This multidisciplinary study contributes to understanding general principles of branching morphogenesis as well as identification of key aspects of normal and pathological cell behaviours.

We investigate the role of FGF2 signalling intensity, myoepithelial cells and mechanical forces in regulation of mammary epithelial branching morphogenesis. To this end, we develop and use deep-learning-based pipelines for segmentation and tracking of 3D organoids as well as individual cells in data from time-lapse microscopy imaging and a computational model of FGF2-induced mammary organoid branching that comprehends the complex interplay of cell signalling and mechanical forces. Our approach is highly iterative: The data obtained from biological experiments inform modelling choices and feed computational simulations, results of which stimulate design of new experiments. Implementation of this multidisciplinary iterative approach allows for both hypothesis testing and discovery to unravel key mechanisms of mammary epithelial branching.

Furthermore, we aim to decipher the ERK signaling code in mammary epithelial morphogenesis and cancer using state-of-the-art imaging of mammary organoids with ERK biosensor, automated analysis of large imaging data, deep computational analysis of the temporal ERK activity fluctuations and the associated cellular fates, mathematical modeling of signal transduction, and perturbation analysis. This multidisciplinary study will contribute to understanding of signaling principles of the crucial ERK pathway. In the era of single-cell techniques and precision medicine, our findings will provide in-depth information on cell fate encoding by ERK signaling dynamics and mechanisms of normal and neoplastic breast cell heterogeneity, with the potential application in development of new rational, tailored treatment strategies and predictions of therapeutic responses.