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Parisi A, Beltran CJ, Furutani KM. Variable RBE in proton radiotherapy: a comparative study with the predictive Mayo Clinic Florida microdosimetric kinetic model and phenomenological models of cell survival. Phys Med Biol 2023; 68:185020. [PMID: 38133518 DOI: 10.1088/1361-6560/acf43b] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2023] [Accepted: 08/25/2023] [Indexed: 12/23/2023]
Abstract
Objectives. (1) To examine to what extent the cell- and exposure- specific information neglected in the phenomenological proton relative biological effectiveness (RBE) models could influence the computed RBE in proton therapy. (2) To explore similarities and differences in the formalism and the results between the linear energy transfer (LET)-based phenomenological proton RBE models and the microdosimetry-based Mayo Clinic Florida microdosimetric kinetic model (MCF MKM). (3) To investigate how the relationship between the RBE and the dose-mean proton LET is affected by the proton energy spectrum and the secondary fragments.Approach. We systematically compared six selected phenomenological proton RBE models with the MCF MKM in track-segment simulations, monoenergetic proton beams in a water phantom, and two spread-out Bragg peaks. A representative comparison within vitrodata for human glioblastoma cells (U87 cell line) is also included.Main results. Marked differences were observed between the results of the phenomenological proton RBE models, as reported in previous studies. The dispersion of these models' results was found to be comparable to the spread in the MCF MKM results obtained by varying the cell-specific parameters neglected in the phenomenological models. Furthermore, while single cell-specific correlation between RBE and the dose-mean proton LET seems reasonable above 2 keVμm-1, caution is necessary at lower LET values due to the relevant contribution of secondary fragments. The comparison within vitrodata demonstrates comparable agreement between the MCF MKM predictions and the results of the phenomenological models.Significance. The study highlights the importance of considering cell-specific characteristics and detailed radiation quality information for accurate RBE calculations in proton therapy. Furthermore, these results provide confidence in the use of the MCF MKM for clonogenic survival RBE calculations in proton therapy, offering a more mechanistic approach compared to phenomenological models.
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Affiliation(s)
- Alessio Parisi
- Department of Radiation Oncology, Mayo Clinic, Jacksonville, FL, United States of America
| | - Chris J Beltran
- Department of Radiation Oncology, Mayo Clinic, Jacksonville, FL, United States of America
| | - Keith M Furutani
- Department of Radiation Oncology, Mayo Clinic, Jacksonville, FL, United States of America
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Warmenhoven JW, Henthorn NT, McNamara AL, Ingram SP, Merchant MJ, Kirkby KJ, Schuemann J, Paganetti H, Prise KM, McMahon SJ. Effects of Differing Underlying Assumptions in In Silico Models on Predictions of DNA Damage and Repair. Radiat Res 2023; 200:509-522. [PMID: 38014593 DOI: 10.1667/rade-21-00147.1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2021] [Accepted: 10/05/2023] [Indexed: 11/29/2023]
Abstract
The induction and repair of DNA double-strand breaks (DSBs) are critical factors in the treatment of cancer by radiotherapy. To investigate the relationship between incident radiation and cell death through DSB induction many in silico models have been developed. These models produce and use custom formats of data, specific to the investigative aims of the researchers, and often focus on particular pairings of damage and repair models. In this work we use a standard format for reporting DNA damage to evaluate combinations of different, independently developed, models. We demonstrate the capacity of such inter-comparison to determine the sensitivity of models to both known and implicit assumptions. Specifically, we report on the impact of differences in assumptions regarding patterns of DNA damage induction on predicted initial DSB yield, and the subsequent effects this has on derived DNA repair models. The observed differences highlight the importance of considering initial DNA damage on the scale of nanometres rather than micrometres. We show that the differences in DNA damage models result in subsequent repair models assuming significantly different rates of random DSB end diffusion to compensate. This in turn leads to disagreement on the mechanisms responsible for different biological endpoints, particularly when different damage and repair models are combined, demonstrating the importance of inter-model comparisons to explore underlying model assumptions.
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Affiliation(s)
- John W Warmenhoven
- Division of Cancer Sciences, University of Manchester, Manchester, United Kingdom
- The Christie NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, United Kingdom
| | - Nicholas T Henthorn
- Division of Cancer Sciences, University of Manchester, Manchester, United Kingdom
- The Christie NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, United Kingdom
| | - Aimee L McNamara
- Physics Division, Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Massachusetts
| | - Samuel P Ingram
- Division of Cancer Sciences, University of Manchester, Manchester, United Kingdom
- Christie Medical Physics and Engineering, The Christie NHS Foundation Trust, Manchester, United Kingdom
| | - Michael J Merchant
- Division of Cancer Sciences, University of Manchester, Manchester, United Kingdom
- The Christie NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, United Kingdom
| | - Karen J Kirkby
- Division of Cancer Sciences, University of Manchester, Manchester, United Kingdom
- The Christie NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, United Kingdom
| | - Jan Schuemann
- Physics Division, Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Massachusetts
| | - Harald Paganetti
- Physics Division, Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Massachusetts
| | - Kevin M Prise
- Patrick G Johnston Centre for Cancer Research, Queen's University Belfast, Belfast, United Kingdom
| | - Stephen J McMahon
- Patrick G Johnston Centre for Cancer Research, Queen's University Belfast, Belfast, United Kingdom
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Rumiantcev M, Li WB, Lindner S, Liubchenko G, Resch S, Bartenstein P, Ziegler SI, Böning G, Delker A. Estimation of relative biological effectiveness of 225Ac compared to 177Lu during [ 225Ac]Ac-PSMA and [ 177Lu]Lu-PSMA radiopharmaceutical therapy using TOPAS/TOPAS-nBio/MEDRAS. EJNMMI Phys 2023; 10:53. [PMID: 37695374 PMCID: PMC10495309 DOI: 10.1186/s40658-023-00567-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2023] [Accepted: 08/07/2023] [Indexed: 09/12/2023] Open
Abstract
AIM Over recent years, [225Ac]Ac-PSMA and [177Lu]Lu-PSMA radiopharmaceutical therapy have evolved as a promising treatment option for advanced prostate cancer. Especially for alpha particle emitter treatments, there is still a need for improving dosimetry, which requires accurate values of relative biological effectiveness (RBE). To achieve that, consideration of DNA damages in the cell nucleus and knowledge of the energy deposition in the location of the DNA at the nanometer scale are required. Monte Carlo particle track structure simulations provide access to interactions at this level. The aim of this study was to estimate the RBE of 225Ac compared to 177Lu. The initial damage distribution after radionuclide decay and the residual damage after DNA repair were considered. METHODS This study employed the TOol for PArtcile Simulation (TOPAS) based on the Geant4 simulation toolkit. Simulation of the nuclear DNA and damage scoring were performed using the TOPAS-nBio extension of TOPAS. DNA repair was modeled utilizing the Python-based program MEDRAS (Mechanistic DNA Repair and Survival). Five different cell geometries of equal volume and two radionuclide internalization assumptions as well as two cell arrangement scenarios were investigated. The radionuclide activity (number of source points) was adopted based on SPECT images of patients undergoing the above-mentioned therapies. RESULTS Based on the simulated dose-effect curves, the RBE of 225Ac compared to 177Lu was determined in a wide range of absorbed doses to the nucleus. In the case of spherical geometry, 3D cell arrangement and full radionuclide internalization, the RBE based on the initial damage had a constant value of approximately 2.14. Accounting for damage repair resulted in RBE values ranging between 9.38 and 1.46 for 225Ac absorbed doses to the nucleus between 0 and 50 Gy, respectively. CONCLUSION In this work, the consideration of DNA repair of the damage from [225Ac]Ac-PSMA and [177Lu]Lu-PSMA revealed a dose dependency of the RBE. Hence, this work suggested that DNA repair is an important aspect to understand response to different radiation qualities.
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Affiliation(s)
- Mikhail Rumiantcev
- Department of Nuclear Medicine, LMU University Hospital, LMU Munich, Munich, Germany.
| | - Wei Bo Li
- Federal Office for Radiation Protection, Medical and Occupational Radiation Protection, Oberschleißheim, Germany
| | - Simon Lindner
- Department of Nuclear Medicine, LMU University Hospital, LMU Munich, Munich, Germany
| | - Grigory Liubchenko
- Department of Nuclear Medicine, LMU University Hospital, LMU Munich, Munich, Germany
| | - Sandra Resch
- Department of Nuclear Medicine, LMU University Hospital, LMU Munich, Munich, Germany
| | - Peter Bartenstein
- Department of Nuclear Medicine, LMU University Hospital, LMU Munich, Munich, Germany
| | - Sibylle I Ziegler
- Department of Nuclear Medicine, LMU University Hospital, LMU Munich, Munich, Germany
| | - Guido Böning
- Department of Nuclear Medicine, LMU University Hospital, LMU Munich, Munich, Germany
| | - Astrid Delker
- Department of Nuclear Medicine, LMU University Hospital, LMU Munich, Munich, Germany
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Han Y, Geng C, Liu Y, Wu R, Li M, Yu C, Altieri S, Tang X. Calculation of the DNA damage yield and relative biological effectiveness in boron neutron capture therapy via the Monte Carlo track structure simulation. Phys Med Biol 2023; 68:175028. [PMID: 37524085 DOI: 10.1088/1361-6560/acec2a] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2023] [Accepted: 07/31/2023] [Indexed: 08/02/2023]
Abstract
Objective.Boron neutron capture therapy (BNCT) is an advanced cellular-level hadron therapy that has exhibited remarkable therapeutic efficacy in the treatment of locally invasive malignancies. Despite its clinical success, the intricate nature of relative biological effectiveness (RBE) and mechanisms responsible for DNA damage remains elusive. This work aims to quantify the RBE of compound particles (i.e. alpha and lithium) in BNCT based on the calculation of DNA damage yields via the Monte Carlo track structure (MCTS) simulation.Approach. The TOPAS-nBio toolkit was employed to conduct MCTS simulations. The calculations encompassed four steps: determination of the angle and energy spectra on the nuclear membrane, quantification of the database containing DNA damage yields for ions with specific angle and energy, accumulation of the database and spectra to obtain the DNA damage yields of compound particles, and calculation of the RBE by comparison yields of double-strand break (DSB) with the reference gamma-ray. Furthermore, the impact of cell size and microscopic boron distribution was thoroughly discussed.Main results. The DSB yields induced by compound particles in three types of spherical cells (radius equal to 10, 8, and 6μm) were found to be 13.28, 17.34, 22.15 Gy Gbp-1for boronophenylalanine (BPA), and 1.07, 3.45, 8.32 Gy Gbp-1for sodium borocaptate (BSH). The corresponding DSB-based RBE values were determined to be 1.90, 2.48, 3.16 for BPA and 0.15, 0.49, 1.19 for BSH. The calculated DSB-based RBE showed agreement with experimentally values of compound biological effectiveness for melanoma and gliosarcoma. Besides, the DNA damage yield and DSB-based RBE value exhibited an increasing trend as the cell radius decreased. The impact of the boron concentration ratio on RBE diminished once the drug enrichment surpasses a certain threshold.Significance. This work is potential to provide valuable guidance for accurate biological-weighted dose evaluation in BNCT.
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Affiliation(s)
- Yang Han
- Department of Nuclear Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, People's Republic of China
- Department of Physics, University of Pavia, Pavia, Italy
| | - Changran Geng
- Department of Nuclear Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, People's Republic of China
| | - Yuanhao Liu
- Department of Nuclear Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, People's Republic of China
- Neuboron Medtech. Ltd, Nanjing, People's Republic of China
| | - Renyao Wu
- Department of Nuclear Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, People's Republic of China
| | - Mingzhu Li
- Department of Nuclear Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, People's Republic of China
| | - Chenxi Yu
- Department of Nuclear Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, People's Republic of China
| | - Saverio Altieri
- Department of Physics, University of Pavia, Pavia, Italy
- Istituto Nazionale di Fisica Nucleare (INFN), the section of Pavia, Pavia, Italy
| | - Xiaobin Tang
- Department of Nuclear Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, People's Republic of China
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Suárez-García D, Cortés-Giraldo MA, Bertolet A. A systematic analysis of the particle irradiation data ensemble in the key of the microdosimetric kinetic model: Should clonogenic data be used for clinical relative biological effectiveness? Radiother Oncol 2023; 185:109730. [PMID: 37301260 PMCID: PMC10528084 DOI: 10.1016/j.radonc.2023.109730] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2022] [Revised: 05/20/2023] [Accepted: 05/31/2023] [Indexed: 06/12/2023]
Abstract
PURPOSE To perform a systematic analysis of the Particle Irradiation Data Ensemble (PIDE) database for clonogenic survival assays in the context of the Microdosimetric Kinetic Model (MKM). METHODS AND MATERIAL Our study used data from the PIDE database containing data on various cell lines and radiation types. Two main parameters of the MKM were determined experiment-wise: the domain radius, which accounts for the increase of the linear parameter as a function of LET or lineal energy, and the nucleus radius, which accounts for the overkilling effect at LET high enough. We used experiments with LET less and more than 75 keV/μm to determine domain and nucleus radius, respectively. Experiments with cells in asynchronous phase of the cell cycle and monoenergetic beams were considered, and data from 294 out of 461 available experiments with protons, alpha, and carbon beams were used. RESULTS Domain and nucleus radii were determined for 32 cell lines as the median among cell-specific experiments after filtering experiments using protons, α-particles, and carbon ions, including 28 human cells and 12 rodent cells. The median values found for domain radii were 380 nm for normal human cells, 390 nm for tumor human cells, 295 nm for normal rodent cells, and 525 nm for tumor rodent cells (only one experiment with rodent tumor cells) with large variability across cell lines and across experiments on each cell line. CONCLUSIONS Large inter-experiment variabilities were found for the same cell lines, based on enormous experimental uncertainties and different experimental conditions. Our analysis raises questions about how convenient is to use clonogenic data to feed RBE models to be utilized in the clinical practice in particle therapy.
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Affiliation(s)
- Daniel Suárez-García
- Departamento de Física Nuclear, Atómica y Molecular, Universidad de Sevilla, Sevilla, Spain
| | | | - Alejandro Bertolet
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
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Guerra Liberal FDC, Thompson SJ, Prise KM, McMahon SJ. High-LET radiation induces large amounts of rapidly-repaired sublethal damage. Sci Rep 2023; 13:11198. [PMID: 37433844 PMCID: PMC10336062 DOI: 10.1038/s41598-023-38295-3] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2022] [Accepted: 07/06/2023] [Indexed: 07/13/2023] Open
Abstract
There is agreement that high-LET radiation has a high Relative Biological Effectiveness (RBE) when delivered as a single treatment, but how it interacts with radiations of different qualities, such as X-rays, is less clear. We sought to clarify these effects by quantifying and modelling responses to X-ray and alpha particle combinations. Cells were exposed to X-rays, alpha particles, or combinations, with different doses and temporal separations. DNA damage was assessed by 53BP1 immunofluorescence, and radiosensitivity assessed using the clonogenic assay. Mechanistic models were then applied to understand trends in repair and survival. 53BP1 foci yields were significantly reduced in alpha particle exposures compared to X-rays, but these foci were slow to repair. Although alpha particles alone showed no inter-track interactions, substantial interactions were seen between X-rays and alpha particles. Mechanistic modelling suggested that sublethal damage (SLD) repair was independent of radiation quality, but that alpha particles generated substantially more sublethal damage than a similar dose of X-rays, [Formula: see text]. This high RBE may lead to unexpected synergies for combinations of different radiation qualities which must be taken into account in treatment design, and the rapid repair of this damage may impact on mechanistic modelling of radiation responses to high LETs.
