Synergies resulting from systems biology approach (Alan Waltar) USA Germany

International Journal of Radiation Biology

ISSN: 0955-3002 (Print) 1362-3095 (Online) Journal homepage: http://www.tandfonline.com/loi/irab20

Synergies resulting from a systems biology approach: integrating radiation epidemiology and radiobiology to optimize protection of the public after exposure to low doses of ionizing radiation Nicholas Dainiak, Ludwig E. Feinendegen, Randall N. Hyer, Paul A. Locke & Alan E. Waltar To cite this article: Nicholas Dainiak, Ludwig E. Feinendegen, Randall N. Hyer, Paul A. Locke & Alan E. Waltar (2018) Synergies resulting from a systems biology approach: integrating radiation epidemiology and radiobiology to optimize protection of the public after exposure to low doses of ionizing radiation, International Journal of Radiation Biology, 94:1, 2-7, DOI: 10.1080/09553002.2018.1407461 To link to this article: https://doi.org/10.1080/09553002.2018.1407461

Accepted author version posted online: 27 Nov 2017.

Published online: 12 Dec 2017.

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Date: 03 January 2018, At: 09:55

INTERNATIONAL JOURNAL OF RADIATION BIOLOGY, 2018 VOL. 94, NO. 1, 2–7 https://doi.org/10.1080/09553002.2018.1407461

COMMENTARY

Synergies resulting from a systems biology approach: integrating radiation epidemiology and radiobiology to optimize protection of the public after exposure to low doses of ionizing radiation Nicholas Dainiaka,b, Ludwig E. Feinendegenc,d, Randall N. Hyere,f, Paul A. Lockeg and Alan E. Waltarh,i a

Radiation Emergency Assistance Center/Training Site (REAC/TS), Oak Ridge Institute for Science and Education, Oak Ridge, TN, USA; Department of Therapeutic Radiology, Yale University School of Medicine, New Haven, CT, USA; cDepartment of Nuclear Medicine, Heinrich-Heine University, Dusseldorf, Germany; dMedical Department, Brookhaven National Laboratory, Upton, NY, USA; e CrisisCommunication.net and Center for Risk Communication, New York, NY, USA; fDynavax Europe GmbH, Dynavax Technologies Corporation, Dusseldorf, Germany; gDepartment of Environmental Health and Engineering, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA; hPacific Northwest National Laboratory, Fast Reactor Safety and Fuels Organizations, Westinghouse Hanford Company, Richland, WA, USA; iDepartment of Nuclear Engineering, Texas A&M University, College Station, TX, USA b

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ARTICLE HISTORY Received 11 July 2017; Revised 8 November 2017; Accepted 12 November 2017 KEYWORDS Systems biology; epidemiology; radiobiology; public protection

How can a systems biology approach integrate radiobiology and radiation epidemiology?

The study of the human health effects of ionizing radiation (IR) is a dynamic and constantly evolving enterprise. This flux is due largely to uncertainties inherent in appropriately designed, population-based studies and well controlled basic science studies, resulting in what appears to be contradictory information regarding our understanding of human health effects from exposure to low dose IR (defined as an effective dose of <100 mGy) (Feinendegen et al. 2008; Dauer et al. 2010; NCRP 2012, 2015). In recent years, populations composed of individuals with radiation-associated malignancy have been analyzed, using a variety of models that incorporate new knowledge of molecular pathways, while the availability of large experimental data sets on the biological effects of low-dose and low doserate exposures to IR has increased substantially. The objectives of integrating emerging concepts in radiation epidemiology and radiobiology include clarifying the shape of the dose–response relationship at doses of <100 mGy, reducing the uncertainties in estimates of potential dose thresholds, refining our understanding of health risk, improving predictive modeling for detrimental or beneficial health effects, and developing guidelines for clinicians to use in weighing the benefit/risk ratio in individuals requiring medical imaging or therapeutic irradiation (NCRP 2015; Dainiak 2016). As explained below, a systems biology approach can serve as a starting point for dialogue concerning the integration of knowledge in the disciplines of radiation epidemiology and radiobiology (Locke 2009).

What technologies may be brought to bear?

The physical effects of IR are well characterized. Together, they predict a linear, no threshold (LNT) dose-effect relationship.

CONTACT Nicholas Dainiak

nick.dainiak@orau.org

ß 2018 Informa UK Limited, trading as Taylor & Francis Group

This model is supported by epidemiological and other data after exposure to doses of >100 mGy. Although a recent analysis of dosimetry used in epidemiological studies evaluating the LNT model over the past 15 years demonstrates a wide variation in the quality of the dosimetry underlying each study (Till et al. 2017), this model has withstood the test of time, and is readily applied to prudent protection of the general public (Boice 2017). In addition, an extensive review of the effects of dose rates on cell and molecular responses indicates that exposure to low dose rates produces a less effective change than does exposure to high dose rates, and in some instances decreases damage to below levels observed in unexposed cells (Brooks et al. 2016; Feinendegen 2016).

