Estimating long-term health risks after breast cancer radiotherapy: Merging evidence from low and high doses.

In breast cancer radiotherapy, substantial radiation exposure of organs other than the treated breast cannot be avoided, potentially inducing second primary cancer or heart disease. While distant organs and large parts of nearby ones receive doses in the mGy-Gy range, small parts of the heart, lung and bone marrow often receive doses as high as 50 Gy. Contemporary treatment planning allows for considerable flexibility in the distribution of this exposure. To optimise treatment with regards to long-term health risks, evidence-based risk estimates are required for the entire broad range of exposures. Here, we thus propose an approach that combines data from medical and epidemiological studies with different exposure conditions. Approximating cancer induction as a local process, we estimate organ cancer risks by integrating organ-specific dose-response relationships over the organ dose distributions. For highly exposed organ parts, specific high-dose risk models based on studies with medical exposure are applied. For organs or their parts receiving relatively low doses, established dose-response models based on radiation-epidemiological data are used. Joining the models in the intermediate dose range leads to a combined, in general non-linear, dose response supported by data over the whole relevant dose range. For heart diseases, a linear model consistent with high- and low-dose studies is presented. The resulting estimates of long-term health risks are largely compatible with rate ratios observed in randomised breast cancer radiotherapy trials. The risk models have been implemented in a software tool PASSOS that estimates long-term risks for individual breast cancer patients

Long-term health risk after breast-cancer radiotherapy: Overview of passos methodology and software.

Breast-cancer radiotherapy reduces the recurrence rates and improves patient survival. However, it also increases the incidence of second cancers and of heart disease. These radiation-induced long-term health risks become increasingly important with improved cure rates and prolonged patient survival. Radiation doses to nearby as well as distant organs strongly vary between different irradiation techniques and among individual patients. To provide personalized lifetime risk estimates, the German national project PASSOS combines individual anatomy, dosimetric estimates, organ-specific low- and high-dose risk models and personal risk factors such as smoking. A dedicated software tool is under development to assist clinical decision-making processes

ProZES: The methodology and software tool for assessment of assigned share of radiation in probability of cancer occurrence.

ProZES is a software tool for estimating the probability that a given cancer was caused by preceding exposure to ionising radiation. ProZES calculates this probability, the assigned share, for solid cancers and hematopoietic malignant diseases, in cases of exposures to low-LET radiation, and for lung cancer in cases of exposure to radon. User-specified inputs include birth year, sex, type of diagnosed cancer, age at diagnosis, radiation exposure history and characteristics, and smoking behaviour for lung cancer. Cancer risk models are an essential part of ProZES. Linking disease and exposure to radiation involves several methodological aspects, and assessment of uncertainties received particular attention. ProZES systematically uses the principle of multi-model inference. Models of radiation risk were either newly developed or critically re-evaluated for ProZES, including dedicated models for frequent types of cancer and, for less common diseases, models for groups of functionally similar cancer sites. The low-LET models originate mostly from the study of atomic bomb survivors in Hiroshima and Nagasaki. Risks predicted by these models are adjusted to be applicable to the population of Germany and to different time periods. Adjustment factors for low dose rates and for a reduced risk during the minimum latency time between exposure and cancer are also applied. The development of the methodology and software was initiated and supported by the German Federal Ministry for the Environment, Nature Conservation and Nuclear Safety (BMU) taking up advice by the German Commission on Radiological Protection (SSK, Strahlenschutzkommission). These provide the scientific basis to support decision making on compensation claims regarding malignancies following occupational exposure to radiation in Germany

A naturally monomeric infrared fluorescent protein for protein labeling in vivo

Infrared fluorescent proteins (IFPs) provide an additional color to GFP and its red homologs in protein labeling. Based on structural analysis of the dimer interface, a monomeric bateriophytochrome is identified from a sequence database, and is engineered into a naturally-monomeric IFP (mIFP). We demonstrate that mIFP correctly labels proteins in live Drosophila and zebrafish requiring no exogenous cofactor, and will thus be useful in molecular, cell and developmental biology