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Updated: Aug 16, 2025
Studying Triple Negative Breast Cancer Using Orthotopic Breast Cancer Model
Published on: March 20, 2020
Mathematical Model of Triple-Negative Breast Cancer in Response to Combination Chemotherapies
Angelica A Davenport1, Yun Lu2,3, Carlos A Gallegos4
1Department of Mathematics, Florida State University, 1017 Academic Way, Tallahassee, FL, 32304, USA. ad16z@fsu.edu.
Abstract:
Triple-negative breast cancer (TNBC) is a heterogenous disease that is defined by its lack of targetable receptors, thus limiting treatment options and resulting in higher rates of metastasis and recurrence. Combination chemotherapy treatments, which inhibit tumor cell proliferation and regeneration, are a major component of standard-of-care treatment of TNBC. In this manuscript, we build a coupled ordinary differential equation model of TNBC with compartments that represent tumor proliferation, necrosis, apoptosis, and immune response to computationally describe the biological tumor affect to a combination of chemotherapies, doxorubicin (DRB) and paclitaxel (PTX). This model is parameterized using longitudinal [18F]-fluorothymidine positron emission tomography (FLT-PET) imaging data which allows for a noninvasive molecular imaging approach to quantify the tumor proliferation and tumor volume measurements for two murine models of TNBC. Animal models include a human cell line xenograft model, MDA-MB-231, and a syngeneic 4T1 mammary carcinoma model. The mathematical models are parameterized and the percent necrosis at the end time point is predicted and validated using histological hematoxylin and eosin (H&E) data. Global Sobol' sensitivity analysis is conducted to further understand the role each parameter plays in the model's goodness of fit to the data. In both the MDA-MB-231 and the 4T1 tumor models, the designed mathematical model can accurately describe both tumor volume changes and final necrosis volume. This can give insight into the ordering, dosing, and timing of DRB and PTX treatment. More importantly, this model can also give insight into future novel combinations of therapies and how the immune system plays a role in therapeutic response to TNBC, due to its calibration to two types of TNBC murine models.
Insights
This study developed a mathematical model to predict triple-negative breast cancer (TNBC) treatment response. The model accurately describes tumor changes and necrosis, offering insights into combination chemotherapy strategies for TNBC.
Area of Science:
- Computational Biology
- Mathematical Oncology
- Cancer Research
Background:
- Triple-negative breast cancer (TNBC) lacks targeted receptors, limiting treatment options and leading to poor outcomes.
- Combination chemotherapy is a cornerstone of TNBC treatment, but optimal strategies require further understanding.
- Mathematical modeling offers a powerful tool to simulate tumor dynamics and treatment effects.
Purpose of the Study:
- To develop and parameterize a coupled ordinary differential equation model for TNBC.
- To computationally describe the effects of doxorubicin (DRB) and paclitaxel (PTX) combination chemotherapy on TNBC.
- To provide insights into treatment optimization and novel therapeutic combinations for TNBC.
Main Methods:
- A mathematical model was constructed with compartments for tumor proliferation, necrosis, apoptosis, and immune response.
- The model was parameterized using longitudinal [18F]-fluorothymidine positron emission tomography (FLT-PET) imaging data from two TNBC murine models (MDA-MB-231 and 4T1).
- Model predictions of necrosis were validated with histological (H&E) data, and global sensitivity analysis was performed.
Main Results:
- The mathematical model accurately described tumor volume changes and predicted final necrosis volume in both MDA-MB-231 and 4T1 models.
- Sensitivity analysis identified key parameters influencing model fit to experimental data.
- The model successfully captured tumor dynamics under combination chemotherapy.
Conclusions:
- The developed mathematical model can accurately simulate TNBC response to doxorubicin and paclitaxel combination chemotherapy.
- This model provides valuable insights for optimizing treatment timing, dosing, and sequencing for TNBC.
- The model's ability to incorporate immune response and its validation in two distinct TNBC models suggest potential for predicting novel therapy combinations.
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