Differences in DNA repair capacity, cell death and transcriptional response after irradiation between a radiosensitive and a radioresistant cell line

Normal tissue toxicity after radiotherapy shows variability between patients, indicating inter-individual differences in radiosensitivity. Genetic variation probably contributes to these differences. The aim of the present study was to determine if two cell lines, one radiosensitive (RS) and another radioresistant (RR), showed differences in DNA repair capacity, cell viability, cell cycle progression and, in turn, if this response could be characterised by a differential gene expression profile at different post-irradiation times. After irradiation, the RS cell line showed a slower rate of γ-H2AX foci disappearance, a higher frequency of incomplete chromosomal aberrations, a reduced cell viability and a longer disturbance of the cell cycle when compared to the RR cell line. Moreover, a greater and prolonged transcriptional response after irradiation was induced in the RS cell line. Functional analysis showed that 24h after irradiation genes involved in "DNA damage response", "direct p53 effectors" and apoptosis were still differentially up-regulated in the RS cell line but not in the RR cell line. The two cell lines showed different response to IR and can be distinguished with cell-based assays and differential gene expression analysis. The results emphasise the importance to identify biomarkers of radiosensitivity for tailoring individualized radiotherapy protocols

Differences in DNA repair capacity, cell death and transcriptional response after irradiation between a radiosensitive and a radioresistant cell line

Normal tissue toxicity after radiotherapy shows variability between patients, indicating inter-individual differences in radiosensitivity. Genetic variation probably contributes to these differences. The aim of the present study was to determine if two cell lines, one radiosensitive (RS) and another radioresistant (RR), showed differences in DNA repair capacity, cell viability, cell cycle progression and, in turn, if this response could be characterised by a differential gene expression profile at different post-irradiation times. After irradiation, the RS cell line showed a slower rate of γ-H2AX foci disappearance, a higher frequency of incomplete chromosomal aberrations, a reduced cell viability and a longer disturbance of the cell cycle when compared to the RR cell line. Moreover, a greater and prolonged transcriptional response after irradiation was induced in the RS cell line. Functional analysis showed that 24h after irradiation genes involved in "DNA damage response", "direct p53 effectors" and apoptosis were still differentially up-regulated in the RS cell line but not in the RR cell line. The two cell lines showed different response to IR and can be distinguished with cell-based assays and differential gene expression analysis. The results emphasise the importance to identify biomarkers of radiosensitivity for tailoring individualized radiotherapy protocols

Risk Factors for Childhood Leukemia: Radiation and Beyond

© 2021 Schmidt, Hornhardt, Erdmann, Sánchez-García, Fischer, Schüz and Ziegelberger.Childhood leukemia (CL) is undoubtedly caused by a multifactorial process with genetic as well as environmental factors playing a role. But in spite of several efforts in a variety of scientific fields, the causes of the disease and the interplay of possible risk factors are still poorly understood. To push forward the research on the causes of CL, the German Federal Office for Radiation Protection has been organizing recurring international workshops since 2008 every two to three years. In November 2019 the 6th International Workshop on the Causes of CL was held in Freising and brought together experts from diverse disciplines. The workshop was divided into two main parts focusing on genetic and environmental risk factors, respectively. Two additional special sessions addressed the influence of natural background radiation on the risk of CL and the progress in the development of mouse models used for experimental studies on acute lymphoblastic leukemia, the most common form of leukemia worldwide. The workshop presentations highlighted the role of infections as environmental risk factor for CL, specifically for acute lymphoblastic leukemia. Major support comes from two mouse models, the Pax5+/− and Sca1-ETV6-RUNX1 mouse model, one of the major achievements made in the last years. Mice of both predisposed models only develop leukemia when exposed to common infections. These results emphasize the impact of gene-environment-interactions on the development of CL and warrant further investigation of such interactions — especially because genetic predisposition is detected with increasing frequency in CL. This article summarizes the workshop presentations and discusses the results in the context of the international literature.The Federal Ministry for the Environment, Nature Conservation and Nuclear Safety Germany funded the international workshop (3619I02454). Open access publication fees were funded by the German Federal Office for Radiation Protection

Natural Cubic Spline Regression Modeling Followed by Dynamic Network Reconstruction for the Identification of Radiation-Sensitivity Gene Association Networks from Time-Course Transcriptome Data.

Gene expression time-course experiments allow to study the dynamics of transcriptomic changes in cells exposed to different stimuli. However, most approaches for the reconstruction of gene association networks (GANs) do not propose prior-selection approaches tailored to time-course transcriptome data. Here, we present a workflow for the identification of GANs from time-course data using prior selection of genes differentially expressed over time identified by natural cubic spline regression modeling (NCSRM). The workflow comprises three major steps: 1) the identification of differentially expressed genes from time-course expression data by employing NCSRM, 2) the use of regularized dynamic partial correlation as implemented in GeneNet to infer GANs from differentially expressed genes and 3) the identification and functional characterization of the key nodes in the reconstructed networks. The approach was applied on a time-resolved transcriptome data set of radiation-perturbed cell culture models of non-tumor cells with normal and increased radiation sensitivity. NCSRM detected significantly more genes than another commonly used method for time-course transcriptome analysis (BETR). While most genes detected with BETR were also detected with NCSRM the false-detection rate of NCSRM was low (3%). The GANs reconstructed from genes detected with NCSRM showed a better overlap with the interactome network Reactome compared to GANs derived from BETR detected genes. After exposure to 1 Gy the normal sensitive cells showed only sparse response compared to cells with increased sensitivity, which exhibited a strong response mainly of genes related to the senescence pathway. After exposure to 10 Gy the response of the normal sensitive cells was mainly associated with senescence and that of cells with increased sensitivity with apoptosis. We discuss these results in a clinical context and underline the impact of senescence-associated pathways in acute radiation response of normal cells. The workflow of this novel approach is implemented in the open-source Bioconductor R-package splineTimeR

