Tseropoulos, G. | Search bioRxiv

bioRxiv2024

PTEN Regulates Myofibroblast Activation in Valvular Interstitials Cells based on Subcellular Localization

Aortic valve stenosis (AVS) is characterized by altered mechanics of the valve leaflets, which disrupts blood flow through the aorta and can cause left ventricle hypotrophy. These changes in the valve tissue result in activation of resident valvular interstitial cells (VICs) into myofibroblasts, which have increased levels of SMA in their stress fibers. The persistence of VIC myofibroblast activation is a hallmark of AVS. In recent years, the tumor suppressor gene phosphatase and tensin homolog (PTEN) has emerged as an important player in the regulation of fibrosis in various tissues (e.g., lung, skin), which motivated us to investigate PTEN as a potential protective factor against matrix-induced myofibroblast activation in VICs. In aortic valve samples from humans, we found high levels of PTEN in healthy tissue and low levels of PTEN in diseased tissue. Then, using pharmacological inducers to treat VIC cultures, we observed PTEN overexpression prevented stiffness-induced myofibroblast activation, whereas genetic and pharmacological inhibition of PTEN further activated myofibroblasts. We also observed increased nuclear PTEN localization in VICs cultured on stiff matrices, and nuclear PTEN also correlated with smaller nuclei, altered expression of histones and a quiescent fibroblast phenotype. Together, these results suggest that PTEN not only suppresses VIC activation, but functions to promote quiescence, and could serve as a potential pharmacological target for the treatment of AVS.

cell biology↗

bioRxiv2024

Automated Prediction of Fibroblast Phenotypes Using Mathematical Descriptors of Cellular Features

Fibrosis is caused by pathological activation of resident fibroblasts to myofibroblasts that leads to aberrant tissue stiffening and diminished function of affected organs with limited pharmacological interventions. Despite the prevalence of myofibroblasts in fibrotic tissue, existing methods to grade fibroblast phenotypes are typically subjective and qualitative, yet important for screening of new therapeutics. Here, we develop mathematical descriptors of cell morphology and intracellular structures to identify quantitative and interpretable cell features that capture the fibroblast-to-myofibroblast phenotypic transition in immunostained images. We train and validate models on features extracted from over 2,500 primary heart valve interstitial cells (VICs) and test their predictive performance on VICs treated with the small molecule drug 5-azacytidine, which inhibited myofibroblast activation. Collectively, this work introduces an analytical framework that unveils key features associated with distinct fibroblast phenotypes via quantitative image analysis and is broadly applicable for high-throughput screening assays of candidate treatments for fibrotic diseases.

bioengineering↗