Seventy Years of Dose-response Models: From the Target Theory to the Use of Big Databases Involving Cell Survival and DNA Repair.

Abstract

Radiobiological data, whether obtained at the clinical, biological or molecular level has significantly contributed to a better description and prediction of the individual dose-response to ionizing radiation and a better estimation of the radiation-induced risks. Particularly, over the last seventy years, the amount of radiobiological data has considerably increased, and permitted the mathematical formulas describing dose-response to become less empirical. A better understanding of the basic radiobiological mechanisms has also contributed to establish quantitative inter-correlations between clinical, biological and molecular biomarkers, refining again the mathematical models of description. Today, big data approaches and, more recently, artificial intelligence may finally complete and secure this long process of thinking from the multi-scale description of radiation-induced events to their prediction. Here, we reviewed the major dose-response models applied in radiobiology for quantifying molecular and cellular radiosensitivity and aimed to explain their evolution: Specifically, we highlighted the advances concerning the target theory with the cell survival models and the progressive introduction of the DNA repair process in the mathematical models. Furthermore, we described how the technological advances have changed the description of DNA double-strand break (DSB) repair kinetics by introducing the important notion of DSB recognition, independent of that of DSB repair. Initially developed separately, target theory on one hand and, DSB recognition and repair, on the other hand may be now fused into a unified model involving the cascade of phosphorylations mediated by the ATM kinase in response to any genotoxic stress.