The relevance of the LNT model to doses of <100 mGy has been called into question. Biological responses to IR in cellular and molecular in vitro systems, although incompletely understood, do not a priori adhere to a linear dose–effect function. Understanding their mechanics requires an appreciation of the cell’s capacity to prevent, repair and remove daily damage from reactive oxygen species (ROS), as well as an understanding of cell-to-cell communication and tissue responses to IR (Dauer et al. 2010; Dainiak 2016; Feinendegen 2016). Redox biology is a rapidly emerging area of study that is directly linked to intercellular signaling. For example, shed microvesicles harbor redox-regulated metalloproteinases, nitric oxide and other free radicals that are transferred to target cells (Larson et al. 2014). During evolution, antioxidant defense systems have developed to prevent injury that is mediated by oxidative stress (Sies et al. 2017).

Human cells are under the constant threat of oxidants that are known to induce apoptosis. It has been suggested that hydrogen peroxide, a central redox signaling molecule, may play a critical role in defense against IR-induced apoptosis by

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activating molecular switches such as the Nrf2/kapp-aeap1 and NF-kappa-B/I-kappa-B systems, thereby promoting eustress through adaptive stress responses (Sies and Feinendegen 2017). Although exposure to low-dose IR (such as 0.1 mGy X-rays) may induce significant DNA damage (including single- and double-strand breaks) that is approximately equivalent to the damage that is produced in a day

by ROS from cell metabolism (Feinendegen 2016), the counterbalance of antioxidant systems may protect radiationexposed cells. Recently, scavengers of IR-induced ROS have been leveraged to reduce oxidative stress by improving mitochondrial dysfunction (Zhang et al. 2017). Therefore, the study of bystander effects, adaptive response and redox biology may provide new mechanistic insights into biological effects at doses of <100 mGy (Dauer et al. 2010) and lead to the development of novel therapeutic options.

Application of laboratory investigative tools such as tissue and organoid culture under oxygen restriction, ‘next generation sequencing’, supercomputers for analysis of large data sets, microarray technology, miRNAomics, quantitative polymerase chain reaction, two-dimensional gel electrophoresis, mass spectroscopy, atomic force microscopy, stimulated emission depleted (STED) microscopy, and DNA break-related markers, may elucidate mechanisms of action of low dose radiation at the level of the gene (transcription and translation), mitochondria, proteins (including their phosphorylation), molecular pathways, the plasma membrane, microvesicles/ exosomes (including their release, targeting and recirculation), whole cell (apoptosis as a repair process) and epigenetics (including DNA methylation) (Aypar et al. 2011; UNSCEAR 2012; DeCamilli 2014). Applying such tools to the study of low dose IR has the potential to yield insights that can help address the uncertainties associated with epidemiological studies. For example, STED microscopy may be used to image the movement of a single protein molecule from an irradiated cell to its extracellular vesicle during the process of vesiculation (DeCamilli 2014), and then from the vesicle to an unirradiated target cell. If transfer of this protein is restricted to exposure doses of <100 mGy, a novel low-dose radiation-dependent signaling mechanism will have been identified. Furthermore, if the intercellular exchange of this protein results in a survival benefit to either the irradiated cell or to the unirradiated target cell upon subsequent exposure to IR, a deviation from the LNT relationship may be predicted based on mathematical models that account for intercellular communication.

It is also important to recognize the role and contribution of animal models to the understanding of effects of IR in whole organisms. As far as ethical constraints permit, the compatibilities of responses in animals and humans are well accepted. Moreover, many dramatic advances in clinical medicine have resulted from observations in animal experiments. There appears to be no reason to make an exception when it comes to biological responses to IR.

A potential integrative role for systems biology It is possible that current risks from exposure to IR might be better understood as our knowledge of the relationship

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between complex disease processes and IR is further characterized. To fully understand the processes of disease progression, it is critical to examine the structure and interactions of cell function and intercellular signaling, and not merely the characteristics of isolated parts of cells, their organelles or the entire organism. This approach is captured in the concept of systems biology, which recognizes that the whole is greater than the sum of its parts (Kitano 2002; NIOSH 2014).

The complexities of health effects in populations, including variability among individuals in response to the same IR dose, and diversity of biological responses at cellular and tissue levels, may be better understood through integrated expressions of radiation effects (Locke 2009; Dauer et al.

