Unmasking Chaotic Attributes in Time Series of Living Cell Populations

. Such complicated dynamics are generally the result of a combination of stochastic events and deterministic regulation. Assessing the role, if any, of chaotic regulation is difficult. However, unmasking chaotic dynamics is essential for analysis of cellular processes related to proliferation rate, including metabolic activity, telomere homeostasis, gene expression, and tumor growth.Using a simple, original, nonlinear method based on return maps, we previously found a geometrical deterministic structure coordinating such fluctuations in populations of various cell types. However, nonlinearity and determinism are only necessary conditions for chaos; they do not by themselves constitute a proof of chaotic dynamics. Therefore, we used the same analytical method to analyze the oscillations of four well-known, low-dimensional, chaotic oscillators, originally designed in diverse settings and all possibly well-adapted to model the fluctuations of cell populations: the Lorenz, Rössler, Verhulst and Duffing oscillators. All four systems also display this geometrical structure, coordinating the oscillations of one or two variables of the oscillator. No such structure could be observed in periodic or stochastic fluctuations.Theoretical models predict various cell population dynamics, from stable through periodically oscillating to a chaotic regime. Periodic and stochastic fluctuations were first described long ago in various mammalian cells, but by contrast, chaotic regulation had not previously been evidenced. The findings with our nonlinear geometrical approach are entirely consistent with the notion that fluctuations of cell populations can be chaotically controlled

Hepatocyte Nuclear Factor 4 Provokes Expression of Epithelial Marker Genes, Acting As a Morphogen in Dedifferentiated Hepatoma Cells

Abstract. We have recently shown that stable expression of an epitope-tagged cDNA of the hepatocyte- enriched transcription factor, hepatocyte nuclear factor (HNF)4, in dedifferentiated rat hepatoma H5 cells is sufficient to provoke reexpression of a set of hepatocyte marker genes. Here, we demonstrate that the effects of HNF4 expression extend to the reestablishment of differentiated epithelial cell morphology and simple epithelial polarity. The acquisition of epithelial morphology occurs in two steps. First, expression of HNF4 results in reexpression of cytokeratin proteins and partial reestablishment of E-cadherin production. Only the transfectants are competent to respond to the synthetic glucocorticoid dexamethasone, which induces the second step of morphogenesis, including formation of the junctional complex and expression of a polarized cell phenotype. Cell fusion experiments revealed that the transfectant cells, which show only partial restoration of E-cadherin expression, produce an extinguisher that is capable of acting in trans to downregulate the E-cadherin gene of well-differentiated hepatoma cells. Bypass of this repression by stable expression of E-cadherin in H5 cells is sufficient to establish some epithelial cell characteristics, implying that the morphogenic potential of HNF4 in hepatic cells acts via activation of the E-cadherin gene. Thus, HNF4 seems to integrate the genetic programs of liver-specific gene expression and epithelial morphogenesis

Can we negotiate with a tumor?

Recent progress in deciphering the molecular portraits of tumors promises an era of more personalized drug choices. However, current protocols still follow standard fixed-time schedules, which is not entirely coherent with the common observation that most tumors do not grow continuously. This unpredictability of the increases in tumor mass is not necessarily an obstacle to therapeutic efficiency, particularly if tumor dynamics could be exploited. We propose a model of tumor mass evolution as the integrated result of the dynamics of two linked complex systems, tumor cell population and tumor microenvironment, and show the practical relevance of this nonlinear approach