School of Medicine Publications and Presentations
Document Type
Article
Publication Date
5-23-2023
Abstract
Background: Triple-negative locally advanced breast cancer is an aggressive tumor type. Currently, the standard sequence treatment is applied, administering anthracyclines first and then a taxane plus platinum. Clinical studies for all possible treatment combinations are not practical or affordable, but mathematical modeling of the active mitotic cell population is possible. Our study aims to show the regions with the tumor’s most substantial cellular population variation by utilizing all possible values of the parameters (𝛼𝑖𝑠) that define the annihilatory drug capacity according to the proposed treatment.
Method: A piecewise linear mathematical model was used to analyze the cell population growth by applying four treatments: standard sequences of 21 days (SS21) and 14 days (SS14), administering anthracyclines first, followed by a taxane plus platinum, and inverted sequences of 21 days (IS21) and 14 days (IS14), administering a taxane plus platinum first then anthracyclines.
Results: The simulation showed a higher effect of IS14 over SS14 when the rate of drug resistance was larger in the cell population during DNA synthesis (G1 and S) compared to cells in mitosis (G2 and M). However, if the proportion of resistant cells in both populations was equivalent, then treatments did not differ.
Conclusions: When resistance is considerable, IS14 is more efficient than SS14, reducing the tumor population to a minimum.
Recommended Citation
López-Alvarenga, J. C., Minzoni-Alessio, A., Olvera-Chávez, A., Cruz-Pacheco, G., Chimal-Eguia, J. C., Hernández-Ruíz, J., ... & Quispe-Siccha, R. M. (2023). A Mathematical Model to Optimize the Neoadjuvant Chemotherapy Treatment Sequence for Triple-Negative Locally Advanced Breast Cancer. Mathematics, 11(11), 2410. https://doi.org/10.3390/math11112410
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Publication Title
Mathematics
DOI
10.3390/math11112410
Academic Level
faculty
Mentor/PI Department
Population Health and Biostatistics
Comments
© 2023 by the authors.