Multiscale Models of Breast Cancer Progression

Abstract

Breast cancer initiation, invasion and metastasis span multiple length and time scales. Molecular events at short length scales lead to an initial tumorigenic population, which left unchecked by immune action, acts at increasingly longer length scales until eventually the cancer cells escape from the primary tumor site. This series of events is highly complex, involving multiple cell types interacting with (and shaping) the microenvironment. Multiscale mathematical models have emerged as a powerful tool to quantitatively integrate the convective-diffusion-reaction processes occurring on the systemic scale, with the molecular signaling processes occurring on the cellular and subcellular scales. In this study, we reviewed the current state of the art in cancer modeling across multiple length scales, with an emphasis on the integration of intracellular signal transduction models with pro-tumorigenic chemical and mechanical microenvironmental cues. First, we reviewed the underlying biomolecular origin of breast cancer, with a special emphasis on angiogenesis. Then, we summarized the development of tissue engineering platforms which could provide highfidelity ex vivo experimental models to identify and validate multiscale simulations. Lastly, we reviewed top-down and bottom-up multiscale strategies that integrate subcellular networks with the microenvironment. We present models of a variety of cancers, in addition to breast cancer specific models. Taken together, we expect as the sophistication of the simulations increase, that multiscale modeling and bottom-up agent-based models in particular will become an increasingly important platform technology for basic scientific discovery, as well as the identification and validation of potentially novel therapeutic targets.

An agent-based model of cancer stem cell initiated avascular tumour growth and metastasis: the effect of seeding frequency and location

“…Multiscale in silico systems biology approaches have been applied previously in studies of cancer [41,42] and angiogenesis [40,[43][44][45] (see [46][47][48] for reviews), but there has been a limited number of computational models investigating metastasis. The goal of this study is to examine the effect of stem cell seeding and location from the primary tumour or metastatic growth in a three-dimensional environment using a previously developed agent-based model [35,36,38,49].…”

A multiscale road map of cancer spheroids – incorporating experimental and mathematical modelling to understand cancer progression

“…These inter-relationships are intrinsically related to multicellular cancer growth and invasion. Multiscale, hybrid models that integrate cellular and tissue scales into a single modelling framework permit simulations that better mimic intracellular signalling pathways, intercellular mechanical interactions and microenvironmental variables to ultimately predict disease progression (Anderson and Quaranta, 2008;Chakrabarti et al, 2012).…”

“…The multiscale modelling of breast cancer initiation, invasion, metastasis, angiogenesis, its microenvironment and advances of experimental approaches have been reviewed elsewhere (Chakrabarti et al, 2012). Multiscale, agent-based methods (ABM) were combined with signalling pathways to address basic research questions and to identify novel molecular targets (Chakrabarti et al, 2012).…”

“…Such computational models are designed to improve our knowledge of the 'pathophysiological phenomena' of cancer, to screen chemoand radiotherapeutics, and in some cases to help us develop surgical strategies to arrest the growth of primary tumours and disease progression to secondary sites (Brown and Palmer, 2009;Kohandel et al, 2006;Montalenti et al, 1998;Panetta, 1997). The majority of previous mathematical models have focused on breast and prostate cancer, as both cancer types have the highest incidence rates in females and males, respectively (Chakrabarti et al, 2012;Jain et al, 2011;Siegel et al, 2012). However, there are a few studies that mathematically model ovarian cancer and address relevant aspects of tumour growth and angiogenesis, which indicates the efficacy of predictive techniques in hypothesis testing related to anti-cancer agents, such as cellcycle and non-cell-cycle-specific therapeutics (Brown and Palmer, 2009;Kohandel et al, 2006;Montalenti et al, 1998;Panetta, 1997).…”

Ductal carcinoma in situ of the breast: the importance of morphologic and molecular interactions

“…It is known that the tumor-associated stromal cells secrete factors such as vascular endothelial growth factor, IL-6, and IL-8, which promote angiogenesis and breast cancer progression [45].…”