Topological signatures in regulatory network enable phenotypic heterogeneity in small cell lung cancer

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, and abysmal prognosis. Discrete and continuous dynamical simulations of this network reveal its multistable behavior that can explain the co-existence of four experimentally observed phenotypes. Analysis of the network topology uncovers that multistability emerges from two subgroups of nodes in the network that are mutually inhibitory across the subgroups but mutually activatory within subgroups. Deciphering these topological signatures in apparently complex cancer-related regulatory networks can unravel their underlying organizing principles and offer a minimalistic rational approach to characterize phenotypic heterogeneity in a tumor.