Development of a three dimensional, lattice-free multiscale model of the mammary terminal end bud

An Intravital Microscopy Toolbox to Study Mammary Gland Dynamics from Cellular Level to Organ Scale

The architecture of the mouse mammary gland is highly dynamic and constantly remodeled during pubertal development and estrous cycle-driven sprouting and regression of alveolar side branches. During each of these developmental stages, turnover is driven by distinct subsets of mammary epithelial cells. Extensive previous research has shed light on the unique morphological and cell biological characteristics of each stage. However, technological shortcomings failed to capture the dynamics and single-cell contributions to mammary remodeling. Here, we developed in vivo imaging strategies to follow the same mammary ducts over time and quantify the dynamics of mammary gland growth and remodeling from single-cell level to organ scale. Using a combination of intravital microscopy and genetic reporter systems we show how proliferative heterogeneity drives ductal morphogenesis during different developmental stages. To visualize pubertal growth at the cellular level, we performed long-term time-lapse imaging of extending terminal end buds through a mammary imaging window. We show that single-cells within the terminal end buds are extremely motile and continuously exchange position whilst the duct is elongating. To visualize short-term remodeling in the adult mammary gland at the single cell level, we performed multi-day intravital imaging in photoconvertible Kikume Green-Red mice and fluorescent ubiquitination-based cell cycle indicator mice. We demonstrate that the contribution of single-cells to estrous-driven remodeling is highly variable between cells in the same micro-environment. To assess the effects of this dynamic proliferative contribution on the long-term stability of tissue architecture, we developed a repeated skin flap method to assess mammary gland morphology by intravital microscopy over extended time spans for up to six months. Interestingly, in contrast to the short-term dynamic remodeling, the long-term morphology of the mammary gland remains remarkably stable. Together, our tool box of imaging strategies allows to identify and map transient and continuing dynamics of single cells to the architecture of the mammary gland.

Towards personalized computational oncology: from spatial models of tumour spheroids, to organoids, to tissues

A main goal of mathematical and computational oncology is to develop quantitative tools to determine the most effective therapies for each individual patient. This involves predicting the right drug to be administered at the right time and at the right dose. Such an approach is known as precision medicine. Mathematical modelling can play an invaluable role in the development of such therapeutic strategies, since it allows for relatively fast, efficient and inexpensive simulations of a large number of treatment schedules in order to find the most effective. This review is a survey of mathematical models that explicitly take into account the spatial architecture of three-dimensional tumours and address tumour development, progression and response to treatments. In particular, we discuss models of epithelial acini, multicellular spheroids, normal and tumour spheroids and organoids, and multi-component tissues. Our intent is to showcase how these in silico models can be applied to patient-specific data to assess which therapeutic strategies will be the most efficient. We also present the concept of virtual clinical trials that integrate standard-of-care patient data, medical imaging, organ-on-chip experiments and computational models to determine personalized medical treatment strategies.