Cells may use their neighbours as a reference after radiation

Some laboratory-grown cells respond to radiation in a counterintuitive way. At low doses, their ability to reproduce can fall unusually sharply, yet at a somewhat higher dose it can partially recover before declining again. A new mathematical model suggests that this pattern may arise because cells respond not only to their own damage, but also to damage-related signals from nearby cells.

The study by researchers at the HUN-REN Centre for Energy Research was published in Scientific Reports.

The phenomenon is known as low-dose hyper-radiosensitivity and induced radioresistance. It has been observed in some cell lines: colony-forming survival decreases steeply at doses around 0.1 Gray (Gy), then may rise between roughly 0.3 and 0.7 Gy. In these experiments, “survival” means that a cell remains able to divide repeatedly and form a colony.

The researchers’ Minimum Mutation Load model proposes a possible reason for this behaviour. At a low dose, only a few cells may carry appreciable mutagenic damage. In the model, these cells stand out from their less-damaged neighbours and are more likely to be removed from the reproducing cell population.

As the dose increases, however, damage becomes more widespread. Eliminating every affected cell would require the remaining cells to divide more often to replace them. Because DNA replication can itself introduce mutations, excessive cell elimination may eventually create more mutations than retaining some moderately damaged cells.

The model therefore balances two risks: mutations that may arise from radiation damage, and mutations that may arise when cells divide to replace those that have been removed. Each cell’s fate depends on its own damage in relation to the damage level inferred from local signals.

“Removing every damaged cell is not necessarily the best way to minimise mutations,” said Balázs G. Madas, corresponding author of the study. “A tissue must also account for the new cell divisions needed for replacement. Our model explores how information from neighbouring cells could help balance these competing risks.”

The team tested the model against 99 previously published clonogenic-survival datasets, drawn from 46 articles and representing 45 cell types. Across all datasets, the model achieved an average adjusted R² of 0.74, a statistical measure of agreement between predicted and observed survival.

The researchers also compared it with the established Induced Repair model, which is widely used to describe the same low-dose pattern. Among 77 datasets for which both models produced positive adjusted R² values, the new model fitted better in 42 cases and the established model in 35. The differences were generally small.

The authors therefore do not claim that their model is consistently more accurate. Its main contribution is a testable biological interpretation. The established model describes the shape of the survival curve phenomenologically, whereas the Minimum Mutation Load model links it to local cell-to-cell communication and the competing mutation costs of damage and replacement.

The study does not identify a particular signalling molecule or pathway. The model represents damage-related communication in an abstract, distance-dependent form. Soluble factors or extracellular vesicles are among the possible mediators discussed by the authors, but their role was not tested directly.

The findings should not be interpreted as showing that a larger radiation dose is safer than a smaller one, or as a basis for changing radiation-protection or clinical recommendations. Instead, the study presents an experimentally testable explanation for an unusual cellular response.

More broadly, the framework raises the possibility that the radiation response observed in these experiments reflects a more general protective process that is not specific to radiation. By selectively removing cells that are unusually damaged relative to their neighbours, tissues may limit the accumulation of mutations and genomic instability, thereby potentially reducing cancer risk. In this view, ionising radiation serves as a controlled way to reveal a process that could also operate in response to other forms of mutagenic stress.