Zhao Boyang, Hemann Michael T, Lauffenburger Douglas A
Computational and Systems Biology Program, Massachusetts Institute of Technology, Cambridge, MA 02139.
The David H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02139.
Trends Cancer. 2016 Mar;2(3):144-158. doi: 10.1016/j.trecan.2016.02.001.
Cancer is a clonal evolutionary process. This presents challenges for effective therapeutic intervention, given the constant selective pressure towards drug resistance. Mathematical modeling from population genetics, evolutionary dynamics, and engineering perspectives are being increasingly employed to study tumor progression, intratumoral heterogeneity, drug resistance, and rational drug scheduling and combinations design. In this review, we discuss promising opportunities these inter-disciplinary approaches hold for advances in cancer biology and treatment. We propose that quantitative modeling perspectives can complement emerging experimental technologies to facilitate enhanced understanding of disease progression and improved capabilities for therapeutic drug regimen designs.
癌症是一个克隆进化过程。鉴于对耐药性的持续选择压力，这给有效的治疗干预带来了挑战。从群体遗传学、进化动力学和工程学角度进行的数学建模正越来越多地用于研究肿瘤进展、肿瘤内异质性、耐药性以及合理的药物调度和联合设计。在本综述中，我们讨论了这些跨学科方法在癌症生物学和治疗进展方面所带来的有前景的机会。我们提出，定量建模观点可以补充新兴的实验技术，以促进对疾病进展的深入理解，并提高治疗药物方案设计的能力。
