Department of Statistics, Rice University Houston, TX, USA ; Department of Bioengineering, Rice University Houston, TX, USA.
Front Oncol. 2013 Apr 29;3:89. doi: 10.3389/fonc.2013.00089. eCollection 2013.
We present a stochastic model of driver mutations in the transition from severe congenital neutropenia to myelodysplastic syndrome to acute myeloid leukemia (AML). The model has the form of a multitype branching process. We derive equations for the distributions of the times to consecutive driver mutations and set up simulations involving a range of hypotheses regarding acceleration of the mutation rates in successive mutant clones. Our model reproduces the clinical distribution of times at diagnosis of secondary AML. Surprisingly, within the framework of our assumptions, stochasticity of the mutation process is incapable of explaining the spread of times at diagnosis of AML in this case; it is necessary to additionally assume a wide spread of proliferative parameters among disease cases. This finding is unexpected but generally consistent with the wide heterogeneity of characteristics of human cancers.
我们提出了一个从严重先天性中性粒细胞减少症到骨髓增生异常综合征再到急性髓系白血病(AML)的驱动基因突变的随机模型。该模型采用多类型分支过程的形式。我们推导出了连续驱动突变时间分布的方程,并建立了涉及一系列关于连续突变克隆中突变率加速假设的模拟。我们的模型再现了继发性 AML 诊断时时间的临床分布。令人惊讶的是,在我们的假设框架内,突变过程的随机性无法解释 AML 诊断时时间的传播;有必要额外假设疾病病例之间的增殖参数广泛分布。这一发现出人意料,但与人类癌症特征的广泛异质性总体一致。