Dynamic DNA Damage and Repair Modeling: Bridging the Gap Between Experimental Damage Readout and Model Structure

Weyland, Mathias S.; Thumser-Henner, Pauline; Bley, Carla Rohrer; Ulzega, Simone; Petri‐Fink, Alke; Lattuada, Marco; Scheidegger, Stephan; Füchslin, Rudolf Marcel

doi:10.1007/978-3-030-21733-4_10

Cited by 1 publication

(14 citation statements)

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“…The full set of equations is given in the supplementary materials; a summary of the model parameters is presented in Table 1. See [12,26,27] for the derivation, validation, and further discussion of the MHR model. For hyperthermia, the two variables Y and Λ are introduced to track the state of active (Y) and inactive (Λ) repair proteins.…”

Section: The Multi-hit-repair Modelmentioning

confidence: 99%

“…The rate at which inactive repair protein is reactivated, k 2 , is assumed to be constant in prior research [12,26,27,30] and throughout this work. While the reactivation may be temperature-dependent, the authors are unaware of any research supporting that hypothesis, thus, following the principle of assuming simple circumstances whenever possible and, k 2 is not a function of temperature.…”

Section: The Multi-hit-repair Modelmentioning

confidence: 99%

“…The mapping to comet data is somewhat more elaborate and was introduced in [27]: The comet readout at a given point in time consists of the quantification of DNA damage in a number of (typically m = 100) cells. Depending on the amount of DNA damage, each cell is assigned to a bin h i : the first bin h 0 tracks the cells with little to no damage and the second bin h 1 tracks cells with more damage, etc.…”

Section: Model/readoutmentioning

confidence: 99%

“…The correct mapping between physical DNA damage as reported by the comet assay and the model populations H i presumes knowledge about how much physical DNA damage constitutes one hit. In other words, the relative tail intensities quantifying DNA damage must be scaled prior to the mapping to H i to maintain the semantics implied by the MHR model (i.e., the Figure 3: High-level illustration of the MHR model [27]. The boxes depict the chain structure with the populations H i ; the arrows denote how cells accumulate hits (to the right), undergo cell death (to the top), or undergo repair (to the left).…”

Section: Model/readoutmentioning

confidence: 99%

“…From the damage metrics offered by the software, the relative tail intensity (RTI) was chosen because it provides a linear relationship between the number of DNA strand breaks and the quantified damage [31,32]-a property highly desired for the data-mapping introduced in Section 2.5. The resulting data was used in a previous publication [27].…”

mentioning

confidence: 99%

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Holistic View on Cell Survival and DNA Damage: How Model-Based Data Analysis Supports Exploration of Dynamics in Biological Systems

Weyland

Thumser-Henner

Nytko

et al. 2020

Computational and Mathematical Methods in Medicine

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In this work, a method is established to calibrate a model that describes the basic dynamics of DNA damage and repair. The model can be used to extend planning for radiotherapy and hyperthermia in order to include the biological effects. In contrast to “syntactic” models (e.g., describing molecular kinetics), the model used here describes radiobiological semantics, resulting in a more powerful model but also in a far more challenging calibration. Model calibration is attempted from clonogenic assay data (doses of 0–6 Gy) and from time-resolved comet assay data obtained within 6 h after irradiation with 6 Gy. It is demonstrated that either of those two sources of information alone is insufficient for successful model calibration, and that both sources of information combined in a holistic approach are necessary to find viable model parameters. Approximate Bayesian computation (ABC) with simulated annealing is used for parameter search, revealing two aspects that are beneficial to resolving the calibration problem: (1) assessing posterior parameter distributions instead of point-estimates and (2) combining calibration runs from different assays by joining posterior distributions instead of running a single calibration run with a combined, computationally very expensive objective function.

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Section: The Multi-hit-repair Modelmentioning

confidence: 99%