Sinusoidal swinging dynamics of the telomere repair and cell growth activation functions of telomerase in rat liver cancer cells

Wolfrom, C.; Martin, O. C.; Laurent, Michel; Deschatrette, Jean

doi:10.1016/j.febslet.2006.12.007

Cited by 3 publications

(3 citation statements)

References 29 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, further mathematical studies are required to determine 1) why this convergence of the bisecting lines occurs in chaotic settings, and 2) the statistical limitations of the sampling in this analytical approach. From a practical point of view, knowledge of underlying chaotic dynamics is critical to the analysis of various mammalian cell functions related to proliferation rate, including metabolic pathway activity, telomere homeostasis [28], [29], and gene expression [13]. It is also of use in appraisal of tumor growth rate and prediction of anticancer drug efficiency [30], [31].…”

Section: Discussionmentioning

confidence: 99%

Unmasking Chaotic Attributes in Time Series of Living Cell Populations

2010

Self Cite

View full text Add to dashboard Cite

BackgroundLong-range oscillations of the mammalian cell proliferation rate are commonly observed both in vivo and in vitro. 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.Methodology/Principal FindingsUsing 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.Conclusion/SignificanceTheoretical 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.

show abstract

Section: Discussionmentioning

confidence: 99%

Unmasking Chaotic Attributes in Time Series of Living Cell Populations

2010

Self Cite

View full text Add to dashboard Cite

show abstract

“…Interestingly, control values were also modified time dependently, cyclin B being diminished, p21 enhanced after 5 days, compared to the 3‐day values. Possibly, periodic alterations of p21 and cyclin B levels take place, which may account for the persistent proliferation of cancer cells [27]. If this is the case, the effects of VPA might be due to its dampening this oscillatory behaviour, returning the cells to normal dissipative dynamics.…”

Section: Discussionmentioning

confidence: 99%

The histone deacetylase inhibitor valproic acid alters growth properties of renal cell carcinoma in vitro and in vivo

Jones

Juengel

Mickuckyte

et al. 2008

J Cellular Molecular Medi

View full text Add to dashboard Cite

Histone deacetylase (HDAC) inhibitors represent a promising class of antineoplastic agents which affect tumour growth, differentiation and invasion. The effects of the HDAC inhibitor valproic acid (VPA) were tested in vitro and in vivo on pre‐clinical renal cell carcinoma (RCC) models. Caki‐1, KTC‐26 or A498 cells were treated with various concentrations of VPA during in vitro cell proliferation 3‐(4,5‐dimethylthiazol‐2‐yl)‐2,5‐diphenyltetrazolium bromide assays and to evaluate cell cycle manipulation. In vivo tumour growth was conducted in subcutaneous xenograft mouse models. The anti‐tumoural potential of VPA combined with low‐dosed interferon‐α (IFN‐α) was also investigated. VPA significantly and dose‐dependently up‐regulated histones H3 and H4 acetylation and caused growth arrest in RCC cells. VPA altered cell cycle regulating proteins, in particular CDK2, cyclin B, cyclin D3, p21 and Rb. In vivo, VPA significantly inhibited the growth of Caki‐1 in subcutaneous xenografts, accompanied by a strong accumulation of p21 and bax in tissue specimens of VPA‐treated animals. VPA–IFN‐α combination markedly enhanced the effects of VPA monotherapy on RCC proliferation in vitro, but did not further enhance the anti‐tumoural potential of VPA in vivo. VPA was found to have profound effects on RCC cell growth, lending support to the initiation of clinical testing of VPA for treating advanced RCC.

show abstract

“…The rationale for the choice of the “Cell” oscillator was as follows: i ) a two-well oscillator was selected because our previous work on chaotic-like oscillations of tumor and progenitor cell proliferation, in vitro and in vivo , had shown a balance between high/low fixed points [43]–[45]; and ii ) the level of complexity of the oscillator required at least three linked variables to reflect interplay between three critical and complex mechanisms which control a cell population: cell death, which varies greatly in some tumors [46]–[48], cell proliferation which fluctuates, and genetic status, including telomere repair [19], [43] and gene expression, which displays oscillations [48], [49]. The three-variable Lorenz oscillator was adapted to these constraints, and was used to illustrate the “Cell” oscillator (Figure 1A), which was written thus: …”

Section: Model and Methodsmentioning

confidence: 99%

Can We Negotiate with a Tumor?

2014

Self Cite

View full text Add to dashboard Cite

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.

show abstract

Sinusoidal swinging dynamics of the telomere repair and cell growth activation functions of telomerase in rat liver cancer cells

Cited by 3 publications

References 29 publications

Unmasking Chaotic Attributes in Time Series of Living Cell Populations

Unmasking Chaotic Attributes in Time Series of Living Cell Populations

The histone deacetylase inhibitor valproic acid alters growth properties of renal cell carcinoma in vitro and in vivo

Can We Negotiate with a Tumor?

Contact Info

Product

Resources

About