Challenges for understanding and predicting ionizing-radiation

health effectsAndrea Ottolenghi

Dipartimento di Fisica Nucleare e Teorica, Università di Pavia and INFN, Pavia

Workshop

RADIAZIONI IONIZZANTI: NUOVI MODELLI PER LA STIMA DEL RISCHIO1 ottobre 2008 ENEA – Via Giulio Romano, 41 ROMA

Ente per le Nuove tecnologie,L’Energia e l’Ambiente

Sezione di Pavia

• to understand the mechanisms of radiation action on biological targets from physical interactions to biological damage, at sub-cellular, cellular, tissue, organ and systemic levels.

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General objective of Radiobiology:

• to predict radiation risk (cancer and non cancer)

• to optimize the clinical use of radiation (in diagnostics and therapy).

Examples of Applicationsa linear / no threshold [LNT]b downwardly curvingc upwardly curvingd thresholde hormetic

Barcellos-Hoff et al, Nature Reviews Cancer, 2005

≈ 100000 Ionisations≈ 2000 Ion. in DNA

1 Gy γ-rays in one nucleus

≈ 0.5-1 lethal events≈ 10-5 HPRT mut.≈ 10-5 neopl. trasf.

<< 10-5 cancers

≈ 0.5-1 Chrom. Ab.

≈ 1000 ssb≈ 40 dsb≈ 1-2 cl

Cross sections

Dissociation schemes

Diffusion coefficients

Reaction rate constants

≈2 nm

10-15 s

minutes

hours

10-6 s

10-12 s

yearsDamage at organ and organism levels

?

Irradiation

Excitations and Ionisations in the hit cell

Dissociation: production of radicals

Diffusion

Damage to DNA and other mol.

Damage at cell level•mutation•transformation•cell death•…………….

Chromosome aberrations

DNA breaks

Cell-to-cell communication

Bystandereffects

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Irradiated cell

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? ?

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Gen.inst.

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Barcellos-Hoff et al, Nature Reviews Cancer, 2005

Challenges for understanding and predicting ionizing-radiation health effects in humans:

to understand how cellular responses occurring in a multicellular context are integrated to produce an organismal response

to understand how the physical characteristics of different radiation qualities determine different initial damage and different damage evolutions

Ionizing radiation effects have to be studied as results of a perturbation of the cellular and supra-cellular systems with a multi-scale approach(Systems Radiation Biology) UNIPV-DFNT

Cross sections

Dissociation schemes

Diffusion coefficients

Reaction rate constants

≈2 nm

Damage at organ and organism levels

?

Irradiation

Excitations and Ionisations in the hit cell

Dissociation: production of radicals

Diffusion

Damage to DNA and other mol.

Damage at cell level•mutation•transformation•cell death•…………….

Chromosome aberrations

DNA breaks

Cell-to-cell communication

Bystandereffects

??????????

?

?

Irradiated cell

?

??

?

? ?

? ?

?

?

Gen.inst.

UNIPV-DFNTConcerning the dependence on the quality of radiation, we are very good in modelling and simulating:

- track structure- radical production, diffusion and interactions- DNA damage and its complexity- radiation induced chromosomal aberration

…..but we certainly need further studies to understand the damage evolution and particularly to relate the initial insult to the so-called “non-targeted” effects

Barcellos-Hoff et al, Nature Reviews Cancer, 2005

Challenges for understanding and predicting ionizing-radiation health effects in humans:

to understand how cellular responses occurring in a multicellular context are integrated to produce an organismal response

to understand how the physical characteristics of different radiation qualities determine different initial damage and different damage evolutions

Ionizing radiation effects have to be studied as results of a perturbation of the cellular and supra-cellular systems with a multi-scale approach(Systems Radiation Biology) UNIPV-DFNT

AdaptiveResponse

GenomicInstability

BystanderEffects

FROM BEIR VII (2006) Research Needs:• ….• Evaluation of the relevance of adaptation, low dose hypersensitivity,

bystander effect, and genomic instability for radiation carcinogenesis• ……

“NON-TARGETED” EFFECTSUNIPV-DFNT

Genomic instabilityUNIPV-DFNT

from W.F.Morgan, Rad. Res. 159 (2003)

