Kozin, S. V., Niemierko, A., Huang, P., Silva, J., Doppke, K. P. and Suit, H. D. Inter- and Intramouse Heterogeneity of Radiation Response for a Growing Paired Organ. Radiat. Res. 170, 264–267 (2008).

An intensive search for predictive markers of individual radiation response of apparently normal tissues in cancer patients is in progress at the genetic and epigenetic levels. However, the relative impact of variability at these levels is not clear. Experimental results obtained in inbred rodents, which have significantly reduced genetic heterogeneity relative to a population of human patients, may help to clarify this issue. We investigated a paired-organ mouse system in a strain of inbred mice to evaluate the intermouse variability of normal tissue radiation response, singled out from measurement errors and stochastic effects. The legs of 5-day-old C3H mice were homogeneously γ-irradiated with a range of single doses. The lengths of the right and left tibiae were measured in 30 kVp X-ray images taken at the time of irradiation and at 84 days postirradiation. The dose–effect curves were smooth and well defined, with bone growth retardation evident at ∼14 Gy and higher, and were marginally gender-dependent. The intramouse (left compared to right) variability of the tibia length on day 89, which characterized stochastic effects, was not distinguishable from the measurement error for doses less than 16–18 Gy and slightly exceeded measurement errors only at the largest doses of 20–22 Gy. The corresponding intermouse variability was greater than the measurement error and stochastic effects at all doses used. Interestingly, the total variability, judged by the γ₅₀ values of ∼7 we obtained, was similar to that reported for severe late reactions in human normal tissue. If the variations of response determined by epigenetic events in human patients free of known factors associated with altered radiation sensitivity are comparable to those observed in this mouse model, our results imply a relatively low power of genetic approaches alone to predict individual side effects in radiotherapy.