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Dynamic Rendering of the Heterogeneous Cell Response to Anticancer Treatments

Overview of attention for article published in PLoS Computational Biology, October 2013
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Title
Dynamic Rendering of the Heterogeneous Cell Response to Anticancer Treatments
Published in
PLoS Computational Biology, October 2013
DOI 10.1371/journal.pcbi.1003293
Pubmed ID
Authors

Francesca Falcetta, Monica Lupi, Valentina Colombo, Paolo Ubezio

Abstract

The antiproliferative response to anticancer treatment is the result of concurrent responses in all cell cycle phases, extending over several cell generations, whose complexity is not captured by current methods. In the proposed experimental/computational approach, the contemporary use of time-lapse live cell microscopy and flow cytometric data supported the computer rendering of the proliferative process through the cell cycle and subsequent generations during/after treatment. The effects of treatments were modelled with modules describing the functional activity of the main pathways causing arrest, repair and cell death in each phase. A framework modelling environment was created, enabling us to apply different types of modules in each phase and test models at the complexity level justified by the available data. We challenged the method with time-course measures taken in parallel with flow cytometry and time-lapse live cell microscopy in X-ray-treated human ovarian cancer cells, spanning a wide range of doses. The most suitable model of the treatment, including the dose-response of each effect, was progressively built, combining modules with a rational strategy and fitting simultaneously all data of different doses and platforms. The final model gave for the first time the complete rendering in silico of the cycling process following X-ray exposure, providing separate and quantitative measures of the dose-dependence of G1, S and G2M checkpoint activities in subsequent generations, reconciling known effects of ionizing radiations and new insights in a unique scenario.

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The data shown below were compiled from readership statistics for 26 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 4%
Unknown 25 96%

Demographic breakdown

Readers by professional status Count As %
Researcher 6 23%
Student > Bachelor 4 15%
Professor > Associate Professor 3 12%
Student > Ph. D. Student 3 12%
Student > Doctoral Student 2 8%
Other 4 15%
Unknown 4 15%
Readers by discipline Count As %
Agricultural and Biological Sciences 7 27%
Biochemistry, Genetics and Molecular Biology 4 15%
Medicine and Dentistry 4 15%
Computer Science 2 8%
Engineering 2 8%
Other 2 8%
Unknown 5 19%