2010). The risk to an exposed individual derives from the multitude of reactions and responses at the various levels of biological organization, including the molecular, cellular, tissue and whole body levels. The value of broad systems-level approaches is appreciated by national organizations, international groups and private industry, including the National Council on Radiation Protection and Measurements (NCRP), the Multidisciplinary European Low Dose Initiative (MELODI) and the Electric Power Research Institute (UNSCEAR 2012).

Biological modeling of radiation responses Quantitative modeling has been used to discern potentially informative measures of health effects and cellular responses (Brenner et al. 2014; Shuryak 2017). Brenner and colleagues have distinguished models that focus on the short-term effects of radiation occurring within approximately one month of exposure, from those characterizing long-term effects (Brenner et al. 2014). Short-term models assess near endpoints such as mutations and chromosome aberrations that have been used as surrogates for stochastic risk, and are applicable to radiation risk at low doses. They are heavily dependent on mechanistic assumptions, and are populated largely by data generated in molecular biology laboratories. Both linear quadratic and LNT relationships were described for radiation protection estimates at very low doses. In an analysis of DNA double-strand break rejoining, a bi-exponential model (with two discrete decay rates and a mono-exponential model with gamma-distributed decay rate) was found to best fit the data from 61 mammalian cell lines after high-dose-rate photon or heavy ion irradiation (Herr et al. 2015).

In contrast, long-term models assess far endpoints such as the development of and mortality from cancer. Populationbased data from radiation epidemiology and molecular studies are primary sources of data that populate these models.

Their value lies in their inclusion of a latent period that may last for years, during which time cells may pass through multiple stages characterized by accumulating multiple mutations and/or epigenetic changes, undergoing clonal expansion and acquiring genomic instability (Brenner et al.

2014). Thus, one may conceive of two-stage or multi-stage models with or without clonal expansion or genomic instability and in which a ‘pre-malignant’ cell undergoes a proliferative advantage over unaffected cells.

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These alterations may be accompanied by changes that occur during normal ageing, as stem cells capable of differentiation and proliferation, and their neighboring cells (i.e. â&#x20AC;&#x2DC;accessoryâ&#x20AC;&#x2122; cells) in microenvironmental niches may experience a decline in these functions, undergo apoptosis or acquire telomere dysfunction, resulting in impaired renewal, decreased immunity and malignant transformation (Sharpless and DePinho 2007). In some cases, such as chronic myelogenous leukemia, a single mutation (i.e. a translocation between chromosomes 9 and 22, resulting in the BCR-ABL fusion oncogene) is sufficient to account for the age incidence of a malignancy (Michor et al. 2006). Additional modeling is needed to better understand the interrelationship of mechanisms for ageing with those for cancer suppression.

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Application of quantitative models to molecular changes and health effects Mathematical descriptions of radiation carcinogenesis are being developed that incorporate the biology associated with intracellular and intercellular responses (UNSCEAR 2012), and molecular biomarkers/indicators (Vogelstein et al. 2013) in both epidemiological studies and experimental animal studies. Today, mathematical models are being used to predict secondary tumors (Correa et al. 2017; Dasu and TomaDasu 2017), to explain maintenance and renewal of stem cells and their progeny (Little and Hendry 2017), and to integrate the opposing effects from chromosomal aberrations and the adaptive response after exposure (Dobrzynski et al.

2016). New strategies are being designed to identify and characterize potential genetic signatures of radio-sensitivity by combining mathematical models with statistical analysis and data mining (Zyla et al. 2014). In addition, the ratio of biological effects has been proposed as a tool to compare radiations at the same dose in an effort to scale health risks from low-LET to high-LET (Shuryak et al. 2017).

The intersection of radiation epidemiology with cell and molecular biology is being examined with new models that are applicable to low dose/dose-rate exposures. Although the LNT model is supported by DNA damage and mis-repair models of cancer risk and by some studies examining intercellular communication (Dauer et al. 2010), other emerging concepts of carcinogenesis and non-targeted effects (NTE) offer conflicting information. Some investigators suggest that models based on NTE are superior to those based on targeted effects with DNA damage/mis-repair in predicting biological events (Cacao et al. 2016; Chang et al. 2016).

