title: An agent-based model of cancer stem cell initiated avascular tumour growth and metastasis: the effect of seeding frequency and location.
abstract: It is very important to understand the onset and growth pattern of breast primary tumours as well as their metastatic dissemination. In most cases, it is the metastatic disease that ultimately kills the patient. There is increasing evidence that cancer stem cells are closely linked to the progression of the metastatic tumour. Here, we investigate stem cell seeding to an avascular tumour site using an agent-based stochastic model of breast cancer metastatic seeding. The model includes several important cellular features such as stem cell symmetric and asymmetric division, migration, cellular quiescence, senescence, apoptosis and cell division cycles. It also includes external features such as stem cell seeding frequency and location. Using this model, we find that cell seeding rate and location are important features for tumour growth. We also define conditions in which the tumour growth exhibits decremented and exponential growth patterns. Overall, we find that seeding, senescence and division limit affect not only the number of stem cells, but also their spatial and temporal distribution.
authors.affiliation: Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Johns Hopkins University, Baltimore, MD 21205, USA kerri.norton@gmail.com.
authors.forename: Kerri-Ann
authors.initials: KA
authors.lastname: Norton
authors.affiliation: Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Johns Hopkins University, Baltimore, MD 21205, USA Department of Oncology and Sidney Kimmel Comprehensive Cancer Center, Baltimore, MD 21205, USA.
authors.forename: Aleksander S
authors.initials: AS
authors.lastname: Popel
mesh_terms: D001943:Breast Neoplasms / Q000378:metabolism* / Q000473:pathology; D005260:Female; D006801:Humans; D008954:Models, Biological; D009362:Neoplasm Metastasis; D014411:Neoplastic Stem Cells / Q000378:metabolism* / Q000473:pathology
keywords: computational modelling; metastatic niche; progenitor cells