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Affiliation(s)
- Francisco D C Guerra Liberal
- Patrick G Johnston Centre for Cancer Research, Queen's University Belfast, 97 Lisburn Road, Belfast, BT9 7AE, UK
| | - Shannon J Thompson
- Patrick G Johnston Centre for Cancer Research, Queen's University Belfast, 97 Lisburn Road, Belfast, BT9 7AE, UK
| | - Kevin M Prise
- Patrick G Johnston Centre for Cancer Research, Queen's University Belfast, 97 Lisburn Road, Belfast, BT9 7AE, UK
| | - Stephen J McMahon
- Patrick G Johnston Centre for Cancer Research, Queen's University Belfast, 97 Lisburn Road, Belfast, BT9 7AE, UK.
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Zhao L, Tang A, Long F, Mi D, Sun Y. Modeling of ionizing radiation-induced chromosome aberration and tumor prevalence based on two classes of DNA double-strand breaks clustering in chromatin domains. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2023; 259:115038. [PMID: 37229870 DOI: 10.1016/j.ecoenv.2023.115038] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/22/2023] [Revised: 04/24/2023] [Accepted: 05/17/2023] [Indexed: 05/27/2023]
Abstract
There has been some controversy over the use of radiobiological models when modeling the dose-response curves of ionizing radiation (IR)-induced chromosome aberration and tumor prevalence, as those curves usually show obvious non-targeted effects (NTEs) at low doses of high linear energy transfer (LET) radiation. The lack of understanding the contribution of NTEs to IR-induced carcinogenesis can lead to distinct deviations of relative biological effectiveness (RBE) estimations of carcinogenic potential, which are widely used in radiation risk assessment and radiation protection. In this work, based on the initial pattern of two classes of IR-induced DNA double-strand breaks (DSBs) clustering in chromatin domains and the subsequent incorrect repair processes, we proposed a novel radiobiological model to describe the dose-response curves of two carcinogenic-related endpoints within the same theoretical framework. The representative experimental data was used to verify the consistency and validity of the present model. The fitting results indicated that, compared with targeted effect (TE) and NTE models, the current model has better fitting ability when dealing with the experimental data of chromosome aberration and tumor prevalence induced by multiple types of IR with different LETs. Notably, the present model without introducing an NTE term was adequate to describe the dose-response curves of IR-induced chromosome aberration and tumor prevalence with NTEs in low-dose regions. Based on the fitting parameters, the LET-dependent RBE values were calculated for three given low doses. Our results showed that the RBE values predicted by the current model gradually decrease with the increase of doses for the endpoints of chromosome aberration and tumor prevalence. In addition, the calculated RBE was also compared with those evaluated from other models. These analyses show that the proposed model can be used as an alternative tool to well describe dose-response curves of multiple carcinogenic-related endpoints and effectively estimate RBE in low-dose regions.
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Affiliation(s)
- Lei Zhao
- Institute of Environmental Systems Biology, College of Environmental Science and Engineering, Dalian Maritime University, Dalian 116026, Liaoning, China.
| | - Aiping Tang
- College of Science, Dalian Maritime University, Dalian 116026, Liaoning, China
| | - Fei Long
- Institute of Environmental Systems Biology, College of Environmental Science and Engineering, Dalian Maritime University, Dalian 116026, Liaoning, China
| | - Dong Mi
- College of Science, Dalian Maritime University, Dalian 116026, Liaoning, China.
| | - Yeqing Sun
- Institute of Environmental Systems Biology, College of Environmental Science and Engineering, Dalian Maritime University, Dalian 116026, Liaoning, China.
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The Mayo Clinic Florida Microdosimetric Kinetic Model of Clonogenic Survival: Application to Various Repair-Competent Rodent and Human Cell Lines. Int J Mol Sci 2022; 23:ijms232012491. [PMID: 36293348 PMCID: PMC9604502 DOI: 10.3390/ijms232012491] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2022] [Revised: 10/04/2022] [Accepted: 10/11/2022] [Indexed: 11/30/2022] Open
Abstract
The relative biological effectiveness (RBE) calculations used during the planning of ion therapy treatments are generally based on the microdosimetric kinetic model (MKM) and the local effect model (LEM). The Mayo Clinic Florida MKM (MCF MKM) was recently developed to overcome the limitations of previous MKMs in reproducing the biological data and to eliminate the need for ion-exposed in vitro data as input for the model calculations. Since we are considering to implement the MCF MKM in clinic, this article presents (a) an extensive benchmark of the MCF MKM predictions against corresponding in vitro clonogenic survival data for 4 rodent and 10 cell lines exposed to ions from 1H to 238U, and (b) a systematic comparison with published results of the latest version of the LEM (LEM IV). Additionally, we introduce a novel approach to derive an approximate value of the MCF MKM model parameters by knowing only the animal species and the mean number of chromosomes. The overall good agreement between MCF MKM predictions and in vitro data suggests the MCF MKM can be reliably used for the RBE calculations. In most cases, a reasonable agreement was found between the MCF MKM and the LEM IV.
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Parisi A, Beltran CJ, Furutani KM. The Mayo Clinic Florida microdosimetric kinetic model of clonogenic survival: formalism and first benchmark against in vitro and in silico data. Phys Med Biol 2022; 67. [DOI: 10.1088/1361-6560/ac7375] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2022] [Accepted: 05/25/2022] [Indexed: 12/30/2022]
Abstract
Abstract
Objective. To develop a new model (Mayo Clinic Florida microdosimetric kinetic model, MCF MKM) capable of accurately describing the in vitro clonogenic survival at low and high linear energy transfer (LET) using single-event microdosimetric spectra in a single target. Methodology. The MCF MKM is based on the ‘post-processing average’ implementation of the non-Poisson microdosimetric kinetic model and includes a novel expression to compute the particle-specific quadratic-dependence of the cell survival with respect to dose (β of the linear-quadratic model). A new methodology to a priori calculate the mean radius of the MCF MKM subnuclear domains is also introduced. Lineal energy spectra were simulated with the Particle and Heavy Ion Transport code System (PHITS) for 1H, 4He, 12C, 20Ne, 40Ar, 56Fe, and 132Xe ions and used in combination with the MCF MKM to calculate the ion-specific LET-dependence of the relative biological effectiveness (RBE) for Chinese hamster lung fibroblasts (V79 cell line) and human salivary gland tumor cells (HSG cell line). The results were compared with in vitro data from the Particle Irradiation Data Ensemble (PIDE) and in silico results of different models. The possibility of performing experiment-specific predictions to explain the scatter in the in vitro RBE data was also investigated. Finally, a sensitivity analysis on the model parameters is also included. Main results. The RBE values predicted with the MCF MKM were found to be in good agreement with the in vitro data for all tested conditions. Though all MCF MKM model parameters were determined a priori, the accuracy of the MCF MKM was found to be comparable or superior to that of other models. The model parameters determined a priori were in good agreement with the ones obtained by fitting all available in vitro data. Significance. The MCF MKM will be considered for implementation in cancer radiotherapy treatment planning with accelerated ions.
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Flint DB, Ruff CE, Bright SJ, Yepes P, Wang Q, Manandhar M, Kacem MB, Turner BX, Martinus DKJ, Shaitelman SF, Sawakuchi GO. An empirical model of proton RBE based on the linear correlation between x-ray and proton radiosensitivity. Med Phys 2022; 49:6221-6236. [PMID: 35831779 PMCID: PMC10360139 DOI: 10.1002/mp.15850] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2022] [Revised: 06/12/2022] [Accepted: 06/24/2022] [Indexed: 11/08/2022] Open
Abstract
BACKGROUND Proton relative biological effectiveness (RBE) is known to depend on physical factors of the proton beam, such as its linear energy transfer (LET), as well as on cell-line specific biological factors, such as their ability to repair DNA damage. However, in a clinical setting, proton RBE is still considered to have a fixed value of 1.1 despite the existence of several empirical models that can predict proton RBE based on how a cell's survival curve (linear-quadratic model [LQM]) parameters α and β vary with the LET of the proton beam. Part of the hesitation to incorporate variable RBE models in the clinic is due to the great noise in the biological datasets on which these models are trained, often making it unclear which model, if any, provides sufficiently accurate RBE predictions to warrant a departure from RBE = 1.1. PURPOSE Here, we introduce a novel model of proton RBE based on how a cell's intrinsic radiosensitivity varies with LET, rather than its LQM parameters. METHODS AND MATERIALS We performed clonogenic cell survival assays for eight cell lines exposed to 6 MV x-rays and 1.2, 2.6, or 9.9 keV/µm protons, and combined our measurements with published survival data (n = 397 total cell line/LET combinations). We characterized how radiosensitivity metrics of the form DSF% , (the dose required to achieve survival fraction [SF], e.g., D10% ) varied with proton LET, and calculated the Bayesian information criteria associated with different LET-dependent functions to determine which functions best described the underlying trends. This allowed us to construct a six-parameter model that predicts cells' proton survival curves based on the LET dependence of their radiosensitivity, rather than the LET dependence of the LQM parameters themselves. We compared the accuracy of our model to previously established empirical proton RBE models, and implemented our model within a clinical treatment plan evaluation workflow to demonstrate its feasibility in a clinical setting. RESULTS Our analyses of the trends in the data show that DSF% is linearly correlated between x-rays and protons, regardless of the choice of the survival level (e.g., D10% , D37% , or D50% are similarly correlated), and that the slope and intercept of these correlations vary with proton LET. The model we constructed based on these trends predicts proton RBE within 15%-30% at the 68.3% confidence level and offers a more accurate general description of the experimental data than previously published empirical models. In the context of a clinical treatment plan, our model generally predicted higher RBE-weighted doses than the other empirical models, with RBE-weighted doses in the distal portion of the field being up to 50.7% higher than the planned RBE-weighted doses (RBE = 1.1) to the tumor. CONCLUSIONS We established a new empirical proton RBE model that is more accurate than previous empirical models, and that predicts much higher RBE values in the distal edge of clinical proton beams.
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Affiliation(s)
- David B. Flint
- Department of Radiation PhysicsThe University of Texas MD Anderson Cancer CenterHoustonTexasUSA
| | - Chase E. Ruff
- Department of Radiation PhysicsThe University of Texas MD Anderson Cancer CenterHoustonTexasUSA
| | - Scott J. Bright
- Department of Radiation PhysicsThe University of Texas MD Anderson Cancer CenterHoustonTexasUSA
| | - Pablo Yepes
- Department of Radiation PhysicsThe University of Texas MD Anderson Cancer CenterHoustonTexasUSA
- Department of Physics and AstronomyRice UniversityHoustonTexasUSA
| | - Qianxia Wang
- Department of Radiation PhysicsThe University of Texas MD Anderson Cancer CenterHoustonTexasUSA
- Department of Physics and AstronomyRice UniversityHoustonTexasUSA
| | - Mandira Manandhar
- Department of Radiation PhysicsThe University of Texas MD Anderson Cancer CenterHoustonTexasUSA
| | - Mariam Ben Kacem
- Department of Radiation PhysicsThe University of Texas MD Anderson Cancer CenterHoustonTexasUSA
| | - Broderick X. Turner
- Department of Radiation PhysicsThe University of Texas MD Anderson Cancer CenterHoustonTexasUSA
- The University of Texas MD Anderson Cancer Center UTHealth Graduate School of Biomedical SciencesHoustonTexasUSA
| | - David K. J. Martinus
- Department of Radiation PhysicsThe University of Texas MD Anderson Cancer CenterHoustonTexasUSA
- The University of Texas MD Anderson Cancer Center UTHealth Graduate School of Biomedical SciencesHoustonTexasUSA
| | - Simona F. Shaitelman
- Department of Radiation OncologyThe University of Texas MD Anderson Cancer CenterHoustonTexasUSA
| | - Gabriel O. Sawakuchi
- Department of Radiation PhysicsThe University of Texas MD Anderson Cancer CenterHoustonTexasUSA
- The University of Texas MD Anderson Cancer Center UTHealth Graduate School of Biomedical SciencesHoustonTexasUSA
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Ingram SP, Warmenhoven JW, Henthorn NT, Chadiwck AL, Santina EE, McMahon SJ, Schuemann J, Kirkby NF, Mackay RI, Kirkby KJ, Merchant MJ. A computational approach to quantifying miscounting of radiation-induced double-strand break immunofluorescent foci. Commun Biol 2022; 5:700. [PMID: 35835982 PMCID: PMC9283546 DOI: 10.1038/s42003-022-03585-5] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2021] [Accepted: 06/14/2022] [Indexed: 11/09/2022] Open
Abstract
Immunofluorescent tagging of DNA double-strand break (DSB) markers, such as γ-H2AX and other DSB repair proteins, are powerful tools in understanding biological consequences following irradiation. However, whilst the technique is widespread, there are many uncertainties related to its ability to resolve and reliably deduce the number of foci when counting using microscopy. We present a new tool for simulating radiation-induced foci in order to evaluate microscope performance within in silico immunofluorescent images. Simulations of the DSB distributions were generated using Monte Carlo track-structure simulation. For each DSB distribution, a corresponding DNA repair process was modelled and the un-repaired DSBs were recorded at several time points. Corresponding microscopy images for both a DSB and (γ-H2AX) fluorescent marker were generated and compared for different microscopes, radiation types and doses. Statistically significant differences in miscounting were found across most of the tested scenarios. These inconsistencies were propagated through to repair kinetics where there was a perceived change between radiation-types. These changes did not reflect the underlying repair rate and were caused by inconsistencies in foci counting. We conclude that these underlying uncertainties must be considered when analysing images of DNA damage markers to ensure differences observed are real and are not caused by non-systematic miscounting. PyFoci is a tool that simulates distributions of fluorescently labeled DNA double-strand break marker protein foci and allows the estimation of miscounting under different radiation types, doses and microscopy settings.