Major advances in our understanding of signaling among cells via microvesicles that are exfoliated or shed from the surface membrane and exosomes that are secreted into the microenvironment (Dainiak and Cohen 1982; Dainiak 1991; Tuck et al. 1994; Albanese and Dainiak 2003; Flamant and Tamarat 2016; Nawaz et al. 2016) have enabled scientists to visualize signals as they traffic among cell populations. IR induces the release of death ligand (FasL; TNFSF6) on shed microvesicles (Albanese and Dainiak 2000), stimulates exosome release and target cell uptake (Arscott et al. 2013), and initiates a biological effect on neighboring, unirradiated cells

(i.e. the bystander effect) that is mediated by exosomes (Jella et al. 2014). In addition, IR alters the redox status of target cells (causing surges in intracellular levels of ROS) and induces genomic instability in progeny of bystander cells via connexins, proteins that mediate gap-junction intercellular communication (Klammer et al. 2013; de Toledo et al. 2017).

Quantitative models that have been developed to account for intercellular communication between targeted and nontargeted cell populations (Brenner et al. 2001) may be used to better understand the impact of IR on biological effects at low doses of radiation.

At the level of molecular pathways, low-dose responses and interactions between pathways for ATM signaling and TGF-beta signaling after low-LET or high-LET radiations are being quantified, using a modular system that includes ATM activation by DNA damage and by the generation of ROS (Cucinotta 2016). An integrated analysis of the biological impact of IR on multiple pathways is needed to clarify radiation effects. For example, a two-stage model of clonal expansion (TSCE) has been found to compare favorably to the empirical risk for lung cancer mortality among 16,236 Eldorado uranium miners (Eidemuller et al. 2012). The TSCE model predicts a reduced rate of clonal expansion for intermediate lung cells at higher age of exposure, and suggests that exposure to decay products of radon results in a non-linear increase in the rate of clonal expansion with a steep increase at low exposure rates and a small increase at a high exposure rate. This model may also provide a mechanism for radiation-induced genomic instability based on activation of distinct molecular pathways, compared to those activated after spontaneous mutation (Eidemuller et al. 2015). Based on a review of mechanistic models for human cancer, Ruhm and colleagues concluded that the TSCE model of carcinogenesis may be a promising approach to evaluate the risk from exposure to low doses and low dose rates, and that new processes for carcinogenesis should be incorporated â&#x201A;Źhm et al. 2017). into this and other models (Ru Primary drivers of colon cancer may include instability of both chromosomes and microsatellites (Kaiser et al. 2014).

A biological model that combines these two phenomena has been used to assess IR-associated colon cancer among Japanese a-bomb survivors recorded in the life span study.

An imbalance of an order of magnitude was found among young birth cohorts of either gender where chromosomal instability contributed more extensively to IR-related cancer than did microsatellite instability (Kaiser et al. 2014).

However, this model is limited by the large number of molecular pathways that may be triggered by potentially mutated genes (over 200), of which only a few are common to the majority of colorectal cancers. In the future, more complex models will need to be developed to analyze pathway-specific colon cancer risk.

Recently, mechanistic modeling was applied to thyroid carcinogenesis (Kaiser et al. 2016). A model of papillary thyroid cancer based on overexpression of the CLIP2 gene, using distinct mathematical formulations for two molecular pathways, was applied to a Ukranian-American cohort of approximately 13,000 subjects who were exposed at age <19 years following the Chernobyl catastrophe.

Molecular

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measurements of the CLIP2 marker were made in tissues from 141 patients who had enhanced medical surveillance since 1998. Age-dependent estimates of the excess relative risk (ERR) from exposure were successfully generated from pathway alterations in CLIP2 (Kaiser et al. 2016), thereby creating a direct link between radiation epidemiology and molecular biology.

Furthermore, understanding comparative health risks from all types of toxic exposures to an individual during his/her lifetime (a cumulative exposure analysis) may aid in assigning relative risks or benefits from exposure to IR. Recently, the ‘exposome’ has been described as a measure of all lifetime risks (NIOSH 2014). An analysis of non-radiation exposures can be applied to radiation risk by examining the intersection of toxin-induced molecular pathways with low-dose IRinduced molecular changes, resulting in the development of mechanistic models that may be useful in predicting cumulative risk. A systems biology approach can be valuable as a framework to integrate these mechanistic data into risk assessments that are vital to protecting the general public (Locke 2009).

