ArticleFrontiers in oncology2021
A Mechanistic DNA Repair and Survival Model (Medras): Applications to Intrinsic Radiosensitivity, Relative Biological Effectiveness and Dose-Rate.
Article in Frontiers in oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
17 citing papers in PubMed.
- Fe/Pharmaceutics · 2026Article
- Assessment of Carrier-Free Metallacarboranes for Targeted Radiation Therapies PBFT and BNCT: Comparative Cellular Effects and Dosimetry Studies with [Pharmaceuticals (Basel, Switzerland) · 2025Article
- Assessing the Relative Contribution of DSB Repair Proteins as a Function of LET.International journal of particle therapy · 2025Article
- A mathematical model for the investigation of combined treatment of radiopharmaceutical therapy and PARP inhibitors.European journal of nuclear medicine and molecular imaging · 2025Article
- A mechanistic simulation of induced DNA damage in a bacterial cell by X- and gamma rays: a parameter study.Physical and engineering sciences in medicine · 2024Article
- Effects of Differing Underlying Assumptions in In Silico Models on Predictions of DNA Damage and Repair.Radiation research · 2023Article
- High-LET radiation induces large amounts of rapidly-repaired sublethal damage.Scientific reports · 2023Article
- Characterization of Intrinsic Radiation Sensitivity in a Diverse Panel of Normal, Cancerous and CRISPR-Modified Cell Lines.International journal of molecular sciences · 2023Article
- Simulation of DNA damage using Geant4-DNA: an overview of the "molecularDNA" example application.Precision radiation oncology · 2023Article
- Use of 3D Spheroid Models for the Assessment of RT Response in Head and Neck Cancer.International journal of molecular sciences · 2023Article
- A fast Monte Carlo cell-by-cell simulation for radiobiological effects in targeted radionuclide therapy using pre-calculated single-particle track standard DNA damage data.Frontiers in nuclear medicine · 2023Article
- Cellular lethal damage ofFrontiers in medicine · 2023Article
- Impact of DNA Geometry and Scoring on Monte Carlo Track-Structure Simulations of Initial Radiation-Induced Damage.Radiation research · 2022Article
- RadSigBench: a framework for benchmarking functional genomics signatures of cancer cell radiosensitivity.Briefings in bioinformatics · 2022Article
- Article
- Radiobiological Modeling with Monte Carlo Tools - Simulating Cellular Responses to Ionizing Radiation.Technology in cancer research & treatmentReview
- Linear Energy Transfer and Relative Biological Effectiveness Investigation of Various Structures for a Cohort of Proton Patients With Brain Tumors.Advances in radiation oncologyArticle
Corrections and comments
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Authors and funding
2 authors.
Funding
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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Registered trials
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