Literature DB >> 12556330

Biophysical model of the radiation-induced bystander effect.

Hooshang Nikjoo1, Igor K Khvostunov.   

Abstract

PURPOSE: To construct a quantitative model of the radiation-induced bystander effect based on diffusion-type spreading of bystander signal communication between the hit and non-hit cells. Cell inactivation and induced oncogenic transformation by broad- and microbeam irradiation systems are considered.
MATERIALS AND METHODS: The biophysical model ByStander Diffusion Modelling (BSDM) postulates that the oncogenic bystander response observed in non-hit cells originates from specific signals received from inactivated cells. The bystander signals are assumed to be protein-like molecules spreading in the culture media by Brownian motion. The bystander signals are assumed to switch cells into a state of cell death (apoptotic/mitotic/necrosis) or induced oncogenic transformation modes.
RESULTS: The bystander cell survival observed after treatment with the irradiated conditioned medium (ICM) using the broad-beam and the microbeam irradiation modalities were analysed and interpreted in the framework of the BSDM model. The model predictions for cell inactivation and induced oncogenic transformation frequencies agree well with observed data from micro and broad-beam experiments. In the case of irradiation with constant fraction of cells, transformation frequency for the bystander effect increases with increasing radiation dose.
CONCLUSIONS: Bystander modelling based on diffusion of signals is in good agreement with experimental cell survival data and induced oncogenic transformation frequencies. The data confirm the protein-like nature of the bystander signal. Linear extrapolation of the cell response to low doses of radiation might underestimate carcinogenic risk, for example for domestic radon hazards, if the contribution from the bystander effect is neglected. The BSDM predicts that the bystander effect cannot be interpreted solely as a low-dose effect phenomenon. It is shown that the bystander component of radiation response can increase with dose and be observed at high doses as well as at low doses. The validity of this conclusion is supported by analysis of experimental results from high-linear energy transfer microbeam experiments.

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Year:  2003        PMID: 12556330

Source DB:  PubMed          Journal:  Int J Radiat Biol        ISSN: 0955-3002            Impact factor:   2.694


  21 in total

1.  Computational modeling of signaling pathways mediating cell cycle checkpoint control and apoptotic responses to ionizing radiation-induced DNA damage.

Authors:  Yuchao Zhao; In Chio Lou; Rory B Conolly
Journal:  Dose Response       Date:  2011-10-25       Impact factor: 2.658

2.  Modeling cell response to low doses of photon irradiation: Part 2--application to radiation-induced chromosomal aberrations in human carcinoma cells.

Authors:  Micaela Cunha; Etienne Testa; Olga V Komova; Elena A Nasonova; Larisa A Mel'nikova; Nina L Shmakova; Michaël Beuve
Journal:  Radiat Environ Biophys       Date:  2015-12-26       Impact factor: 1.925

3.  Protective bystander effects simulated with the state-vector model.

Authors:  Helmut Schöllnberger; Peter M Eckl
Journal:  Dose Response       Date:  2007-06-26       Impact factor: 2.658

4.  Computational modeling of cellular effects post-irradiation with low- and high-let particles and different absorbed doses.

Authors:  Adriana Alexandre S Tavares; João Manuel R S Tavares
Journal:  Dose Response       Date:  2012-03-19       Impact factor: 2.658

Review 5.  Health risks of space exploration: targeted and nontargeted oxidative injury by high-charge and high-energy particles.

Authors:  Min Li; Géraldine Gonon; Manuela Buonanno; Narongchai Autsavapromporn; Sonia M de Toledo; Debkumar Pain; Edouard I Azzam
Journal:  Antioxid Redox Signal       Date:  2013-12-06       Impact factor: 8.401

6.  Effect of site-specific bronchial radon progeny deposition on the spatial and temporal distributions of cellular responses.

Authors:  Arpád Farkas; Werner Hofmann; Imre Balásházy; István Szoke; Balázs G Madas; Mona Moustafa
Journal:  Radiat Environ Biophys       Date:  2011-02-15       Impact factor: 1.925

7.  A reaction-diffusion model for radiation-induced bystander effects.

Authors:  Oluwole Olobatuyi; Gerda de Vries; Thomas Hillen
Journal:  J Math Biol       Date:  2016-12-29       Impact factor: 2.259

8.  On the Inclusion of Short-distance Bystander Effects into a Logistic Tumor Control Probability Model.

Authors:  David G Tempel; N Patrik Brodin; Wolfgang A Tomé
Journal:  Cureus       Date:  2018-01-01

Review 9.  Current knowledge on tumour induction by computed tomography should be carefully used.

Authors:  Cristian Candela-Juan; Alegría Montoro; Enrique Ruiz-Martínez; Juan Ignacio Villaescusa; Luis Martí-Bonmatí
Journal:  Eur Radiol       Date:  2013-11-27       Impact factor: 5.315

10.  Detrimental and protective bystander effects: a model approach.

Authors:  H Schöllnberger; R E J Mitchel; J L Redpath; D J Crawford-Brown; W Hofmann
Journal:  Radiat Res       Date:  2007-11       Impact factor: 2.841

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