The development of cancer in a human body is a tremendously complex process, involving cascades of rare, subtle and fine-tuned events. Understanding the sequence of stages of cancer evolution from its onset by critical mutations until the final invading and mostly fatal, metastasizing phase is a challenging, interdisciplinary scientific and practical problem. Solutions of this problem can be the basis for innovative therapy design.
Despite the immense progress over the past decades in unraveling the details of biochemical pathways of cancer cell physiology, we still lack a principal understanding of the precise causes and consequences of the critical events, which trigger the progression of cancer. During the development of cancer, pre-cancer and cancer cell populations undergo a complex set of evolutionary events that lead to genetic, as well as epigenetic changes. These primary evolutionary events occur on large time-scales of the order of several years if not decades. Cellular sub- populations may develop cancerous tissues at short or medium time scales. However, the complex dynamics of these growth processes and their regulation are only poorly understood. Mathematical modeling aims on understanding the coupling and the dynamics of these diverse processes acting on different spatiotemporal scales.
The intention of the envisioned cooperation-group is on the design of new model approaches and the adaptation of novel mathematical methods for various important aspects of tumor progression and regulation - from the early accumulation of genetic defects till the late metastatic phase. Although each of these topics has its own specific group of questions, established models and methods, they are all highly interlinked and condition each other. We envisage the development of an integrative mathematical framework that connects various cancer development aspects.
We believe that it is of primary importance that work of the people involved in the cooperation group would give a long lasting impact in terms of novel interdisciplinary thinking, models and methods to the entire field rather than to produce a few print ready results which are just modifications of existing approaches.