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

IF 1.7 4区 工程技术 Q2 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS Complexity Pub Date : 2025-03-04 DOI:10.1155/cplx/9007322
Sooyoun Choi, Yunil Roh, Yong Dam Jeong, Il Hyo Jung
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引用次数: 0

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.

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来源期刊
Complexity
Complexity 综合性期刊-数学跨学科应用
CiteScore
5.80
自引率
4.30%
发文量
595
审稿时长
>12 weeks
期刊介绍: Complexity is a cross-disciplinary journal focusing on the rapidly expanding science of complex adaptive systems. The purpose of the journal is to advance the science of complexity. Articles may deal with such methodological themes as chaos, genetic algorithms, cellular automata, neural networks, and evolutionary game theory. Papers treating applications in any area of natural science or human endeavor are welcome, and especially encouraged are papers integrating conceptual themes and applications that cross traditional disciplinary boundaries. Complexity is not meant to serve as a forum for speculation and vague analogies between words like “chaos,” “self-organization,” and “emergence” that are often used in completely different ways in science and in daily life.
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