Dutch Research Council rewards three Maastricht research proposals

Bert Smeets (FHML, MHeNs)

LAMA2 Muscular Dystrophy (LAMA2-MD) is a rare, incurable, hereditary disorder that is usually caused by the complete absence of the LAMA2 protein, which is responsible for anchoring muscle fibers to the surrounding connective tissue. As a result, muscles become progressively weaker and less powerful. LAMA2 patients are typically unable to walk independently and suffer from severe respiratory problems. A new treatment, being investigated in this project, involves administering LAMA2 mRNA via cultured stem cells to the affected muscles. This mRNA is then translated into the missing LAMA2 protein within the muscle fibers. 

A major challenge is that mRNA is inherently unstable, while sustained production of the LAMA2 protein is required. To address this, the project encapsulates the mRNA in nanoparticles, protecting it from degradation. These nanoparticles gradually release the mRNA into the muscle fibers, enabling long-term production of the LAMA2 protein. If successful, this method could also be applied to other muscular diseases caused by the absence of an essential protein.

Dylan Mostert (FHML, CARIM)

With the Open Science XS grant, I will study how the developmental stage of heart muscle cells grown from human stem cells affects their ability to connect with their environment and respond to mechanical stimulation. Since heart cells naturally exist in a constantly moving environment due to the beating of the heart, understanding how they react to mechanical stimulation is crucial. By using both flat (2D) and three-dimensional (3D) lab-grown models of the human heart, my goal is to improve our understanding of how heart cells sense and respond to mechanical signals. This research could help us find new ways to repair damaged heart tissue in the future. 

Monica Savioli (FSE, DACS)

Several technologies are available for taking “pictures” of gene expression in a sample of cells under a biological condition of interest, for example cancer. However, because different groups of genes lead to different outcomes in different patients, identifying relevant genes is not trivial. Cooperative game theory, dealing with players and coalitions, will allow us to consider the contribution of single genes as well as their interactions and to rank the genes based on their importance for the prognosis. We will compare our results to those obtained using other methods (penalized regression models) and validate them using publicly available pan-cancer datasets.