Mechanistic Modelling of DNA Repair and Cellular Survival Following Radiation-Induced DNA Damage
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作者:
McMahon, Stephen J.
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Massachusetts Gen Hosp, Dept Radiat Oncol, 30 Fruit St, Boston, MA 02114 USA
Queens Univ Belfast, Ctr Canc Res & Cell Biol, Belfast BT9 7AE, Antrim, North IrelandMassachusetts Gen Hosp, Dept Radiat Oncol, 30 Fruit St, Boston, MA 02114 USA
McMahon, Stephen J.
[1
,2
]
Schuemann, Jan
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机构:
Massachusetts Gen Hosp, Dept Radiat Oncol, 30 Fruit St, Boston, MA 02114 USAMassachusetts Gen Hosp, Dept Radiat Oncol, 30 Fruit St, Boston, MA 02114 USA
Schuemann, Jan
[1
]
Paganetti, Harald
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Massachusetts Gen Hosp, Dept Radiat Oncol, 30 Fruit St, Boston, MA 02114 USAMassachusetts Gen Hosp, Dept Radiat Oncol, 30 Fruit St, Boston, MA 02114 USA
Paganetti, Harald
[1
]
Prise, Kevin M.
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Queens Univ Belfast, Ctr Canc Res & Cell Biol, Belfast BT9 7AE, Antrim, North IrelandMassachusetts Gen Hosp, Dept Radiat Oncol, 30 Fruit St, Boston, MA 02114 USA
Prise, Kevin M.
[2
]
机构:
[1] Massachusetts Gen Hosp, Dept Radiat Oncol, 30 Fruit St, Boston, MA 02114 USA
[2] Queens Univ Belfast, Ctr Canc Res & Cell Biol, Belfast BT9 7AE, Antrim, North Ireland
Characterising and predicting the effects of ionising radiation on cells remains challenging, with the lack of robust models of the underlying mechanism of radiation responses providing a significant limitation to the development of personalised radiotherapy. In this paper we present a mechanistic model of cellular response to radiation that incorporates the kinetics of different DNA repair processes, the spatial distribution of double strand breaks and the resulting probability and severity of misrepair. This model enables predictions to be made of a range of key biological endpoints (DNA repair kinetics, chromosome aberration and mutation formation, survival) across a range of cell types based on a set of 11 mechanistic fitting parameters that are common across all cells. Applying this model to cellular survival showed its capacity to stratify the radiosensitivity of cells based on aspects of their phenotype and experimental conditions such as cell cycle phase and plating delay (correlation between modelled and observed Mean Inactivation Doses R-2 > 0.9). By explicitly incorporating underlying mechanistic factors, this model can integrate knowledge from a wide range of biological studies to provide robust predictions and may act as a foundation for future calculations of individualised radiosensitivity.