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Modeling optimal timing of immunotherapy and chemotherapy to prevent resistance and recurrence in triple-negative breast cancer
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  • Published: 01 April 2026

Modeling optimal timing of immunotherapy and chemotherapy to prevent resistance and recurrence in triple-negative breast cancer

  • Mobina Daneshparvar1,
  • Mojtaba Ghanizadeh1,
  • Seyed Peyman Shariatpanahi1,
  • Bahram Goliaei1,
  • Reza Mehdizadeh2 &
  • …
  • Curzio Rüegg3 

Scientific Reports , Article number:  (2026) Cite this article

We are providing an unedited version of this manuscript to give early access to its findings. Before final publication, the manuscript will undergo further editing. Please note there may be errors present which affect the content, and all legal disclaimers apply.

Subjects

  • Applied mathematics
  • Breast cancer
  • Cancer therapy
  • Differential equations
  • Population dynamics
  • Tumour heterogeneity

Abstract

One intrinsic characteristic of Triple Negative Breast Cancer (TNBC) is its high plasticity, resulting in heterogeneous cancer cell subpopulations with distinct interactions with the immune system. To address TNBC plasticity, we set to model the dynamics of tumor cell subpopulations derived from the murine TNBC-like 4T1 cell line, by developing a system of ordinary differential equations (ODEs) based on experimental results, distinguishing between Sca1⁺ (Stem Cell Antigen 1) and Sca1⁻ cells and identifying chemotherapy-resistant populations. The model incorporates interactions with immune cells, including natural killer (NK) cells, T lymphocytes, and myeloid-derived suppressor cells (MDSCs). We investigated the effects of chemotherapy and anti-MDSC immune-boosting agent—methotrexate (MTX) and Abequolixron, respectively—through various treatment regimens and combinations. Simulations were conducted to explore different treatment initiation times and variations in immune cell killing rates. Our findings suggest treatment timing and administration order as key determinants of therapeutic outcome. Initiating chemotherapy in synchrony with immune-killer cell oscillations—near their local peak—promoted tumor elimination, whereas mistimed treatment led to tumor escape. An optimal chemotherapy exposure window was required for elimination; exposures that were too short or prolonged favored escape of MTX-sensitive and MTX-resistant cells, respectively. Longer MTX-free intervals shifted tumors from dormancy toward elimination, suggesting reduced recurrence risk. Administering immune-boosting therapy before chemotherapy broadened the effective therapeutic window, and combination treatment with Abequolixron and MTX further improved outcomes. These results provide, for the first time a quantitative mathematical framework based on experimental data, leveraging TNBC cell plasticity for optimizing combined chemo-immunotherapy scheduling in TNBC.

Code availability

The code used in this study is openly available on Zenodo at: https://doi.org/10.5281/zenodo.15723767. The corresponding GitHub repository can be accessed at: https://github.com/Mobina-Daneshparvar/cancer-immune-dynamics.

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Acknowledgements

This work was supported by a grant from the Swiss National Science Foundation (310030_208136) to CR.

Author information

Authors and Affiliations

  1. Laboratory of Biophysics and Molecular Biology, Institute of Biochemistry and Biophysics, University of Tehran, Tehran, Iran

    Mobina Daneshparvar, Mojtaba Ghanizadeh, Seyed Peyman Shariatpanahi & Bahram Goliaei

  2. Institute for Stochastics and Applications, University of Stuttgart, Stuttgart, Germany

    Reza Mehdizadeh

  3. Laboratory of Experimental and Translational Oncology, Pathology, Department of Oncology, Microbiology and Immunology, Faculty of Science and Medicine, University of Fribourg, Fribourg, 1700, Switzerland

    Curzio Rüegg

Authors
  1. Mobina Daneshparvar
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  2. Mojtaba Ghanizadeh
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  3. Seyed Peyman Shariatpanahi
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  4. Bahram Goliaei
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  5. Reza Mehdizadeh
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  6. Curzio Rüegg
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Contributions

M.D.: Conceptualization, simulation data collection, data analysis, and manuscript draft preparation. M.G.: Conceptualization, simulation data collection, and manuscript draft preparation and revision. S.P.S.: Project supervision, conceptualization, and manuscript revision. B.G.: Project administration and project supervision. R.M.: Manuscript revision. C.R.: Project supervision and manuscript revision. All authors have read and agreed to the published version of the manuscript.

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Correspondence to Curzio Rüegg.

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Daneshparvar, M., Ghanizadeh, M., Shariatpanahi, S.P. et al. Modeling optimal timing of immunotherapy and chemotherapy to prevent resistance and recurrence in triple-negative breast cancer. Sci Rep (2026). https://doi.org/10.1038/s41598-026-44611-4

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  • Received: 24 June 2025

  • Accepted: 12 March 2026

  • Published: 01 April 2026

  • DOI: https://doi.org/10.1038/s41598-026-44611-4

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Keywords

  • Triple Negative Breast Cancer (TNBC)
  • Ordinary differential equations (ODEs)
  • Tumor heterogeneity
  • Drug resistance
  • Methotrexate (MTX)
  • Abequolixron (RGX-104)
  • Combination therapy
  • Immune cell killing rate
  • Tumor plasticity
  • Recurrence
  • Immunoediting
  • Dormancy
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