A Multiscale Agent-Based Model of Ductal Carcinoma in Situ

Joseph D. Butner, David Fuentes, Bulent Ozpolat, George A. Calin, Xiaobo Zhou, John Lowengrub, Vittorio Cristini, Zhihui Wang

Research output: Contribution to journalArticlepeer-review

11 Scopus citations

Abstract

Objective: we present a multiscale agent-based model of Ductal Carcinoma in Situ (DCIS) in order to gain a detailed understanding of the cell-scale population dynamics, phenotypic distributions, and the associated interplay of important molecular signaling pathways that are involved in DCIS ductal invasion into the duct cavity (a process we refer to as duct advance rate here). Methods: DCIS is modeled mathematically through a hybridized discrete cell-scale model and a continuum molecular scale model, which are explicitly linked through a bidirectional feedback mechanism. Results: we find that duct advance rates occur in two distinct phases, characterized by an early exponential population expansion, followed by a long-term steady linear phase of population expansion, a result that is consistent with other modeling work. We further found that the rates were influenced most strongly by endocrine and paracrine signaling intensity, as well as by the effects of cell density induced quiescence within the DCIS population. Conclusion: our model analysis identified a complex interplay between phenotypic diversity that may provide a tumor adaptation mechanism to overcome proliferation limiting conditions, allowing for dynamic shifts in phenotypic populations in response to variation in molecular signaling intensity. Further, sensitivity analysis determined DCIS axial advance rates and calcification rates were most sensitive to cell cycle time variation. Significance: this model may serve as a useful tool to study the cell-scale dynamics involved in DCIS initiation and intraductal invasion, and may provide insights into promising areas of future experimental research.

Original languageEnglish (US)
Article number8862917
Pages (from-to)1450-1461
Number of pages12
JournalIEEE Transactions on Biomedical Engineering
Volume67
Issue number5
DOIs
StatePublished - May 2020

Keywords

  • Breast cancer
  • DCIS modeling
  • cell lineage
  • mammography
  • mathematical modeling
  • molecular signaling

ASJC Scopus subject areas

  • Biomedical Engineering

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