School of Physics, University of Sydney, Building A28 Physics Road, NSW 2006, Australia.
School of Physics, University of Sydney, Building A28 Physics Road, NSW 2006, Australia; VectorLAB, Department of Radiation Oncology, Chris O'Brien Lifehouse, Missenden Rd, Camperdown, Sydney, NSW 2050, Australia.
J Theor Biol. 2018 Oct 14;455:16-25. doi: 10.1016/j.jtbi.2018.06.027. Epub 2018 Jul 2.
Bystander responses to radiation are responsible for a significant fraction of cell death, but are not included in the conventional linear-quadratic (LQ) radiobiological model. Strong dose gradients in radiation fields affect the distribution of bystander signals and can be used to decrease the survival of cancer cells. Predictive models incorporating bystander effects are needed to design the dose gradients in modulated fields to improve cancer treatments. Fundamental questions concern the nature and range of bystander signalling. Some authors propose bystander signals are carried by diffusing molecular factors expressed into the extracellular medium and that strong dose gradients drive their diffusion. Others propose bystander effects occur between neighbouring cells through gap-junctions, leaving no universal agreement. Here we test three assumptions concerning the effective range of bystander signals using both average and local measures of survival. Model 1 assumes short range signalling (e.g. gap-junction mediated) proportional to the local dose gradient, without relying on diffusion across the extracellular medium; Model 2 assumes metabolite diffusion governed by Fick's second law with either negative or both signs of bystander effect; Model 3 assumes that the extent of signal production is dependent on the average of the dose gradient over the field and that the signals have long range distribution. A single bystander parameter for each model was fitted to observed average survival of cancer cells in uniform and modulated fields. All models gave better fits than the classical LQ model. Model 2 fitted best with one sign of bystander effect on survival. Model 3 gave the best overall fit of average survival. The models were then used to predict local survival and survival as a function of dose in modulated fields, using independent datasets, without changing the bystander parameter. Model 3 gave the best overall prediction. This study demonstrates that the bystander effect can be controlled by design of the radiation field modulation.
旁观者反应是细胞死亡的重要原因，但不在传统的线性二次（LQ）放射生物学模型中。辐射场中的强剂量梯度会影响旁观者信号的分布，可用于降低癌细胞的存活率。需要包含旁观者效应的预测模型来设计调制场中的剂量梯度，以改善癌症治疗效果。基本问题涉及旁观者信号的性质和范围。一些作者提出，旁观者信号是由扩散到细胞外介质中的表达分子因子携带的，强剂量梯度会驱动其扩散。另一些作者则提出，旁观者效应通过缝隙连接在相邻细胞之间发生，目前尚无普遍共识。在这里，我们使用平均和局部存活数据来检验关于旁观者信号有效范围的三个假设。模型 1 假设短程信号（例如缝隙连接介导的信号）与局部剂量梯度成正比，而不依赖于细胞外介质中的扩散；模型 2 假设代谢物扩散受菲克第二定律支配，具有负的或两种符号的旁观者效应；模型 3 假设信号产生的程度取决于场中平均剂量梯度，并且信号具有长程分布。对于每个模型，都使用观察到的均匀和调制场中癌细胞的平均存活数据来拟合一个旁观者参数。与经典的 LQ 模型相比，所有模型都提供了更好的拟合。模型 2 对生存有一个符号的旁观者效应的拟合最好。模型 3 对平均存活的总体拟合效果最好。然后，使用独立的数据集，在不改变旁观者参数的情况下，将这些模型用于预测调制场中的局部存活和剂量存活。模型 3 提供了最佳的总体预测。本研究表明，通过设计辐射场调制，可以控制旁观者效应。
