Evidence map›Paper›PMID 41922423›Full record

ArticleScientific reports2026

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

Mobina Daneshparvar, Mojtaba Ghanizadeh, Seyed Peyman Shariatpanahi, Bahram Goliaei, Reza Mehdizadeh, Curzio Rüegg

Abstract read
In one paragraph

Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Mobina DaneshparvarLaboratory of Biophysics and Molecular Biology, Institute of Biochemistry and Biophysics, University of Tehran, Tehran, Iran.
Mojtaba GhanizadehLaboratory of Biophysics and Molecular Biology, Institute of Biochemistry and Biophysics, University of Tehran, Tehran, Iran.
Seyed Peyman ShariatpanahiLaboratory of Biophysics and Molecular Biology, Institute of Biochemistry and Biophysics, University of Tehran, Tehran, Iran.
Bahram GoliaeiLaboratory of Biophysics and Molecular Biology, Institute of Biochemistry and Biophysics, University of Tehran, Tehran, Iran.
Reza MehdizadehInstitute for Stochastics and Applications, University of Stuttgart, Stuttgart, Germany.
Curzio RüeggLaboratory of Experimental and Translational Oncology, Pathology, Department of Oncology, Microbiology and Immunology, Faculty of Science and Medicine, University of Fribourg, Fribourg, 1700, Switzerland. curzio.ruegg@unifr.ch.

Funding

Swiss National Science Foundation 310030_208136
6 · The paper itself

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.

Indexed as

Drug Resistance, NeoplasmImmunotherapyNeoplasm Recurrence, LocalTriple Negative Breast NeoplasmsAnimalsCell Line, TumorFemaleHumansMethotrexateMiceModels, BiologicalMethotrexateAbequolixron (RGX-104)Combination therapyDormancyDrug resistanceImmune cell killing rateImmunoeditingMethotrexate (MTX)Ordinary differential equations (ODEs)RecurrenceTriple Negative Breast Cancer (TNBC)Tumor heterogeneityTumor plasticity

Identifiers

PMID41922423
PMCPMC13183867

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.