Humanitas Clinical and Research Center, Italy
Fabio Grizzi graduated in Biological Sciences from the University of Milan in 1995 and, in the same year, received the Steven Newburgh Annual Award for his contributions to the fi eld of basic and applied biomedical research. In 2008, he was invited to become a member of the National Cancer Institute-sponsored Pilot Cancer Antigen Prioritization Process, of the US National Institute of Health. He is currently working in the Laboratory of Molecular Gastroenterology of the Humanitas Clinical and Research Center, Milan, Italy. He has published more than one hundred peer-reviewed articles, twenty-three book chapters, and has recently been commissioned by Springer Publishing to prepare a book entitled “The Complexity of Cancer”.
Cancer is a heterogeneous disease: more than 100 types of human cancer have been described. Th is phenotypical variability is what primarily determines the self-progression of neoplasia and its response to therapy. Variability in cell response has important clinical implications. It is now known that in a heterogeneous population, patients may display a multiplicity of genetic variations that respond diff erently to a given medical intervention. Th e same treatment could be of benefi t to some patients yet harmful to others. Human carcinogenesis is a dynamical process that depends on a large number of variables and is regulated at multiple spatial and temporal scales and whose behavior does not follow clearly predictable and repeatable pathways. Th is multiple scale causality not only recognizes multiple processes and controls acting at multiple scales. In other words, the observed phenomenon at each scale has structural and behavioral properties that do not exist at lower or higher organizational levels. To understand human cancer as a complex system we need to determine the type of data that needs to be collected at each level of organization, the boundary conditions to use when describing the disease, and the technologies and approaches best suited to reveal its underlying biological behavior. Th is “quantitative” way of thinking that unites physicians, biologists, mathematicians and epidemiologists, may help to discover new biomarkers with potential clinical value.