Modeling Optimal Timing of Immunotherapy and Chemotherapy to Prevent Resistance and Recurrence in Triple-Negative Breast Cancer

The intrinsic characteristics of Triple Negative Breast Cancer (TNBC) contribute to tumor plasticity, resulting in heterogeneous subpopulations with distinct interactions with the immune system. To address TNBC plasticity, we set to model the dynamics of murine TNBC subpopulations, by developing an experimentally validated system of ordinary differential equations (ODEs) distinguishing between Sca1⁺ (Stem Cell Antigen 1) and Sca1⁻ cells and identifying chemotherapy-resistant populations. The model incorporates interactions with immune killer cells, including natural killer (NK) cells, T lymphocytes, and the immunosuppressive effects of myeloid-derived suppressor cells (MDSCs). We investigated the effects of chemotherapy and immune-boosting agent—methotrexate (MTX) and Abequolixron, respectively—through various treatment regimens and combinations using experimental data. Simulations were conducted to explore different treatment initiation times and variations in immune cell killing rates.Our findings indicate that the duration of the resting period in chemotherapy cycles plays a critical role in treatment outcomes. A longer rest period may help prevent the formation of drug-resistant subpopulations, which is a primary cause of disease recurrence. Additionally, the sequence of treatments is also important. According to our model, administering immunotherapy before chemotherapy is more effective in eradicating all cancer subpopulations. In particular, our model indicates that the synchronizing of chemotherapy with the initiation of immune killer cells peak during their oscillation may help preventing the development of drug-resistant tumor cell subpopulations.