A new validated mathematical model of the Wnt signalling pathway predicts effective combinational therapy by sFRP and Dkk
Abstract
The Wnt signalling pathway controls cell proliferation and differentiation, and its deregulation is implicated in different diseases including cancer. Learning how to manipulate this pathway could substantially contribute to the development of therapies. We developed a mathematical model describing the initial sequence of events in the Wnt pathway, from ligand binding to β-catenin accumulation, and the effects of inhibitors, such as sFRPs (secreted Frizzled-related proteins) and Dkk (Dickkopf). Model parameters were retrieved from experimental data reported previously. The model was retrospectively validated by accurately predicting the effects of Wnt3a and sFRP1 on β-catenin levels in two independent published experiments (R2 between 0.63 and 0.91). Prospective validation was obtained by testing the model's accuracy in predicting the effect of Dkk1 on Wnt-induced β-catenin accumulation (R2≈0.94). Model simulations under different combinations of sFRP1 and Dkk1 predicted a clear synergistic effect of these two inhibitors on β-catenin accumulation, which may point towards a new treatment avenue. Our model allows precise calculation of the effect of inhibitors applied alone or in combination, and provides a flexible framework for identifying potential targets for intervention in the Wnt signalling pathway.
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Only a few simulation models were both calibrated and validated based on wet-lab data, namely those of Lee et al. (2003) [28], Kogan et al. (2012) [45], and Haack et al. (2015) [51].
“When looking at the CSM and VSM activities, we detect that only a few simulation models were both calibrated and validated based on wet-lab data, namely those of Lee et al. (2003) [28], Kogan et al. (2012) [45], and Haack et al. (2015) [51].”
From Relating simulation studies by provenance—Developing a family of Wnt signaling models (2021) · cites this paper as [45]
Six out of 19 publications recorded their own wet-lab data [28, 31, 32, 45, 51, 57].
“When looking at Wet-lab Data, six out of 19 publications recorded their own wet-lab data [28, 31, 32, 45, 51, 57].”
From Relating simulation studies by provenance—Developing a family of Wnt signaling models (2021) · cites this paper as [45]
A second cluster forms around the simulation studies [45, 46, 51, 56, 57] and either includes the same wet-lab data from [105, 106], the Cell cycle [46] or ROS [51, 57].
“A second cluster forms around the simulation studies [45, 46, 51, 56, 57] and either includes the same wet-lab data from [105, 106], the Cell cycle [46] or ROS [51, 57].”
From Relating simulation studies by provenance—Developing a family of Wnt signaling models (2021) · cites this paper as [45]
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- Authors
- Kogan, Y., Halevi-Tobias, K. E., Hochman, G., Baczmanska, A. K., Leyns, L., & Agur, Z.
- Affiliations
- Institute for Medical BioMathematics (IL)
- Vrije Universiteit Brussel (BE)
- Corresponding author
- Kogan, Yuri
- Hochman, Gili
- Agur, Zvia
- Venue
- Biochemical Journal
- Publisher
- Portland Press Ltd.
- Published
- 2012-04-26
- Volume
- 444
- Issue
- 1
- Pages
- 115-125
- ISSN
- 0264-6021 (ISSN-L)
- 1470-8728
- OpenAlex
- W2170619426
- Cited by
- 39
- References
- 49
- Citations by year
- 2026: 2 · 2025: 1 · 2023: 3 · 2022: 1 · 2021: 3 · 2019: 1 · 2018: 2 · 2017: 9 · 2016: 4 · 2015: 3 · 2014: 3 · 2013: 6 · 2012: 1
- FWCI
- 1.67
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Biochemical Journal (publishedVersion)
- PubMed (publishedVersion)
- VUBIR (Vrije Universiteit Brussel) (submittedVersion)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Wnt/β-catenin signaling in development and cancer
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Hedgehog Signaling Pathway Studies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene Regulatory Network Analysis
- Keywords
- Wnt signalling pathway, mathematical model, beta-catenin accumulation, secreted frizzled-related proteins, SFRP1, Dickkopf, DKK1, Wnt3a, combination therapy, synergistic inhibition, pathway inhibitors, cancer therapy targets
- MeSH terms
- Frizzled-Related Proteins, Animals, Antineoplastic Agents, Cell Count, Computer Simulation, Drug Synergism, Glycoproteins, L Cells, Signal Transduction, Intercellular Signaling Peptides and Proteins, Intracellular Signaling Peptides and Proteins, beta Catenin, Mice, Wnt3A Protein
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