Modelling Rubinstein-Taybi Syndrome: Functionalizing a rare, monogenic disease to address the therapeutic potential of stress-response pathways in neuronal disorders – RUBINeuroStress

Neurodevelopmental disorders (NDDs) affect ~10% of children and are a source of lifelong handicap. NDDs result from the failure of the brain to develop and mature properly and are characterized by high variability of the clinical picture, even when a genetic cause has been identified, which has hampered the development of therapeutic strategies. A great need exists in the field for a shift of paradigm to identify and develop new treatments by bridging the gap between fundamental and clinical research. Recent research progress has shown that, despite their heterogeneity, NDDs share common pathomechanisms characterized, in particular, by abnormal activity of stress-responsive pathways that are able to shape multiple aspects of NDD neurodevelopmental defects. Based on this new conceptual frame, the overarching aim of this project is to develop and validate a patient-based disease model of the rare monogenic Rubinstein-Taybi Syndrome (RSTS), as a paradigm of NDD pathomechanisms, to foster therapy development. The project builds on the use of innovative technologies and approaches, easing the deciphering of critical mechanisms involved in this rare genetic disease. We have unraveled a common reading key of NDDs, of which RSTS is highly representative: the deregulation of the stress-responsive HSF pathway. This pathway represents a unique entry point acting as a hub between stress, neurodevelopment and adult brain integrity. We will investigate the remarkable integrative contribution of the HSF pathway in the sculpting of NDD phenotypes and, modulate this pathway pharmacologically, in order to damper these multifaceted neurodevelopmental defects and, eventually, ameliorate patient outcome. By combining patient-based iPSC generation and genome editing to the production of 2- and 3-dimensional cell models (cerebral organoids), we will delineate the HSF contribution to RSTS, using the functional readouts of neuronal integrity and of cell-to-cell variability (as a first readout of NDD phenotypic variability) that we will identify by: 1) cutting-edge genome-wide single-cell approaches; 2) disruptive phenotyping technologies, based on novel high throughput/high content imaging and implementation of artificial neuronal networks and deep learning approaches. This project, aiming at building a box of clinical compounds with known or anticipated biological activity, constitutes a pioneering pharmacological study and obligatory step for future drug discovery campaigns.