Rodriguez-Brenes Ignacio A, Wodarz Dominik
Department of Ecology and Evolutionary Biology, Ayala School of Biological Sciences, University of California, Irvine, CA 92697; Department of Mathematics, University of California, Irvine, CA 92697.
Department of Ecology and Evolutionary Biology, Ayala School of Biological Sciences, University of California, Irvine, CA 92697; Department of Mathematics, University of California, Irvine, CA 92697
Proc Natl Acad Sci U S A. 2015 Jul 21;112(29):8843-50. doi: 10.1073/pnas.1501730112.
Clonal evolutionary processes can drive pathogenesis in human diseases, with cancer being a prominent example. To prevent or treat cancer, mechanisms that can potentially interfere with clonal evolutionary processes need to be understood better. Mathematical modeling is an important research tool that plays an ever-increasing role in cancer research. This paper discusses how mathematical models can be useful to gain insights into mechanisms that can prevent disease initiation, help analyze treatment responses, and aid in the design of treatment strategies to combat the emergence of drug-resistant cells. The discussion will be done in the context of specific examples. Among defense mechanisms, we explore how replicative limits and cellular senescence induced by telomere shortening can influence the emergence and evolution of tumors. Among treatment approaches, we consider the targeted treatment of chronic lymphocytic leukemia (CLL) with tyrosine kinase inhibitors. We illustrate how basic evolutionary mathematical models have the potential to make patient-specific predictions about disease and treatment outcome, and argue that evolutionary models could become important clinical tools in the field of personalized medicine.
克隆进化过程可推动人类疾病的发病机制，癌症就是一个突出的例子。为了预防或治疗癌症，需要更好地理解那些可能干扰克隆进化过程的机制。数学建模是一种重要的研究工具，在癌症研究中发挥着越来越重要的作用。本文讨论了数学模型如何有助于深入了解预防疾病发生的机制、帮助分析治疗反应以及辅助设计治疗策略以对抗耐药细胞的出现。讨论将结合具体实例进行。在防御机制方面，我们探讨端粒缩短诱导的复制极限和细胞衰老如何影响肿瘤的发生和演变。在治疗方法方面，我们考虑用酪氨酸激酶抑制剂对慢性淋巴细胞白血病（CLL）进行靶向治疗。我们举例说明基本的进化数学模型如何有潜力针对疾病和治疗结果做出针对个体患者的预测，并认为进化模型可能成为个性化医学领域重要的临床工具。