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Affiliation(s)
- Samuel P Ingram
- Division of Cancer Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Oxford Rd, Manchester, M13 9PL, UK. .,Christie Medical Physics and Engineering, The Christie NHS Foundation Trust, Wilmslow Rd, Manchester, M20 4BX, UK.
| | - John-William Warmenhoven
- Division of Cancer Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Oxford Rd, Manchester, M13 9PL, UK.,The Christie NHS Foundation Trust, Manchester Academic Health Science Centre, Wilmslow Rd, Manchester, M20 4BX, UK
| | - Nicholas T Henthorn
- Division of Cancer Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Oxford Rd, Manchester, M13 9PL, UK.,The Christie NHS Foundation Trust, Manchester Academic Health Science Centre, Wilmslow Rd, Manchester, M20 4BX, UK
| | - Amy L Chadiwck
- Division of Cancer Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Oxford Rd, Manchester, M13 9PL, UK.,The Christie NHS Foundation Trust, Manchester Academic Health Science Centre, Wilmslow Rd, Manchester, M20 4BX, UK
| | - Elham E Santina
- Division of Cancer Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Oxford Rd, Manchester, M13 9PL, UK.,The Christie NHS Foundation Trust, Manchester Academic Health Science Centre, Wilmslow Rd, Manchester, M20 4BX, UK
| | - Stephen J McMahon
- Patrick G Johnston Centre for Cancer Research, Queens University Belfast, 97 Lisburn Rd, Belfast, BT9 7AE, UK
| | - Jan Schuemann
- Massachusetts General Hospital and Harvard Medical School, Department of Radiation Oncology, 30 Fruit Street, Boston, MA, 02114, USA
| | - Norman F Kirkby
- Division of Cancer Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Oxford Rd, Manchester, M13 9PL, UK.,The Christie NHS Foundation Trust, Manchester Academic Health Science Centre, Wilmslow Rd, Manchester, M20 4BX, UK
| | - Ranald I Mackay
- Division of Cancer Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Oxford Rd, Manchester, M13 9PL, UK.,Christie Medical Physics and Engineering, The Christie NHS Foundation Trust, Wilmslow Rd, Manchester, M20 4BX, UK
| | - Karen J Kirkby
- Division of Cancer Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Oxford Rd, Manchester, M13 9PL, UK.,The Christie NHS Foundation Trust, Manchester Academic Health Science Centre, Wilmslow Rd, Manchester, M20 4BX, UK
| | - Michael J Merchant
- Division of Cancer Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Oxford Rd, Manchester, M13 9PL, UK.,The Christie NHS Foundation Trust, Manchester Academic Health Science Centre, Wilmslow Rd, Manchester, M20 4BX, UK
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Parisi A, Furutani KM, Beltran CJ. On the calculation of the relative biological effectiveness of ion radiation therapy using a biological weighting function, the microdosimetric kinetic model (MKM) and subsequent corrections (non-Poisson MKM and modified MKM). Phys Med Biol 2022; 67. [DOI: 10.1088/1361-6560/ac5fdf] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2021] [Accepted: 03/22/2022] [Indexed: 12/31/2022]
Abstract
Abstract
Objective. To investigate similarities and differences in the formalism, processing, and the results of relative biological effectiveness (RBE) calculations with a biological weighting function (BWF), the microdosimetric kinetic model (MKM) and subsequent modifications (non-Poisson MKM, modified MKM). This includes: (a) the extension of the V79-RBE10% BWF to model the RBE for other clonogenic survival levels; (b) a novel implementation of MKMs as weighting functions; (c) a benchmark against Chinese Hamster lung fibroblast (V79) in vitro data; (d) a study on the effect of pre- or post- processing the average biophysical quantities used for the RBE calculations; (e) a possible modification of the modified MKM parameters to improve the model accuracy at high linear energy transfer (LET). Methodology. Lineal energy spectra were simulated for two spherical targets (diameter = 0.464 or 1.0 μm) using PHITS for 1H, 4He, 12C, 20Ne, 40Ar, 56Fe and 132Xe ions. The results of the in silico calculations were compared with published in vitro data. Main results. All models appear to underestimate the RBE
α
of hydrogen ions. All MKMs generally overestimate the RBE50%, RBE10% and RBE1% for ions with an LET greater than ∼200 keV μm−1. This overestimation is greater for small surviving fractions and is likely due to the assumption of a radiation-independent quadratic term of clonogenic survival (ß). The overall RBE trends seem to be best described by the novel ‘post-processing average’ implementation of the non-Poisson MKM. In case of calculations with the non-Poisson MKM, pre- or post- processing the average biophysical quantities affects the computed RBE values significantly. Significance. This study presents a systematic analysis of the formalism and results of widely used microdosimetric models of clonogenic survival for ions relevant for cancer particle therapy and space radiation protection. Points for improvements were highlighted and will contribute to the development of upgraded biophysical models.
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13
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Thompson SJ, Rooney A, Prise KM, McMahon SJ. Evaluating Iodine-125 DNA Damage Benchmarks of Monte Carlo DNA Damage Models. Cancers (Basel) 2022; 14:cancers14030463. [PMID: 35158731 PMCID: PMC8833774 DOI: 10.3390/cancers14030463] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2021] [Revised: 01/13/2022] [Accepted: 01/14/2022] [Indexed: 02/01/2023] Open
Abstract
Simple Summary Simulation of initial radiation-induced DNA damage remains a major area of research, with numerous Monte Carlo models having been developed to model radiation effects on the cellular scale. While many models have been reasonably fit to a range of biological endpoints, there remains a lack of robust benchmarking data. Here, we investigate the application of a dataset on strand breaking in a single DNA strand through incorporation of radioactive Iodine-125 to distinguish between different Monte Carlo nanoscale physics models. We find that, while all models are able to effectively fit this data, they do so using significantly different best-fitting parameters and make substantially different predictions for other endpoints. These observations suggest that most nanoscale models broadly agree on the distribution of energy and can be made to fit to single datasets, but robust, multi-endpoint analysis is required to fully optimize and validate these approaches. Abstract A wide range of Monte Carlo models have been applied to predict yields of DNA damage based on nanoscale track structure calculations. While often similar on the macroscopic scale, these models frequently employ different assumptions which lead to significant differences in nanoscale dose deposition. However, the impact of these differences on key biological readouts remains unclear. A major challenge in this area is the lack of robust datasets which can be used to benchmark models, due to a lack of resolution at the base pair level required to deeply test nanoscale dose deposition. Studies investigating the distribution of strand breakage in short DNA strands following the decay of incorporated 125I offer one of the few benchmarks for model predictions on this scale. In this work, we have used TOPAS-nBio to evaluate the performance of three Geant4-DNA physics models at predicting the distribution and yield of strand breaks in this irradiation scenario. For each model, energy and OH radical distributions were simulated and used to generate predictions of strand breakage, varying energy thresholds for strand breakage and OH interaction rates to fit to the experimental data. All three models could fit well to the observed data, although the best-fitting strand break energy thresholds ranged from 29.5 to 32.5 eV, significantly higher than previous studies. However, despite well describing the resulting DNA fragment distribution, these fit models differed significantly with other endpoints, such as the total yield of breaks, which varied by 70%. Limitations in the underlying data due to inherent normalisation mean it is not possible to distinguish clearly between the models in terms of total yield. This suggests that, while these physics models can effectively fit some biological data, they may not always generalise in the same way to other endpoints, requiring caution in their extrapolation to new systems and the use of multiple different data sources for robust model benchmarking.
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14
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Pfuhl T, Friedrich T, Scholz M. Comprehensive comparison of local effect model IV predictions with the particle irradiation data ensemble. Med Phys 2021; 49:714-726. [PMID: 34766635 DOI: 10.1002/mp.15343] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2021] [Revised: 10/18/2021] [Accepted: 10/21/2021] [Indexed: 11/08/2022] Open
Abstract
PURPOSE The increased relative biological effectiveness (RBE) of ions is one of the key benefits of ion radiotherapy compared to conventional radiotherapy with photons. To account for the increased RBE of ions during the process of ion radiotherapy treatment planning, a robust model for RBE predictions is indispensable. Currently, at several ion therapy centers the local effect model I (LEM I) is applied to predict the RBE, which varies with biological and physical impacting factors. After the introduction of LEM I, several model improvements were implemented, leading to the current version, LEM IV, which is systematically tested in this study. METHODS As a comprehensive RBE model should give consistent results for a large variety of ion species and energies, the particle irradiation data ensemble (PIDE) is used to systematically validate the LEM IV. The database covers over 1100 photon and ion survival experiments in form of their linear-quadratic parameters for a wide range of ion types and energies. This makes the database an optimal tool to challenge the systematic dependencies of the RBE model. After appropriate filtering of the database, 571 experiments were identified and used as test data. RESULTS The study confirms that the LEM IV reflects the RBE systematics observed in measurements well. It is able to reproduce the dependence of RBE on the linear energy transfer (LET) as well as on the αγ /βγ ratio for several ion species in a wide energy range. Additionally, the systematic quantitative analysis revealed precision capabilities and limits of the model. At lower LET values, the LEM IV tends to underestimate the RBE with an increasing underestimation with increasing atomic number of the ion. At higher LET values, the LEM IV overestimates the RBE for protons or helium ions, whereas the predictions for heavier ions match experimental data well. CONCLUSIONS The LEM IV is able to predict general RBE characteristics for several ion species in a broad energy range. The accuracy of the predictions is reasonable considering the small number of input parameters needed by the model. The detailed quantification of possible systematic deviations, however, enables to identify not only strengths but also limitations of the model. The gained knowledge can be used to develop model adjustments to further improve the model accuracy, which is on the way.
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Affiliation(s)
- Tabea Pfuhl
- Biophysics Department, GSI Helmholtzzentrum für Schwerionenforschung, Darmstadt, Germany.,Institute for Solid State Physics, Technische Universität Darmstadt, Darmstadt, Germany
| | - Thomas Friedrich
- Biophysics Department, GSI Helmholtzzentrum für Schwerionenforschung, Darmstadt, Germany
| | - Michael Scholz
- Biophysics Department, GSI Helmholtzzentrum für Schwerionenforschung, Darmstadt, Germany
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15
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Parisi A, Struelens L, Vanhavere F. Comparison between the results of a recently-developed biological weighting function (V79-RBE 10BWF) and the in vitroclonogenic survival RBE 10of other repair-competent asynchronized normoxic mammalian cell lines and ions not used for the development of the model. Phys Med Biol 2021; 66. [PMID: 34710862 DOI: 10.1088/1361-6560/ac344e] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2021] [Accepted: 10/28/2021] [Indexed: 11/11/2022]
Abstract
728 simulated microdosimetric lineal energy spectra (26 different ions between 1H and 238U, 28 energy points from 1 to 1000 MeV/n) were used in combination with a recently-developed biological weighting function (Parisi et al., 2020) and 571 published in vitro clonogenic survival curves in order to: 1) assess prediction intervals for the in silico results by deriving an empirical indication of the experimental uncertainty from the dispersion in the in vitro hamster lung fibroblast (V79) data used for the development of the biophysical model; 2) explore the possibility of modeling the relative biological effectiveness (RBE) of the 10% clonogenic survival of asynchronized normoxic repair-competent mammalian cell lines other than the one used for the development of the model (V79); 3) investigate the predictive power of the model through a comparison between in silico results and in vitro data for 10 ions not used for the development of the model. At first, different strategies for the assessment of the in silico prediction intervals were compared. The possible sources of uncertainty responsible for the dispersion in the in vitro data were also shortly reviewed. Secondly, also because of the relevant scatter in the in vitro data, no statistically-relevant differences were found between the RBE10 of the investigated different asynchronized normoxic repair-competent mammalian cell lines. The only exception (Chinese Hamster peritoneal fibroblasts, B14FAF28), is likely due to the limited dataset (all in vitro ion data were extracted from a single publication), systematic differences in the linear energy transfer (LET) calculations for the employed very-heavy ions, and the use of reference photon survival curves extracted from a different publication. Finally, the in silico predictions for the 10 ions not used for the model development were in good agreement with the corresponding in vitro data.
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Affiliation(s)
- Alessio Parisi
- Radiation Protection Dosimetry and Calibration, Studiecentrum voor Kernenergie, Boeretang 200, Mol, Belgiun, Mol, 2400, BELGIUM
| | - Lara Struelens
- Radiation Protection, Dosimetry and Calibration, Belgian Nuclear Research Centre SCK.CEN, Boeretang 200, Mol, 2400, BELGIUM
| | - Filip Vanhavere
- Institute of Advanced Nuclear Systems, Belgian Nuclear Research Centre SCK.CEN, Boeretang 200, B-2400 Mol, Mol, BELGIUM
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16
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Liew H, Meister S, Mein S, Tessonnier T, Kopp B, Held T, Haberer T, Abdollahi A, Debus J, Dokic I, Mairani A. Combined DNA Damage Repair Interference and Ion Beam Therapy: Development, Benchmark, and Clinical Implications of a Mechanistic Biological Model. Int J Radiat Oncol Biol Phys 2021; 112:802-817. [PMID: 34710524 DOI: 10.1016/j.ijrobp.2021.09.048] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2021] [Revised: 09/10/2021] [Accepted: 09/28/2021] [Indexed: 12/11/2022]
Abstract
PURPOSE Our purpose was to develop a mechanistic model that describes and predicts radiation response after combined DNA damage repair interference (DDRi) and particle radiation therapy. METHODS AND MATERIALS The heterogeneous dose distributions of protons and 4He ions were implemented into the "UNIfied and VERSatile bio-response Engine" (UNIVERSE). Predictions for monoenergetic and mixed fields over clinically relevant dose and linear energy transfer range were compared with experimental in vitro survival data measured in this work as well as data available in the literature, including different cell lines and DDR interferences. Ultimately, UNIVERSE predictions were investigated in a patient plan. RESULTS UNIVERSE accurately predicts survival of cell lines with and without DDRi in clinical settings of ion beam therapy based only on 3 parameters derived from photon data. With increasing dose or linear energy transfer, the radiosensitizing effect of DDRi decreases, resulting in diminished relative biological effect of ion beam radiation for cells subjected to DDRi in comparison to cells that are not. Similar trends were observed in patient plan recalculations; however, this analysis also suggests that DDRi + particle radiation therapy may better preserve the therapeutic window in comparison to DDRi + photon radiation therapy. CONCLUSIONS The presented framework represents the first mechanistic model of combined DDRi and particle radiation therapy comprehensively benchmarked in clinically relevant scenarios and a step toward more personalized treatment. It reveals potential differences between DDRi + photon radiation therapy versus DDRi + particle radiation therapy, which have not been described so far. UNIVERSE could aid in appraising the clinical viability of combined administration of radiosensitizing drugs and charged particle therapy, as well as the identification of patients with known DDR deficiencies in the tumor who might benefit from therapy with light ions, freeing limited space at heavy ion therapy centers.
