ArticleJournal of the Royal Society, Interface2020
Mathematical modelling of breast cancer cells in response to endocrine therapy and Cdk4/6 inhibition.
Article in Journal of the Royal Society, Interface, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
12 citing papers in PubMed, 25 citations in OpenAlex.
- Cell Population Dynamics Informed by Cell-Cycle Regulation: A Deterministic Modeling Toolkit.Computational and structural biotechnology journal · 2026Review
- WEE1 inhibition delays resistance to CDK4/6 inhibitor and antiestrogen treatment in ER+ MCF7 cells.NPJ systems biology and applications · 2025Article
- Probability Distribution for Rare Neutral Mutations in Cancers and Application to Dynamic Precision Medicine of Cancer.bioRxiv : the preprint server for biology · 2025Article
- Personalized cancer treatment strategies incorporating irreversible and reversible drug resistance mechanisms.NPJ systems biology and applications · 2025Article
- Personalizing neoadjuvant chemotherapy regimens for triple-negative breast cancer using a biology-based digital twin.NPJ systems biology and applications · 2025Article
- Experimentally-driven mathematical model to understand the effects of matrix deprivation in breast cancer metastasis.NPJ systems biology and applications · 2024Article
- Modeling of Mouse Experiments Suggests that Optimal Anti-Hormonal Treatment for Breast Cancer is Diet-Dependent.Bulletin of mathematical biology · 2024Article
- OvercomingFrontiers in microbiology · 2024Article
- Article
- Mathematically Modeling the Effect of Endocrine and Cdk4/6 Inhibitor Therapies on Breast Cancer Cells.Methods in molecular biology (Clifton, N.J.) · 2023Article
- Can Systems Biology Advance Clinical Precision Oncology?Cancers · 2021Review
- Personalized Medicine for Neuroblastoma: Moving from Static Genotypes to Dynamic Simulations of Drug Response.Journal of personalized medicine · 2021Review
Corrections and comments
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
Abstract
Oestrogen receptor (ER)-positive breast cancer is responsive to a number of targeted therapies used clinically. Unfortunately, the continuous application of any targeted therapy often results in resistance to the therapy. Our ultimate goal is to use mathematical modelling to optimize alternating therapies that not only decrease proliferation but also stave off resistance. Toward this end, we measured levels of key proteins and proliferation over a 7-day time course in ER+ MCF-7 breast cancer cells. Treatments included endocrine therapy, either oestrogen deprivation, which mimics the effects of an aromatase inhibitor, or fulvestrant, an ER degrader. These data were used to calibrate a mathematical model based on key interactions between ER signalling and the cell cycle. We show that the calibrated model is capable of predicting the combination treatment of fulvestrant and oestrogen deprivation. Further, we show that we can add a new drug, palbociclib, to the model by measuring only two key proteins, cMyc and hyperphosphorylated RB1, and adjusting only parameters associated with the drug. The model is then able to predict the combination treatment of oestrogen deprivation and palbociclib. We illustrate the model's potential to explore protocols that limit proliferation and hold off resistance by not depending on any one therapy.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.