Agent-based modeling of ductal carcinoma in situ: application to patient-specific breast cancer modeling

Paul Macklin, Jahun Kim, Giovanna Tomaiuolo, Mary E. Edgerton, Vittorio Cristini

    Research output: Chapter in Book/Report/Conference proceedingChapter

    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.
    Original languageEnglish
    Title of host publicationComputational biology: issues and applications in oncology
    EditorsTuan Pham
    PublisherSpringer
    Pages77-111
    Number of pages35
    ISBN (Print)9781441908100
    DOIs
    Publication statusPublished - 2010

    Publication series

    NameApplied bioinformatics and biostatistics in cancer research
    Number77(3)

    Keywords

    • Computational oncology
    • Cancer development
    • Breast cancer
    • Data modeling

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