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Formation of E-Cadherin/β-Catenin–based Adherens Junctions in Hepatocytes Requires Serine-10 in p27(Kip1)

The adhesion between epithelial cells at adherens junctions is regulated by signaling pathways that mediate the intracellular trafficking and assembly of its core components. Insight into the molecular mechanisms of this is necessary to understand how adherens junctions contribute to the functional organization of epithelial tissues. Here, we demonstrate that in human hepatic HepG2 cells, oncostatin M-p42/44 mitogen-activated protein kinase signaling stimulates the phosphorylation of p27(Kip1) on Ser-10 and promotes cell–cell adhesion. The overexpression of wild-type p27 or a phospho-mimetic p27S10D mutant in HepG2 cells induces a hyper-adhesive phenotype. In contrast, the overexpression of a nonphosphorylatable p27S10A mutant prevents the mobilization of E-cadherin and β-catenin at the cell surface, reduces basal cell–cell adhesion strength, and prevents the stimulatory effect of oncostatin M on cell–cell adhesion. As part of the underlying molecular mechanism, it is shown that in p27S10A-expressing cells β-catenin interacts with p27 and is prevented from interacting with E-cadherin. The intracellular retention of E-cadherin and β-catenin is also observed in hepatocytes from p27S10A knockin mice that express the p27S10A mutant instead of wild-type p27. Together, these data suggest that the formation of adherens junctions in hepatocytes requires Ser-10 in p27

Oncostatin M-stimulated Apical Plasma Membrane Biogenesis Requires p27(Kip1)-Regulated Cell Cycle Dynamics

Oncostatin M regulates membrane traffic and stimulates apicalization of the cell surface in hepatoma cells in a protein kinase A-dependent manner. Here, we show that oncostatin M enhances the expression of the cyclin-dependent kinase (cdk)2 inhibitor p27(Kip1), which inhibits G(1)-S phase progression. Forced G(1)-S-phase transition effectively renders presynchronized cells insensitive to the apicalization-stimulating effect of oncostatin M. G(1)-S-phase transition prevents oncostatin M-mediated recruitment of protein kinase A to the centrosomal region and precludes the oncostatin M-mediated activation of a protein kinase A-dependent transport route to the apical surface, which exits the subapical compartment (SAC). This transport route has previously been shown to be crucial for apical plasma membrane biogenesis. Together, our data indicate that oncostatin M-stimulated apicalization of the cell surface is critically dependent on the ability of oncostatin M to control p27(Kip1)/cdk2-mediated G(1)-S-phase progression and suggest that the regulation of apical plasma membrane-directed traffic from SAC is coupled to centrosome-associated signaling pathways

USP9x-mediated deubiquitination of EFA6 regulates de novo tight junction assembly

In epithelial cells, the tight junction (TJ) functions as a permeability barrier and is involved in cellular differentiation and proliferation. Although many TJ proteins have been characterized, little is known about the sequence of events and temporal regulation of TJ assembly in response to adhesion cues. We report here that the deubiquitinating enzyme USP9x has a critical function in TJ biogenesis by controlling the levels of the exchange factor for Arf6 (EFA6), a protein shown to facilitate TJ formation, during a narrow temporal window preceding the establishment of cell polarity. At steady state, EFA6 is constitutively ubiquitinated and turned over by the proteasome. However, at newly forming contacts, USP9x-mediated deubiquitination protects EFA6 from proteasomal degradation, leading to a transient increase in EFA6 levels. Consistent with this model, USP9x and EFA6 transiently co-localize at primordial epithelial junctions. Furthermore, knockdown of either EFA6 or USP9x impairs TJ biogenesis and EFA6 overexpression rescues TJ biogenesis in USP9x-knockdown cells. As the loss of cell polarity is a critical event in the metastatic spread of cancer, these findings may help to understand the pathology of human carcinomas

Comparing six cardiovascular risk prediction models in Haiti: implications for identifying high-risk individuals for primary prevention

Abstract Background Cardiovascular diseases (CVD) are rapidly increasing in low-middle income countries (LMICs). Accurate risk assessment is essential to reduce premature CVD by targeting primary prevention and risk factor treatment among high-risk groups. Available CVD risk prediction models are built on predominantly Caucasian risk profiles from high-income country populations, and have not been evaluated in LMIC populations. We aimed to compare six existing models for predicted 10-year risk of CVD and identify high-risk groups for targeted prevention and treatment in Haiti. Methods We used cross-sectional data within the Haiti CVD Cohort Study, including 1345 adults ≥ 40 years without known history of CVD and with complete data. Six CVD risk prediction models were compared: pooled cohort equations (PCE), adjusted PCE with updated cohorts, Framingham CVD Lipids, Framingham CVD Body Mass Index (BMI), WHO Lipids, and WHO BMI. Risk factors were measured during clinical exams. Primary outcome was continuous and categorical predicted 10-year CVD risk. Secondary outcome was statin eligibility. Results Sixty percent were female, 66.8% lived on a daily income of ≤ 1 USD, 52.9% had hypertension, 14.9% had hypercholesterolemia, 7.8% had diabetes mellitus, 4.0% were current smokers, and 2.5% had HIV. Predicted 10-year CVD risk ranged from 3.6% in adjusted PCE (IQR 1.7–8.2) to 9.6% in Framingham-BMI (IQR 4.9–18.0), and Spearman rank correlation coefficients ranged from 0.86 to 0.98. The percent of the cohort categorized as high risk using model specific thresholds ranged from 1.8% using the WHO-BMI model to 41.4% in the PCE model (χ2 = 1416, p value < 0.001). Statin eligibility also varied widely. Conclusions In the Haiti CVD Cohort, there was substantial variation in the proportion identified as high-risk and statin eligible using existing models, leading to very different treatment recommendations and public health implications depending on which prediction model is chosen. There is a need to design and validate CVD risk prediction tools for low-middle income countries that include locally relevant risk factors. Trial registration clinicaltrials.gov NCT03892265 .http://deepblue.lib.umich.edu/bitstream/2027.42/173513/1/12889_2022_Article_12963.pd