Protective bystander effects simulated with the state-vector model

REVIEW OF QUANTITATIVE MECHANISTIC MODELS OF RADIATION-INDUCED NON-TARGETED EFFECTS (NTE)

Quantitative mechanistic modeling of the biological effects of ionizing radiation has a long rich history. Initially, it was dominated by target theory, which quantifies damage caused by traversal of cellular targets like DNA by ionizing tracks. The discovery that mutagenesis, death and/or altered behavior sometimes occur in cells that were not themselves traversed by any radiation tracks but merely interacted with traversed cells was initially seen as surprising. As more evidence of such 'non-targeted' or 'bystander' effects accumulated, the importance of their contribution to radiation-induced damage became more recognized. Understanding and modeling these processes is important for quantifying and predicting radiation-induced health risks. Here we review the variety of mechanistic mathematical models of nontargeted effects that emerged over the past 2-3 decades. This review is not intended to be exhaustive, but focuses on the main assumptions and approaches shared or distinct between models, and on identifying areas for future research.

The LNT model for cancer induction is not supported by radiobiological data

The hallmarks of cancer have been the focus of much research and have influenced the development of risk models for radiation-induced cancer. However, natural defenses against cancer, which constitute the hallmarks of cancer prevention, have largely been neglected in developing cancer risk models. These natural defenses are enhanced by low doses and dose rates of ionizing radiation, which has aided in the continuation of human life over many generations. Our natural defenses operate at the molecular, cellular, tissue, and whole-body levels and include epigenetically regulated (epiregulated) DNA damage repair and antioxidant production, selective p53-independent apoptosis of aberrant cells (e.g. neoplastically transformed and tumor cells), suppression of cancer-promoting inflammation, and anticancer immunity (both innate and adaptive components). This publication reviews the scientific bases for the indicated cancer-preventing natural defenses and evaluates their implication for assessing cancer risk after exposure to low radiation doses and dose rates. Based on the extensive radiobiological evidence reviewed, it is concluded that the linear-no-threshold (LNT) model (which ignores natural defenses against cancer), as it relates to cancer risk from ionizing radiation, is highly implausible. Plausible models include dose-threshold and hormetic models. More research is needed to establish when a given model (threshold, hormetic, or other) applies to a given low-dose-radiation exposure scenario.

Non-targeted effects of ionising radiation and radiotherapy

Modern radiobiology is undergoing rapid change due to new discoveries contradicting the target concept which is currently used to predict dose-response relationships. Thus relatively recently discovered radiation-induced bystander effects (RIBEs), that include additional death, mutation and radio-adaptation in non-irradiated cells, change our understanding of the target concept and broadens its boundaries. This can be significant from a radioprotection point of view and also has the potential to reassess radiation damage models currently used in radiotherapy. This article reviews briefly the general concepts of RIBEs such as the proposed underlying mechanisms of signal induction and propagation, experimental approaches and biological end points used to investigate these phenomena. It also summarises several mathematical models currently proposed in an attempt to quantify RIBE. The main emphasis of this article is to review and highlight the potential impact of the bystander phenomena in radiotherapy.

Mammogram and diagnostic X-rays--evidence of protective Bystander, Adaptive Response (AR) radio-protection and AR retention at high dose levels

PURPOSE

The recently published dose response data by Dr Redpath's research group for low energy (30 kVp) mammography X-rays, displaying Adaptive Response (AR) radio-protective behavior, is significant for millions of American women that undergo annual breast cancer screening. We here, using the recently developed Microdose Model that encompasses the Bystander Effect (BE) and AR behavior, examine the data for BE, AR and high radiation domination by the priming radiations high dose Direct Damage.

RESULTS

The dose response is divided into three regions, Bystander Effect Region, Adaptive Response Region and Direct Damage Region (with possible retention of the AR protection). The Bystander Effect Region is below the microdose Specific Energy deposition for single photon induced charged particle traversals through the cell nucleus (the microdose Specific Energy Deposition per Traversal value = < z1 > = 0.638 cGy per Hit). Strong evidence is shown that a protective BE of about 50% occurs at a very low dose of 0.054 cGy, the BE is depleted reverting the response back to nearly the zero dose control value at 0.27 cGy, a 42% AR protection then is developed at 1.08 cGy and then the Direct Damage increasingly begins to dominate in the range from 5.4-21.6 cGy. Using the precise Method of Maximum Likelihood Estimator (MLE), the high dose Direct Damage Region is examined. We show that to the dose of 21.6 cGy the AR protection is retained in spite of the significant Direct Damage. We apply the same MLE analysis to the Redpath data for 137Cs gammas and find that the AR protection is completely dissipated at high Direct Damage inducing doses of 100 cGy.

CONCLUSIONS

The model shows that a protective BE of about 50% occurs at a low factor of 12 below single tracks traversals where less than 10% of the cell nuclei have been hit. Poisson distributed single tracks activates the 42% AR protection. The AR protection is retained at high dose but one needs to understand why 137Cs does not. Other Redpath group AR data sets for 137Cs, 232 MeV protons, and brachytherapy 125I photons did not reveal BE since the lowest data points were above the < z1 > for the radiations, but diagnostic X-rays do.

