Unreveling the Biological Complexity Through Modeling and Computer Simulations: Angiogenesis as a Case Study

Marko Scalerandi

INFM – Dip. Fisica, Politecnico di Torino, Italy
Marco.scalerandi@infm.polito.it

      A detailed understanding of the dynamics of healthy and cancerous tissue growth and reorganisation is one of the great challenges of modern science and is a prerequisite for devising novel and patient-oriented therapeutic strategies. However, despite the large amount of information at a molecular and cellular level, very little of it is effectively transferred to clinical applications. Indeed, translation from one scale to the nearest one (e.g. subcellular to cellular, cellular to in vitro, in vitro to in vivo) is not easy at all, due to the formidable complexity of biological systems and the lack of compatibility among different experimental models on different space scale, particularly evident, e.g., in oncology.
      Mathematical models based on physical principles might help to simplify the huge number of chemical and biological interactions, by introducing a simple mathematical description which, at a certain scale (and complexity) level, should be able to reproduce (at least partly) macroscopic observations. Once proven their reliability, models and computer simulations, thanks to the ease to apply them in different and controlled conditions, may help supporting and/or suggesting new real-world experiments, designing therapeutic protocols and optimizing time and cost of research (e.g. replacing some animal experiments with fast and reproducible virtual experiments).
      We will present a strategy for modeling the spatio-temporal dynamics (growth and reorganization) of cells, based on a continuum, rather than microscopic, approach, which allows us to simulate larger blocks of tissues, at the cost of loosing detailed microscopic informations. The proposed method has been applied, as a case study, to model angiogenesis during tumor growth and the interaction with angiogenesis modulators (like monoclonal antibodies inhibition of the VEGFR-2). Despite the simplicity of the approach and the drastic simplification of the assumptions, the morphology of the neo-vascular network and its infiltration in the tumor mass is well reproduced. Also, simulation results for what concerns the effects of angiogenesis inhibitors are in qualitative agreement with literature and suggest some novel, albeit controversial, hypotheses for antiangiogenetic treatments.