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Affiliation(s)
- Hans Liew
- Clinical Cooperation Unit Translational Radiation Oncology, German Cancer Consortium (DKTK) Core-Center Heidelberg, National Center for Tumor Diseases (NCT), Heidelberg University Hospital (UKHD) and German Cancer Research Center (DKFZ), Heidelberg, Germany; Division of Molecular and Translational Radiation Oncology, Heidelberg Faculty of Medicine (MFHD) and Heidelberg University Hospital (UKHD), Heidelberg Ion-Beam Therapy Center (HIT), Heidelberg, Germany; Heidelberg Institute of Radiation Oncology (HIRO), National Center for Radiation Oncology (NCRO), Heidelberg University and German Cancer Research Center (DKFZ), Heidelberg, Germany; Faculty of Physics and Astronomy, Heidelberg University, Heidelberg, Germany
| | - Sarah Meister
- Clinical Cooperation Unit Translational Radiation Oncology, German Cancer Consortium (DKTK) Core-Center Heidelberg, National Center for Tumor Diseases (NCT), Heidelberg University Hospital (UKHD) and German Cancer Research Center (DKFZ), Heidelberg, Germany; Division of Molecular and Translational Radiation Oncology, Heidelberg Faculty of Medicine (MFHD) and Heidelberg University Hospital (UKHD), Heidelberg Ion-Beam Therapy Center (HIT), Heidelberg, Germany; Heidelberg Institute of Radiation Oncology (HIRO), National Center for Radiation Oncology (NCRO), Heidelberg University and German Cancer Research Center (DKFZ), Heidelberg, Germany; Faculty of Biology, Heidelberg University, Heidelberg, Germany
| | - Stewart Mein
- Clinical Cooperation Unit Translational Radiation Oncology, German Cancer Consortium (DKTK) Core-Center Heidelberg, National Center for Tumor Diseases (NCT), Heidelberg University Hospital (UKHD) and German Cancer Research Center (DKFZ), Heidelberg, Germany; Division of Molecular and Translational Radiation Oncology, Heidelberg Faculty of Medicine (MFHD) and Heidelberg University Hospital (UKHD), Heidelberg Ion-Beam Therapy Center (HIT), Heidelberg, Germany; Heidelberg Institute of Radiation Oncology (HIRO), National Center for Radiation Oncology (NCRO), Heidelberg University and German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Thomas Tessonnier
- Heidelberg Ion-Beam Therapy Center (HIT), Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany
| | - Benedikt Kopp
- Clinical Cooperation Unit Translational Radiation Oncology, German Cancer Consortium (DKTK) Core-Center Heidelberg, National Center for Tumor Diseases (NCT), Heidelberg University Hospital (UKHD) and German Cancer Research Center (DKFZ), Heidelberg, Germany; Division of Molecular and Translational Radiation Oncology, Heidelberg Faculty of Medicine (MFHD) and Heidelberg University Hospital (UKHD), Heidelberg Ion-Beam Therapy Center (HIT), Heidelberg, Germany; Heidelberg Institute of Radiation Oncology (HIRO), National Center for Radiation Oncology (NCRO), Heidelberg University and German Cancer Research Center (DKFZ), Heidelberg, Germany; Faculty of Physics and Astronomy, Heidelberg University, Heidelberg, Germany
| | - Thomas Held
- Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg Institute of Radiation Oncology (HIRO), University Hospital Heidelberg, National Center for Tumor Diseases (NCT), University Hospital Heidelberg, Heidelberg, Germany
| | - Thomas Haberer
- Heidelberg Ion-Beam Therapy Center (HIT), Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany
| | - Amir Abdollahi
- Clinical Cooperation Unit Translational Radiation Oncology, German Cancer Consortium (DKTK) Core-Center Heidelberg, National Center for Tumor Diseases (NCT), Heidelberg University Hospital (UKHD) and German Cancer Research Center (DKFZ), Heidelberg, Germany; Division of Molecular and Translational Radiation Oncology, Heidelberg Faculty of Medicine (MFHD) and Heidelberg University Hospital (UKHD), Heidelberg Ion-Beam Therapy Center (HIT), Heidelberg, Germany; Heidelberg Institute of Radiation Oncology (HIRO), National Center for Radiation Oncology (NCRO), Heidelberg University and German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Jürgen Debus
- Division of Molecular and Translational Radiation Oncology, Heidelberg Faculty of Medicine (MFHD) and Heidelberg University Hospital (UKHD), Heidelberg Ion-Beam Therapy Center (HIT), Heidelberg, Germany; Heidelberg Institute of Radiation Oncology (HIRO), National Center for Radiation Oncology (NCRO), Heidelberg University and German Cancer Research Center (DKFZ), Heidelberg, Germany; Faculty of Physics and Astronomy, Heidelberg University, Heidelberg, Germany; Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg Institute of Radiation Oncology (HIRO), University Hospital Heidelberg, National Center for Tumor Diseases (NCT), University Hospital Heidelberg, Heidelberg, Germany; Clinical Cooperation Unit Radiation Oncology, German Cancer Consortium (DKTK) Core-Center Heidelberg, National Center for Tumor Diseases (NCT), Heidelberg University Hospital (UKHD) and German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Ivana Dokic
- Clinical Cooperation Unit Translational Radiation Oncology, German Cancer Consortium (DKTK) Core-Center Heidelberg, National Center for Tumor Diseases (NCT), Heidelberg University Hospital (UKHD) and German Cancer Research Center (DKFZ), Heidelberg, Germany; Division of Molecular and Translational Radiation Oncology, Heidelberg Faculty of Medicine (MFHD) and Heidelberg University Hospital (UKHD), Heidelberg Ion-Beam Therapy Center (HIT), Heidelberg, Germany; Heidelberg Institute of Radiation Oncology (HIRO), National Center for Radiation Oncology (NCRO), Heidelberg University and German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Andrea Mairani
- Heidelberg Ion-Beam Therapy Center (HIT), Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany; National Centre of Oncological Hadrontherapy (CNAO), Medical Physics, Pavia, Italy.
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17
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Keta O, Petković V, Cirrone P, Petringa G, Cuttone G, Sakata D, Shin WG, Incerti S, Petrović I, Ristić Fira A. DNA double-strand breaks in cancer cells as a function of proton linear energy transfer and its variation in time. Int J Radiat Biol 2021; 97:1229-1240. [PMID: 34187289 DOI: 10.1080/09553002.2021.1948140] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2021] [Revised: 06/14/2021] [Accepted: 06/21/2021] [Indexed: 01/08/2023]
Abstract
PURPOSE The complex relationship between linear energy transfer (LET) and cellular response to radiation is not yet fully elucidated. To better characterize DNA damage after irradiations with therapeutic protons, we monitored formation and disappearance of DNA double-strand breaks (DNA DSB) as a function of LET and time. Comparisons with conventional γ-rays and high LET carbon ions were also performed. MATERIALS AND METHODS In the present work, we performed immunofluorescence-based assay to determine the amount of DNA DSB induced by different LET values along the 62 MeV therapeutic proton Spread out Bragg peak (SOBP) in three cancer cell lines, i.e. HTB140 melanoma, MCF-7 breast adenocarcinoma and HTB177 non-small lung cancer cells. Time dependence of foci formation was followed as well. To determine irradiation positions, corresponding to the desired LET values, numerical simulations were carried out using Geant4 toolkit. We compared γ-H2AX foci persistence after irradiations with protons to that of γ-rays and carbon ions. RESULTS With the rise of LET values along the therapeutic proton SOBP, the increase of γ-H2AX foci number is detected in the three cell lines up to the distal end of the SOBP, while there is a decrease on its distal fall-off part. With the prolonged incubation time, the number of foci gradually drops tending to attain the residual level. For the maximum number of DNA DSB, irradiation with protons attain higher level than that of γ-rays. Carbon ions produce more DNA DSB than protons but not substantially. The number of residual foci produced by γ-rays is significantly lower than that of protons and particularly carbon ions. Carbon ions do not produce considerably higher number of foci than protons, as it could be expected due to their physical properties. CONCLUSIONS In situ visualization of γ-H2AX foci reveal creation of more lesions in the three cell lines by clinically relevant proton SOBP than γ-rays. The lack of significant differences in the number of γ-H2AX foci between the proton and carbon ion-irradiated samples suggests an increased complexity of DNA lesions and slower repair kinetics after carbon ions compared to protons. For all three irradiation types, there is no major difference between the three cell lines shortly after irradiations, while later on, the formation of residual foci starts to express the inherent nature of tested cells, therefore increasing discrepancy between them.
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Affiliation(s)
- Otilija Keta
- Vinča Institute of Nuclear Sciences, University of Belgrade, Belgrade, Serbia
| | - Vladana Petković
- Vinča Institute of Nuclear Sciences, University of Belgrade, Belgrade, Serbia
| | - Pablo Cirrone
- Laboratori Nazionali del Sud, Istituto Nazionale di Fisica Nuceare, Catania, Italy
- Physics and Astronomy Department "E. Majorana", University of Catania, Catania, Italy
- Centro Siciliano di Fisica Nucleare e Struttura della Materia (CSFNSM), Catania, Italy
| | - Giada Petringa
- Laboratori Nazionali del Sud, Istituto Nazionale di Fisica Nuceare, Catania, Italy
- Institute of Physics (IoP) of the Czech Academy of Science (CAS), ELI-Beamlines, Prague, Czech Republic
| | - Giacomo Cuttone
- Laboratori Nazionali del Sud, Istituto Nazionale di Fisica Nuceare, Catania, Italy
- Physics and Astronomy Department "E. Majorana", University of Catania, Catania, Italy
| | - Dousatsu Sakata
- Department of Accelerator and Medical Physics, NIRS, Chiba, QST, Japan
| | - Wook-Geun Shin
- Department of Radiation Oncology, Seoul National University Hospital, Seoul, Korea
| | | | - Ivan Petrović
- Vinča Institute of Nuclear Sciences, University of Belgrade, Belgrade, Serbia
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18
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McMahon SJ, Prise KM. A Mechanistic DNA Repair and Survival Model (Medras): Applications to Intrinsic Radiosensitivity, Relative Biological Effectiveness and Dose-Rate. Front Oncol 2021; 11:689112. [PMID: 34268120 PMCID: PMC8276175 DOI: 10.3389/fonc.2021.689112] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2021] [Accepted: 05/31/2021] [Indexed: 01/04/2023] Open
Abstract
Variations in the intrinsic radiosensitivity of different cells to ionizing radiation is now widely believed to be a significant driver in differences in response to radiotherapy. While the mechanisms of radiosensitivity have been extensively studied in the laboratory, there are a lack of models which integrate this knowledge into a predictive framework. This paper presents an overview of the Medras model, which has been developed to provide a mechanistic framework in which different radiation responses can be modelled and individual responses predicted. This model simulates the repair of radiation-induced DNA damage, incorporating the overall kinetics of repair and its fidelity, to predict a range of biological endpoints including residual DNA damage, mutation, chromosome aberration, and cell death. Validation of this model against a range of exposure types is presented, including considerations of varying radiation qualities and dose-rates. This approach has the potential to inform new tools to deliver mechanistic predictions of radiation sensitivity, and support future developments in treatment personalization.
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Affiliation(s)
- Stephen Joseph McMahon
- Patrick G Johnston Centre for Cancer Research, Queen’s University Belfast, Belfast, United Kingdom
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19
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Vatner R, James CD, Sathiaseelan V, Bondra KM, Kalapurakal JA, Houghton PJ. Radiation therapy and molecular-targeted agents in preclinical testing for immunotherapy, brain tumors, and sarcomas: Opportunities and challenges. Pediatr Blood Cancer 2021; 68 Suppl 2:e28439. [PMID: 32827353 DOI: 10.1002/pbc.28439] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/12/2020] [Revised: 04/24/2020] [Accepted: 05/07/2020] [Indexed: 01/07/2023]
Abstract
Despite radiation therapy (RT) being an integral part of the treatment of most pediatric cancers and the recent discovery of novel molecular-targeted agents (MTAs) in this era of precision medicine with the potential to improve the therapeutic ratio of modern chemoradiotherapy regimens, there are only a few preclinical trials being conducted to discover novel radiosensitizers and radioprotectors. This has resulted in a paucity of translational clinical trials combining RT and novel MTAs. This report describes the opportunities and challenges of investigating RT together with MTAs in preclinical testing for immunotherapy, brain tumors, and sarcomas in pediatric oncology. We discuss the need for improving the collaboration between radiation oncologists, biologists, and physicists to improve the reliability, reproducibility, and translational potential of RT-based preclinical research. Current translational clinical trials using RT and MTAs for immunotherapy, brain tumors, and sarcomas are described. The technologic advances in experimental RT, availability of novel experimental tumor models, advances in immunology and tumor biology, and the discovery of novel MTAs together hold considerable promise for good quality preclinical and clinical multimodality research to improve the current rates of survival and toxicity in children afflicted with cancer.
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Affiliation(s)
- Ralph Vatner
- Radiation Oncology, University of Cincinnati and Cincinnati Children's Hospital, Cincinnati, Ohio
| | | | | | - Kathryn M Bondra
- Greehey Children's Cancer Research Institute, University of Texas, San Antonio, Texas
| | | | - Peter J Houghton
- Greehey Children's Cancer Research Institute, University of Texas, San Antonio, Texas
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Kalospyros SA, Nikitaki Z, Kyriakou I, Kokkoris M, Emfietzoglou D, Georgakilas AG. A Mathematical Radiobiological Model (MRM) to Predict Complex DNA Damage and Cell Survival for Ionizing Particle Radiations of Varying Quality. Molecules 2021; 26:molecules26040840. [PMID: 33562730 PMCID: PMC7914858 DOI: 10.3390/molecules26040840] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2020] [Revised: 01/26/2021] [Accepted: 01/29/2021] [Indexed: 01/10/2023] Open
Abstract
Predicting radiobiological effects is important in different areas of basic or clinical applications using ionizing radiation (IR); for example, towards optimizing radiation protection or radiation therapy protocols. In this case, we utilized as a basis the ‘MultiScale Approach (MSA)’ model and developed an integrated mathematical radiobiological model (MRM) with several modifications and improvements. Based on this new adaptation of the MSA model, we have predicted cell-specific levels of initial complex DNA damage and cell survival for irradiation with 11Β, 12C, 14Ν, 16Ο, 20Νe, 40Αr, 28Si and 56Fe ions by using only three input parameters (particle’s LET and two cell-specific parameters: the cross sectional area of each cell nucleus and its genome size). The model-predicted survival curves are in good agreement with the experimental ones. The particle Relative Biological Effectiveness (RBE) and Oxygen Enhancement Ratio (OER) are also calculated in a very satisfactory way. The proposed integrated MRM model (within current limitations) can be a useful tool for the assessment of radiation biological damage for ions used in hadron-beam radiation therapy or radiation protection purposes.
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Affiliation(s)
- Spyridon A. Kalospyros
- Physics Department, School of Applied Mathematical and Physical Sciences, National Technical University of Athens (NTUA), 15780 Zografou, Greece; (S.A.K.); (Z.N.); (M.K.)
| | - Zacharenia Nikitaki
- Physics Department, School of Applied Mathematical and Physical Sciences, National Technical University of Athens (NTUA), 15780 Zografou, Greece; (S.A.K.); (Z.N.); (M.K.)
| | - Ioanna Kyriakou
- Medical Physics Lab, Department of Medicine, University of Ioannina, 45110 Ioannina, Greece; (I.K.); (D.E.)
| | - Michael Kokkoris
- Physics Department, School of Applied Mathematical and Physical Sciences, National Technical University of Athens (NTUA), 15780 Zografou, Greece; (S.A.K.); (Z.N.); (M.K.)
| | - Dimitris Emfietzoglou
- Medical Physics Lab, Department of Medicine, University of Ioannina, 45110 Ioannina, Greece; (I.K.); (D.E.)
| | - Alexandros G. Georgakilas
- Physics Department, School of Applied Mathematical and Physical Sciences, National Technical University of Athens (NTUA), 15780 Zografou, Greece; (S.A.K.); (Z.N.); (M.K.)
