| Cerebral cavernous malformations (CCM) are the second most common class of cerebrovascular brain malformations affecting .1-.5% of the population. The disease is manifested in endothelial cells as lesions of thin, dilated, and leaky capillaries lacking normal blood vessel-stromal interactions. Lesions cause varied symptoms ranging from minor headaches to seizure and hemorrhagic stroke. CCMs can be incurred sporadically or inherited in an autosomal dominant manner from loss of function mutations in one of three genes, CCM1/Krit1, CCM2/OSM, or CCM3/PDCD10. These mutations affect the actin cytoskeleton due to deregulated RhoA/ROCK signaling, which increases stress fiber incidence, reduces endothelial cell barrier function, and decreases angiogenesis in vitro. We demonstrate through global kinome profiling that numerous kinases controlling the actin cytoskeleton are deregulated. Of these, we demonstrate that the RhoA/ROCK effector Lim kinase is overactive and phosphorylates and in activates the actin depolymerizing factor cofilin. Importantly, in vitro CCM phenotypes are rescued with knock down of Lim kinase in CCM protein deficient cells. We further show that a potential molecular mechanism governing the elevated RhoA levels and activity is through the E3 ubiquitin ligase Smurf1, which associates with CCM2 but not CCM1 or CCM3 and is responsible for ubiquitinating GTP bound RhoA. Current cell culture and animal models of CCM have given insight into CCM phenotypes, but the study of patient cells are needed to validate these models and to test potential therapeutics. Thus, we provide proof of principle studies demonstrating the utility of both endothelial progenitor derived endothelial cells and pluripotent stem cells in CCM disease modeling for the ultimate goal of producing a library of patient induced pluripotent stem cells. Overall, our findings elaborate on and provide insight into the complex molecular pathways involved in CCM phenotypes while also making the first steps towards in vitro patient specific CCM disease modeling. |
