Mathematical model identifies effective P53 accumulation with target gene binding affinity in DNA damage response for cell fate decision

• Published in: Cell cycle (Georgetown, Tex.) Vol. 17; no. 24; pp. 2716 - 2730
• Main Authors: Sun, Tingzhe, Mu, Dan, Cui, Jun
• Format: Journal Article
• Language: English
• Published: United States Taylor & Francis 17.12.2018
• Subjects: Apoptosis - drug effects; cell fate decision; DNA damage; DNA Damage - drug effects; DNA Repair; Doxorubicin - pharmacology; Humans; Imidazoles - pharmacology; Models, Biological; P53 terminal pulse; Piperazines - pharmacology; Research Paper; Signal Transduction - drug effects; Tumor Suppressor Protein p53 - metabolism; cell fate decision; DNA damage; P53 terminal pulse
• ISSN: 1538-4101; 1551-4005
• DOI: 10.1080/15384101.2018.1553342

Functional p53 signaling is essential for appropriate responses to diverse stimuli. P53 dynamics employs the information from the stimulus leading to selective gene expression and cell fate decision. However, the decoding mechanism of p53 dynamics under DNA damage challenge remains poorly understood. Here we mathematically modeled the recently dual-phase p53 dynamics under doxorubicin treatment. We found that p53 could perform sequential pulses followed by a high-amplitude terminal pulse at relatively low doxorubicin treatment, whereas p53 became steadily accumulated when damage level was high. The effective p53 integral above a threshold but not the absolute accumulation of p53 precisely discriminated survival and death. Silencing negative regulators in p53 network might promote the occurrence of terminal pulse. Furthermore, lower binding affinity and degradation rate of p53 target genes could favorably discriminate high and low dose doxorubicin treatment. Grouping by temporal profiles suggested that the p53 dynamics rather than the doxorubicin doses could better discriminate cellular outcomes and confer less variation for effective p53 integral reemphasizing the importance of p53 level regulation. Our model has established a theoretical framework that p53 dynamics can work cooperatively with its binding affinity to target genes leading to cell fate choice, providing new clues of optimized clinical design by manipulating p53 dynamics.