Heritable, genome-wide process of instability that leads to a persisting enhanced frequency of genetic and functional changes in the non-

irradiated progeny

Prevailing paradigm

Genomic instability

Where observed (endpoints)

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• chromosomal alterations• changes in ploidy• micronucleus formation • gene mutations and amplifications• microsatellite instabilities• decreased plating efficiency

Genomic instabilityPossible mechanisms

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Probably directly induced DNA damage such as DSB is NOT an important mechanismDeficiencies in cellular response to DNA damageChanges in gene expressionPerturbation in cellular homeostasis………………….

The nucleus may be the ultimate target, BUT enhanced oxidative stress (and more generally extranuclear and even extracellular events) can play a role.

Loss of genomic stability is postulated as an early event in cancer that contributes to the genetic diversity observed in most solid cancers (Barcellos-Hoff and Brooks, 2001)

Goldberg and Lehnert, IJO, 2002

bystander effects:

a) consist of a potentially broad spectrum of responses that may be cell type specific,

b) can occur in a manner that may preclude predictive extrapolations from effects induced in directly irradiated cells,

c) may have either or both benign and detrimental effects,

d) can be communicated• by soluble transmissible factors, • by direct cell-cell communications

via gap junctions, • ………

Bystander effects: generalUNIPV-DFNT

Which are the initiating targets for the induction of “nontargeted”phenomena, such as the bystander effect?In other words: Which are the biological structures involved in the starting events leading to bystander effects?

The DNA of the hit cell?The membranes of the hit cell?Any specific cytoplasm constituent of the hit cell (e.g. mitocondria)?The extracellular microenvironment, including extracellular fluidsand the extracellular matrix (in vivo)?…………..

Bystander effect: Possible initiating targetsUNIPV-DFNT

• Ca++

• c-AMP (cyclic-AMP)• Antioxidants (thiols)• (long-lived) organic radicals• Nitric Oxide• ……………………..

• Cytokines, e.g.:- IL-6, IL-8, IL-10 (Interleukin-6, 8, 10)- TNFα (Tumor Necrosis Factor- α)- TGFβ (Tumor Growth Factor- β)

• Lipid peroxidation products• ……………………..

via Gap Junctions via Extracellular Environment

ROS (Reactive oxygen species: H2O2, O2 , etc.)

Bystander effect: Possible signals

_

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Trosko & Ruch1998, Frontiers in Bioscience3

Microenvironment and cell communication have been studied by biologists since

long time ago, but they have been extensively considered in

radiobiology only after bystander-effect observations!

Bystander effects studies: classical in vitro methods

≈5 Gy

Medium transfer Transwell insert culture dish

medium

Alpha particle irradiation

medium

a)

b)

9.5 mm

Alpha particle irradiation

In vivo studies

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Bystander effectUNIPV-DFNT

In vitro Phenomenology

Bystander effects is observed forcell death, both by clonogenic inactivation and by apoptosis endpoints that generally are not lethal for the cell, e.g.

- gene mutations- alterations in gene expression- cell oncogenic transformation- sister chromatid exchanges

Genomic Instability was observed in progeny of unirradiatedneighbours of irradiated cells since 1998 (Lorimore et al.)

• they appear at very low doses (≈ mGy)• dose-response is not linear (sharp initial increase + plateau)

• strong dependence on:● culture conditions (cell contact degree, medium

constituents…)● cell line (normal or tumoral, human or animal,

cell type, cell-cycle stage…)● particular observed endpoint● radiation quality and dose rate

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Bystander effectGeneral features

Bystander effectQuestions on the mechanisms underlying experimental evidence

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nature of the signal: protein-like molecules (cytokines, interleukines…) or small ions?

relative role of transmission via medium and via gap junctions

nature of the triggering event in the hit cell (DNA damage?)

role of radiation qualityrole of cell type: emission/reception of the signals are

cell-type specific; role of adaptive response: bystander mechanisms might

trigger an increase of cell resistance to low dose radiation

Bystander effectIn vivo BE (I)

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Example: the abscopal effect, term coined by Mole in 1953!!! From the Latin prefix “ab” (away from) and the Greek word “skopos” target).