Low dose ionizing radiation effects on the immune system

International audienceIonizing radiation interacts with the immune system in many ways with a multiplicity that mirrors thecomplexity of the immune system itself: namely the need to maintain a delicate balance between differentcompartments, cells and soluble factors that work collectively to protect, maintain, and restore tissue function inthe face of severe challenges including radiation damage. The cytotoxic effects of high dose radiation are lessrelevant after low dose exposure, where subtle quantitative and functional effects predominate that may gounnoticed until late after exposure or after a second challenge reveals or exacerbates the effects. For example,low doses may permanently alter immune fitness and therefore accelerate immune senescence and pave the wayfor a wide spectrum of possible pathophysiological events, including early-onset of age-related degenerativedisorders and cancer. By contrast, the so called low dose radiation therapy displays beneficial, anti-inflammatoryand pain relieving properties in chronic inflammatory and degenerative diseases. In this review, epidemiological,clinical and experimental data regarding the effects of low-dose radiation on the homeostasis and functionalintegrity of immune cells will be discussed, as will be the role of immune-mediated mechanisms in the systemicmanifestation of localized exposures such as inflammatory reactions. The central conclusion is that ionizingradiation fundamentally and durably reshapes the immune system. Further, the importance of discovery ofimmunological pathways for modifying radiation resilience amongst other research directions in this field isimplied

Studying biomarkers reflecting the adverse outcome pathways from exposures to diseases using molecular epidemiology: example of the molecular epidemiology protocol developed as part of the Concerted Uranium Research in Europe (CURE) project

International audienceResults produced during recent years have shown that epidemiology still has a strong potential to quantify radiation-related health effects after low dose exposures, even below 100 mGy. However below certain dose levels, which may differ according to the disease considered and population characteristics (e.g.: age at exposure), direct observations of dose-risk relationships by classical epidemiological studies are not possible. Indirect evidence, including subtle changes in various physiological functions and biomarkers (sub-clinical/ pre-pathological) reflecting key events in response to low or even very low doses will need to be determined in order to draw inferences on risk after exposures to very low doses. Such inference will be possible for instance, if very large cohorts, - which can even be non-radiation cohorts - quantify the relationships between (combinations of) these biomarkers or changes in physiological function and disease risks. Such inferences are in line with the so-called “meet-in-the-middle” approach. Following this philosophy, as part of the CURE project which aimed to prepare protocols to study the health effects of chronic uranium exposures at low dose, a rational approach was employed to select biomarkers of exposures and subclinical biomarkers of effects in uranium target organs (kidney, lung, bone, brain) and in systems in which potential effects could be suspected (e.g.: vascular system). The use of non-targeted techniques (omics) is also essential to generate new hypotheses of induced signal cascades resulting finally in disease pathways and disease onset (Adverse Outcome Pathways, AOP). A full molecular epidemiology protocol was then developed, including a questionnaire and other means of data collection to measure potential confounding factors. Such an approach will be useful in order 1) to determine the changes in biomarkers which may be attributed to uranium itself and 2) to better appreciate the relative influence of uranium versus other stressors on these biomarker changes, as part of AOP leading to chronic diseases. 3) These yet hypothetical diseases and their development can subsequently be studied in classical epidemiological approaches (at higher doses) and through well-justified radiobiological experiments. Finally, indirect evidence gained from molecular epidemiology studies will prove useful to quantify risks after very low dose exposures, in addition to experimental studies and classical epidemiology

Studying biomarkers reflecting the adverse outcome pathways from exposures to diseases using molecular epidemiology: example of the molecular epidemiology protocol developed as part of the Concerted Uranium Research in Europe (CURE) project

International audienceResults produced during recent years have shown that epidemiology still has a strong potential to quantify radiation-related health effects after low dose exposures, even below 100 mGy. However below certain dose levels, which may differ according to the disease considered and population characteristics (e.g.: age at exposure), direct observations of dose-risk relationships by classical epidemiological studies are not possible. Indirect evidence, including subtle changes in various physiological functions and biomarkers (sub-clinical/ pre-pathological) reflecting key events in response to low or even very low doses will need to be determined in order to draw inferences on risk after exposures to very low doses. Such inference will be possible for instance, if very large cohorts, - which can even be non-radiation cohorts - quantify the relationships between (combinations of) these biomarkers or changes in physiological function and disease risks. Such inferences are in line with the so-called “meet-in-the-middle” approach. Following this philosophy, as part of the CURE project which aimed to prepare protocols to study the health effects of chronic uranium exposures at low dose, a rational approach was employed to select biomarkers of exposures and subclinical biomarkers of effects in uranium target organs (kidney, lung, bone, brain) and in systems in which potential effects could be suspected (e.g.: vascular system). The use of non-targeted techniques (omics) is also essential to generate new hypotheses of induced signal cascades resulting finally in disease pathways and disease onset (Adverse Outcome Pathways, AOP). A full molecular epidemiology protocol was then developed, including a questionnaire and other means of data collection to measure potential confounding factors. Such an approach will be useful in order 1) to determine the changes in biomarkers which may be attributed to uranium itself and 2) to better appreciate the relative influence of uranium versus other stressors on these biomarker changes, as part of AOP leading to chronic diseases. 3) These yet hypothetical diseases and their development can subsequently be studied in classical epidemiological approaches (at higher doses) and through well-justified radiobiological experiments. Finally, indirect evidence gained from molecular epidemiology studies will prove useful to quantify risks after very low dose exposures, in addition to experimental studies and classical epidemiology