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Prevention of EMT‐Mediated Metastasis via Optimal Modulation Strategies for the Dysregulated WNT Pathway Interacting With TGF‐β

Author

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  • Sooyoun Choi
  • Yunil Roh
  • Yong Dam Jeong
  • Il Hyo Jung

Abstract

Cancer metastasis is one of the leading causes of death in cancer patients. Dysregulation of the WNT signaling pathway is known to increase the risk of cancer metastasis by leading to excessive accumulation of β‐catenin, which activates epithelial–mesenchymal transition (EMT) mechanisms that induce cell motility. Although mono and combination therapies are being developed to prevent metastasis by controlling the abnormally elevated levels of β‐catenin, there are limitations in comparing and predicting the treatment effects due to the complexity of cell signaling pathways. In addition, uncertainty exists in determining the optimal combination ratio of each therapy in combination treatments. In this study, we aim to address these challenges by investigating optimal modulation strategies to minimize β‐catenin concentration, using a mathematical model that comprehensively describes the interactions between the WNT signaling pathway and transforming growth factor‐β (TGF‐β) involved in EMT, along with optimal control theory. We analyze the efficacy of monotherapy strategies to prevent the hyperactivation of β‐catenin and quantitatively determine the optimal combination ratio for preventing EMT, based on the E‐cadherin biomarker as an indicator of EMT. Furthermore, we identify the optimal therapy protocol that minimizes patient burden while maximizing therapeutic efficacy by incorporating considerations of control sequences and delay times. Our findings are expected to not only enhance the understanding of the complex signaling pathways underlying cancer metastasis but also contribute to the development of novel therapeutic approaches.

Suggested Citation

  • Sooyoun Choi & Yunil Roh & Yong Dam Jeong & Il Hyo Jung, 2025. "Prevention of EMT‐Mediated Metastasis via Optimal Modulation Strategies for the Dysregulated WNT Pathway Interacting With TGF‐β," Complexity, John Wiley & Sons, vol. 2025(1).
  • Handle: RePEc:wly:complx:v:2025:y:2025:i:1:n:9007322
    DOI: 10.1155/cplx/9007322
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    References listed on IDEAS

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    1. Yong Dam Jeong & Kwang Su Kim & Yunil Roh & Sooyoun Choi & Shingo Iwami & Il Hyo Jung, 2022. "Optimal Feedback Control of Cancer Chemotherapy Using Hamilton–Jacobi–Bellman Equation," Complexity, John Wiley & Sons, vol. 2022(1).
    2. Yong Dam Jeong & Kwang Su Kim & Yunil Roh & Sooyoun Choi & Shingo Iwami & Il Hyo Jung & Guang Li, 2022. "Optimal Feedback Control of Cancer Chemotherapy Using Hamilton–Jacobi–Bellman Equation," Complexity, Hindawi, vol. 2022, pages 1-11, April.
    3. Rodrigues, D.S. & Mancera, P.F.A. & Carvalho, T. & Gonçalves, L.F., 2019. "A mathematical model for chemoimmunotherapy of chronic lymphocytic leukemia," Applied Mathematics and Computation, Elsevier, vol. 349(C), pages 118-133.
    4. Xin He & Zhigang Chen & Minyue Jia & Xiaoying Zhao, 2013. "Downregulated E-Cadherin Expression Indicates Worse Prognosis in Asian Patients with Colorectal Cancer: Evidence from Meta-Analysis," PLOS ONE, Public Library of Science, vol. 8(7), pages 1-8, July.
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