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Agent-Based Modeling of Ductal Carcinoma In Situ: Application to Patient-Specific Breast Cancer Modeling

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Abstract

Ductal carcinoma in situ (DCIS) of the breast is the most common precursor to invasive carcinoma (IC), the second-leading cause of death in women in USA. There has been great progress in modeling DCIS at both the cellular scale (e.g., using cellular automata and agent-based models) and the population scale (e.g., using partial differential equations or systems of ordinary differential equations), but these past efforts have been difficult to calibrate with patient-specific molecular and cellular measurements. We develop a biophysically justified, agent-based cellular model of DCIS that is well-suited to patient-specific calibration. The model is modular in nature and can thus be readily extended to incorporate more advanced biology. We give an example of recently developed, patient-specific calibration of the model and conduct parameter studies that generate testable biological hypotheses.

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Notes

  1. 1.

    While using the interarrival time ordinarily gives probability of having at least one proliferation event (rather than precisely one) in the interval (t, t + Δt], our form of αP in (4.10) precludes this, because αP decreases to zero until completing proliferation.

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Acknowledgments

This work was partially funded by a generous grant from the Cullen Trust for Health Care (VC) and by the National Science Foundation (VC). We thank Yao-Li Chuang and Sandeep Sanga at the University of Texas Health Science Center-Houston for insightful discussions on tumor growth and protein signaling modeling.

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  1. School of Health Information Sciences, University of Texas Health Science Center, Houston, TX, USA

    Paul Macklin (Assistant Professor of Health Informatics)

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  1. Paul Macklin
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  2. Jahun Kim
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  3. Giovanna Tomaiuolo
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Correspondence to Paul Macklin .

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  1. Discipline of Information Technology, James Cook University, Townsville, 4811, Australia

    Tuan Pham

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Macklin, P., Kim, J., Tomaiuolo, G., Edgerton, M.E., Cristini, V. (2009). Agent-Based Modeling of Ductal Carcinoma In Situ: Application to Patient-Specific Breast Cancer Modeling. In: Pham, T. (eds) Computational Biology. Applied Bioinformatics and Biostatistics in Cancer Research. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-0811-7_4

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