Evolutionary Theory Group, Max-Planck-Institute for Evolutionary Biology, Plön, Germany.
PLoS One. 2011;6(12):e28955. doi: 10.1371/journal.pone.0028955. Epub 2011 Dec 22.
In the last decade, cancer research has been a highly active and rapidly evolving scientific area. The ultimate goal of all efforts is a better understanding of the mechanisms that discriminate malignant from normal cell biology in order to allow the design of molecular targeted treatment strategies. In individual cases of malignant model diseases addicted to a specific, ideally single oncogene, e.g. Chronic myeloid leukemia (CML), specific tyrosine kinase inhibitors (TKI) have indeed been able to convert the disease from a ultimately life-threatening into a chronic disease with individual patients staying in remission even without treatment suggestive of operational cure. These developments have been raising hopes to transfer this concept to other cancer types. Unfortunately, cancer cells tend to develop both primary and secondary resistance to targeted drugs in a substantially higher frequency often leading to a failure of treatment clinically. Therefore, a detailed understanding of how cells can bypass targeted inhibition of signaling cascades crucial for malignant growths is necessary. Here, we have performed an in vitro experiment that investigates kinetics and mechanisms underlying resistance development in former drug sensitive cancer cells over time in vitro. We show that the dynamics observed in these experiments can be described by a simple mathematical model. By comparing these experimental data with the mathematical model, important parameters such as mutation rates, cellular fitness and the impact of individual drugs on these processes can be assessed. Excitingly, the experiment and the model suggest two fundamentally different ways of resistance evolution, i.e. acquisition of mutations and phenotype switching, each subject to different parameters. Most importantly, this complementary approach allows to assess the risk of resistance development in the different phases of treatment and thus helps to identify the critical periods where resistance development is most likely to occur.
在过去的十年中，癌症研究一直是一个高度活跃和快速发展的科学领域。所有努力的最终目标都是更好地理解区分恶性和正常细胞生物学的机制，以便能够设计分子靶向治疗策略。在依赖特定、理想的单一癌基因的恶性模型疾病的个别情况下，例如慢性髓性白血病 (CML)，特定的酪氨酸激酶抑制剂 (TKI) 确实能够将疾病从危及生命的疾病转变为慢性疾病，个别患者即使没有治疗也能缓解，这表明已经治愈。这些进展使人们希望将这一概念转移到其他癌症类型。不幸的是，癌细胞往往会以更高的频率对靶向药物产生原发性和继发性耐药，这通常导致治疗临床失败。因此，必须详细了解细胞如何绕过对恶性生长至关重要的信号级联的靶向抑制。在这里，我们进行了一项体外实验，研究了以前对药物敏感的癌细胞在体外随时间推移耐药性发展的动力学和机制。我们表明，这些实验中观察到的动力学可以用一个简单的数学模型来描述。通过将这些实验数据与数学模型进行比较，可以评估重要参数，如突变率、细胞适应性以及单个药物对这些过程的影响。令人兴奋的是，实验和模型提出了两种基本不同的耐药性进化方式，即获得突变和表型转换，每种方式都受到不同参数的影响。最重要的是，这种互补的方法可以评估在不同治疗阶段耐药性发展的风险，从而有助于确定最有可能发生耐药性发展的关键时期。
