Cell Cycle Phase-Specific CHemotherapy: Computation Methods for Guiding Treatment

Gardner, Shea N.

doi:10.4161/cc.1.6.258

Cited by 29 publications

(21 citation statements)

References 48 publications

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“…Other authors designed specific models of the anticancer therapy (13,14), some theoretical, others oriented to fit data, and some including a modelization of cell proliferation through the cell cycle.…”

Section: Discussionmentioning

confidence: 99%

Quantitative Assessment of the Complex Dynamics of G1, S, and G2-M Checkpoint Activities

et al. 2009

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Although studies of cell cycle perturbation and growth inhibition are common practice, they are unable to properly measure the activity of cell cycle checkpoints and frequently convey misinterpretation or incomplete pictures of the response to anticancer treatment. A measure of the strength of the treatment response of all checkpoints, with their time and dose dependence, provides a new way to evaluate the antiproliferative activity of the drugs, fully accounting for variation of the cell fates within a cancer cell line. This is achieved with an interdisciplinary approach, joining information from independent experimental platforms and interpreting all data univocally with a simple mathematical model of cell cycle proliferation. The model connects the dynamics of checkpoint activities at the molecular level with populationbased flow cytometric and growth inhibition time course measures. With this method, the response to five drugs, characterized by different molecular mechanisms of action, was studied in a synoptic way, producing a publicly available database of time course measures with different techniques in a range of drug concentrations, from sublethal to frankly cytotoxic. Using the computer simulation program, we were able to closely reproduce all the measures in the experimental database by building for each drug a scenario of the time and dose dependence of G 1 , S, and G 2 -M checkpoint activities. We showed that the response to each drug could be described as a combination of a few types of activities, each with its own strength and concentration threshold. The results gained from this method provide a means for exploring new concepts regarding the drug-cell cycle interaction. [Cancer Res 2009;69(12):5234-40]

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Section: Discussionmentioning

confidence: 99%

Quantitative Assessment of the Complex Dynamics of G1, S, and G2-M Checkpoint Activities

et al. 2009

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“…only when the cell is in a (set) of specific phases of its cycle [5]. Moreover, the distribution of phases over a given population of tumor cells is unlikely to be uniform, that is to say, the phase-in-the-cycle is an individual component of each cell's current state description.…”

Section: Introductionmentioning

confidence: 99%

“…an efficiency greater than the additive ones), by targeting different processes in the cell cycle, see [12]. The evolution of the cell cycle-mediated drug resistance, or kinetics resistance, has been addressed by means of mathematical and computational models, summarized in [5], employed also for control-based therapeutic design, see [14], [9]. While some therapy agents are able to kill a cell during all the phases of its cycle, cell-cycle specific agents are efficient This work was not supported by any organization M. Alamir and M. Fiacchini are with CNRS, Gipsa-lab, Control System Department, University of Grenoble Alpes.…”

Section: Introductionmentioning

confidence: 99%

Observer-based efficiency enhancement in cell-cycle specific therapies

Alamir

Fiacchini

2016

2016 IEEE 55th Conference on Decision and Control (CDC)

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Abstract-Cell-cycle specific drugs affect cells when they are in specific phases of their periodic cycle. However, injecting drug's strategy can only by global. This rises the problem of optimizing a global constrained decision variable (drug delivery profile with limited volume) when its effect depends on many local unknown characteristics (the individual cells phases). In this paper, an observer-based framework is proposed that enables a rational decision making in this particular circumstance. Simulation on a simple case are proposed to show the relevance of the proposed framework.

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“…A number of reports have also suggested that cell cycle control points, such as the G 1 /S and G 2 /M transitions, are potential targets for chemoprevention and cancer treatment in humans (3)(4)(5).…”

Section: Introductionmentioning

confidence: 99%

Equol induced apoptosis via cell cycle arrest in human breast cancer MDA-MB-453 but not MCF-7 cells

Choi

Kim²

2008

Mol Med Report

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Abstract.To investigate the effects of equol on cell cycle distribution and apoptosis in human breast cancer cells, we first determined the antiproliferative effects of various concentrations of equol (1 nM to 100 μM) on MCF-7 and MDA-MB-453 cells at 24, 48 or 72 h of exposure. Equol significantly inhibited proliferation in MDA-MB-453 cells in a dose-and time-dependent manner. In contrast, equol at low concentrations (<1 μM) stimulated proliferation in MCF-7 cells, with increased expression of proliferating cell nuclear antigen (PCNA), and only inhibited proliferation at a high concentration (100 μM). Similarly, equol treatment of MDA-MB-453 cells resulted in significant cell cycle arrest at the G 1 /S transition and in the G 2 /M phase, whereas it caused the slight cell cycle arrest of MCF-7 cells in the G 2 /M phase after 72 h of treatment. Also, when cells were treated with 50 and 100 μM equol for 72 h, the equol affected cell cycle regulatory proteins more significantly in MDA-MB-453 than in MCF-7 cells. During equol-induced apoptosis, equol increased the number of cells in the sub-G 0 phase and enhanced the level of p53. The expression of Bax and cytochrome c, downstream targets of p53, was markedly increased by treatment with higher concentrations of equol. Equol-induced cell cycle arrest and apoptosis apparently involves a p53-dependent pathway in different types of breast cancer cells.

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Cell Cycle Phase-Specific CHemotherapy: Computation Methods for Guiding Treatment

Cited by 29 publications

References 48 publications

Quantitative Assessment of the Complex Dynamics of G1, S, and G2-M Checkpoint Activities

Quantitative Assessment of the Complex Dynamics of G1, S, and G2-M Checkpoint Activities

Observer-based efficiency enhancement in cell-cycle specific therapies

Equol induced apoptosis via cell cycle arrest in human breast cancer MDA-MB-453 but not MCF-7 cells

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