Multiple case reports describing an abscopal effect observed after radiotherapy have been published with a variety of malignancies including lymphoma, papillary adenocarcinoma, melanoma, adenocarcinoma of the esophagus, chronic lymphocytic leukemia, and hepatocellular carcinoma(Camphausen et al, 2003),

but according to Goldberg and Lehnert (2002) the clinical literature did not yet provide strong evidence for or against the existence of radiation bystander effects, and by extension abscopal effects, in vivo.

Bystander effectIn vivo BE (II)

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Example: radiation induced clastogenic factors.

Plasma from irradiated animals and humans can contain “factors” capable of inducing damage in unexposed cells (with very large individualvaribility).

The precise nature of clastogenic factors isunknown, but endogenous viruses, interferencewith DNA repair, and/or the increased production of free radicals have all been implicated (Morgan, 2003)

Bystander effectIn vivo BE (III)

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2008

in vivo, is BE more likely to be a protective mechanism (aimed to eliminate groups of damaged/potentially damaged cells (e.g. tumor cells) to be substituted by new, undamaged cells), as suggested by the results with tissue explants (Belyakov et al) and modelled by Bauer?

If so, should we expect a sub-linearity in risk at low doses?

Or should we expect supralinearity (as suggested by Brenner)?

Or should we expect no influence for radiation risk?

Bystander effectUNIPV-DFNT

Why important (I): The question on in vivo scenarios

Bystander effect: Possible implicationsUNIPV-DFNT

Why important (2): The question on beneficial bystander effect• Signals emitted by radiation damaged cell (e.g. tranformed)

may induce selective apoptotic signals from intact cells?• Cell communication induced by radiation can selectively

remove tumor cells?

Possible natural anticancermechanism

Bauer et al. 2004 Portess et al. 2007

natural anticancer mechanismstimulated by low doses

Feedback and signal depletion(autocrine)

Signal degradationcytokine scavenger

(e.g. enzyme)

cell

Perturbing agents (radiation)

CULTURE MEDIUM

Signal release

Enzymes?

Example of cell communication and bystander effectmodelling in vitro (via soluble factors in the medium) (I)

cell

signal depletion(paracrine)

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General objective: to better understand the inter-cellular signaling mechanisms that might account for non-targeted effects in vitro.

Specific objectives: to develop a modeling approach able to reproduce/predict the release/motion/reception of candidate signals and their modulation by radiation.

Modeling approaches

Monte Carlo code: • investigation of local mechanisms•“single cytokine history”

Analytical model: “system biology approach” to determine key parameters in signaling mechanism

Stochastic approach Deterministic approach

Example of cell communication and bystander effectmodelling in vitro (via soluble factors in the medium) (II)

)t(N)t(k)t(kdt)t(dN

21 -=

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BUT: We need to interpret the in vitro observations to understand in which extent they can be used to understand in vivo phenomena!!

Feedback and signal depletion(autocrine)

Signal degradationcytokine scavenger

(e.g. enzyme)

cell

Perturbing agents (radiation)

CULTURE MEDIUM

Signal release

Enzymes?

cell

signal depletion(paracrine)

Example: in vivo half life of IL-6 is ∼ 4 hours,

in vitro it is ∼ 400 hours

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In vitroIn vivo

A BRIDGE BETWEEN CELL AND IN VIVO STUDIES: TISSUES (I)

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Stratum corneum

Basal Cell Layer

LEAD SHIELDING

signalling

radiation

To be measured and modelled: processes (particularly signalling) and endpoints

Human keratinocytes, isolated from adult skin, to generate an epidermal construct on a collagen layer alone.

The stratification of keratinocytes generated 3-dimensional synthetic constructs displaying a tissue architecture comparable with that of natural epidermis. Epithelial cells expressed specific markers of keratinocyte terminal differentiation.

