@article{OttenKnoxBouldayetal.2018, author = {Otten, Cecile and Knox, Jessica and Boulday, Gwenola and Eymery, Mathias and Haniszewski, Marta and Neuenschwander, Martin and Radetzki, Silke and Vogt, Ingo and Haehn, Kristina and De Luca, Coralie and Cardoso, Cecile and Hamad, Sabri and Igual Gil, Carla and Roy, Peter and Albiges-Rizo, Corinne and Faurobert, Eva and von Kries, Jens P. and Campillos, Monica and Tournier-Lasserve, Elisabeth and Derry, William Brent and Abdelilah-Seyfried, Salim}, title = {Systematic pharmacological screens uncover novel pathways involved in cerebral cavernous malformations}, series = {EMBO molecular medicine}, volume = {10}, journal = {EMBO molecular medicine}, number = {10}, publisher = {Wiley}, address = {Hoboken}, issn = {1757-4676}, doi = {10.15252/emmm.201809155}, pages = {17}, year = {2018}, abstract = {Cerebral cavernous malformations (CCMs) are vascular lesions in the central nervous system causing strokes and seizures which currently can only be treated through neurosurgery. The disease arises through changes in the regulatory networks of endothelial cells that must be comprehensively understood to develop alternative, non-invasive pharmacological therapies. Here, we present the results of several unbiased small-molecule suppression screens in which we applied a total of 5,268 unique substances to CCM mutant worm, zebrafish, mouse, or human endothelial cells. We used a systems biology-based target prediction tool to integrate the results with the whole-transcriptome profile of zebrafish CCM2 mutants, revealing signaling pathways relevant to the disease and potential targets for small-molecule-based therapies. We found indirubin-3-monoxime to alleviate the lesion burden in murine preclinical models of CCM2 and CCM3 and suppress the loss-of-CCM phenotypes in human endothelial cells. Our multi-organism-based approach reveals new components of the CCM regulatory network and foreshadows novel small-molecule-based therapeutic applications for suppressing this devastating disease in patients.}, language = {en} }