis, that a small population of tumour cells are responsible for tumorigenesis and cancer progression, is becoming widely accepted and recent evidence has suggested a prognostic and predictive role for such cells. |
Abstract | Infra-tumour heterogeneity, the diversity of the cancer cell population within the tumour of an individual patient, is related to cancer stem cells and is also considered a potential prognostic indicator in oncology. |
Abstract | The measurement of cancer stem cell abundance and infra-tumour heterogeneity in a clinically relevant manner however, currently presents a challenge. |
Author Summary | The Cancer Stem Cell (CSC) hypothesis, the idea that a small population of tumour cells have the capacity to seed and grow the tumour, and intra-tumour heterogeneity, the diversity of the cancer cell population Within the tumour of an individual patient, have long been considered the basis of potential prognostic indicators in oncology. |
Introduction | Over recent years considerable evidence has arisen supporting the hypothesis that some cancers are hierarchically organised, akin to the organisation of healthy cells, with a small population of Cancer Stem Cells (CSCs) driving a heterogeneous, hierarchical structure [1, 2]. |
Introduction | Indeed, we showed that human embryonic stem cells and induced pluripotent stem cells eXhibited the highest levels of signalling entropy, with adult stem cells (e.g. |
Introduction | hematopoietic stem cells ) showing significantly lower values, and terminally differentiated cells eXhibiting the lowest entropy values within a lineage [16]. |
Rationale of signalling entropy as a prognostic measure | As shown by us previously, stem cells have a high signalling entropy which decreases during differentiation, a result not forthcoming using other molecular entropy measures [16, 28]. |
Rationale of signalling entropy as a prognostic measure | Thus, given a homogeneous cell population, a high signalling entropy suggests that signalling within each cell is very promiscuous and that the cells may therefore have a plastic stem cell like phenotype. |
The prognostic impact of signalling entropy is associated with genes involved in cancer stem cells and treatment resistance | The prognostic impact of signalling entropy is associated with genes involved in cancer stem cells and treatment resistance |
Abstract | Identifying control strategies for biological networks is paramount for practical applications that involve reprogramming a cell’s fate, such as disease therapeutics and stem cell reprogramming. |
Author Summary | Practical applications in modern molecular and systems biology such as the search for new therapeutic targets for diseases and stem cell reprogramming have generated a great interest in controlling the internal dynamics of a cell. |
Discussion | Identifying control targets for intracellular networks is of crucial importance for practical applications such as disease treatment and stem cell reprogramming. |
Discussion | Finally, the stable motif control interventions for our case studies target only a few nodes (between one and five out of more than fifty), which matches what is expected from stem cell reprogramming experiments [1—3, 8]. |
Introduction | Practical applications such as stem cell reprogramming [1—3] and the search for new therapeutic targets for diseases [4—6] have also motivated a great interest in the general task of cell fate reprogramming, i.e., controlling the internal state of a cell so that it is driven from an initial state to a final target state (see references [7—13]). |
Introduction | In contrast, experimental work in stem cell reprogramming suggests that for biologically admissible states the number of nodes required for control is drastically lower (five or fewer genes [1—3, 8]). |
A comprehensive model of WNT/,B-catenin signaling | In addition, several other studies describe continuous autocrine canonical WNT signaling in the context of neural stem cells [50] and cancer [51, 52]. |
Author Summary | However, to control hNPC differentiation within the scope of stem cell engineering, a thorough understanding of cell fate determination and its endogenous regulation is required. |
Introduction | However, controlling NPC differentiation in stem cell engineering demands a thorough understanding of neuronal and glial cell fate determination and its endogenous regulation. |