School of Mathematics and Statistics, University of St Andrews, St Andrews, Scotland.
Department of Mathematics, College of Science, Swansea University, Swansea, Wales, United Kingdom.
PLoS Comput Biol. 2020 Aug 3;16(8):e1008041. doi: 10.1371/journal.pcbi.1008041. eCollection 2020 Aug.
Hypoxia-activated prodrugs (HAPs) present a conceptually elegant approach to not only overcome, but better yet, exploit intra-tumoural hypoxia. Despite being successful in vitro and in vivo, HAPs are yet to achieve successful results in clinical settings. It has been hypothesised that this lack of clinical success can, in part, be explained by the insufficiently stringent clinical screening selection of determining which tumours are suitable for HAP treatments. Taking a mathematical modelling approach, we investigate how tumour properties and HAP-radiation scheduling influence treatment outcomes in simulated tumours. The following key results are demonstrated in silico: (i) HAP and ionising radiation (IR) monotherapies may attack tumours in dissimilar, and complementary, ways. (ii) HAP-IR scheduling may impact treatment efficacy. (iii) HAPs may function as IR treatment intensifiers. (iv) The spatio-temporal intra-tumoural oxygen landscape may impact HAP efficacy. Our in silico framework is based on an on-lattice, hybrid, multiscale cellular automaton spanning three spatial dimensions. The mathematical model for tumour spheroid growth is parameterised by multicellular tumour spheroid (MCTS) data.
缺氧激活前药(HAPs)不仅提供了一种概念上的巧妙方法来克服肿瘤内缺氧,而且更好的是,可以利用肿瘤内缺氧。尽管在体外和体内都取得了成功,但 HAP 在临床环境中尚未取得成功。据推测,这种临床成功的缺乏部分可以通过临床筛选来解释,确定哪些肿瘤适合 HAP 治疗。通过数学建模方法,我们研究了肿瘤特性和 HAP-辐射方案如何影响模拟肿瘤中的治疗结果。在计算机模拟中证明了以下关键结果:(i)HAP 和电离辐射(IR)单独治疗可能以不同的和互补的方式攻击肿瘤。(ii)HAP-IR 方案可能会影响治疗效果。(iii)HAP 可作为 IR 治疗增强剂。(iv)时空肿瘤内氧景观可能会影响 HAP 的疗效。我们的计算机模拟框架基于一个晶格、混合、多尺度细胞自动机,跨越三个空间维度。肿瘤球体生长的数学模型由多细胞肿瘤球体(MCTS)数据参数化。