A path forward Today is the time for acknowledgement of new models within a systems biology framework. Application of a systems biology approach has the potential to create novel paradigms of radiation-induced biological effects that are determined by a combination of alterations at molecular, cellular and tissue levels of organization (Feinendegen et al. 2008; Locke 2009). New paradigms will be informed in part, by elucidation of mechanisms for adaptive responses in and intercellular signaling among hit cells, bystander cells and their progeny, and by the impact of these responses on radiogenic and non-radiogenic DNA damage in different tissues. These new paradigms, together with novel mathematical and mechanistic models, may be exploited to derive more realistic dose-effect relationships in the lowdose range, modify current risk estimates, and serve as information nodes from which radiation epidemiologists and radiobiologists can exchange their scientific data and create novel hypotheses. It is recognized that some of these techniques are likely to be more informative than others, and that their valuation and integration presents a challenge. It is therefore, time to encourage a dialogue among scientists in these disciplines, a dialogue that will shed new light on: (1) low dose, dose-rate effects on biological processes and human disease; (2) the relative values of models for DNA damage/misrepair, intercellular signaling, bystander effects, two-stage clonal expansion, molecular pathway-specific alterations, whole animal morbidity and mortality, and the combination of radiation plus nonradiation toxic exposures; and (3) how this plethora of new scientific data and mechanistic modeling can be used to reduce the magnitude of uncertainties required for prudent decision making.

In support of a forum for scientific dialogue, a meeting will be held on the topic of ‘Applicability of RadiationResponse Models to Low-Dose Protection Standards’ in TriCities, Washington, September 30–October 3, 2018 (http://

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www.anseasternwashington.org/lowdose-2018.html).

This meeting is timed to follow the 64th Annual Meeting of the Radiation Research Society, Chicago, IL, to permit radiation specialists to attend both conferences. The most recent developments in epidemiology and radiobiology will be discussed within a systems biology framework, with the goal of integrating knowledge from these important disciplines.

Representatives of key advisory groups such as UNSCEAR, NCRP and ICRP will be present, along with many members of the regulatory community. Protecting the public will be emphasized, and regulatory guidelines will be discussed.

Issues surrounding the valuable contributions and limitations of the LNT and threshold models will be examined, and presentation of models that can approximate the realities of biological risk will be encouraged. In addition to public fears of low-dose exposure, the costs of regulations and implications for the medical/industrial communities will be discussed. We believe that a systems-based, shared approach to evolving research will (1) transform the science of radiation effects, (2) encourage young scientists to enter our exciting field, (3) enhance the societal benefits of radiation use, and (4) improve understanding of radiation science throughout the world. Established investigators and young scientists are encouraged to present and discuss their research in the context of integration. The deadline for submission of abstracts is now extended to March 1, 2018. Early submittals are encouraged to permit scheduling of presentations on a plenary session.

Disclosure statement No potential conflict of interest was reported by the authors.

Notes on contributors Nicholas Dainiak, MD, FACP, is Medical and Technical Director, Radiation Assistance Center and Training Site (REAC=TS), Oak Ridge, TN, and Professor, Adjunct Faculty, Department of Therapeutic Radiology, Yale University School of Medicine, New Haven, CT. He previously served as Professor of Medicine and Chair, Department of Medicine, Yale New Haven Health – Bridgeport for 18 years. He has published over 300 original papers, book chapters, reviews and abstracts, and edited 7 books in hematopoietic stem cell biology and radiation biology.

Ludwig E. Feinendegen, MD, University of Cologne, Germany, worked at Brookhaven National Laboratory, NY, USA, at Euratom in Brussels, Belgium, and Institute du Radium, Paris, France, before becoming Full Professor, Nuclear Medicine, Heinrich-Heine-University Duesseldorf, and Research Center Juelich Germany. As Professor Emeritus, he was program manager, US Department of Energy, and then Fogarty Scholar at the US National Institutes of Health, remaining Guest Scientist, Brookhaven National Laboratory.

Dr. Randall N. Hyer is a leading risk and crisis communication expert with over 25 years’ practical experience in managing high-profile emergencies, organizational changes, and emotionally-charged crises. He has been at the front line of Zika, Ebola, bird flu, product failures, political campaigns, mergers, and nuclear emergencies. He has been a medical officer at the World Health Organization, and is Co-Founder=Principal, CrisisCommunication.net and Deputy Director, Center for Risk Communication.

Paul A. Locke is Associate Professor, Johns Hopkins Bloomberg School of Public Health. He holds doctoral and master’s degrees in environmental

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health studies, and a law degree. At Hopkins, Dr. Locke leads an integrated program on evidence-based, research-to-practice solutions for pressing environmental health problems. His research spans science and law, including evaluation of predictivity of in vitro models for hepatocarcinogenesis, personalized cancer risk assessments for space radiation exposures, and low dose radiation policy and decision-making.

Alan E. Waltar, PhD, is Past President and Fellow of the American Nuclear Society, Retired Professor and Chair, Department of Nuclear Engineering, Texas A&M University, and Retired Director of Nuclear Energy, Pacific Northwest National Laboratory. He has written four books, two textbooks on fast reactors and two non-technical radiation books for the general public. He helped found the Summer Institute for the World Nuclear University and has led People-to-People nuclear delegations to China and India.

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