Predicting cardiovascular tissue regeneration
Cardiovascular disease remains one of the world’s leading causes of death, driving an urgent need for therapies that restore damaged tissues rather than simply manage symptoms. Although engineered blood vessel and heart valve replacements offer a promising approach, replicating the complex structure and function of native tissues has proven challenging.
Understanding tissue regeneration
To address this limitation, the ERC-funded MechanoSignaling project investigated how mechanical forces interact with cellular communication pathways to guide tissue regeneration. The project focused on the Notch signalling pathway(opens in new window), a critical regulator of cardiovascular development and tissue remodelling. Notch signalling controls how cells communicate and organise themselves, influencing key biological processes. Researchers hypothesised that understanding how mechanical forces influence Notch signalling could provide a powerful tool for controlling regeneration in engineered tissues. Cardiovascular cells are continuously exposed to haemodynamic forces(opens in new window) generated by blood pressure and flow, making the interaction between biomechanics and signalling pathways particularly important. “Mechanical factors strongly influence how cells behave inside cardiovascular tissues. Understanding how these forces regulate Notch signalling will help us design regenerative therapies,” explains principal investigator Sandra Loerakker.
Predictive models of cardiovascular adaptation
Researchers combined laboratory experiments with advanced computational modelling(opens in new window). Cells were subjected to varying degrees of mechanical deformation to determine how force changes affect signalling dynamics, cellular organisation and protein production. The team also manipulated Notch activity directly to establish causal relationships between signalling and tissue behaviour. Alongside experimental work, the consortium developed computational frameworks capable of simulating Notch interactions between cells and linking these processes to tissue mechanics. One of the first models(opens in new window) created described how Notch signalling operates across interacting cells. Simulations revealed that cell organisation may have limited influence on signalling outcomes when specific proteins dominate communication dynamics. These signalling models were subsequently combined to biomechanical models of blood vessels to investigate how blood pressure regulates cellular signalling and, in turn, drive tissue adaptation. Using this framework, the project demonstrated how conditions such as hypertension can alter Notch signalling and may contribute to structural adaptation of blood vessels. Next, the project delivered the first multiscale computational models linking subcellular Notch interactions(opens in new window) to tissue-scale cardiovascular adaptation. These models provide a new framework for understanding how local cellular events drive the emergence of functional tissue structures. The team also developed computational models for tissue-engineered heart valves, allowing them to estimate local mechanical stresses and analyse how these cues influence tissue formation. “Computational modelling allows us to analyse mechanisms that are extremely difficult to study experimentally and helps identify the most promising regenerative strategies far more efficiently,” highlights Loerakker.
Accelerating the future of regenerative medicine
By revealing how mechanical forces and cellular signalling cooperate during regeneration, MechanoSignaling established the scientific basis for next-generation engineered cardiovascular therapies. Researchers now aim to investigate how synthetic biomaterials transform into living tissues. They specifically aim to integrate immune cell behaviour into future models, reflecting its critical role in biomaterial-driven regeneration. The project also highlights the growing importance of predictive computational models in regenerative medicine, helping identify robust therapeutic strategies and support patient stratification.