Our understanding of radiation-induced cellular damage has greatly improved over the past few decades. Despite this progress, there are still many obstacles to fully understand how radiation interacts with biologically relevant cellular components, such as DNA, to cause observable end points such as cell killing. Damage in DNA is identified as a major route of cell killing. One hurdle when modeling biological effects is the difficulty in directly comparing results generated by members of different research groups. Multiple Monte Carlo codes have been developed to simulate damage induction at the DNA scale, while at the same time various groups have developed models that describe DNA repair processes with varying levels of detail. These repair models are intrinsically linked to the damage model employed in their development, making it difficult to disentangle systematic effects in either part of the modeling chain. These modeling chains typically consist of track-structure Monte Carlo simulations of the physical interactions creating direct damages to DNA, followed by simulations of the production and initial reactions of chemical species causing so-called “indirect” damages. After the induction of DNA damage, DNA repair models combine the simulated damage patterns with biological models to determine the biological consequences of the damage. To date, the effect of the environment, such as molecular oxygen (normoxic vs. hypoxic), has been poorly considered. We propose a new standard DNA damage (SDD) data format to unify the interface between the simulation of damage induction in DNA and the biological modeling of DNA repair processes, and introduce the effect of the environment (molecular oxygen or other compounds) as a flexible parameter. Such a standard greatly facilitates inter-model comparisons, providing an ideal environment to tease out model assumptions and identify persistent, underlying mechanisms. Through inter-model comparisons, this unified standard has the potential to greatly advance our understanding of the underlying mechanisms of radiation-induced DNA damage and the resulting observable biological effects when radiation parameters and/or environmental conditions change.

Stewart, R. D., Ratnayake, R. K. and Jennings, K. Microdosimetric Model for the Induction of Cell Killing through Medium-Borne Signals. Radiat. Res. 165, 460–469 (2006). Microbeam, medium-transfer and low-dose experiments have demonstrated that intercellular signals can initiate many of the same biological events and processes as direct exposure to ionizing radiation. These phenomena cast doubt on cell-autonomous modes of action and the linear, no-threshold carcinogenesis paradigm. To account for the effects of intercellular signals, new approaches are needed to relate dosimetric quantities to the emission and processing of signals by irradiated and unirradiated cells. In this paper, microdosimetric principles are used to develop a stochastic model to relate absorbed dose to the emission and processing of cell death signals by unirradiated cells. Our analyses of published results of medium transfer experiments performed using HPV-G human keratinocytes suggest that the emission of death signals is a bi-exponential function of dose with a distinct plateau in the 5- to 100-mGy range. However, the emission of death signals by HPV-G cells may not become fully saturated until the absorbed dose becomes larger than 0.6 Gy. Similar saturation effects have been observed in microbeam and medium-transfer experiments with other mammalian cell lines. The model predicts that the cell-killing effect of medium-borne death signals decreases exponentially as the absorbed dose becomes small compared to the frequency-mean specific energy per radiation event.

Semenenko, V. A., Stewart, R. D. and Ackerman, E. J. Monte Carlo Simulation of Base and Nucleotide Excision Repair of Clustered DNA Damage Sites. I. Model Properties and Predicted Trends. Radiat. Res. 164, 180–193 (2005). DNA is constantly damaged through endogenous processes and by exogenous agents, such as ionizing radiation. Base excision repair (BER) and nucleotide excision repair (NER) help maintain the stability of the genome by removing many different types of DNA damage. We present a Monte Carlo excision repair (MCER) model that simulates key steps in the short-patch and long-patch BER pathways and the NER pathway. The repair of both single and clustered damages, except double-strand breaks (DSBs), is simulated in the MCER model. Output from the model includes estimates of the probability that a cluster is repaired correctly, the fraction of the clusters converted into DSBs through the action of excision repair enzymes, the fraction of the clusters repaired with mutations, and the expected number of repair cycles needed to completely remove a clustered damage site. The quantitative implications of alternative hypotheses regarding the postulated repair mechanisms are investigated through a series of parameter sensitivity studies. These sensitivity studies are also used to help define the putative repair characteristics of clustered damage sites other than DSBs.

Semenenko, V. A. and Stewart, R. D. Monte Carlo Simulation of Base and Nucleotide Excision Repair of Clustered DNA Damage Sites. II. Comparisons of Model Predictions to Measured Data. Radiat. Res. 164, 194–201 (2005). Clustered damage sites other than double-strand breaks (DSBs) have the potential to contribute to deleterious effects of ionizing radiation, such as cell killing and mutagenesis. In the companion article (Semenenko et al., Radiat. Res. 164, 180–193, 2005), a general Monte Carlo framework to simulate key steps in the base and nucleotide excision repair of DNA damage other than DSBs is proposed. In this article, model predictions are compared to measured data for selected low-and high-LET radiations. The Monte Carlo model reproduces experimental observations for the formation of enzymatic DSBs in Escherichia coli and cells of two Chinese hamster cell lines (V79 and xrs5). Comparisons of model predictions with experimental values for low-LET radiation suggest that an inhibition of DNA backbone incision at the sites of base damage by opposing strand breaks is active over longer distances between the damaged base and the strand break in hamster cells (8 bp) compared to E. coli (3 bp). Model estimates for the induction of point mutations in the human hypoxanthine guanine phosphoribosyl transferase ( HPRT ) gene by ionizing radiation are of the same order of magnitude as the measured mutation frequencies. Trends in the mutation frequency for low- and high-LET radiation are predicted correctly by the model. The agreement between selected experimental data sets and simulation results provides some confidence in postulated mechanisms for excision repair of DNA damage other than DSBs and suggests that the proposed Monte Carlo scheme is useful for predicting repair outcomes.

Semenenko, V. A. and Stewart, R. D. A Fast Monte Carlo Algorithm to Simulate the Spectrum of DNA Damages Formed by Ionizing Radiation. Radiat. Res. 161, 451–457 (2004). Ionizing radiation produces both singly and multiply damaged DNA sites. Multiply damaged sites (MDS) have been implicated in radiation-induced cell killing and mutagenesis. The spatial distribution of elementary damages (strand breaks and base damages) that constitute MDS is of special interest, since the complexity of MDS has an impact on damage repair. A fast and easy-to-implement algorithm to simulate the local clustering of elementary damages produced by ionizing radiation is proposed. This algorithm captures the major trends in the DNA damage spectrum predicted using detailed track- structure simulations. An attractive feature of the proposed algorithm is that only four adjustable parameters need to be identified to simulate the formation of DNA damage. A convenient recipe to determine the parameters used in the fast Monte Carlo damage simulation algorithm is provided for selected low- and high-LET radiations. The good agreement among the damage yields predicted by the fast and detailed damage formation algorithms suggests that the small-scale spatial distribution of damage sites is determined primarily by independent and purely stochastic events and processes.

Stewart, R. D. Two-Lesion Kinetic Model of Double-Strand Break Rejoining and Cell Killing. Radiat. Res. 156, 365–378 (2001). Radiobiological models, such as the lethal and potentially lethal (LPL) model and the repair-misrepair (RMR) model, have been reasonably successful at explaining the cell killing effects of radiation. However, the models have been less successful at relating cell killing to the formation, repair and misrepair of double-strand breaks (DSBs), which are widely accepted as the main type of DNA damage responsible for radiation-induced cell killing. A fully satisfactory model should be capable of predicting cell killing for a wide range of exposure conditions using a single set of model parameters. Moreover, these same parameters should give realistic estimates for the initial DSB yield, the DSB rejoining rate, and the residual number of unrepaired DSBs after all repair is complete. To better link biochemical processing of the DSB to cell killing, a two-lesion kinetic (TLK) model is proposed. In the TLK model, the family of all possible DSBs is subdivided into simple and complex DSBs, and each kind of DSB may have its own repair characteristics. A unique aspect of the TLK model is that break ends associated with both kinds of DSBs are allowed to interact in pairwise fashion to form irreversible lethal and nonlethal damages. To test the performance of the TLK model, nonlinear optimization methods are used to calibrate the model based on data for the survival of CHO cells for an extensive set of single-dose and split-dose exposure conditions. Then some of the postulated mechanisms of action are tested by comparing measured and predicted estimates of the initial DSB yield and the rate of DSB rejoining. The predictions of the TLK model for CHO cell survival and the initial DSB yield and rejoining rate are all shown to be in good agreement with the measured data. Studies suggest a yield of about 25 DSBs Gy −1 cell −1 . About 20 DSBs Gy −1 cell −1 are rejoined quickly (15-min repair half-time), and 4 to 6 DSBs Gy −1 cell −1 are rejoined very slowly (10- to 15-h repair half-time). Both the slowly and fast-rejoining DSBs make substantial contributions to the killing of CHO cells by radiation. Although the TLK model provides a much more satisfactory formalism to relate biochemical processing of DSBs to cell killing than did the earlier kinetic models, some small differences among the measured and predicted CHO cell survival and DSB rejoining data suggest that additional factors and processes not considered in the present work may affect biochemical processing of DSBs and hence cell killing.