"Protective bystander effects simulated with the state-vector model"--HeLa x skin exposure to Cs not protective bystander response but mammogram and diagnostic X-rays are

The recent Dose Response journal article "Protective Bystander Effects Simulated with the State-Vector Model" (Schollnberger and Eckl 2007) identified the suppressive (below natural occurring, zero primer dose, spontaneous level) dose response for HeLa x skin exposure to (137)Cs gamma rays (Redpath et al 2001) as a protective Bystander Effect (BE) behavior. I had previously analyzed the Redpath et al (2001) data with a Microdose Model and conclusively showed that the suppressive response was from Adaptive Response (AR) radio-protection (Leonard 2005, 2007a). The significance of my microdose analysis has been that low LET radiation induced single (i.e. only one) charged particle traversals through a cell can initiate a Poisson distributed activation of AR radio-protection. The purpose of this correspondence is to clarify the distinctions relative to the BE and the AR behaviors for the Redpath groups (137)Cs data, show conversely however that the Redpath group data for mammography (Ko et al 2004) and diagnostic (Redpath et al 2003) X-rays do conclusively reflect protective bystander behavior and also herein emphasize the need for radio-biologist to apply microdosimetry in planning and analyzing their experiments for BE and AR. Whether we are adamantly pro-LNT, adamantly anti-LNT or, like most of us, just simple scientists searching for the truth in radio-biology, it is important that we accurately identify our results, especially when related to the LNT hypothesis controversy.

A composite microdose Adaptive Response (AR) and Bystander Effect (BE) model-application to low LET and high LET AR and BE data

PURPOSE

It has been suggested that Adaptive Response (AR) may reduce risk of adverse health effects due to ionizing radiation. But very low dose Bystander Effects (BE) may impose dominant deleterious human risks. These conflicting behaviors have stimulated controversy regarding the Linear No-Threshold human risk model. A dose and dose rate-dependent microdose model, to examine AR behavior, was developed in prior work. In the prior work a number of in vitro and in vivo dose response data were examined with the model. Recent new data show AR behavior with some evidence of very low dose BE. The purpose of this work is to supplement the microdose model to encompass the Brenner and colleagues BaD (Bystander and Direct Damage) model and apply this composite model to obtain new knowledge regarding AR and BE and illustrate the use of the model to plan radio-biology experiments.

MATERIALS AND METHODS

The biophysical composite AR and BE Microdose Model quantifies the accumulation of hits (Poisson distributed, microdose specific energy depositions) to cell nucleus volumes. This new composite AR and BE model provides predictions of dose response at very low dose BE levels, higher dose AR levels and even higher dose Direct (linear-quadratic) Damage radiation levels.

RESULTS

We find good fits of the model to both BE data from the Columbia University microbeam facility and combined AR and BE data for low Linear Energy Transfer (LET) and high LET data. A Bystander Factor of about 27,000 and an AR protection factor of 0.61 are obtained for the low LET in vivo mouse spleen exposures. A Bystander Factor of 317 and an AR protection factor of 0.53 are obtained for high LET radon alpha particles in human lymphocytes. In both cases the AR is activated at most by one or two radiation induced charged particle traversals through the cell nucleus.

CONCLUSIONS

The results of the model analysis is consistent with a premise that both Bystander damage and Adaptive Response radioprotection can occur in the same cell type, derived from the same cell species. The model provides an analytical tool to biophysically study the combined effects of BE and AR.

Low dose radiation and intercellular induction of apoptosis: potential implications for the control of oncogenesis

PURPOSE

This review is focused on the potential impact of low dose radiation effects on intercellular induction of apoptosis and the underlying reactive-oxygen species (ROS)-mediated signaling pathways.

RESULTS

Transformed cells are subject to ROS-mediated apoptosis induction by non-transformed cells ('intercellular induction of apoptosis') and by ROS-mediated autocrine self-destruction. Sensitivity to intercellular induction of apoptosis and autocrine self-destruction are strictly correlated to the expression of the transformed state. Extracellular superoxide anions generated by transformed target cells drive the selectivity and sensitivity of this signaling system which is based on four different signaling pathways. Low dose irradiation of non-transformed cells enhances intercellular induction of apoptosis in transformed cells. This process is controlled by TGF-beta and seems to depend on the induction of peroxidase release. In addition, low dose radiation enhances superoxide anion generation of transformed target cells.

CONCLUSIONS

Low dose radiation-triggered enhancement of intercellular induction of apoptosis and autocrine self-destruction might represent a potential control system during carcinogenesis. It might be the underlying mechanism for the well-known inhibitory effect of low dose radiation on detectable transformation events. However, modifications of the complex intercellular ROS-based signaling system may also lead to configurations in which low dose radiation attenuates ROS-mediated apoptosis induction.

Systems biological and mechanistic modelling of radiation-induced cancer

This paper summarises the five presentations at the First International Workshop on Systems Radiation Biology that were concerned with mechanistic models for carcinogenesis. The mathematical description of various hypotheses about the carcinogenic process, and its comparison with available data is an example of systems biology. It promises better understanding of effects at the whole body level based on properties of cells and signalling mechanisms between them. Of these five presentations, three dealt with multistage carcinogenesis within the framework of stochastic multistage clonal expansion models, another presented a deterministic multistage model incorporating chromosomal aberrations and neoplastic transformation, and the last presented a model of DNA double-strand break repair pathways for second breast cancers following radiation therapy.

Detrimental and protective bystander effects: a model approach

This work integrates two important cellular responses to low doses, detrimental bystander effects and apoptosis-mediated protective bystander effects, into a multistage model for chromosome aberrations and in vitro neoplastic transformation: the State-Vector Model. The new models were tested on representative data sets that show supralinear or U-shaped dose responses. The original model without the new low-dose features was also tested for consistency with LNT-shaped dose responses. Reductions of in vitro neoplastic transformation frequencies below the spontaneous level have been reported after exposure of cells to low doses of low-LET radiation. In the current study, this protective effect is explained with bystander-induced apoptosis. An important data set that shows a low-dose detrimental bystander effect for chromosome aberrations was successfully fitted by additional terms within the cell initiation stage. It was found that this approach is equivalent to bystander-induced clonal expansion of initiated cells. This study is an important step toward a comprehensive model that contains all essential biological mechanisms that can influence dose-response curves at low doses.