Predicting p53-dependent cell transitions from thermodynamic models

A cell’s fate involves transitions among its various states, each defined by a distinct gene expression profile governed by the topology of gene regulatory networks, which are affected by 3D genome organization. Here, we develop thermodynamic models to determine the fate of a malignant cell as governed by the tumor suppressor p53 signaling network, taking into account long-range chromatin interactions in the mean-field approximation. The tumor suppressor p53 responds to stress by selectively triggering one of the potential transcription programs that influence many layers of cell signaling. These range from p53 phosphorylation to modulation of its DNA binding affinity, phase separation phenomena, and internal connectivity among cell fate genes. We use the minimum free energy of the system as a fundamental property of biological networks that influences the connection between the gene network topology and the state of the cell. We constructed models based on network topology and equilibrium thermodynamics. Our modeling shows that the binding of phosphorylated p53 to promoters of target genes can have properties of a first order phase transition. We apply our model to cancer cell lines ranging from breast cancer (MCF-7), colon cancer (HCT116), and leukemia (K562), with each one characterized by a specific network topology that determines the cell fate. Our results clarify the biological relevance of these mechanisms and suggest that they represent flexible network designs for switching between developmental decisions.