AI Article Synopsis
- The study extends a Geant4-DNA radiobiological application to predict DNA rejoining kinetics and cell survival fractions following radiation exposure in Chinese hamster V79 cells, a key model in radiobiology.
- The research utilizes the Two-Lesion Kinetics (TLK) model to estimate residual DNA damage and survival rates, using initial DNA damage complexity as a critical input.
- This is the first research to integrate cell survival and DNA repair kinetics in a detailed Monte Carlo simulation, linking physical damage processes to biological outcomes for varying radiation energy levels.
Article Abstract
Purpose: Track structure Monte Carlo (MC) codes have achieved successful outcomes in the quantitative investigation of radiation-induced initial DNA damage. The aim of the present study is to extend a Geant4-DNA radiobiological application by incorporating a feature allowing for the prediction of DNA rejoining kinetics and corresponding cell surviving fraction along time after irradiation, for a Chinese hamster V79 cell line, which is one of the most popular and widely investigated cell lines in radiobiology.
Methods: We implemented the Two-Lesion Kinetics (TLK) model, originally proposed by Stewart, which allows for simulations to calculate residual DNA damage and surviving fraction along time via the number of initial DNA damage and its complexity as inputs.
Results: By optimizing the model parameters of the TLK model in accordance to the experimental data on V79, we were able to predict both DNA rejoining kinetics at low linear energy transfers (LET) and cell surviving fraction.
Conclusion: This is the first study to demonstrate the implementation of both the cell surviving fraction and the DNA rejoining kinetics with the estimated initial DNA damage, in a realistic cell geometrical model simulated by full track structure MC simulations at DNA level and for various LET. These simulation and model make the link between mechanistic physical/chemical damage processes and these two specific biological endpoints.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11221566 | PMC |
| http://dx.doi.org/10.1016/j.ejmp.2022.11.012 | DOI Listing |
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