Riva F, et al. Tissue Eng. 2007

differentiation

A BRIDGE BETWEEN CELL AND IN VIVO STUDIES: TISSUES (II)

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Irradiatedplane

TISSUES (3)UNIPV-DFNT

1) Collimated or micro- beams can be used, allowing irradiation of cells in defined area of the tissue

2) Unirradiated cells distant from irradiated cells can be investigated, through morphological analysis and immunohistochemistry on serial sections (paraffin embedded and/or frozen) of the tissue in order to evaluate (experimentally and theoretically):

→ the propagation of the signals and associated mechanisms (modelled considering that signallingmolecules can rapidly propagate from irradiated cells to unirradiated cells and their concentration decrease as distance increases).

→ the effects on the cell status and associated processes (the bystander signal can convert cells to a long-lived epigenetically activated state).

TISSUES (4)UNIPV-DFNT

Bystander effectIn vivo

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2008

The experimental results suggest that:• the nature of long-term bystander responses may be tissue specific.• only actively dividing cells were susceptible to bystander effects. In vivo results in mouse

CNS confirm that the proliferative or differentiation state is important for expression of bystander damage.

• a Cx43-mediated gap-junction transfer of the bystander signal in vivo mediates short-term cellular responses that may subsequently trigger long-term carcinogenic effects in mouse CNS. In fact, by TPA-mediated inhibition of GJICs suppression of bystander responses for both endpoints were shown.

• inflammation/oxidative stress is not central in the effects observed (suppression of COX-2 activity in bystander cerebellum by the chemical inhibitor nimesulide did not influence bystander damage)

Adaptive response (and bystander effect)• Adaptive response: the exposure to a low level of radiation

(“priming dose”) seems to render cells resistant to a subsequent exposure (“challenging dose”). This might reduce the effect of radiation (particularly at low doses).

• Bystander effect and adaptive response are probably strictly related by the fundamental role of cell communication and the associatedsignalling systems

Both are phenomena that seem to be of particular importance at low doses and may have a significant impact on the shape of the dose–response relationship

Both phenomena may have completely different characteristics with different qualities of radiation

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priming dose challenging dose

Effe

tto

, ,

priming dose = γ-rays; medium from irradiated cellschallenging dose = γ-rays; charged particlesend point = DNA damage, micronuclei induction and/or clonogenic inattivation

ADAPTIVE RESPONSE – typical cell experiment

ISS, Rome

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Proposed mechanism to be investigated:

• Increased efficiency of DNA repair

• Induction of anti-oxidant enzymes

• Alteration of cell cycle progression• Chromatin conformation change that increases resistance to indirect

damage

A possible model considers, in its first stage, a modulation of the efficiency of DNA repair activity and of the level of anti-oxidant enzymes. This modulation would be active only in given, correlated, ranges of dose and dose rates.

ADAPTIVE RESPONSE

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“Conclusions”We need a common effort (both theoretical and experimental) to better understand mechanisms (and quantify the role) of radiation induced phenomena such as:• Genomic instability• Bystander effects and

cell communication• Adaptive response• Low―dose hyper—radiosensitivity•………………………

Some of the dogmas of radiation science might have to be reviewed and brought into question. These phenomena can strongly influence the different possible extrapolations of measured radiation risks (cancer and non cancer) down to very low doses, and can have important implications for radiation protection and radiation therapy (particularly with high LET hadrons).

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a linear / no threshold [LNT]b downwardly curvingc upwardly curvingd thresholde hormetic

EPICA (2006-2008) - Effects of charged particles: mechanisms of induction of molecular damage and modulation of intercellular signalling”

COUNT-MoMa (2006-2009) - Countermeasures For The Exposure To Galactic Cosmic Rays In Deep Space

RISC-RAD (2004-2008) - DNA damage responses, genomic instability and radiation-induced cancer: the problem of risk at low and protracted doses

NOTE (2006-2010) - Non-targeted effects of ionising radiation

ALLEGRO (Negotiation stage – probable starting date: 2009) - Early and late health risks to normal/healthy tissues from the use of existing and emerging techniques for radiation therapy

