Evolutionary dynamics of feedback escape and the development of stem-cell–driven cancers

Abstract

Cancers are thought to arise in tissue stem cells, and similar to healthy tissue, are thought to be maintained by a small population of tumor stem or initiating cells, whereas the majority of tumor cells are more differentiated with limited replicative potential. Healthy tissue homeostasis is achieved by feedback loops, and particular importance has been attached to signals secreted from differentiated cells that inhibit stem-cell division and stem-cell self-renewal, as documented in the olfactory epithelium and other tissues. Therefore, a key event in carcinogenesis must be escape from these feedback loops, which is studied here using evolutionary computational models. We find that out of all potential evolutionary pathways, only one unique sequence of phenotypic transitions can lead to complete escape in stem-cell–driven tumors, even though the required mutations for these transitions are certainly tissue specific. This insight, supported by data, facilitates the search for driver mutations and for therapeutic targets. Different growth patterns can result from feedback escape, which we call “inhibited,” “uninhibited,” and “sigmoidal,” and which are found in published data. The finding of inhibited growth patterns in data indicates that besides architecture, the regulatory mechanisms of healthy tissue continue to operate to a degree in tumors.

An agent-based model of cancer stem cell initiated avascular tumour growth and metastasis: the effect of seeding frequency and location

“…Angiogenesis is an important stage in tumour growth in which the tumour releases growth factors to recruit vasculature to the tumour site and allows for the expansion of tumour; it is beyond the scope of this manuscript, but will be included in further research. Another simplification is that we do not include clonal evolution of stem and progenitor cells as has been done in other works [27,28,89,90]. While this is an important aspect of cancer, it is not the focus of the manuscript.…”

Minimizing the risk of cancer: tissue architecture and cellular replication limits

“…Thus, if one wishes to examine certain dynamic properties, such as tissue regeneration after an injury, then it is necessary to impose control mechanisms that guarantee the stability of the system. In practice, this means that the division rates (r and v j ) and self-renewal probabilities ( p s and p j ) may be functions that take on different values depending on the state of the system [20][21][22][23][24]. In the case of an injury, the selfrenewal probabilities and division rates might temporarily increase to ensure a faster recovery [22], leading to an increased number of divisions per unit of time.…”

“…We begin by introducing a variant of a widely proposed model of cell dynamics within a cell lineage [20][21][22][23][24][25]. In this model (figure 1), the starting point of the lineage is stem cells S. Downstream from the stem cell population, one finds a series of intermediate cell types often referred to in the literature as progenitor cells or transit-amplifying cells (here named X 0 , .…”

Cancer-Associated Mutations in Healthy Individuals: Assessing the Risk of Carcinogenesis

“…This approach requires the introduction of feedback mechanisms to ensure homeostasis (36)(37)(38). One such mechanism operates through the secretion of negative feedback factors by differentiated cells, which inhibit division and self-renewal in stem cells and progenitors (39).…”