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A Mathematical Model to Optimize the Neoadjuvant Chemotherapy Treatment Sequence for Triple-Negative Locally Advanced Breast Cancer

Author

Listed:
  • Juan C. López-Alvarenga

    (Population Health & Biostatistics, School of Medicine, University of Texas Rio Grande Valley, Edinburgh, TX 78539, USA)

  • Antonmaria Minzoni-Alessio

    (Instituto de Investigaciones en Matemáticas Aplicadas y en Sistemas, Universidad Nacional Autónoma de México, Ciudad de México CP 04510, Mexico
    Deceased on 1 July 2017.)

  • Arturo Olvera-Chávez

    (Instituto de Investigaciones en Matemáticas Aplicadas y en Sistemas, Universidad Nacional Autónoma de México, Ciudad de México CP 04510, Mexico)

  • Gustavo Cruz-Pacheco

    (Instituto de Investigaciones en Matemáticas Aplicadas y en Sistemas, Universidad Nacional Autónoma de México, Ciudad de México CP 04510, Mexico)

  • Juan C. Chimal-Eguia

    (Laboratorio de Ciencias Matemáticas y Computacionales, Centro de Investigación en Computación, Instituto Politécnico Nacional, Ciudad de México CP 07738, Mexico)

  • Joselín Hernández-Ruíz

    (Servicio de Farmacología Clínica, Hospital General de México “Dr. Eduardo Liceaga”, Ciudad de México CP 06726, Mexico)

  • Mario A. Álvarez-Blanco

    (Unidad de Oncología Médica, Servicio de Oncología, Hospital General de México “Dr. Eduardo Liceaga”, Ciudad de México CP 06726, Mexico)

  • María Y. Bautista-Hernández

    (Unidad de Radio Terapia, Servicio de Oncología, Hospital General de México “Dr. Eduardo Liceaga”, Ciudad de México CP 06726, Mexico)

  • Rosa M. Quispe-Siccha

    (Unidad de Investigación y Desarrollo Tecnológico, Hospital General de México “Dr. Eduardo Liceaga”, Ciudad de México CP 06726, Mexico)

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 α s i 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.

Suggested Citation

  • Juan C. López-Alvarenga & Antonmaria Minzoni-Alessio & Arturo Olvera-Chávez & Gustavo Cruz-Pacheco & Juan C. Chimal-Eguia & Joselín Hernández-Ruíz & Mario A. Álvarez-Blanco & María Y. Bautista-Hernánd, 2023. "A Mathematical Model to Optimize the Neoadjuvant Chemotherapy Treatment Sequence for Triple-Negative Locally Advanced Breast Cancer," Mathematics, MDPI, vol. 11(11), pages 1-22, May.
  • Handle: RePEc:gam:jmathe:v:11:y:2023:i:11:p:2410-:d:1153250
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    References listed on IDEAS

    as
    1. Yunbao Pan & Yufen Yuan & Guoshi Liu & Yongchang Wei, 2017. "P53 and Ki-67 as prognostic markers in triple-negative breast cancer patients," PLOS ONE, Public Library of Science, vol. 12(2), pages 1-13, February.
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