A Mathematical Radiobiological Model (MRM) to Predict Complex DNA Damage and Cell Survival for Ionizing Particle Radiations of Varying Quality

Predicting radiobiological effects is important in different areas of basic or clinical applications using ionizing radiation (IR); for example, towards optimizing radiation protection or radiation therapy protocols. In this case, we utilized as a basis the ‘MultiScale Approach (MSA)’ model and developed an integrated mathematical radiobiological model (MRM) with several modifications and improvements. Based on this new adaptation of the MSA model, we have predicted cell-specific levels of initial complex DNA damage and cell survival for irradiation with 11Β, 12C, 14Ν, 16Ο, 20Νe, 40Αr, 28Si and 56Fe ions by using only three input parameters (particle’s LET and two cell-specific parameters: the cross sectional area of each cell nucleus and its genome size). The model-predicted survival curves are in good agreement with the experimental ones. The particle Relative Biological Effectiveness (RBE) and Oxygen Enhancement Ratio (OER) are also calculated in a very satisfactory way. The proposed integrated MRM model (within current limitations) can be a useful tool for the assessment of radiation biological damage for ions used in hadron-beam radiation therapy or radiation protection purposes

Ionizing Radiation and Complex DNA Damage: Quantifying the Radiobiological Damage Using Monte Carlo Simulations

Ionizing radiation is a common tool in medical procedures. Monte Carlo (MC) techniques are widely used when dosimetry is the matter of investigation. The scientific community has invested, over the last 20 years, a lot of effort into improving the knowledge of radiation biology. The present article aims to summarize the understanding of the field of DNA damage response (DDR) to ionizing radiation by providing an overview on MC simulation studies that try to explain several aspects of radiation biology. The need for accurate techniques for the quantification of DNA damage is crucial, as it becomes a clinical need to evaluate the outcome of various applications including both low- and high-energy radiation medical procedures. Understanding DNA repair processes would improve radiation therapy procedures. Monte Carlo simulations are a promising tool in radiobiology studies, as there are clear prospects for more advanced tools that could be used in multidisciplinary studies, in the fields of physics, medicine, biology and chemistry. Still, lot of effort is needed to evolve MC simulation tools and apply them in multiscale studies starting from small DNA segments and reaching a population of cells

Monte Carlo Simulation-Based Calculations of Complex DNA Damage for Incidents of Environmental Ionizing Radiation Exposure

In this paper, we present a useful Monte Carlo (MC)-based methodology that can be utilized to calculate the absorbed dose and the initial levels of complex DNA damage (such as double strand breaks-DSBs) in the case of an environmental ionizing radiation (IR) exposure incident (REI) i.e., a nuclear accident. Our objective is to assess the doses and complex DNA damage by isolating only one component of the total radiation released in the environment after a REI that will affect the health of the exposed individual. More specifically, the radiation emitted by radionuclide 137Cs in the ground (under the individual’s feet). We use a merging of the Monte Carlo N-Particle Transport code (MCNP) with the Monte Carlo Damage Simulation (MCDS) code. The DNA lesions have been estimated through simulations for different surface activities of a 137Cs ground-based γ radiation source. The energy spectrum of the emitted secondary electrons and the absorbed dose in typical mammalian cells have been calculated using the MCNP code, and then these data are used as an input in the MCDS code for the estimation of critical DNA damage levels and types. As a realistic application, the calculated dose is also used to assess the Excess Lifetime Cancer Risk (ELCR) for eight hypothetical individuals, living in different zones around the Chernobyl Nuclear Power Plant, exposed to different time periods at the days of the accident in 1986. We conclude that any exposition of an individual in the near zone of Chernobyl increases the risk of cancer at a moderate to high grade, connected also with the induction of complex DNA damage by radiation. Generally, our methodology has proven to be useful for assessing γ rays-induced complex DNA damage levels of the exposed population, in the case of a REI and for better understanding the long-term health effects of exposure of the population to IR

Molecular Biomarkers for Predicting Cancer Patient Radiosensitivity and Radiotoxicity in Clinical Practice

Radiotherapy (RT) is a major part of cancer treatment. The reported variability in patient response to this modality can interfere with the continuation of best-possible care, promote side effects, and lead to long-term morbidity. Tools to predict a patient’s response to radiation could be highly useful in improving therapeutic outcomes while minimizing unnecessary and toxic exposure to radiation. This study investigates the potential of using molecular biomarkers as predictors of radiosensitivity in clinical practice. We review relative studies researching the positive correlation between various molecular biomarkers and patient radiosensitivity, including DNA damage response and repair proteins, inflammation and apoptosis markers, cell cycle regulators, and other biological markers. The clinical perspectives and applicability of these biomarkers in the prediction of radiosensitivity are also critically discussed. Conclusively, we underline the dynamics of molecular biomarkers to improve the efficacy and safety of radiotherapy in clinical practice and highlight the need for further research in this field. Identification of the most prominent markers is crucial for the personalization of therapies entailing ionizing radiation