- Correspondence: ; Tel.: +30-210-772-4453
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21
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Bertolet A, Cortés-Giraldo M, Carabe-Fernandez A. Implementation of the microdosimetric kinetic model using analytical microdosimetry in a treatment planning system for proton therapy. Phys Med 2021; 81:69-76. [DOI: 10.1016/j.ejmp.2020.11.024] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/10/2020] [Revised: 10/17/2020] [Accepted: 11/19/2020] [Indexed: 02/06/2023] Open
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22
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Zhu H, McNamara AL, McMahon SJ, Ramos-Mendez J, Henthorn NT, Faddegon B, Held KD, Perl J, Li J, Paganetti H, Schuemann J. Cellular Response to Proton Irradiation: A Simulation Study with TOPAS-nBio. Radiat Res 2020; 194:9-21. [PMID: 32401689 DOI: 10.1667/rr15531.1] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2019] [Accepted: 04/11/2020] [Indexed: 12/21/2022]
Abstract
The cellular response to ionizing radiation continues to be of significant research interest in cancer radiotherapy, and DNA is recognized as the critical target for most of the biologic effects of radiation. Incident particles can cause initial DNA damages through physical and chemical interactions within a short time scale. Initial DNA damages can undergo repair via different pathways available at different stages of the cell cycle. The misrepair of DNA damage results in genomic rearrangement and causes mutations and chromosome aberrations, which are drivers of cell death. This work presents an integrated study of simulating cell response after proton irradiation with energies of 0.5-500 MeV (LET of 60-0.2 keV/µm). A model of a whole nucleus with fractal DNA geometry was implemented in TOPAS-nBio for initial DNA damage simulations. The default physics and chemistry models in TOPAS-nBio were used to describe interactions of primary particles, secondary particles, and radiolysis products within the nucleus. The initial DNA double-strand break (DSB) yield was found to increase from 6.5 DSB/Gy/Gbp at low-linear energy transfer (LET) of 0.2 keV/µm to 21.2 DSB/Gy/Gbp at high LET of 60 keV/µm. A mechanistic repair model was applied to predict the characteristics of DNA damage repair and dose response of chromosome aberrations. It was found that more than 95% of the DSBs are repaired within the first 24 h and the misrepaired DSB fraction increases rapidly with LET and reaches 15.8% at 60 keV/µm with an estimated chromosome aberration detection threshold of 3 Mbp. The dicentric and acentric fragment yields and the dose response of micronuclei formation after proton irradiation were calculated and compared with experimental results.
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Affiliation(s)
- Hongyu Zhu
- Department of Radiation Oncology, Massachusetts General Hospital, Boston, Massachusetts 02114.,Department of Engineering Physics, Tsinghua University, Beijing 100084, P.R. China.,Key Laboratory of Particle & Radiation Imaging (Tsinghua University), Ministry of Education, Beijing 100084, P.R. China
| | - Aimee L McNamara
- Department of Radiation Oncology, Massachusetts General Hospital, Boston, Massachusetts 02114.,Harvard Medical School, Boston, Massachusetts 02114
| | - Stephen J McMahon
- Centre for Cancer Research and Cell Biology, Queens University Belfast, Belfast, United Kingdom
| | - Jose Ramos-Mendez
- Department of Radiation Oncology, University of California San Francisco, California 94143
| | - Nicholas T Henthorn
- Division of Molecular and Clinical Cancer Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, United Kingdom
| | - Bruce Faddegon
- Department of Radiation Oncology, University of California San Francisco, California 94143
| | - Kathryn D Held
- Department of Radiation Oncology, Massachusetts General Hospital, Boston, Massachusetts 02114.,Harvard Medical School, Boston, Massachusetts 02114
| | - Joseph Perl
- SLAC National Accelerator Laboratory, Menlo Park, California
| | - Junli Li
- Department of Engineering Physics, Tsinghua University, Beijing 100084, P.R. China.,Key Laboratory of Particle & Radiation Imaging (Tsinghua University), Ministry of Education, Beijing 100084, P.R. China
| | - Harald Paganetti
- Department of Radiation Oncology, Massachusetts General Hospital, Boston, Massachusetts 02114.,Harvard Medical School, Boston, Massachusetts 02114
| | - Jan Schuemann
- Department of Radiation Oncology, Massachusetts General Hospital, Boston, Massachusetts 02114.,Harvard Medical School, Boston, Massachusetts 02114
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23
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Parisi A, Sato T, Matsuya Y, Kase Y, Magrin G, Verona C, Tran L, Rosenfeld A, Bianchi A, Olko P, Struelens L, Vanhavere F. Development of a new microdosimetric biological weighting function for the RBE 10 assessment in case of the V79 cell line exposed to ions from 1H to 238U. Phys Med Biol 2020; 65:235010. [PMID: 33274727 DOI: 10.1088/1361-6560/abbf96] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
An improved biological weighting function (IBWF) is proposed to phenomenologically relate microdosimetric lineal energy probability density distributions with the relative biological effectiveness (RBE) for the in vitro clonogenic cell survival (surviving fraction = 10%) of the most commonly used mammalian cell line, i.e. the Chinese hamster lung fibroblasts (V79). The IBWF, intended as a simple and robust tool for a fast RBE assessment to compare different exposure conditions in particle therapy beams, was determined through an iterative global-fitting process aimed to minimize the average relative deviation between RBE calculations and literature in vitro data in case of exposure to various types of ions from 1H to 238U. By using a single particle- and energy- independent function, it was possible to establish an univocal correlation between lineal energy and clonogenic cell survival for particles spanning over an unrestricted linear energy transfer range of almost five orders of magnitude (0.2 keV µm-1 to 15 000 keV µm-1 in liquid water). The average deviation between IBWF-derived RBE values and the published in vitro data was ∼14%. The IBWF results were also compared with corresponding calculations (in vitro RBE10 for the V79 cell line) performed using the modified microdosimetric kinetic model (modified MKM). Furthermore, RBE values computed with the reference biological weighting function (BWF) for the in vivo early intestine tolerance in mice were included for comparison and to further explore potential correlations between the BWF results and the in vitro RBE as reported in previous studies. The results suggest that the modified MKM possess limitations in reproducing the experimental in vitro RBE10 for the V79 cell line in case of ions heavier than 20Ne. Furthermore, due to the different modelled endpoint, marked deviations were found between the RBE values assessed using the reference BWF and the IBWF for ions heavier than 2H. Finally, the IBWF was unchangingly applied to calculate RBE values by processing lineal energy density distributions experimentally measured with eight different microdosimeters in 19 1H and 12C beams at ten different facilities (eight clinical and two research ones). Despite the differences between the detectors, irradiation facilities, beam profiles (pristine or spread out Bragg peak), maximum beam energy, beam delivery (passive or active scanning), energy degradation system (water, PMMA, polyamide or low-density polyethylene), the obtained IBWF-based RBE trends were found to be in good agreement with the corresponding ones in case of computer-simulated microdosimetric spectra (average relative deviation equal to 0.8% and 5.7% for 1H and 12C ions respectively).
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Ingram SP, Henthorn NT, Warmenhoven JW, Kirkby NF, Mackay RI, Kirkby KJ, Merchant MJ. Hi-C implementation of genome structure for in silico models of radiation-induced DNA damage. PLoS Comput Biol 2020; 16:e1008476. [PMID: 33326415 PMCID: PMC7773326 DOI: 10.1371/journal.pcbi.1008476] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2020] [Revised: 12/30/2020] [Accepted: 10/28/2020] [Indexed: 02/06/2023] Open
Abstract
Developments in the genome organisation field has resulted in the recent methodology to infer spatial conformations of the genome directly from experimentally measured genome contacts (Hi-C data). This provides a detailed description of both intra- and inter-chromosomal arrangements. Chromosomal intermingling is an important driver for radiation-induced DNA mis-repair. Which is a key biological endpoint of relevance to the fields of cancer therapy (radiotherapy), public health (biodosimetry) and space travel. For the first time, we leverage these methods of inferring genome organisation and couple them to nano-dosimetric radiation track structure modelling to predict quantities and distribution of DNA damage within cell-type specific geometries. These nano-dosimetric simulations are highly dependent on geometry and are benefited from the inclusion of experimentally driven chromosome conformations. We show how the changes in Hi-C contract maps impact the inferred geometries resulting in significant differences in chromosomal intermingling. We demonstrate how these differences propagate through to significant changes in the distribution of DNA damage throughout the cell nucleus, suggesting implications for DNA repair fidelity and subsequent cell fate. We suggest that differences in the geometric clustering for the chromosomes between the cell-types are a plausible factor leading to changes in cellular radiosensitivity. Furthermore, we investigate changes in cell shape, such as flattening, and show that this greatly impacts the distribution of DNA damage. This should be considered when comparing in vitro results to in vivo systems. The effect may be especially important when attempting to translate radiosensitivity measurements at the experimental in vitro level to the patient or human level.
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Affiliation(s)
- Samuel P. Ingram
- Division of Cancer Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, United Kingdom
- Christie Medical Physics and Engineering, The Christie NHS Foundation Trust, Manchester, United Kingdom
| | - Nicholas T. Henthorn
- Division of Cancer Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, United Kingdom
- The Christie NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, United Kingdom
| | - John W. Warmenhoven
- Division of Cancer Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, United Kingdom
- The Christie NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, United Kingdom
| | - Norman F. Kirkby
- Division of Cancer Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, United Kingdom
- The Christie NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, United Kingdom
| | - Ranald I. Mackay
- Division of Cancer Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, United Kingdom
- Christie Medical Physics and Engineering, The Christie NHS Foundation Trust, Manchester, United Kingdom
| | - Karen J. Kirkby
- Division of Cancer Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, United Kingdom
- The Christie NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, United Kingdom
| | - Michael J. Merchant
- Division of Cancer Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, United Kingdom
- The Christie NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, United Kingdom
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25
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Ramos-Méndez J, Domínguez-Kondo N, Schuemann J, McNamara A, Moreno-Barbosa E, Faddegon B. LET-Dependent Intertrack Yields in Proton Irradiation at Ultra-High Dose Rates Relevant for FLASH Therapy. Radiat Res 2020; 194:351-362. [PMID: 32857855 PMCID: PMC7644138 DOI: 10.1667/rade-20-00084.1] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2020] [Accepted: 07/13/2020] [Indexed: 01/01/2023]
Abstract
FLASH radiotherapy delivers a high dose (≥10 Gy) at a high rate (≥40 Gy/s). In this way, particles are delivered in pulses as short as a few nanoseconds. At that rate, intertrack reactions between chemical species produced within the same pulse may affect the heterogeneous chemistry stage of water radiolysis. This stochastic process suits the capabilities of the Monte Carlo method, which can model intertrack effects to aid in radiobiology research, including the design and interpretation of experiments. In this work, the TOPAS-nBio Monte Carlo track-structure code was expanded to allow simulations of intertrack effects in the chemical stage of water radiolysis. Simulation of the behavior of radiolytic yields over a long period of time (up to 50 s) was verified by simulating radiolysis in a Fricke dosimeter irradiated by 60Co γ rays. In addition, LET-dependent G values of protons delivered in single squared pulses of widths, 1 ns, 1 µs and 10 µs, were obtained and compared to simulations using no intertrack considerations. The Fricke simulation for the calculated G value of Fe3+ ion at 50 s was within 0.4% of the accepted value from ICRU Report 34. For LET-dependent G values at the end of the chemical stage, intertrack effects were significant at LET values below 2 keV/µm. Above 2 keV/µm the reaction kinetics remained limited locally within each track and thus, effects of intertrack reactions remained low. Therefore, when track structure simulations are used to investigate the biological damage of FLASH irradiation, these intertrack reactions should be considered. The TOPAS-nBio framework with the expansion to intertrack chemistry simulation provides a useful tool to assist in this task.
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Affiliation(s)
- J. Ramos-Méndez
- Department of Radiation Oncology, University of California San Francisco, San Francisco, California
| | - N. Domínguez-Kondo
- Facultad de Ciencias Físico-Matemáticas, Benemérita Universidad Autónoma de Puebla, Puebla, Mexico
| | - J. Schuemann
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts
| | - A. McNamara
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts
| | - E. Moreno-Barbosa
- Facultad de Ciencias Físico-Matemáticas, Benemérita Universidad Autónoma de Puebla, Puebla, Mexico
| | - Bruce Faddegon
- Department of Radiation Oncology, University of California San Francisco, San Francisco, California
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26
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Carabe A, Karagounis IV, Huynh K, Bertolet A, François N, Kim MM, Maity A, Abel E, Dale R. Radiobiological effectiveness difference of proton arc beams versus conventional proton and photon beams. Phys Med Biol 2020; 65:165002. [PMID: 32413889 DOI: 10.1088/1361-6560/ab9370] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
This paper aims to demonstrate the difference in biological effectiveness of proton monoenergetic arc therapy (PMAT) compared to intensity modulated proton therapy (IMPT) and conventional 6 MV photon therapy, and to quantify this difference when exposing cells of different radiosensitivity to the same experimental conditions for each modality. V79, H1299 and H460 cells were cultured in petri dishes placed in the central axis of a cylindrical and homogeneous solid water phantom of 20 cm in diameter. For the PMAT plan, cells were exposed to 13 mono-energetic proton beams separated every 15° over a 180° arc, designed to deliver a uniform dose of higher LET to the petri dishes. For the IMPT plans, 3 fields were used, where each field was modulated to cover the full target. Cells were also exposed to 6 MV photon beams in petri dishes to characterize their radiosensitivity. The relative biological effectiveness of the PMAT plans compared with those of IMPT was measured using clonogenic assays. Similarly, in order to study the quantity and quality of the DNA damage induced by the PMAT plans compared to that of IMPT and photons, γ-H2AX assays were conducted to study the relative amount of DNA damage induced by each modality, and their repair rate over time. The clonogenic assay revealed similar survival levels to the same dose delivered with IMPT or x-rays. However, a systematic average of up to a 43% increase in effectiveness in PMAT plans was observed when compared with IMPT. In addition, the repair kinetic assays proved that PMAT induces larger and more complex DNA damage (evidenced by a slower repair rate and a larger proportion of unrepaired DNA damage) than IMPT. The repair kinetics of IMPT and 6 MV photon therapy were similar. Mono-energetic arc beams offer the possibility of taking advantage of the enhanced LET of proton beams to increase TCP. This study presents initial results based on exposing cells with different radiosensitivity to other modalities under the same experimental conditions, but more extensive clonogenic and in-vivo studies will be required to confirm the validity of these results.
