(91e) Proteomics-Informed Signal Transduction Modeling of Valve Interstitial Cell Activation

Calcific aortic valve disease (CAVD) is the most common valvular heart disease in the Western world, resulting in fibrosis and calcification of the aortic valve that can only be treated surgically. The resident valve interstitial cells are tissue-specific fibroblasts under normal conditions but become activated to myofibroblasts early in CAVD development. These myofibroblasts secrete both new extracellular matrix components and proteases that degrade the extracellular matrix, thereby remodeling the structure of the aortic valve. Targeting this myofibroblast transition with pharmaceutical therapies is expected to reverse or halt CAVD progression; however, drug targets for CAVD remain elusive.

One primary driver of the myofibroblast transition in CAVD is transforming growth factor beta (TGFβ). TGFβ can be released from the extracellular matrix in response to matrix degradation and mechanical deformation and is also newly synthesized by myofibroblasts in response to a variety of external stimuli. The relevant signaling network is comprised of both canonical and non-canonical components and many uncertainties remain. Therefore, we have begun to model the signal transduction network stemming from TGFβ to better understand the effects of this key stimulus on the myofibroblast transition in valve interstitial cells.

Models of signal transduction networks are classically informed by a priori deciding which proteins and post-translational modifications are important and then designing experiments to collect these selected measurements. This approach usually greatly limits the number of experiments that can be conducted and limits the size of the model being developed. However, newer proteomics strategies can measure tens of thousands of different peptides, including those with post-translational modifications, from thousands of proteins in a single experiment without the requirement of specifying specific proteins or modifications beforehand. Therefore, this paper uses a label-free data independent acquisition proteomics strategy to collect data from canonical and non-canonical TGFβ signaling to inform a mathematical model of the myofibroblast transition in valve interstitial cells.