Uncovering dual oscillatory regimes in p53-mdm2 dynamics: A data-driven modeling approach with implications for

Kathryn K Menta1, Majid Bani-Yaghoub1, Bi-Botti C Youan2

  • 1Division of Computing, Analytics & Mathematics, School of Science and Engineering, University of Missouri-Kansas City, 5100 Rockhill Rd., Kansas City, MO 64110, USA.

Bio Systems
|July 31, 2025
PubMed

Insights

This study presents a new mathematical model for p53-Mdm2 dynamics, revealing distinct oscillatory behaviors crucial for cancer suppression and therapeutic targeting. The model accurately fits experimental data, offering insights into cellular stress responses.

Area of Science:

  • Biophysics
  • Systems Biology
  • Cancer Research

Background:

  • The p53-Mdm2 interaction is a key regulator of cancer suppression.
  • Experimental data show p53-Mdm2 dynamics oscillate following DNA damage.
  • Existing mathematical models often fail to replicate these oscillations accurately.

Purpose of the Study:

  • To develop a robust mathematical model for p53-Mdm2 dynamics.
  • To accurately quantify stable periodic solutions (limit cycles) of p53-Mdm2 interactions.
  • To validate the model against experimental data and explore oscillatory regimes.

Main Methods:

  • Developed a simple ordinary differential equation model.
  • Employed a two-step numerical calibration algorithm.
  • Validated the model against four distinct experimental datasets.

Main Results:

  • The model successfully quantifies stable periodic solutions for p53-Mdm2 dynamics.
  • Two distinct oscillatory regimes were identified.
  • One regime showed Mdm2 oscillations 2.67 times greater in amplitude than p53, indicating amplified feedback.

Conclusions:

  • The developed model accurately captures p53-Mdm2 oscillatory behavior.
  • Variability in oscillations may enable context-dependent p53 target activation for fine-tuned stress responses.
  • This work provides a foundation for understanding cancer suppression and therapeutic targeting.

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