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Affiliation(s)
- Alejandro Carabe
- Department of Radiation Oncology, Perelman School of Medicine, University of Pennsylvania, PA, United States of America. Author to whom any correspondence should be addressed
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27
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Warmenhoven JW, Henthorn NT, Ingram SP, Chadwick AL, Sotiropoulos M, Korabel N, Fedotov S, Mackay RI, Kirkby KJ, Merchant MJ. Insights into the non-homologous end joining pathway and double strand break end mobility provided by mechanistic in silico modelling. DNA Repair (Amst) 2020; 85:102743. [DOI: 10.1016/j.dnarep.2019.102743] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2019] [Revised: 10/25/2019] [Accepted: 10/25/2019] [Indexed: 12/26/2022]
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28
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Aguilar-Hernández I, Cárdenas-Chavez DL, López-Luke T, García-García A, Herrera-Domínguez M, Pisano E, Ornelas-Soto N. Discrimination of radiosensitive and radioresistant murine lymphoma cells by Raman spectroscopy and SERS. BIOMEDICAL OPTICS EXPRESS 2020; 11:388-405. [PMID: 32010523 PMCID: PMC6968773 DOI: 10.1364/boe.11.000388] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/03/2019] [Revised: 11/22/2019] [Accepted: 12/02/2019] [Indexed: 05/10/2023]
Abstract
Intrinsic radiosensitivity is a biological parameter known to influence the response to radiation therapy in cancer treatment. In this study, Raman spectroscopy and surface enhanced Raman spectroscopy (SERS) were successfully used in conjunction with principal component analysis (PCA) to discriminate between radioresistant (LY-R) and radiosensitive (LY-S) murine lymphoma sublines (L5178Y). PCA results for normal Raman analysis showed a differentiation between the radioresistant and radiosensitive cell lines based on their specific spectral fingerprint. In the case of SERS with gold nanoparticles (AuNPs), greater spectral enhancements were observed in the radioresistant subline in comparison to its radiosensitive counterpart, suggesting that each subline displays different interaction with AuNPs. Our results indicate that spectroscopic and chemometric techniques could be used as complementary tools for the prediction of intrinsic radiosensitivity of lymphoma samples.
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Affiliation(s)
- Iris Aguilar-Hernández
- Laboratorio de Nanotecnología Ambiental, Tecnologico de Monterrey, Escuela de Ingeniería y Ciencias, Ave. Eugenio Garza Sada 2501, Monterrey, N.L. 64849, Mexico
| | - Diana L. Cárdenas-Chavez
- Tecnologico de Monterrey, Escuela de Ingeniería y Ciencias, Atlixcáyotl 5718, Puebla, Pue., México, 72453, Mexico
| | - Tzarara López-Luke
- Instituto de Investigación en Metalurgia y Materiales, Universidad Michoacana de San Nicolás de Hidalgo, Edificio U, Ciudad Universitaria, 58030 Morelia, Mich., Mexico
| | - Alejandra García-García
- Laboratorio de síntesis y Modificación de Nanoestructuras y Materiales Bidimensionales. Centro de Investigación en Materiales Avanzados S.C. Parque PIIT. C.P. 66628, Apodaca N.L., Mexico
| | - Marcela Herrera-Domínguez
- Laboratorio de Nanotecnología Ambiental, Tecnologico de Monterrey, Escuela de Ingeniería y Ciencias, Ave. Eugenio Garza Sada 2501, Monterrey, N.L. 64849, Mexico
| | - Eduardo Pisano
- Catedras CONACyT – Centro de Investigaciones en Óptica A.C., Alianza Centro 504, PIIT, Apodaca, N.L. 66629, Mexico
| | - Nancy Ornelas-Soto
- Laboratorio de Nanotecnología Ambiental, Tecnologico de Monterrey, Escuela de Ingeniería y Ciencias, Ave. Eugenio Garza Sada 2501, Monterrey, N.L. 64849, Mexico
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A Bi-Exponential Repair Algorithm for Radiation-Induced Double-Strand Breaks: Application to Simulation of Chromosome Aberrations. Genes (Basel) 2019; 10:genes10110936. [PMID: 31744120 PMCID: PMC6896174 DOI: 10.3390/genes10110936] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2019] [Revised: 11/01/2019] [Accepted: 11/12/2019] [Indexed: 01/04/2023] Open
Abstract
Background: Radiation induces DNA double-strand breaks (DSBs), and chromosome aberrations (CA) form during the DSBs repair process. Several methods have been used to model the repair kinetics of DSBs including the bi-exponential model, i.e., N(t) = N1exp(−t/τ1) + N2exp(−t/τ2), where N(t) is the number of breaks at time t, and N1, N2, τ1 and τ2 are parameters. This bi-exponential fit for DSB decay suggests that some breaks are repaired rapidly and other, more complex breaks, take longer to repair. Methods: The bi-exponential repair kinetics model is implemented into a recent simulation code called RITCARD (Radiation Induced Tracks, Chromosome Aberrations, Repair, and Damage). RITCARD simulates the geometric configuration of human chromosomes, radiation-induced breaks, their repair, and the creation of various categories of CAs. The bi-exponential repair relies on a computational algorithm that is shown to be mathematically exact. To categorize breaks as complex or simple, a threshold for the local (voxel) dose was used. Results: The main findings are: i) the curves for the kinetics of restitution of DSBs are mostly independent of dose; ii) the fraction of unrepaired breaks increases with the linear energy transfer (LET) of the incident radiation; iii) the simulated dose–response curves for simple reciprocal chromosome exchanges that are linear-quadratic; iv) the alpha coefficient of the dose–response curve peaks at about 100 keV/µm.
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Plante I, Ponomarev A, Patel Z, Slaba T, Hada M. RITCARD: Radiation-Induced Tracks, Chromosome Aberrations, Repair and Damage. Radiat Res 2019; 192:282-298. [PMID: 31295089 DOI: 10.1667/rr15250.1] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
Abstract
Chromosome aberrations (CAs) are one of the effects of radiation exposure and can have implications for human health in the space environment, since they are related to cancer risk. In radiation research, chromosome aberrations are a convenient biomarker for carcinogenesis. To shed light on the formation and quality of chromosome aberrations in the space environment, many experiments and simulations have been performed using chromosome aberrations in human cells, induced by heavy ions, which are present in galactic cosmic rays (GCRs). In this work, the new simulation program, radiation-induced tracks, chromosome aberrations, repair and damage (RITCARD), is presented. This software program is based on the algorithm used in the NASA Radiation Track Image (NASARTI) model with some improvements. NASARTI and RITCARD are both comprised of four parts: a random walk (RW) algorithm for simulating chromosomes in a nucleus; a deoxyribonucleic acid (DNA) damage algorithm; a break repair process; and a function to assess and count chromosome aberrations. Prior to running RITCARD, the code, relativistic ion tracks (RITRACKS), is used to simulate detailed radiation track structure and calculate time-dependent differential voxel dose maps in a parallelepiped centered on a cell nucleus. The RITCARD program reads the pre-calculated voxel dose and locates the intersections between the voxels and the chromosomes that were simulated by random walk. Radiation-induced breaks occur strictly at these intersections with a probability that is a function of the voxel dose. When a break occurs in the random walk, the corresponding chromosome piece is cut into two fragments where each has a free end at the position of the break. RITCARD generates a collection of all fragments, free ends, and enlists free end pairs. In the next step, the algorithm simulates the time-dependent rejoining of free end pairs, using different probabilities for pairs originating from a given break (proper) or from different breaks (improper), which results in the formation of fragment sequences. By grouping these sequences, the program determines the number and types of aberrations, based on the same criteria used in our experiment. The new program is used to assess the yields of various types of chromosome aberrations in human fibroblast cells for several ions (1H+, 4He2+, 12C6+, 16O8+, 20Ne10+, 28Si14+, 48Ti22+ and 56Fe26+) with energies varying from 10 to 1,000 MeV/n. The results show linear and linear-quadratic dose dependence for most chromosome aberrations types. The calculation results were compared with those obtained by fluorescence in situ hybridization (FISH) experiments that were performed by our group. The simulations and experiments are in better agreement at lower LET. Regarding the simulation results, the coefficient of the linear part of the dose-dependence curve also peaks at an LET value of approximately 100 keV/lm, which evokes a relative biological effectiveness (RBE) peak found by other researchers.
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Affiliation(s)
| | | | | | - Tony Slaba
- NASA Langley Research Center, Hampton, Virginia 23681
| | - Megumi Hada
- Prairie View A&M University, Prairie View, Texas 77446
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31
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Oesten H, Neubeck CV, Jakob A, Enghardt W, Krause M, McMahon SJ, Grassberger C, Paganetti H, Lühr A. Predicting In Vitro Cancer Cell Survival Based on Measurable Cell Characteristics. Radiat Res 2019; 191:532-544. [PMID: 31008688 DOI: 10.1667/rr15265.1] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
Abstract
Variation in cellular characteristics may determine tumor response and, consequently, patient survival in radiation therapy. However, patient-specific prediction of cellular radiation response is currently unavailable for treatment planning. Thus, the importance of developing a novel approach based on clinically accessible parameters prior to treatment (e.g., by biopsy) is high. The goal of this study was to predict in vitro cancer cell survival through the p53mutation status and the number of chromosomes (NoC). To predict cell survival, we modified a mechanistic radiation response model incorporating DNA repair and cell death, originally designed for normal human cells. Cell-specific parameters of 24 cell lines originating from two laboratories (OncoRay, Dresden, Germany and HIMAC, Chiba, Japan) were considered for modeling. In a first step, we obtained estimates of the only unknown model input parameter genome size (GS) by fitting cell survival simulations onto experimental data. We then analyzed measured and published input model parameters (NoC, p53-mutation status and cell-cycle distribution) to assess their impact on measured and simulated parameters (modeled GS, and measured α, β, SF2 and γ-H2AX). The resulting data suggested a linear correlation between NoC and modeled GS (R2 > 0.93) allowing for estimating GS based on NoC. Applying the estimated GS resulted in predicted cell survival that matched measured data mostly within the experimental uncertainty. The measured radiobiological value β increased quadratically with the cell's modeled GS irrespective of other cell-specific parameters. The measured α and SF2 split into two groups, depending on the cells' p53-mutation status, both linearly increasing and decreasing, respectively, with modeled GS. Model predictions of foci numbers were, on average, in agreement with published γ-H2AX measurement data. In conclusion, knowledge of clinically accessible parameters (p53-mutation status and NoC) may support patient stratification in radiotherapy based on cell-specific survival prediction testable in prospective clinical trials.
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Affiliation(s)
- Hakan Oesten
- a Helmholtz-Zentrum Dresden - Rossendorf (HZDR), Institute of Radiooncology - OncoRay, Dresden, Germany.,b OncoRay - National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Helmholtz-Zentrum Dresden - Rossendorf, Dresden, Germany.,c Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts
| | - Cläre von Neubeck
- b OncoRay - National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Helmholtz-Zentrum Dresden - Rossendorf, Dresden, Germany.,d German Cancer Consortium (DKTK), partner site Dresden, and German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Aline Jakob
- b OncoRay - National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Helmholtz-Zentrum Dresden - Rossendorf, Dresden, Germany.,d German Cancer Consortium (DKTK), partner site Dresden, and German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Wolfgang Enghardt
- a Helmholtz-Zentrum Dresden - Rossendorf (HZDR), Institute of Radiooncology - OncoRay, Dresden, Germany.,b OncoRay - National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Helmholtz-Zentrum Dresden - Rossendorf, Dresden, Germany.,e Department of Radiotherapy and Radiation Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
| | - Mechthild Krause
- a Helmholtz-Zentrum Dresden - Rossendorf (HZDR), Institute of Radiooncology - OncoRay, Dresden, Germany.,b OncoRay - National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Helmholtz-Zentrum Dresden - Rossendorf, Dresden, Germany.,d German Cancer Consortium (DKTK), partner site Dresden, and German Cancer Research Center (DKFZ), Heidelberg, Germany.,e Department of Radiotherapy and Radiation Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany.,f National Center for Tumor Diseases (NCT), partner site Dresden, Germany
| | - Stephen J McMahon
- g Centre for Cancer Research and Cell Biology, Queen's University Belfast, Belfast, North Ireland
| | - Clemens Grassberger
- c Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts
| | - Harald Paganetti
- c Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts
| | - Armin Lühr
- a Helmholtz-Zentrum Dresden - Rossendorf (HZDR), Institute of Radiooncology - OncoRay, Dresden, Germany.,b OncoRay - National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Helmholtz-Zentrum Dresden - Rossendorf, Dresden, Germany.,d German Cancer Consortium (DKTK), partner site Dresden, and German Cancer Research Center (DKFZ), Heidelberg, Germany
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Mechanistic Modelling of Radiation Responses. Cancers (Basel) 2019; 11:cancers11020205. [PMID: 30744204 PMCID: PMC6406300 DOI: 10.3390/cancers11020205] [Citation(s) in RCA: 35] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2018] [Revised: 02/04/2019] [Accepted: 02/06/2019] [Indexed: 12/30/2022] Open
Abstract
Radiobiological modelling has been a key part of radiation biology and therapy for many decades, and many aspects of clinical practice are guided by tools such as the linear-quadratic model. However, most of the models in regular clinical use are abstract and empirical, and do not provide significant scope for mechanistic interpretation or making predictions in novel cell lines or therapies. In this review, we will discuss the key areas of ongoing mechanistic research in radiation biology, including physical, chemical, and biological steps, and review a range of mechanistic modelling approaches which are being applied in each area, highlighting the possible opportunities and challenges presented by these techniques.
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Schuemann J, McNamara AL, Ramos-Méndez J, Perl J, Held KD, Paganetti H, Incerti S, Faddegon B. TOPAS-nBio: An Extension to the TOPAS Simulation Toolkit for Cellular and Sub-cellular Radiobiology. Radiat Res 2019; 191:125-138. [PMID: 30609382 DOI: 10.1667/rr15226.1] [Citation(s) in RCA: 107] [Impact Index Per Article: 21.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
The TOPAS Monte Carlo (MC) system is used in radiation therapy and medical imaging research, having played a significant role in making Monte Carlo simulations widely available for proton therapy related research. While TOPAS provides detailed simulations of patient scale properties, the fundamental unit of the biological response to radiation is a cell. Thus, our goal was to develop TOPAS-nBio, an extension of TOPAS dedicated to advance understanding of radiobiological effects at the (sub-)cellular, (i.e., the cellular and sub-cellular) scale. TOPAS-nBio was designed as a set of open source classes that extends TOPAS to model radiobiological experiments. TOPAS-nBio is based on and extends Geant4-DNA, which extends the Geant4 toolkit, the basis of TOPAS, to include very low-energy interactions of particles down to vibrational energies, explicitly simulates every particle interaction (i.e., without using condensed histories) and propagates radiolysis products. To further facilitate the use of TOPAS-nBio, a graphical user interface was developed. TOPAS-nBio offers full track-structure Monte Carlo simulations, integration of chemical reactions within the first millisecond, an extensive catalogue of specialized cell geometries as well as sub-cellular structures such as DNA and mitochondria, and interfaces to mechanistic models of DNA repair kinetics. We compared TOPAS-nBio simulations to measured and published data of energy deposition patterns and chemical reaction rates (G values). Our simulations agreed well within the experimental uncertainties. Additionally, we expanded the chemical reactions and species provided in Geant4-DNA and developed a new method based on independent reaction times (IRT), including a total of 72 reactions classified into 6 types between neutral and charged species. Chemical stage simulations using IRT were a factor of 145 faster than with step-by-step tracking. Finally, we applied the geometric/chemical modeling to obtain initial yields of double-strand breaks (DSBs) in DNA fibers for proton irradiations of 3 and 50 MeV and compared the effect of including chemical reactions on the number and complexity of DSB induction. Over half of the DSBs were found to include chemical reactions with approximately 5% of DSBs caused only by chemical reactions. In conclusion, the TOPAS-nBio extension to the TOPAS MC application offers access to accurate and detailed multiscale simulations, from a macroscopic description of the radiation field to microscopic description of biological outcome for selected cells. TOPAS-nBio offers detailed physics and chemistry simulations of radiobiological experiments on cells simulating the initially induced damage and links to models of DNA repair kinetics.
