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A gene expression-based mathematical modeling approach for breast cancer tumor growth and shrinkage

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Abstract

In this paper, we introduce a personalized parameterization approach, namely prep-g, to explore impact of gene expression values from breast cancer patients on tumor growth and shrinkage characteristics using xenograft models. In construction of prep-g parameterization, in addition to individual effects of the breast cancer-related gene expressions, the impact of the correlation among them and the contribution of their multiple orders are considered. Tumor growth behavior, and delay and shrinkage effects of anti-cancer agents are examined in six case studies using xenograft models implanted with breast cancer cell lines. Tumor growth parameters for er+ cell lines bt-474 and mcf-7, and drug-related shrinkage parameters for cell lines mda-mb-231, mda-mb-468 and bt-474 under the monotherapy of drugs paclitaxel and doxorubicin are computed. Consistency of the experimental data reported in several studies in literature for multiple breast cancer cell lines in mice models and the computed results from prep-g are encouraging, which indicates that construction of mathematical models for tumor growth and shrinkage by combining gene expressions and clinical information may be feasible.

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Acknowledgments

The initial research used in this work was supported by US Army Communications-Electronics RD&E Center contracts W15P7T-09-CS021 and W15P7T-06-C-P217, and by the National Science Foundation Grants ECCS-0421159, CNS-0619577 and IIP-1265265. The contents of this document represent the views of the authors and are not necessarily the official views of, or are endorsed by, the US Government, Department of Commerce, the US Patent and Trademark Office, Department of Defense, Department of the Army or the US Army Communications-Electronics RD&E Center.

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Authors and Affiliations

  1. Department of Electrical Engineering, The City College of the City University of New York, New York, NY, USA

    Aydin Saribudak, Jianmin Zou & M. Ümit Uyar

  2. Patent and Trademarks Office, Alexandria, VA, USA

    Stephen Gundry

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  1. Aydin Saribudak
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  2. Stephen Gundry
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  3. Jianmin Zou
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  4. M. Ümit Uyar
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Correspondence to Aydin Saribudak.

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Saribudak, A., Gundry, S., Zou, J. et al. A gene expression-based mathematical modeling approach for breast cancer tumor growth and shrinkage. Netw Model Anal Health Inform Bioinforma 4, 28 (2015). https://doi.org/10.1007/s13721-015-0099-9

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  • DOI: https://doi.org/10.1007/s13721-015-0099-9

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