Literature DB >> 30407901

A New Standard DNA Damage (SDD) Data Format.

J Schuemann1, A L McNamara1, J W Warmenhoven2, N T Henthorn2, K J Kirkby2, M J Merchant2, S Ingram2, H Paganetti1, K D Held1, J Ramos-Mendez3, B Faddegon3, J Perl4, D T Goodhead5, I Plante6, H Rabus7,8, H Nettelbeck7,8, W Friedland8,9, P Kundrát9, A Ottolenghi10, G Baiocco8,10, S Barbieri8,10, M Dingfelder11, S Incerti12,13, C Villagrasa8,14, M Bueno14, M A Bernal15, S Guatelli16, D Sakata16, J M C Brown17, Z Francis18, I Kyriakou19, N Lampe12, F Ballarini10,20, M P Carante10,20, M Davídková21, V Štěpán21, X Jia22, F A Cucinotta23, R Schulte24, R D Stewart25, D J Carlson26, S Galer27, Z Kuncic28, S Lacombe29, J Milligan30, S H Cho31, G Sawakuchi31, T Inaniwa32, T Sato33, W Li9,34, A V Solov'yov35, E Surdutovich36, M Durante37, K M Prise38, S J McMahon38.   

Abstract

Our understanding of radiation-induced cellular damage has greatly improved over the past few decades. Despite this progress, there are still many obstacles to fully understand how radiation interacts with biologically relevant cellular components, such as DNA, to cause observable end points such as cell killing. Damage in DNA is identified as a major route of cell killing. One hurdle when modeling biological effects is the difficulty in directly comparing results generated by members of different research groups. Multiple Monte Carlo codes have been developed to simulate damage induction at the DNA scale, while at the same time various groups have developed models that describe DNA repair processes with varying levels of detail. These repair models are intrinsically linked to the damage model employed in their development, making it difficult to disentangle systematic effects in either part of the modeling chain. These modeling chains typically consist of track-structure Monte Carlo simulations of the physical interactions creating direct damages to DNA, followed by simulations of the production and initial reactions of chemical species causing so-called "indirect" damages. After the induction of DNA damage, DNA repair models combine the simulated damage patterns with biological models to determine the biological consequences of the damage. To date, the effect of the environment, such as molecular oxygen (normoxic vs. hypoxic), has been poorly considered. We propose a new standard DNA damage (SDD) data format to unify the interface between the simulation of damage induction in DNA and the biological modeling of DNA repair processes, and introduce the effect of the environment (molecular oxygen or other compounds) as a flexible parameter. Such a standard greatly facilitates inter-model comparisons, providing an ideal environment to tease out model assumptions and identify persistent, underlying mechanisms. Through inter-model comparisons, this unified standard has the potential to greatly advance our understanding of the underlying mechanisms of radiation-induced DNA damage and the resulting observable biological effects when radiation parameters and/or environmental conditions change.

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Year:  2018        PMID: 30407901      PMCID: PMC6407706          DOI: 10.1667/RR15209.1

Source DB:  PubMed          Journal:  Radiat Res        ISSN: 0033-7587            Impact factor:   2.841


  19 in total

1.  A parameter sensitivity study for simulating DNA damage after proton irradiation using TOPAS-nBio.

Authors:  Hongyu Zhu; Aimee L McNamara; Jose Ramos-Mendez; Stephen J McMahon; Nicholas T Henthorn; Bruce Faddegon; Kathryn D Held; Joseph Perl; Junli Li; Harald Paganetti; Jan Schuemann
Journal:  Phys Med Biol       Date:  2020-04-23       Impact factor: 3.609

Review 2.  Modelling variable proton relative biological effectiveness for treatment planning.

Authors:  Aimee McNamara; Henning Willers; Harald Paganetti
Journal:  Br J Radiol       Date:  2019-11-18       Impact factor: 3.039

3.  Cellular Response to Proton Irradiation: A Simulation Study with TOPAS-nBio.

Authors:  Hongyu Zhu; Aimee L McNamara; Stephen J McMahon; Jose Ramos-Mendez; Nicholas T Henthorn; Bruce Faddegon; Kathryn D Held; Joseph Perl; Junli Li; Harald Paganetti; Jan Schuemann
Journal:  Radiat Res       Date:  2020-07-08       Impact factor: 2.841

Review 4.  Applications of nanodosimetry in particle therapy planning and beyond.

Authors:  Antoni Rucinski; Anna Biernacka; Reinhard Schulte
Journal:  Phys Med Biol       Date:  2021-12-10       Impact factor: 3.609

5.  Impact of DNA Geometry and Scoring on Monte Carlo Track-Structure Simulations of Initial Radiation-Induced Damage.

Authors:  Alejandro Bertolet; José Ramos-Méndez; Aimee McNamara; Dohyeon Yoo; Samuel Ingram; Nicholas Henthorn; John-William Warmenhoven; Bruce Faddegon; Michael Merchant; Stephen J McMahon; Harald Paganetti; Jan Schuemann
Journal:  Radiat Res       Date:  2022-09-01       Impact factor: 3.372

6.  Multi-scale Monte Carlo simulations of gold nanoparticle-induced DNA damages for kilovoltage X-ray irradiation in a xenograft mouse model using TOPAS-nBio.

Authors:  Alexander P Klapproth; Jan Schuemann; Stefan Stangl; Tianwu Xie; Wei Bo Li; Gabriele Multhoff
Journal:  Cancer Nanotechnol       Date:  2021-10-24

7.  TOPAS-nBio: An Extension to the TOPAS Simulation Toolkit for Cellular and Sub-cellular Radiobiology.

Authors:  J Schuemann; A L McNamara; J Ramos-Méndez; J Perl; K D Held; H Paganetti; S Incerti; B Faddegon
Journal:  Radiat Res       Date:  2019-01-04       Impact factor: 2.841

8.  Mechanistic Modelling of Slow and Fast NHEJ DNA Repair Pathways Following Radiation for G0/G1 Normal Tissue Cells.

Authors:  Yaping Qi; John William Warmenhoven; Nicholas Thomas Henthorn; Samuel Peter Ingram; Xie George Xu; Karen Joy Kirkby; Michael John Merchant
Journal:  Cancers (Basel)       Date:  2021-05-03       Impact factor: 6.639

9.  Recent Developments on gMicroMC: Transport Simulations of Proton and Heavy Ions and Concurrent Transport of Radicals and DNA.

Authors:  Youfang Lai; Xun Jia; Yujie Chi
Journal:  Int J Mol Sci       Date:  2021-06-21       Impact factor: 5.923

10.  A Mechanistic DNA Repair and Survival Model (Medras): Applications to Intrinsic Radiosensitivity, Relative Biological Effectiveness and Dose-Rate.

Authors:  Stephen Joseph McMahon; Kevin M Prise
Journal:  Front Oncol       Date:  2021-06-29       Impact factor: 6.244

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