Uncovering the particularities of the dynamical interaction between cancer-related Epithelial-Mesenchymal Transition and the Mammalian Cell Cycle: a feedback-based Boolean networks interconnection approach

Luis Juarez-Ramiro, J. Dávila-Velderrain, A. Soria-López, E. Álvarez-Buylla, Juan Carlos Martínez-García
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Abstract

Epithelial-to-Mesenchymal Transition (EMT) plays a key role in epithelial-cancer. The state trajectory of its underlying Gene Regulatory Network (GRN) includes three fixed-point attractors characterizing epithelial, senescent, and mesenchymal, cell phenotypes, which implies specific cell-to-cell and cell-to-tissue interactions. The interplay between the GRN driving EMT and the one regulating the Mammalian Cell Cycle (MCC) influences cancer- related cell growing and proliferation. We expose the characteristics of the network arising from the interconnection of the gene regulatory networks associated to EMT and MCC. Our purpose is twofold: first, to elucidate the dynamical properties of cancer-related gene regulatory networks. Subsequently, to propose a computational methodology to address the interconnection of networks related to cancer. Our approach is based on feedback-based interconnection of networks described in discrete Boolean terms.
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揭示癌症相关上皮-间质转化与哺乳动物细胞周期之间动态相互作用的特殊性:基于反馈的布尔网络互连方法
上皮-间充质转化(Epithelial-to-Mesenchymal Transition, EMT)在上皮癌中起着关键作用。其潜在的基因调控网络(GRN)的状态轨迹包括三个定点吸引子,表征上皮细胞、衰老细胞和间充质细胞表型,这意味着特定的细胞与细胞和细胞与组织的相互作用。驱动EMT的GRN与调节哺乳动物细胞周期(MCC)的GRN之间的相互作用影响癌症相关细胞的生长和增殖。我们揭示了与EMT和MCC相关的基因调控网络互连所产生的网络特征。我们的目的有两个:首先,阐明癌症相关基因调控网络的动力学特性。随后,提出了一种计算方法来解决与癌症相关的网络互连问题。我们的方法是基于用离散布尔项描述的基于反馈的网络互连。
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ARCH-COMP23 Category Report: Hybrid Systems Theorem Proving ARCH-COMP23 Category Report: Continuous and Hybrid Systems with Linear Continuous Dynamics ARCH-COMP23 Category Report: Continuous and Hybrid Systems with Nonlinear Dynamics ARCH-COMP23 Repeatability Evaluation Report ARCH-COMP23 Category Report: Artificial Intelligence and Neural Network Control Systems (AINNCS) for Continuous and Hybrid Systems Plants
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