Abstract:
There is increasing evidence that biological systems are modular in both structure and function. Complex biological signaling networks such as gene regulatory networks (GRNs) are proving to be composed of subcategories that are interconnected and hierarchically ranked. These networks contain highly dynamic processes that ultimately dictate cellular function over time, as well as influence phenotypic fate transitions. In this work, we use a stochastic multicellular signaling network of pancreatic cancer (PC) to show that the variance in topological rankings of the most phenotypically influential modules implies a strong relationship between structure and function. We further show that induction of mutations alters the modular structure, which analogously influences the aggression and controllability of the disease in silico. We finally present evidence that the impact and location of mutations with respect to PC modular structure directly corresponds to the efficacy of single agent treatments in silico, because topologically deep mutations require deep targets for control.
摘要:
越来越多的证据表明,生物系统在结构和功能上都是模块化的。复杂的生物信号网络,如基因调控网络(GRN)被证明是由相互联系和分层排列的子类别组成的。这些网络包含高度动态的过程,这些过程最终决定了细胞功能。以及影响表型命运转变。在这项工作中,我们使用胰腺癌(PC)的随机多细胞信号网络显示,最具表型影响的模块的拓扑排序的差异意味着结构和功能之间有很强的关系.我们进一步表明,突变的诱导改变了模块化结构,这类似地影响计算机中疾病的攻击性和可控性。最后,我们提出了证据,表明突变对PC模块化结构的影响和位置直接对应于硅片中单剂治疗的功效,因为拓扑深层突变需要深层目标来控制。