During the last decade, a large number of experimental studies oil the so-called "non-targeted effects", in particular bystander effects, outlined that cellular communication plays a significant role in the pathways leading to radiobiological damage. Although it is known that two main types of cellular communication (i.e. via gap junctions and/or molecular messengers diffusing in the extra-cellular environment, such as cytokines, NO etc.) play a major role, it is of utmost importance to better understand the underlying mechanisms, and how such mechanisms can be modulated by ionizing radiation. Though the "final" goal is of course to elucidate the in vivo scenario, in the meanwhile also in vitro studies can provide useful insights. In the present paper we will discuss key issues oil the mechanisms underlying non-targeted effects and cell communication, for which theoretical models and simulation codes can be of great help. In this framework, we will present in detail three literature models, as well as an approach under development at the University of Pavia. More specifically, we will first focus oil a version of the "State-Vector Model" including bystander-induced apoptosis of initiated cells, which was successfully fitted to in vitro data oil neoplastic transformation supporting the hypothesis of a protective bystander effect mediated by apoptosis. The second analyzed model, focusing oil the kinetics of bystander effects in 3D tissues, was successfully fitted to data oil bystander damage in an artificial 3D skin system, indicating a signal range of the order of 0.7-1 mm. A third model for bystander effect, taking into account of spatial location, cell killing and repopulation, showed dose-response curves increasing approximately linearly at low dose rates but quickly flattening out for higher dose rates, also predicting an effect augmentation following dose fractionation. Concerning the Pavia approach, which can model the release, diffusion and depletion/degradation of candidate signals (e.g. cytokines) travelling in the extra-cellular environment, the good agreement with ad hoc experimental data obtained in our laboratory validated the adopted approach, which in the future can be applied also to other candidate signals. Although the available information is still not sufficient to decide whether the Linear No Threshold approach for low dose risk including space radiation risk - has to be modified, these studies confirmed the need of a paradigm shift in (low-dose) radiobiology, where the DNA-centric vision needs to be integrated by a wider vision where cells constitute an organized population responding to external stimuli in a collective fashion, communicating by means of different molecular signals. Further studies, in particular in vivo (or at least in 3D tissues) and possibly combined with human epidemiological data, will be crucial to help solving such questions in the future

Cellular communication and “non-targeted effects”: Modelling approaches

BALLARINI, FRANCESCA;MARIOTTI, LUCA GIOVANNI;NANO, ROSANNA;OTTOLENGHI, ANDREA DAVIDE
2009-01-01

Abstract

During the last decade, a large number of experimental studies oil the so-called "non-targeted effects", in particular bystander effects, outlined that cellular communication plays a significant role in the pathways leading to radiobiological damage. Although it is known that two main types of cellular communication (i.e. via gap junctions and/or molecular messengers diffusing in the extra-cellular environment, such as cytokines, NO etc.) play a major role, it is of utmost importance to better understand the underlying mechanisms, and how such mechanisms can be modulated by ionizing radiation. Though the "final" goal is of course to elucidate the in vivo scenario, in the meanwhile also in vitro studies can provide useful insights. In the present paper we will discuss key issues oil the mechanisms underlying non-targeted effects and cell communication, for which theoretical models and simulation codes can be of great help. In this framework, we will present in detail three literature models, as well as an approach under development at the University of Pavia. More specifically, we will first focus oil a version of the "State-Vector Model" including bystander-induced apoptosis of initiated cells, which was successfully fitted to in vitro data oil neoplastic transformation supporting the hypothesis of a protective bystander effect mediated by apoptosis. The second analyzed model, focusing oil the kinetics of bystander effects in 3D tissues, was successfully fitted to data oil bystander damage in an artificial 3D skin system, indicating a signal range of the order of 0.7-1 mm. A third model for bystander effect, taking into account of spatial location, cell killing and repopulation, showed dose-response curves increasing approximately linearly at low dose rates but quickly flattening out for higher dose rates, also predicting an effect augmentation following dose fractionation. Concerning the Pavia approach, which can model the release, diffusion and depletion/degradation of candidate signals (e.g. cytokines) travelling in the extra-cellular environment, the good agreement with ad hoc experimental data obtained in our laboratory validated the adopted approach, which in the future can be applied also to other candidate signals. Although the available information is still not sufficient to decide whether the Linear No Threshold approach for low dose risk including space radiation risk - has to be modified, these studies confirmed the need of a paradigm shift in (low-dose) radiobiology, where the DNA-centric vision needs to be integrated by a wider vision where cells constitute an organized population responding to external stimuli in a collective fashion, communicating by means of different molecular signals. Further studies, in particular in vivo (or at least in 3D tissues) and possibly combined with human epidemiological data, will be crucial to help solving such questions in the future
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11571/582314
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