Dataset Information

Modeling of Mouse Experiments Suggests that Optimal Anti-Hormonal Treatment for Breast Cancer is Diet-Dependent.

ABSTRACT: Estrogen receptor positive breast cancer is frequently treated with anti-hormonal treatment such as aromatase inhibitors (AI). Interestingly, a high body mass index has been shown to have a negative impact on AI efficacy, most likely due to disturbances in steroid metabolism and adipokine production. Here, we propose a mathematical model based on a system of ordinary differential equations to investigate the effect of high-fat diet on tumor growth. We inform the model with data from mouse experiments, where the animals are fed with high-fat or control (normal) diet. By incorporating AI treatment with drug resistance into the model and by solving optimal control problems we found differential responses for control and high-fat diet. To the best of our knowledge, this is the first attempt to model optimal anti-hormonal treatment for breast cancer in the presence of drug resistance. Our results underline the importance of considering high-fat diet and obesity as factors influencing clinical outcomes during anti-hormonal therapies in breast cancer patients.

SUBMITTER: Akman T

PROVIDER: S-EPMC11310292 | biostudies-literature | 2024 Mar

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Modeling of Mouse Experiments Suggests that Optimal Anti-Hormonal Treatment for Breast Cancer is Diet-Dependent.

Akman Tuğba T Arendt Lisa M LM Geisler Jürgen J Kristensen Vessela N VN Frigessi Arnoldo A Köhn-Luque Alvaro A

Bulletin of mathematical biology 20240318 4

Estrogen receptor positive breast cancer is frequently treated with anti-hormonal treatment such as aromatase inhibitors (AI). Interestingly, a high body mass index has been shown to have a negative impact on AI efficacy, most likely due to disturbances in steroid metabolism and adipokine production. Here, we propose a mathematical model based on a system of ordinary differential equations to investigate the effect of high-fat diet on tumor growth. We inform the model with data from mouse experi ...[more]

PMID: 38498130

Similar Datasets

Project description:BackgroundBreast and cervical cancers are the commonest cancers among women. Secondary prevention of cancer through screening minimizes disease burden and improves survival outcomes. Optimizing screening strategies for breast and cervical cancers is a challenge in resource-limited settings with a high population density such as China. Therefore, we aimed at assessing the efficiency of different combined screening strategies for breast and cervical cancers under different budgets in China.MethodsMarkov cohort model was used to evaluate the cost-effectiveness of 36 strategy combinations for breast and cervical cancer screening with varying screening modality and intervals. The results were used as inputs in the Integer Programming (IP) model to determine the combination of the different screening options under different budgets.ResultsThe optimal combination strategy was biennial breast ultrasonography (BUS) and mammography (MAM) in parallel screening and quinquennial human papillomavirus (HPV) for breast and cervical cancer screening under the threshold of the annual per capita social cost investment (PCSCI) (18.80 USD) in China. Using this strategy, the total investment cost for 100,000 females was 1,877,984.50 USD, and the incremental life-years compared with no screening was 3,122 life-years. The optimal combination strategy included annual clinical breast examination (CBE), BUS and MAM in series screening, and biennial thin-layer liquid-based cytology (TCT) and HPV in series screening with the annual PCSCI reaching 37.60 USD. Thereafter, as the cost input continued to increase, the optimal combination strategy remained unchanged, and the sum of incremental life-years and actual input costs did not increase.ConclusionsFrom a social cost-benefit perspective, biennial BUS and MAM in parallel screening, and quinquennial HPV screening is the most efficient combination strategy with limited budget, while annual CBE, BUS and MAM in series screening and biennial TCT and HPV in series screening are the most efficient combination strategy with sufficient budget.

Dataset Information

Modeling of Mouse Experiments Suggests that Optimal Anti-Hormonal Treatment for Breast Cancer is Diet-Dependent.

Publications

Modeling of Mouse Experiments Suggests that Optimal Anti-Hormonal Treatment for Breast Cancer is Diet-Dependent.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets