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Towards Predicting the Response of a Solid Tumour to Chemotherapy and Radiotherapy Treatments: Clinical Insights from a Computational Model

Overview of attention for article published in PLoS Computational Biology, July 2013
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Title
Towards Predicting the Response of a Solid Tumour to Chemotherapy and Radiotherapy Treatments: Clinical Insights from a Computational Model
Published in
PLoS Computational Biology, July 2013
DOI 10.1371/journal.pcbi.1003120
Pubmed ID
Authors

Gibin G. Powathil, Douglas J. A. Adamson, Mark A. J. Chaplain

Abstract

In this paper we use a hybrid multiscale mathematical model that incorporates both individual cell behaviour through the cell-cycle and the effects of the changing microenvironment through oxygen dynamics to study the multiple effects of radiation therapy. The oxygenation status of the cells is considered as one of the important prognostic markers for determining radiation therapy, as hypoxic cells are less radiosensitive. Another factor that critically affects radiation sensitivity is cell-cycle regulation. The effects of radiation therapy are included in the model using a modified linear quadratic model for the radiation damage, incorporating the effects of hypoxia and cell-cycle in determining the cell-cycle phase-specific radiosensitivity. Furthermore, after irradiation, an individual cell's cell-cycle dynamics are intrinsically modified through the activation of pathways responsible for repair mechanisms, often resulting in a delay/arrest in the cell-cycle. The model is then used to study various combinations of multiple doses of cell-cycle dependent chemotherapies and radiation therapy, as radiation may work better by the partial synchronisation of cells in the most radiosensitive phase of the cell-cycle. Moreover, using this multi-scale model, we investigate the optimum sequencing and scheduling of these multi-modality treatments, and the impact of internal and external heterogeneity on the spatio-temporal patterning of the distribution of tumour cells and their response to different treatment schedules.

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Geographical breakdown

Country Count As %
United Kingdom 2 2%
Italy 1 1%
Germany 1 1%
Spain 1 1%
United States 1 1%
Unknown 89 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 28 29%
Researcher 20 21%
Student > Master 7 7%
Student > Doctoral Student 5 5%
Student > Bachelor 4 4%
Other 16 17%
Unknown 15 16%
Readers by discipline Count As %
Mathematics 21 22%
Medicine and Dentistry 12 13%
Engineering 9 9%
Physics and Astronomy 8 8%
Computer Science 7 7%
Other 21 22%
Unknown 17 18%