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

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|May 14, 2020
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Proton irradiation causes DNA double-strand breaks (DSBs), with higher yields at increased linear energy transfer (LET). Most DSBs are repaired within 24 hours, but misrepair increases with LET, leading to chromosome aberrations in cancer radiotherapy research.

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Area of Science:

  • Radiation biology
  • Radiobiology
  • Cancer radiotherapy

Background:

  • DNA is the primary target for ionizing radiation effects in cancer radiotherapy.
  • Cellular response to radiation involves DNA damage, repair, and potential misrepair leading to mutations and aberrations.
  • Understanding these processes is crucial for optimizing radiotherapy efficacy.

Purpose of the Study:

  • To simulate and analyze the cellular response to proton irradiation across a range of energies (0.5-500 MeV).
  • To model initial DNA damage, repair dynamics, and chromosome aberration formation.
  • To compare simulation results with experimental data for validation.

Main Methods:

  • Utilized TOPAS-nBio with a fractal DNA geometry model for simulating initial DNA damage.
  • Employed default physics and chemistry models to simulate particle and radiolysis product interactions.
  • Applied a mechanistic repair model to predict DNA damage repair and chromosome aberration dose responses.

Main Results:

  • Initial DNA double-strand break (DSB) yield increased from 6.5 to 21.2 DSB/Gy/Gbp with increasing linear energy transfer (LET) from 0.2 to 60 keV/µm.
  • Over 95% of DSBs were repaired within 24 hours.
  • The misrepaired DSB fraction rose with LET, reaching 15.8% at 60 keV/µm, with a chromosome aberration detection threshold of 3 Mbp.

Conclusions:

  • Proton irradiation induces dose-dependent DNA damage, with higher LET protons causing more complex and misrepaired DSBs.
  • The developed model accurately predicts DNA damage and repair kinetics, supporting its use in radiotherapy research.
  • Simulation results for dicentric, acentric fragment, and micronuclei yields align with experimental findings, validating the model's predictive power.