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Disease progression model of 4T1 metastatic breast cancer

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Journal of Pharmacokinetics and Pharmacodynamics Aims and scope Submit manuscript

Abstract

Cancer metastasis is the main cause of death in various types of cancer. However, in the field of pharmacometrics, cancer disease progression models focus on the growth of primary tumors with tumor volume or weight as target values, while the metastasis process is less mentioned. We propose a series of mathematical models to quantitatively describe and predict the disease progression of 4T1 breast cancer in the aspect of primary breast tumor, lung metastasis and white blood cell. The 4T1 cells were injected into breast fat pad of female BALB/c mice to establish an animal model of breast cancer metastasis. The number and volume of lung metastases at different times were measured. Based on the above data, a disease progression model of breast cancer lung metastasis was established and parameter values were estimated. The white blood cell growth and the primary tumor growth of 4T1 mouse are also modeled. The established models can describe the lung metastasis of 4T1 breast cancer in three aspects: (1) the increase in metastasis number; (2) the growth of metastasis volume; (3) metastasis number-size distribution at different time points. Compared with the prior metastasis models based on von Forester equation, our models distinguished the growth rate of primary tumor and metastasis and got parameter values for 4T1 mouse model. And the current models optimized the metastasis number-size distribution model by utilizing logistic function instead of the prior power function. This study provides a comprehensive description of lung metastasis progression for 4T1 breast cancer model, as well as an alternative disease progression model structure for further pharmacodynamics modeling.

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Abbreviations

-2LL:

-2 Times the maximum likelihood logarithm

AIC:

Akaike's information criteria

IIV:

Inter individual variability

GOF:

Goodness of fit

IPRED:

Individual predictions

CWRES:

Conditional weighted residual

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Acknowledgements

This work was funded by Natural Science Foundation of Beijing Municipality (Grant No. 7192100).

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Authors and Affiliations

  1. Beijing Key Laboratory of Molecular Pharmaceutics and New Drug Delivery System, Department of Pharmaceutics, School of Pharmaceutical Sciences, Peking University, Beijing, 100191, China

    Liang Yang, Ling Yong, Yaoyao Feng, Yu Fu, Daming Kong, Wei Lu & Tian-yan Zhou

  2. School of Pharmacy, University of Otago, Dunedin, 9054, New Zealand

    Xiao Zhu

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  1. Liang Yang
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  2. Ling Yong
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  7. Wei Lu
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Contributions

T-yZ, LY designed research; LY, LY, Y-YF performed experiments; LY, LY, XZ, YF, D-mK, WL performed the mathematical model; LY wrote the paper.

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Correspondence to Tian-yan Zhou.

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The authors declare that they have no conflict of interest.

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All applicable international, national, and/or institutional guidelines for the care and use of animals were followed. All procedures performed in studies involving animals were in accordance with the ethical standards of the Institutional Animal Care and Use Committee of Peking University (LA2018272) at which the studies were conducted.

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Yang, L., Yong, L., Zhu, X. et al. Disease progression model of 4T1 metastatic breast cancer. J Pharmacokinet Pharmacodyn 47, 105–116 (2020). https://doi.org/10.1007/s10928-020-09673-5

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