Modelling heterogeneous cell clusters and their environment

Cell movement is one of the most fascinating processes in biology. It plays a crucial role in many areas of life: during early development, cells migrate to form tissues and organs; in wound healing, they move to close injuries; and in cancer, cells that leave the primary tumor can spread throughout the body, a process called metastasis. Surprisingly, research has shown that cancer cells often travel in clusters, and that these clusters are much more effective at forming new tumors than individual cells. Why this happens, however, is still a mystery. Our project aims to shed light on this and other questions of collective cell migration by combining mathematics, biology, and computer science. We are especially interested in how cells coordinate with one another, adapt to their surroundings, and use communication signals to move as a team. To study this, we develop mathematical models that describe cell behavior in precise equations. These models allow us to test ideas, guide experiments, and make testable biological predictions. We work closely with experimental data from real cancer cells, including patient-derived breast cancer cells, to ensure that our models reflect reality. One focus of our research is to understand how the environmentthe tissue landscape that cells move throughaffects whether cells migrate alone or in groups. Another focus is on cell heterogeneity: cells can have different characteristics, such as motility or stickiness, and this diversity may actually make clusters more adaptable and successful. Finally, we study how cells communicate and regulate their internal states, using biochemical signaling networks, to coordinate their movement. By linking these pieces together, we hope to explain how and why cell cluster movement differs from single cell movement. This knowledge is not only valuable for cancer research but also contributes to our general understanding of how living systems organize and cooperate. What makes this project special is its interdisciplinary approach. We bridge mathematics and biology in a way that allows us to study cell migration across multiple levels: from individual cells, to clusters, to entire populations. We use advanced computer simulations, optimization techniques, and machine learning to explore possible strategies cells might use. This combination of theory and experiment gives us a powerful toolbox to address questions that neither field could solve on its own. Ultimately, our research could help explain one of the big open questions in cancer biology: why moving together makes cancer cells so successful. With this understanding, we may pave the way for new strategies to interfere with metastasis. At the same time, our models and insights will have broad relevance, helping to explain processes as diverse as embryonic development, tissue repair, and the collective behavior of cells in health and disease.