AcknowledgementsUNIPV-DFNT

Thank you for your attention

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Bystander effectUNIPV-DFNT

Questions we need to go into in more depth, relative to cell communication and bystander effects

Specific of radiation-induced bystander effects:• nature of initial lesion(s) triggering bystander response • nature of possible communication pathways (e.g.

medium, gap junctions etc.)• nature of signalling molecules

General (for cancer risk): role of radiation in modulating (intra and inter) cell signalling, thus modifying the ability to control:

• proliferation• differentiation• apoptosis

Basic approaches of RISC-RAD modelling groupto develop mechanistic models at cell/tissue level in

order to understand the mechanisms and study the influence of BE on radiation damage (e.g. GSF, UNIPV, etc.)

relations between BE, genomic instability and adaptive response

in parallel, to incorporate phenomenological descriptions of BE into (already existing) models of carcinogenesis (e.g. ICSM, USALZ, GSF, etc.), in order to draw conclusions on radiation risk at low doses

The final goal is to combine mechanistic and phenomenological approaches to generate robust risk models

RISC-RAD European Consortium – Bystander and genomic instability modelling groupUNIPV-DFNT

An example of modelling approach:The BaD Approach (D. Brenner)

Bystander effectUNIPV-DFNT

Conclusions (I)General:Mechanistic ab initio models and simulations are fundamental

tools to understand the role of stochastic phenomena and of the different mechanisms leading to radiation damage

Specific:1) Monte Carlo simulations with PARTRAC code allow the

quantification of the protective effects and the relative roles of scavengers and DNA structures (typically chromatin folding and histones) in the induction of single- and double-strand breaks.

2) Both the complexity of DNA damage (nm scale) and the spatial distribution of CL (μm scale) play a fundamental role in chromosome aberration induction

3) In specific cases, models and simulation codes for chromosome aberration modelling can be used for predicting cancer risk.

but …………………….

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“New” Challenging topics(e.g. “nontargeted” and delayed effects)

Genomic instability

from W.F.Morgan, Rad. Res. 159 (2003)

Heritable, genome-wide process of instability that leads to a persisting enhanced frequency of genetic and functional changes in the non-irradiated progeny

Radiation induced bystander effect:Damage induction in cells not directly hit by radiation

Goldberg and Lehnert, IJO, 2002

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EXAMPLES OF PAPERS ON RADIATION-INDUCED BYSTANDER-EFFECT MODELLING

• Brenner et al. 2001, The bystander effect in radiation oncogenesis: II. A quantitative model.Radiat Res 155, 402

• Little & Wakeford 2001, The bystander effect in C3H10T1/2 cells and radon-induced lung cancer.Radiat Res 156, 695

• Nikjoo & Khvostunov 2003, Biophysical model of the radiation-induced bystander effect. Int J Radiat Biol 79, 43

• Scott 2004, A biological-based model that links genomic instability, bystander effects, and adaptive response. Mutat Res 568, 129

• Sachs et al. 2005, Modeling intercellular interactions during carcinogenesis. RadiatRes 164, 324

• Little et al. 2005, A model for radiation-induced bystander effects, with allowance for spatial position and the effects of cell turnover.J Theor Biol 232, 329

• Ballarini F, Alloni D, Facoetti A, Mairani A, Nano R and Ottolenghi A. 2006, Modelling radiation-induced bystander effect and cellular communication. Radiat Prot Dosim122, 244

• Stewart et al. 2006, Microdosimetric model for the induction of cell killing through medium-borne signals. Radiat Res 165, 460

• Richard et al. 2007, A mathematical model of response of cells to radiation. Nucl InstrMeth B 255, 18

• Schöllnberger et al. 2007, Detrimental and protective bystander effects: a model approach. Radiat Res 168, 614

• Shuryak et al. 2007, Biophysical models of radiation bystander effects: 1. Spatial effects in three-dimensional tissues. Radiat Res 168, 741

• Facoetti A, Ballarini F, Bertolotti A, Mariotti L, Nano R, Pasi F and Ottolenghi A 2008, Hotspots for experimentalists and modellers to study cytokine release for radiation induced bystander effect. Submitted to IntJ Radiat Biol