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Affiliation(s)
- J Schuemann
- a Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts
| | - A L McNamara
- a Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts
| | - J Ramos-Méndez
- b Department of Radiation Oncology, University of California San Francisco, San Francisco, California
| | - J Perl
- c SLAC National Accelerator Laboratory, Menlo Park, California
| | - K D Held
- a Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts
| | - H Paganetti
- a Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts
| | - S Incerti
- d CNRS, IN2P3, CENBG, UMR 5797, F-33170 Gradignan, France.,e University of Bordeaux, CENBG, UMR 5797, F-33170 Gradignan, France
| | - B Faddegon
- b Department of Radiation Oncology, University of California San Francisco, San Francisco, California
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McMahon SJ. The linear quadratic model: usage, interpretation and challenges. ACTA ACUST UNITED AC 2018; 64:01TR01. [DOI: 10.1088/1361-6560/aaf26a] [Citation(s) in RCA: 125] [Impact Index Per Article: 20.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
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McMahon SJ, Paganetti H, Prise KM. LET-weighted doses effectively reduce biological variability in proton radiotherapy planning. ACTA ACUST UNITED AC 2018; 63:225009. [DOI: 10.1088/1361-6560/aae8a5] [Citation(s) in RCA: 34] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
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36
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Schuemann J, McNamara AL, Warmenhoven JW, Henthorn NT, Kirkby KJ, Merchant MJ, Ingram S, Paganetti H, Held KD, Ramos-Mendez J, Faddegon B, Perl J, Goodhead DT, Plante I, Rabus H, Nettelbeck H, Friedland W, Kundrát P, Ottolenghi A, Baiocco G, Barbieri S, Dingfelder M, Incerti S, Villagrasa C, Bueno M, Bernal MA, Guatelli S, Sakata D, Brown JMC, Francis Z, Kyriakou I, Lampe N, Ballarini F, Carante MP, Davídková M, Štěpán V, Jia X, Cucinotta FA, Schulte R, Stewart RD, Carlson DJ, Galer S, Kuncic Z, Lacombe S, Milligan J, Cho SH, Sawakuchi G, Inaniwa T, Sato T, Li W, Solov'yov AV, Surdutovich E, Durante M, Prise KM, McMahon SJ. A New Standard DNA Damage (SDD) Data Format. Radiat Res 2018; 191:76-92. [PMID: 30407901 DOI: 10.1667/rr15209.1] [Citation(s) in RCA: 42] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
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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Affiliation(s)
- J Schuemann
- a Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts
| | - A L McNamara
- a Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts
| | - J W Warmenhoven
- b Division of Cancer Sciences, The University of Manchester, Manchester, United Kingdom
| | - N T Henthorn
- b Division of Cancer Sciences, The University of Manchester, Manchester, United Kingdom
| | - K J Kirkby
- b Division of Cancer Sciences, The University of Manchester, Manchester, United Kingdom
| | - M J Merchant
- b Division of Cancer Sciences, The University of Manchester, Manchester, United Kingdom
| | - S Ingram
- b Division of Cancer Sciences, The University of Manchester, Manchester, United Kingdom
| | - H Paganetti
- a Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts
| | - K D Held
- a Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts
| | - J Ramos-Mendez
- c Department of Radiation Oncology, University of California San Francisco, San Francisco, California
| | - B Faddegon
- c Department of Radiation Oncology, University of California San Francisco, San Francisco, California
| | - J Perl
- d SLAC National Accelerator Laboratory, Menlo Park, California
| | - D T Goodhead
- e Medical Research Council, Harwell, United Kingdom
| | | | - H Rabus
- g Physikalisch-Technische Bundesanstalt (PTB), Braunschweig, Germany.,h Task Group 6.2 "Computational Micro- and Nanodosimetry", European Radiation Dosimetry Group e.V., Neuherberg, Germany
| | - H Nettelbeck
- g Physikalisch-Technische Bundesanstalt (PTB), Braunschweig, Germany.,h Task Group 6.2 "Computational Micro- and Nanodosimetry", European Radiation Dosimetry Group e.V., Neuherberg, Germany
| | - W Friedland
- h Task Group 6.2 "Computational Micro- and Nanodosimetry", European Radiation Dosimetry Group e.V., Neuherberg, Germany.,i Institute of Radiation Protection, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
| | - P Kundrát
- i Institute of Radiation Protection, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
| | - A Ottolenghi
- j Physics Department, University of Pavia, Pavia, Italy
| | - G Baiocco
- h Task Group 6.2 "Computational Micro- and Nanodosimetry", European Radiation Dosimetry Group e.V., Neuherberg, Germany.,j Physics Department, University of Pavia, Pavia, Italy
| | - S Barbieri
- h Task Group 6.2 "Computational Micro- and Nanodosimetry", European Radiation Dosimetry Group e.V., Neuherberg, Germany.,j Physics Department, University of Pavia, Pavia, Italy
| | - M Dingfelder
- k Department of Physics, East Carolina University, Greenville, North Carolina
| | - S Incerti
- l CNRS, IN2P3, CENBG, UMR 5797, F-33170 Gradignan, France.,m University of Bordeaux, CENBG, UMR 5797, F-33170 Gradignan, France
| | - C Villagrasa
- h Task Group 6.2 "Computational Micro- and Nanodosimetry", European Radiation Dosimetry Group e.V., Neuherberg, Germany.,n Institut de Radioprotection et Sûreté Nucléaire, F-92262 Fontenay aux Roses Cedex, France
| | - M Bueno
- n Institut de Radioprotection et Sûreté Nucléaire, F-92262 Fontenay aux Roses Cedex, France
| | - M A Bernal
- o Applied Physics Department, Gleb Wataghin Institute of Physics, State University of Campinas, Campinas, SP, Brazil
| | - S Guatelli
- p Centre for Medical Radiation Physics, University of Wollongong, Wollongong, NSW, Australia
| | - D Sakata
- p Centre for Medical Radiation Physics, University of Wollongong, Wollongong, NSW, Australia
| | - J M C Brown
- q Department of Radiation Science and Technology, Delft University of Technology, Delft, The Netherlands
| | - Z Francis
- r Department of Physics, Faculty of Science, Saint Joseph University, Beirut, Lebanon
| | - I Kyriakou
- s Medical Physics Laboratory, University of Ioannina Medical School, Ioannina, Greece
| | - N Lampe
- l CNRS, IN2P3, CENBG, UMR 5797, F-33170 Gradignan, France
| | - F Ballarini
- j Physics Department, University of Pavia, Pavia, Italy.,t Italian National Institute of Nuclear Physics, Section of Pavia, I-27100 Pavia, Italy
| | - M P Carante
- j Physics Department, University of Pavia, Pavia, Italy.,t Italian National Institute of Nuclear Physics, Section of Pavia, I-27100 Pavia, Italy
| | - M Davídková
- u Department of Radiation Dosimetry, Nuclear Physics Institute of the CAS, Řež, Czech Republic
| | - V Štěpán
- u Department of Radiation Dosimetry, Nuclear Physics Institute of the CAS, Řež, Czech Republic
| | - X Jia
- v Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, Texas
| | - F A Cucinotta
- w Health Physics and Diagnostic Sciences, University of Nevada Las Vegas, Las Vegas, Nevada
| | - R Schulte
- x Division of Biomedical Engineering Sciences, School of Medicine, Loma Linda University, Loma Linda, California
| | - R D Stewart
- y Department of Radiation Oncology, University of Washington, Seattle, Washington
| | - D J Carlson
- z Department of Therapeutic Radiology, Yale University School of Medicine, New Haven, Connecticut
| | - S Galer
- aa Medical Radiation Science Group, National Physical Laboratory, Teddington, United Kingdom
| | - Z Kuncic
- bb School of Physics, University of Sydney, Sydney, NSW, Australia
| | - S Lacombe
- cc Institut des Sciences Moléculaires d'Orsay (UMR 8214) University Paris-Sud, CNRS, University Paris-Saclay, 91405 Orsay Cedex, France
| | | | - S H Cho
- ee Department of Radiation Physics and Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - G Sawakuchi
- ee Department of Radiation Physics and Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - T Inaniwa
- ff Department of Accelerator and Medical Physics, National Institute of Radiological Sciences, Chiba, Japan
| | - T Sato
- gg Japan Atomic Energy Agency, Nuclear Science and Engineering Center, Tokai 319-1196, Japan
| | - W Li
- i Institute of Radiation Protection, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany.,hh Task Group 7.7 "Internal Micro- and Nanodosimetry", European Radiation Dosimetry Group e.V., Neuherberg, Germany
| | - A V Solov'yov
- ii MBN Research Center, 60438 Frankfurt am Main, Germany
| | - E Surdutovich
- jj Department of Physics, Oakland University, Rochester, Michigan
| | - M Durante
- kk GSI Helmholtzzentrum für Schwerionenforschung, Biophysics Department, Darmstadt, Germany
| | - K M Prise
- ll Centre for Cancer Research and Cell Biology, Queens University Belfast, Belfast, United Kingdom
| | - S J McMahon
- ll Centre for Cancer Research and Cell Biology, Queens University Belfast, Belfast, United Kingdom
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Wang W, Li C, Qiu R, Chen Y, Wu Z, Zhang H, Li J. Modelling of Cellular Survival Following Radiation-Induced DNA Double-Strand Breaks. Sci Rep 2018; 8:16202. [PMID: 30385845 PMCID: PMC6212584 DOI: 10.1038/s41598-018-34159-3] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2018] [Accepted: 07/24/2018] [Indexed: 12/30/2022] Open
Abstract
A mechanistic model of cellular survival following radiation-induced DNA double-strand breaks (DSBs) was proposed in this study. DSBs were assumed as the initial lesions in the DNA of the cell nucleus induced by ionizing radiation. The non-homologous end-joining (NHEJ) pathway was considered as the domain pathway of DSB repair in mammalian cells. The model was proposed to predict the relationship between radiation-induced DSBs in nucleus and probability of cell survival, which was quantitatively described by two input parameters and six fitting parameters. One input parameter was the average number of primary particles which caused DSB, the other input parameter was the average number of DSBs yielded by each primary particle that caused DSB. The fitting parameters were used to describe the biological characteristics of the irradiated cells. By determining the fitting parameters of the model with experimental data, the model is able to estimate surviving fractions for the same type of cells exposed to particles with different physical parameters. The model further revealed the mechanism of cell death induced by the DSB effect. Relative biological effectiveness (RBE) of charged particles at different survival could be calculated with the model, which would provide reference for clinical treatment.
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Affiliation(s)
- Wenjing Wang
- Department of Engineering Physics, Tsinghua University, Beijing, China
- Key Laboratory of Particle & Radiation Imaging (Tsinghua University), Ministry of Education, Beijing, China
| | - Chunyan Li
- Department of Engineering Physics, Tsinghua University, Beijing, China
- Nuctech Company Limited, Beijing, China
| | - Rui Qiu
- Department of Engineering Physics, Tsinghua University, Beijing, China.
- Key Laboratory of Particle & Radiation Imaging (Tsinghua University), Ministry of Education, Beijing, China.
| | - Yizheng Chen
- Department of Engineering Physics, Tsinghua University, Beijing, China
- Key Laboratory of Particle & Radiation Imaging (Tsinghua University), Ministry of Education, Beijing, China
| | - Zhen Wu
- Department of Engineering Physics, Tsinghua University, Beijing, China
- Nuctech Company Limited, Beijing, China
| | - Hui Zhang
- Department of Engineering Physics, Tsinghua University, Beijing, China
- Key Laboratory of Particle & Radiation Imaging (Tsinghua University), Ministry of Education, Beijing, China
| | - Junli Li
- Department of Engineering Physics, Tsinghua University, Beijing, China
- Key Laboratory of Particle & Radiation Imaging (Tsinghua University), Ministry of Education, Beijing, China
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Lazar AA, Schulte R, Faddegon B, Blakely EA, Roach M. Clinical trials involving carbon-ion radiation therapy and the path forward. Cancer 2018; 124:4467-4476. [PMID: 30307603 DOI: 10.1002/cncr.31662] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2018] [Revised: 06/22/2018] [Accepted: 06/29/2018] [Indexed: 02/06/2023]
Abstract
To describe the international landscape of clinical trials in carbon-ion radiotherapy (CIRT), the authors reviewed the current status of 63 ongoing clinical trials (median, 47 participants) involving CIRT identified from the US clinicaltrials.gov trial registry and the World Health Organization International Clinical Trials Platform Registry. The objectives were to evaluate the potential for these trials to define the role of this modality in the treatment of specific cancer types and identify the major challenges and opportunities to advance this technology. A significant body of literature suggested the potential for advantageous dose distributions and, in preclinical biologic studies, the enhanced effectiveness for CIRT compared with photons and protons. In addition, clinical evidence from phase I/II trials, although limited, indicated the potential for CIRT to improve cancer outcomes. However, current high-level phase III randomized clinical trial evidence does not exist. Although there has been an increase in the number of trials investigating CIRT since 2010, and the number of countries and sites offering CIRT is slowly growing, this progress has excluded other countries. Several recommendations are proposed to study this modality to accelerate progress in the field, including: 1) increasing the number of multinational randomized clinical trials, 2) leveraging the existing CIRT facilities to launch larger multinational trials directed at common cancers combined with high-level quality assurance; and 3) developing more compact and less expensive next-generation treatment systems integrated with radiobiologic research and preclinical testing.
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Affiliation(s)
- Ann A Lazar
- Department of Preventive and Restorative Dental Sciences, University of California San Francisco (UCSF), San Francisco, California.,Department of Epidemiology and Biostatistics, UCSF, San Francisco, California
| | - Reinhard Schulte
- Department of Radiation Oncology, UCSF, San Francisco, California.,Department of Basic Sciences, Division of Biomedical Engineering Sciences, Loma Linda University, Loma Linda, California
| | - Bruce Faddegon
- Department of Radiation Oncology, UCSF, San Francisco, California
| | - Eleanor A Blakely
- Division of Biological Systems and Engineering, Lawrence Berkeley National Laboratory, Berkeley, California
| | - Mack Roach
- Department of Radiation Oncology, UCSF, San Francisco, California
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Paganetti H. Proton Relative Biological Effectiveness - Uncertainties and Opportunities. Int J Part Ther 2018; 5:2-14. [PMID: 30370315 DOI: 10.14338/ijpt-18-00011.1] [Citation(s) in RCA: 45] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Abstract
Proton therapy treatments are prescribed using a biological effectiveness relative to photon therapy of 1.1, that is, proton beams are considered to be 10% more biologically effective. Debate is ongoing as to whether this practice needs to be revised. This short review summarizes current knowledge on relative biological effectiveness variations and uncertainties in vitro and in vivo. Clinical relevance is discussed and strategies toward biologically guided treatment planning are presented.
