Exploration of the intercellular heterogeneity of topotecan uptake into human breast cancer cells through compartmental modelling

Cheung, S.Y. Amy; Evans, Neil D.; Chappell, Michael J.; Godfrey, K.R.; Smith, Paul J.; Errington, Rachel J.

doi:10.1016/j.mbs.2008.03.008

Cited by 20 publications

(20 citation statements)

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“…2A). The model is based on established pharmacodynamics and known effects of each of the agents [21][22][23][24][25][26][27][28][29] on the cell cycle for 10 tumor types [31][32][33][34][35][36][37][38] and for erythroblasts 39 (erythroblasts have the highest proliferative index of marrow (Fig. 2B).…”

Section: Drug Selectionmentioning

confidence: 99%

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Novel phase I study combining G1 phase, S phase, and G2/M phase cell cycle inhibitors in patients with advanced malignancies

et al. 2015

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PURPOSE:Cancer is a manifestation of aberrant cellular proliferation, and the cell cycle is one of the most successfully drugged targets in oncology. No prior study has been reported that simultaneously targets the 3 principal cell cycle phases populated by proliferating cells -G 1 , S, and G 2 /M.METHODS: Temsirolimus (G 1 inhibitor), topotecan (S inhibitor), and bortezomib (G 2 /M inhibitor) were administered in combination to patients with advanced malignancies using a 3+3 dose escalation schedule to assess the safety and establish the maximum tolerated dose (primary endpoints) of this cell cycle targeting approach. An in silico pharmacodynamic model using established effects of each of these agents on the cell cycle was used to validate the regimen and to guide the dosing regimen.RESULTS: Sixty-two subjects were enrolled. The most common adverse events and dose-limiting toxicities were cytopenias, consistent with the cell cycle targeting approach employed. All cytopenias resolved to baseline values upon holding study drug administration. The maximum tolerated dose was temsirolimus 15 mg/kg IV D1, 8, 15; topotecan 2.8 mg/m 2 IV D1, 8; and bortezomib 0.9 mg/m 2 IV D1, 4, 8, 11 of a 21-day cycle. In silico modeling suggests the regimen induces cell population shifts from G 2 /M and S phases to G 1 phase and the quiescent G 0 phase. Eighteen percent of subjects (11/62) achieved partial response (n D 2, serous ovarian and papillary thyroid) or stable disease for > 6 months (n D 9).

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Section: Drug Selectionmentioning

confidence: 99%

“…f(t) is a probability of effect based on the individual [16][17][18][19][20] or combined [21][22][23][24][25][26][27][28][29] effects of temsirolimus, topotecan, and bortezomib which have been previously described.…”

Section: Monitoring and Treatment Assessmentmentioning

confidence: 99%

Novel phase I study combining G1 phase, S phase, and G2/M phase cell cycle inhibitors in patients with advanced malignancies

et al. 2015

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“…The next step is to use the extended singlecell model in this paper to consider compartmental modelling for a population of cells and compare it to the multi-cell model described in Cheung et al [37], to determine sensitivity, model robustness and model validation. Moreover, the current kinetics model will be coupled with a dynamics model to study the response of the regulatory protein cyclin B with the presence of the anti-cancer agent TPT to assist in drug design.…”

Section: Discussionmentioning

confidence: 99%

Kinetic modelling of the role of the aldehyde dehydrogenase enzyme and the breast cancer resistance protein in drug resistance and transport

Atari

Chappell

Errington

et al. 2009

IFAC Proceedings Volumes

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Article Title: Kinetic modelling of the role of the aldehyde dehydrogenase enzyme and the breast cancer resistance protein in drug resistance and transport Year of publication: 2010Link to publication: http://www.cmpbjournal.com/home Link to published article: http://dx.doi. org/10.1016/j.cmpb.2010.06.008 Copyright statement: This is the author's version of a work that was accepted for publication in Computer Methods and Programs in Biomedicine. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Computer Methods and Programs in Biomedicine, [Vol.104, (No. Verification of the proposed model is achieved using scanning-laser microscopy data from live human breast cancer cells. Before estimating the unknown model parameters from the experimental in vitro data it is essential to determine parameter uniqueness (or otherwise) from this imposed output structure. This is formally performed as a structural identifiability analysis, which demonstrates that all of the unknown model parameters are uniquely determined by the output structure corresponding to the experiment.

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“…This approach is exemplified in Chapman et al (2003), Cheung et al (2008), Saccomani et al (2003), and Vicini and Cobelli (1999). The approach assumes that the postulated state space model has known input-output behavior, involves no model error, and that noise free data (ie model output) is available.…”

Section: Model Development: Model Identifiability and Parameter Estimmentioning

confidence: 99%

Modeling the Cardiovascular-Respiratory Control System: Data, Model Analysis, and Parameter Estimation

Batzel

Bachar

2010

Acta Biotheor

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Several key areas in modeling the cardiovascular and respiratory control systems are reviewed and examples are given which reflect the research state of the art in these areas. Attention is given to the interrelated issues of data collection, experimental design, and model application including model development and analysis. Examples are given of current clinical problems which can be examined via modeling, and important issues related to model adaptation to the clinical setting.

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Exploration of the intercellular heterogeneity of topotecan uptake into human breast cancer cells through compartmental modelling

Cited by 20 publications

References 41 publications

Novel phase I study combining G1 phase, S phase, and G2/M phase cell cycle inhibitors in patients with advanced malignancies

Novel phase I study combining G1 phase, S phase, and G2/M phase cell cycle inhibitors in patients with advanced malignancies

Kinetic modelling of the role of the aldehyde dehydrogenase enzyme and the breast cancer resistance protein in drug resistance and transport

Modeling the Cardiovascular-Respiratory Control System: Data, Model Analysis, and Parameter Estimation

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