Bystander effects and their implications for clinical radiation therapy: Insights from multiscale in silico experiments

TL;DR

This paper uses a multiscale mathematical model to investigate how bystander effects influence cell damage in low-dose radiotherapy, revealing they may cause more harm than direct radiation effects.

Contribution

It introduces a hybrid multiscale model to analyze radiation and bystander effects, highlighting their significance at low doses in cancer treatment.

Findings

Bystander effects can cause more cell damage than direct radiation at low doses.

Survival curves show hyper-radiosensitivity at low doses not predicted by traditional models.

Bystander responses are crucial for designing effective radiotherapy protocols.

Abstract

Radiotherapy is a commonly used treatment for cancer and is usually given in varying doses. At low radiation doses relatively few cells die as a direct response to radiation but secondary radiation effects such as DNA mutation or bystander effects affect many cells. Consequently it is at low radiation levels where an understanding of bystander effects is essential in designing novel therapies with superior clinical outcomes. In this article, we use a hybrid multiscale mathematical model to study the direct effects of radiation as well as radiation-induced bystander effects on both tumour cells and normal cells. We show that bystander responses may play a major role in mediating radiation damage to cells at low-doses of radiotherapy, doing more damage than that due to direct radiation. The survival curves derived from our computational simulations showed an area of hyper-radiosensitivity at low-doses that are not obtained using a traditional radiobiological model.