ArticleJournal of the Royal Society, Interface2014
Mathematical models of the transitions between endocrine therapy responsive and resistant states in breast cancer.
Article in Journal of the Royal Society, Interface, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed.
- A comprehensive review of computational cell cycle models in guiding cancer treatment strategies.NPJ systems biology and applications · 2024Review
- Modeling of Mouse Experiments Suggests that Optimal Anti-Hormonal Treatment for Breast Cancer is Diet-Dependent.Bulletin of mathematical biology · 2024Article
- Towards early diagnosis of Alzheimer's disease: advances in immune-related blood biomarkers and computational approaches.Frontiers in immunology · 2024Review
- Can Systems Biology Advance Clinical Precision Oncology?Cancers · 2021Review
- Optimal solution of the fractional order breast cancer competition model.Scientific reports · 2021Article
- Personalized Medicine for Neuroblastoma: Moving from Static Genotypes to Dynamic Simulations of Drug Response.Journal of personalized medicine · 2021Review
- Quantifying the Landscape and Transition Paths for Proliferation-Quiescence Fate Decisions.Journal of clinical medicine · 2020Article
- Hybrid modeling frameworks of tumor development and treatment.Wiley interdisciplinary reviews. Systems biology and medicine · 2020Review
- Exposing the Underlying Relationship of Cancer Metastasis to Metabolism and Epithelial-Mesenchymal Transitions.iScience · 2019Article
- Modelling bistable tumour population dynamics to design effective treatment strategies.Journal of theoretical biology · 2019Article
- Systems biology: perspectives on multiscale modeling in research on endocrine-related cancers.Endocrine-related cancer · 2019Review
- A landscape view on the interplay between EMT and cancer metastasis.NPJ systems biology and applications · 2018Article
- Phenotypic Plasticity and Cell Fate Decisions in Cancer: Insights from Dynamical Systems Theory.Cancers · 2017Review
- Quantifying the landscape and kinetic paths for epithelial-mesenchymal transition from a core circuit.Physical chemistry chemical physics : PCCP · 2016Article
- Endocrine resistance in breast cancer--An overview and update.Molecular and cellular endocrinology · 2015Review
- Unfolding the Role of Stress Response Signaling in Endocrine Resistant Breast Cancers.Frontiers in oncology · 2015Review
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Authors and funding
6 authors.
Funding
Abstract
Endocrine therapy, targeting the oestrogen receptor pathway, is the most common treatment for oestrogen receptor-positive breast cancers. Unfortunately, these tumours frequently develop resistance to endocrine therapies. Among the strategies to treat resistant tumours are sequential treatment (in which second-line drugs are used to gain additional responses) and intermittent treatment (in which a 'drug holiday' is imposed between treatments). To gain a more rigorous understanding of the mechanisms underlying these strategies, we present a mathematical model that captures the transitions among three different, experimentally observed, oestrogen-sensitivity phenotypes in breast cancer (sensitive, hypersensitive and independent). To provide a global view of the transitions between these phenotypes, we compute the potential landscape associated with the model. We show how this oestrogen response landscape can be reshaped by population selection, which is a crucial force in promoting acquired resistance. Techniques from statistical physics are used to create a population-level state-transition model from the cellular-level model. We then illustrate how this population-level model can be used to analyse and optimize sequential and intermittent oestrogen-deprivation protocols for breast cancer. The approach used in this study is general and can also be applied to investigate treatment strategies for other types of cancer.
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