July 8th- 19th, 2019 | IFOM, Milan - Italy
At a very basic level, Mechanobiology is a relatively recent discipline here to help to understand old, yet solid observations. For example, there are obvious benefits of regular physical exercise and the principle of "use it or lose it" in muscle maintenance is well established. But what is the biochemical benefit of physical activity and what are the physical and mechanical principles associated with disease? These processes have not been addressed before because the scientists did not have the tools to address cellular mechanical issues. However, in the last 10-15 years, largely because of technical advancements in other fields of research (like bioengineering, nanotechnology, computing, imaging…), we can now probe cell mechanical and biochemical functions even at the sub-molecular scale.
The molecular biology revolution of the last century has determined the composition of cells including the list of protein parts. In addition, through extensive sequence analysis the genetic and biochemical alterations in many diseases are known. However, we still have not cured many diseases in part because we don’t understand well how cell mechanics alters cell functions. For example, cancer is potentially and primarily a mechanical disease, since cancer cells grow in the wrong mechanical environment. Tumor microenvironment plays a critical role in cancer cell progression and survival. Because the tumor microenvironment is extremely complex, it is almost impossible to determine how individual parameter (such as matrix component, stiffness, topography, neighboring cells, confinement etc.) contributes to tumor progression in vivo. Only reductionist systems that model individual features can define this contribution while offering a degree of reproducibility and interpretability not achievable with in vivo system. We need to understand how ECM composition, stiffness and topography influences on the mechanisms of invasion.
In this course we will focus on using a brain cancer cell mousse model of Glioblatoma and learn how to fabricate and use reductionist system, in a combinatory manner the 3 parameters: Composition, Stiffness and Topography. We will also present and use technics to apply force to cells and measure the mechanical response of those cells.