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Affiliation(s)
- Harald Paganetti
- Department of Radiation Oncology, Massachusetts General Hospital, and Harvard Medical School, Boston, MA, USA
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McNamara AL, Ramos-Méndez J, Perl J, Held K, Dominguez N, Moreno E, Henthorn NT, Kirkby KJ, Meylan S, Villagrasa C, Incerti S, Faddegon B, Paganetti H, Schuemann J. Geometrical structures for radiation biology research as implemented in the TOPAS-nBio toolkit. Phys Med Biol 2018; 63:175018. [PMID: 30088810 DOI: 10.1088/1361-6560/aad8eb] [Citation(s) in RCA: 31] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
Abstract
Computational simulations, such as Monte Carlo track structure simulations, offer a powerful tool for quantitatively investigating radiation interactions within cells. The modelling of the spatial distribution of energy deposition events as well as diffusion of chemical free radical species, within realistic biological geometries, can help provide a comprehensive understanding of the effects of radiation on cells. Track structure simulations, however, generally require advanced computing skills to implement. The TOPAS-nBio toolkit, an extension to TOPAS (TOol for PArticle Simulation), aims to provide users with a comprehensive framework for radiobiology simulations, without the need for advanced computing skills. This includes providing users with an extensive library of advanced, realistic, biological geometries ranging from the micrometer scale (e.g. cells and organelles) down to the nanometer scale (e.g. DNA molecules and proteins). Here we present the geometries available in TOPAS-nBio.
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Affiliation(s)
- Aimee L McNamara
- Department of Radiation Oncology, Massachusetts General Hospital, Harvard Medical School, 30 Fruit St, Boston, MA 02114, United States of America
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Villegas F, Tilly N, Ahnesjö A. Target Size Variation in Microdosimetric Distributions and its Impact on the Linear-Quadratic Parameterization of Cell Survival. Radiat Res 2018; 190:504-512. [PMID: 30106343 DOI: 10.1667/rr15089.1] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
Abstract
The linear-quadratic (LQ) parameterization of survival fraction [SF( D)] inherently assumes that all cells in a population receive the same dose ( D), albeit the distribution of specific energy z over the individual cells f( z, D) can be very wide. From these microdosimetric distributions, which are target size dependent, we estimate the size of the cellular sensitive volume by analyzing its influence on the LQ parameterization of cell survival. A Monte Carlo track structure code was used to simulate detailed tracks from a 60Co source as well as proton and carbon ions of various energies. From these tracks, f( z, D) distributions were calculated for spherical targets with diameters ranging from 10 nm to 12 μm. A cell survival function based on f( z, D) was fitted to experimental LQ α values, revealing an intrinsic limitation that target size imposes on the usage of f( z, D) to describe the linear term of the LQ parameterization. The results indicate that such threshold volume arises naturally from the relationship between the particle's probability of no-hit and the probability of cell survival. Further analysis led to the proposal of a radiobiological property [Formula: see text], defined as the mean lineal energy corresponding to the target size that allows equivalence between the mean inactivation dose (MID) and the mean specific energy [Formula: see text]. The fact that [Formula: see text] is an increasing continuous function of target size within the range of biological targets of interest in radiobiology, ensures the uniqueness of [Formula: see text] for any radiation quality, thus, its potential usefulness in modeling. In conclusion, an accurate estimation of such threshold volumes may be useful for improving modeling of cell survival curves.
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Affiliation(s)
- Fernanda Villegas
- a Medical Radiation Physics, Department of Immunology, Genetics and Pathology, Uppsala University, Akademiska Sjukhuset, Uppsala SE-75185, Sweden
| | - Nina Tilly
- a Medical Radiation Physics, Department of Immunology, Genetics and Pathology, Uppsala University, Akademiska Sjukhuset, Uppsala SE-75185, Sweden.,b Elekta Instrument AB, Stockholm SE-10393, Sweden
| | - Anders Ahnesjö
- a Medical Radiation Physics, Department of Immunology, Genetics and Pathology, Uppsala University, Akademiska Sjukhuset, Uppsala SE-75185, Sweden
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Underwood TS, McMahon SJ. Proton relative biological effectiveness (RBE): a multiscale problem. Br J Radiol 2018; 92:20180004. [PMID: 29975153 DOI: 10.1259/bjr.20180004] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
Proton radiotherapy is undergoing rapid expansion both within the UK and internationally, but significant challenges still need to be overcome if maximum benefit is to be realised from this technique. One major limitation is the persistent uncertainty in proton relative biological effectiveness (RBE). While RBE values are needed to link proton radiotherapy to our existing experience with photon radiotherapy, RBE remains poorly understood and is typically incorporated as a constant dose scaling factor of 1.1 in clinical plans. This is in contrast to extensive experimental evidence indicating that RBE is a function of dose, tissue type, and proton linear energy transfer, among other parameters. In this article, we discuss the challenges associated with obtaining clinically relevant values for proton RBE through commonly-used assays, and highlight the wide range of other experimental end points which can inform our understanding of RBE. We propose that accurate and robust optimization of proton radiotherapy ultimately requires a multiscale understanding of RBE, integrating subcellular, cellular, and patient-level processes.
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Affiliation(s)
- Tracy Sa Underwood
- Department of Medical Physics and Biomedical Engineering, University College London, London, UK
| | - Stephen J McMahon
- Centre for Cancer Research and Cell Biology, School of Medicine, Dentistry and Biomedical Science, Queen's University Belfast, Belfast, UK
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Toward A variable RBE for proton beam therapy. Radiother Oncol 2018; 128:68-75. [PMID: 29910006 DOI: 10.1016/j.radonc.2018.05.019] [Citation(s) in RCA: 56] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2018] [Revised: 05/09/2018] [Accepted: 05/17/2018] [Indexed: 12/19/2022]
Abstract
In the clinic, proton beam therapy (PBT) is based on the use of a generic relative biological effectiveness (RBE) of 1.1 compared to photons in human cancers and normal tissues. However, the experimental basis for this RBE lacks any significant number of representative tumor models and clinically relevant endpoints for dose-limiting organs at risk. It is now increasingly appreciated that much of the variations of treatment responses in cancers are due to inter-tumoral genomic heterogeneity. Indeed, recently it has been shown that defects in certain DNA repair pathways, which are found in subsets of many cancers, are associated with a RBE increase in vitro. However, there currently exist little in vivo or clinical data that confirm the existence of similarly increased RBE values in human cancers. Furthermore, evidence for variable RBE values for normal tissue toxicity has been sparse and conflicting to date. If we could predict variable RBE values in patients, we would be able to optimally use and personalize PBT. For example, predictive tumor biomarkers may facilitate selection of patients with proton-sensitive cancers previously ineligible for PBT. Dose de-escalation may be possible to reduce normal tissue toxicity, especially in pediatric patients. Knowledge of increased tumor RBE may allow us to develop biologically optimized therapies to enhance local control while RBE biomarkers for normal tissues could lead to a better understanding and prevention of unusual PBT-associated toxicity. Here, we will review experimental data on the repair of proton damage to DNA that impact both RBE values and biophysical modeling to predict RBE variations. Experimental approaches for studying proton sensitivity in vitro and in vivo will be reviewed as well and recent clinical findings discussed. Ultimately, therapeutically exploiting the understudied biological advantages of protons and developing approaches to limit treatment toxicity should fundamentally impact the clinical use of PBT.
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Lühr A, von Neubeck C, Pawelke J, Seidlitz A, Peitzsch C, Bentzen SM, Bortfeld T, Debus J, Deutsch E, Langendijk JA, Loeffler JS, Mohan R, Scholz M, Sørensen BS, Weber DC, Baumann M, Krause M. "Radiobiology of Proton Therapy": Results of an international expert workshop. Radiother Oncol 2018; 128:56-67. [PMID: 29861141 DOI: 10.1016/j.radonc.2018.05.018] [Citation(s) in RCA: 79] [Impact Index Per Article: 13.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2018] [Revised: 05/17/2018] [Accepted: 05/17/2018] [Indexed: 12/25/2022]
Abstract
The physical properties of proton beams offer the potential to reduce toxicity in tumor-adjacent normal tissues. Toward this end, the number of proton radiotherapy facilities has steeply increased over the last 10-15 years to currently around 70 operational centers worldwide. However, taking full advantage of the opportunities offered by proton radiation for clinical radiotherapy requires a better understanding of the radiobiological effects of protons alone or combined with drugs or immunotherapy on normal tissues and tumors. This report summarizes the main results of the international expert workshop "Radiobiology of Proton Therapy" that was held in November 2016 in Dresden. It addresses the major topics (1) relative biological effectiveness (RBE) in proton beam therapy, (2) interaction of proton radiobiology with radiation physics in current treatment planning, (3) biological effects in proton therapy combined with systemic treatments, and (4) testing biological effects of protons in clinical trials. Finally, important research avenues for improvement of proton radiotherapy based on radiobiological knowledge are identified. The clinical distribution of radiobiological effectiveness of protons alone or in combination with systemic chemo- or immunotherapies as well as patient stratification based on biomarker expressions are key to reach the full potential of proton beam therapy. Dedicated preclinical experiments, innovative clinical trial designs, and large high-quality data repositories will be most important to achieve this goal.
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Affiliation(s)
- Armin Lühr
- Helmholtz-Zentrum Dresden - Rossendorf, Institute of Radiooncology - OncoRay, Germany; OncoRay - National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Helmholtz-Zentrum Dresden - Rossendorf, Germany; German Cancer Consortium (DKTK), Partner Site Dresden and German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Cläre von Neubeck
- OncoRay - National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Helmholtz-Zentrum Dresden - Rossendorf, Germany; German Cancer Consortium (DKTK), Partner Site Dresden and German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Jörg Pawelke
- Helmholtz-Zentrum Dresden - Rossendorf, Institute of Radiooncology - OncoRay, Germany; OncoRay - National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Helmholtz-Zentrum Dresden - Rossendorf, Germany
| | - Annekatrin Seidlitz
- OncoRay - National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Helmholtz-Zentrum Dresden - Rossendorf, Germany; German Cancer Consortium (DKTK), Partner Site Dresden and German Cancer Research Center (DKFZ), Heidelberg, Germany; Department of Radiotherapy and Radiation Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Germany
| | - Claudia Peitzsch
- OncoRay - National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Helmholtz-Zentrum Dresden - Rossendorf, Germany; German Cancer Consortium (DKTK), Partner Site Dresden and German Cancer Research Center (DKFZ), Heidelberg, Germany; National Center for Tumor Diseases (NCT), Partner Site Dresden, Germany: German Cancer Research Center (DKFZ), Heidelberg, Germany; Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany, and; Helmholtz Association/Helmholtz-Zentrum Dresden - Rossendorf (HZDR), Germany
| | - Søren M Bentzen
- Division of Biostatistics and Bioinformatics, Department of Epidemiology and Public Health and the Maryland Proton Therapy Center, Department of Radiation Oncology, University of Maryland School of Medicine, Baltimore, USA
| | - Thomas Bortfeld
- Physics Division, Department of Radiation Oncology, Massachusetts General Hospital, Boston, USA
| | - Jürgen Debus
- German Cancer Research Center (DKFZ), Heidelberg, Germany; Department of Radiation Oncology, University Heidelberg German Consortium for Translational Oncology (DKTK), Germany; National Center for Tumor Diseases (NCT), Heidelberg, Germany
| | - Eric Deutsch
- Department of Radiation Oncology Gustave Roussy Cancer Campus, INSERM, 1030 Villejuif, France; Université Paris-Sud, Faculté de Medecine du Kremlin Bicetre Paris Sud, Le Kremlin-Bicêtre, France
| | - Johannes A Langendijk
- Department of Radiation Oncology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Jay S Loeffler
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, USA; Department of Neurosurgery, Massachusetts General Hospital and Harvard Medical School, USA
| | - Radhe Mohan
- Department of Radiation Physics, UT MD Anderson Cancer Center, Houston, USA
| | - Michael Scholz
- GSI Helmholtz Center for Heavy Ion Research, Department of Biophysics, Darmstadt, Germany
| | - Brita S Sørensen
- Dept. Experimental Clinical Oncology, Aarhus University Hospital, Denmark
| | - Damien C Weber
- Center for Proton Therapy, Paul Scherrer Institute, ETH Domain, Villigen, Switzerland
| | - Michael Baumann
- Helmholtz-Zentrum Dresden - Rossendorf, Institute of Radiooncology - OncoRay, Germany; OncoRay - National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Helmholtz-Zentrum Dresden - Rossendorf, Germany; German Cancer Consortium (DKTK), Partner Site Dresden and German Cancer Research Center (DKFZ), Heidelberg, Germany; Department of Radiotherapy and Radiation Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Germany; National Center for Tumor Diseases (NCT), Partner Site Dresden, Germany: German Cancer Research Center (DKFZ), Heidelberg, Germany; Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany, and; Helmholtz Association/Helmholtz-Zentrum Dresden - Rossendorf (HZDR), Germany; German Cancer Research Center (DKFZ), Heidelberg, Germany.
| | - Mechthild Krause
- Helmholtz-Zentrum Dresden - Rossendorf, Institute of Radiooncology - OncoRay, Germany; OncoRay - National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Helmholtz-Zentrum Dresden - Rossendorf, Germany; German Cancer Consortium (DKTK), Partner Site Dresden and German Cancer Research Center (DKFZ), Heidelberg, Germany; Department of Radiotherapy and Radiation Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Germany; National Center for Tumor Diseases (NCT), Partner Site Dresden, Germany: German Cancer Research Center (DKFZ), Heidelberg, Germany; Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany, and; Helmholtz Association/Helmholtz-Zentrum Dresden - Rossendorf (HZDR), Germany
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In Silico Non-Homologous End Joining Following Ion Induced DNA Double Strand Breaks Predicts That Repair Fidelity Depends on Break Density. Sci Rep 2018; 8:2654. [PMID: 29422642 PMCID: PMC5805743 DOI: 10.1038/s41598-018-21111-8] [Citation(s) in RCA: 26] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2017] [Accepted: 01/25/2018] [Indexed: 12/19/2022] Open
Abstract
This work uses Monte Carlo simulations to investigate the dependence of residual and misrepaired double strand breaks (DSBs) at 24 hours on the initial damage pattern created during ion therapy. We present results from a nanometric DNA damage simulation coupled to a mechanistic model of Non-Homologous End Joining, capable of predicting the position, complexity, and repair of DSBs. The initial damage pattern is scored by calculating the average number of DSBs within 70 nm from every DSB. We show that this local DSB density, referred to as the cluster density, can linearly predict misrepair regardless of ion species. The models predict that the fraction of residual DSBs is constant, with 7.3% of DSBs left unrepaired following 24 hours of repair. Through simulation over a range of doses and linear energy transfer (LET) we derive simple correlations capable of predicting residual and misrepaired DSBs. These equations are applicable to ion therapy treatment planning where both dose and LET are scored. This is demonstrated by applying the correlations to an example of a clinical proton spread out Bragg peak. Here we see a considerable biological effect past the distal edge, dominated by residual DSBs.
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