Greene James M, Gevertz Jana L, Sontag Eduardo D
Rutgers University, New Brunswick, NJ.
The College of New Jersey, Ewing Township, NJ.
JCO Clin Cancer Inform. 2019 Apr;3:1-20. doi: 10.1200/CCI.18.00087.
Drug resistance is a major impediment to the success of cancer treatment. Resistance is typically thought to arise from random genetic mutations, after which mutated cells expand via Darwinian selection. However, recent experimental evidence suggests that progression to drug resistance need not occur randomly, but instead may be induced by the treatment itself via either genetic changes or epigenetic alterations. This relatively novel notion of resistance complicates the already challenging task of designing effective treatment protocols.
To better understand resistance, we have developed a mathematical modeling framework that incorporates both spontaneous and drug-induced resistance.
Our model demonstrates that the ability of a drug to induce resistance can result in qualitatively different responses to the same drug dose and delivery schedule. We have also proven that the induction parameter in our model is theoretically identifiable and propose an in vitro protocol that could be used to determine a treatment's propensity to induce resistance.
耐药性是癌症治疗成功的主要障碍。通常认为耐药性源于随机的基因突变，之后突变细胞通过达尔文选择进行扩增。然而，最近的实验证据表明，向耐药性的进展不一定是随机发生的，而是可能由治疗本身通过基因变化或表观遗传改变诱导产生。这种相对新颖的耐药性概念使设计有效治疗方案这一原本就具有挑战性的任务变得更加复杂。
为了更好地理解耐药性，我们开发了一个数学建模框架，该框架纳入了自发耐药性和药物诱导的耐药性。
我们的模型表明，药物诱导耐药性的能力可导致对相同药物剂量和给药方案产生质的不同反应。我们还证明了我们模型中的诱导参数在理论上是可识别的，并提出了一种体外方案，可用于确定一种治疗方法诱导耐药性的倾向。
