Investigation of effects of low doses of ionising radiation

Biomathematical cancer models are a modern tool to predict the risks of ionizing radiation. Various model approaches are known in the scientific literature among them deterministic and stochastic multistage models. They allow to simulate various biological endpoints such as neoplastic transformation or lung cancer. One of the key questions in radiation research and radiation protection is whether even smallest amounts of radiation can cause cancer or whether there is a threshold for tumor induction below which either no cancers are induced or where even tumor-reducing effects could happen. The project is intended as a continuation of Dr. Schöllnberger`s experience in the field of low dose research that included four years of postdoctoral training in the U.S. and a two year EU Marie Curie Individual Fellowship. Mathematical tools and software that have been developed in the Marie Curie Individual Fellowship will be used and extended for continued research in the field of risk estimation of low doses of ionizing radiation via mechanistic cancer models. Ongoing collaborations with the partners in the U.S. (Purdue University), Canada (Chalk River Laboratories) and in the Netherlands (RIVM) will be continued. An earlier developed model includes radiologically inducible DNA repair and radical scavengers as well as endogenously produced DNA lesions. It has been developed to describe the effects of low doses of low-LET radiation (gamma- and X-rays) delivered at low doserates on lung cancer induction. This model will be extended to describe possible protective effects of low doses of low-LET radiation delivered at high dose rates. Such irradiation conditions can be encountered at workplaces and in accidents. The currently deterministic cancer model will also be advanced into a state-of-the-art stochastic two-stage model. Biological mechanisms other than those already implemented in the mechanistic cancer model will be incorporated. A special emphasize will be given to apoptosis and cell killing in initiated and/or hypersensitive cell populations. In addition, it is planned to incorporate detrimental and protective bystander effects into the cancer model. Both of these phenomena have been shown in in vitro and in quasi in vivo conditions. Detrimental bystander effects can lead to supra-linear effects at low doses of ionizing radiation. Free model parameters will partially be estimated by testing the model on suitable data and/or are taken from the scientific literature. Model simulations can then be performed to see whether the model can explain published data that relate to low dose irradiation and to investigate which mechanisms influence the shape of the dose-response curve at low doses stronger than others. Recently published data, which show that low doses of gamma-radiation increase tumor latency of spontaneous lymphomas and spinal osteosarcomas in mice, will be used to test the model. Sensitivity analyses applying Monte Carlo techniques with respect to the current uncertainty ranges of the model parameters could prove to be valuable. The aim of the proposed project is to include those biological mechanisms into the cancer model that are most relevant at low doses of ionizing radiation. Model simulations are then performed to see which mechanisms dominate in the low dose region and to predict the shape of the dose-response relationship at low doses of ionizing radiation. With respect to the nuclear power stations at its borders, the planned project is especially relevant for Austria.

Biomathematical cancer models are a modern tool to predict the risks of ionizing radiation. Various model approaches are known in the scientific literature among them deterministic and stochastic multistage models. They allow to simulate various biological endpoints such as neoplastic transformation or lung cancer. One of the key questions in radiation research and radiation protection is whether even smallest amounts of radiation can cause cancer or whether there is a threshold for tumor induction below which either no cancers are induced or where even tumor-reducing effects could happen. The project is intended as a continuation of Dr. Schöllnberger`s experience in the field of low dose research that included four years of postdoctoral training in the U.S. and a two year EU Marie Curie Individual Fellowship. Mathematical tools and software that have been developed in the Marie Curie Individual Fellowship will be used and extended for continued research in the field of risk estimation of low doses of ionizing radiation via mechanistic cancer models. Ongoing collaborations with the partners in the U.S. (Purdue University), Canada (Chalk River Laboratories) and in the Netherlands (RIVM) will be continued. An earlier developed model includes radiologically inducible DNA repair and radical scavengers as well as endogenously produced DNA lesions. It has been developed to describe the effects of low doses of low-LET radiation (gamma- and X-rays) delivered at low doserates on lung cancer induction. This model will be extended to describe possible protective effects of low doses of low-LET radiation delivered at high dose rates. Such irradiation conditions can be encountered at workplaces and in accidents. The currently deterministic cancer model will also be advanced into a state-of-the-art stochastic two-stage model. Biological mechanisms other than those already implemented in the mechanistic cancer model will be incorporated. A special emphasize will be given to apoptosis and cell killing in initiated and/or hypersensitive cell populations. In addition, it is planned to incorporate detrimental and protective bystander effects into the cancer model. Both of these phenomena have been shown in in vitro and in quasi in vivo conditions. Detrimental bystander effects can lead to supra-linear effects at low doses of ionizing radiation. Free model parameters will partially be estimated by testing the model on suitable data and/or are taken from the scientific literature. Model simulations can then be performed to see whether the model can explain published data that relate to low dose irradiation and to investigate which mechanisms influence the shape of the dose-response curve at low doses stronger than others. Recently published data, which show that low doses of gamma-radiation increase tumor latency of spontaneous lymphomas and spinal osteosarcomas in mice, will be used to test the model. Sensitivity analyses applying Monte Carlo techniques with respect to the current uncertainty ranges of the model parameters could prove to be valuable. The aim of the proposed project is to include those biological mechanisms into the cancer model that are most relevant at low doses of ionizing radiation. Model simulations are then performed to see which mechanisms dominate in the low dose region and to predict the shape of the dose-response relationship at low doses of ionizing radiation. With respect to the nuclear power stations at its borders, the planned project is especially relevant for Austria.