Centre for BioSystems Science and Engineering, Indian Institute of Science, Bangalore, India.
Undergraduate Programme, Indian Institute of Science, Bangalore, India.
Elife. 2021 Mar 17;10:e64522. doi: 10.7554/eLife.64522.
Phenotypic (non-genetic) heterogeneity has significant implications for the development and evolution of organs, organisms, and populations. Recent observations in multiple cancers have unraveled the role of phenotypic heterogeneity in driving metastasis and therapy recalcitrance. However, the origins of such phenotypic heterogeneity are poorly understood in most cancers. Here, we investigate a regulatory network underlying phenotypic heterogeneity in small cell lung cancer, a devastating disease with no molecular targeted therapy. Discrete and continuous dynamical simulations of this network reveal its multistable behavior that can explain co-existence of four experimentally observed phenotypes. Analysis of the network topology uncovers that multistability emerges from two teams of players that mutually inhibit each other, but members of a team activate one another, forming a 'toggle switch' between the two teams. Deciphering these topological signatures in cancer-related regulatory networks can unravel their 'latent' design principles and offer a rational approach to characterize phenotypic heterogeneity in a tumor.
表型（非遗传）异质性对器官、生物体和种群的发育和进化具有重要意义。最近在多种癌症中的观察结果揭示了表型异质性在推动转移和治疗抗性方面的作用。然而，在大多数癌症中，这种表型异质性的起源还知之甚少。在这里，我们研究了小细胞肺癌中表型异质性的调控网络，小细胞肺癌是一种毁灭性疾病，目前没有分子靶向治疗方法。对该网络的离散和连续动力学模拟揭示了其多稳态行为，该行为可以解释四种实验观察到的表型的共存。对网络拓扑结构的分析表明，多稳态性源于相互抑制的两组参与者，但同一组的成员会相互激活，从而在两组之间形成一个“切换开关”。在癌症相关调控网络中破译这些拓扑特征，可以揭示它们的“潜在”设计原则，并为表征肿瘤中的表型异质性提供一种合理的方法。
