Quercetin ameliorates atherosclerosis by inhibiting inflammation of vascular endothelial cells via Piezo1 channels.

BACKGROUND: Natural antioxidants, exemplified by quercetin (Qu), have been shown to exert a protective effect against atherosclerosis (AS). However, the precise pharmacological mechanisms of Qu also remain elusive. PURPOSE: Here, we aimed to uncover the anti-atherosclerotic mechanisms of Qu. METHODS/STUDY DESIGNS: The inflammatory cytokine expression, activity of NLRP3 inflammasome and NF-κB, as well as mechanically activated currents and intracellular calcium levels were measured in endothelial cells (ECs). In addition, to explore whether Qu inhibited atherosclerotic plaque formation via Piezo1 channels, Ldlr-/- and Piezo1 endothelial-specific knockout mice (Piezo1△EC) were established. RESULTS: Our findings revealed that Qu significantly inhibited Yoda1-evoked calcium response in human umbilical vein endothelial cells (HUVECs), underscoring its role as a selective modulator of Piezo1 channels. Additionally, Qu effectively reduced mechanically activated currents in HUVECs. Moreover, Qu exhibited a substantial inhibitory effect on inflammatory cytokine expression and reduced the activity of NF-κB/NLRP3 in ECs exposed to ox-LDL or mechanical stretch, and these effects remained unaffected after Piezo1 genetic depletion. Furthermore, our study demonstrated that Qu substantially reduced the formation of atherosclerotic plaques, and this effect remained consistent even after Piezo1 genetic depletion. CONCLUSION: These results collectively provide compelling evidence that Qu ameliorates atherosclerosis by inhibiting the inflammatory response in ECs by targeting Piezo1 channels. In addition, Qu modulated atherosclerosis via inhibiting Piezo1 mediated NFκB/IL-1ß and NLRP3/caspase1/ IL-1ß axis to suppress the inflammation. Overall, this study reveals the potential mechanisms by which natural antioxidants, such as Qu, protect against atherosclerosis.

Serial analysis of the vascular endothelial transcriptome under static and shear stress conditions.

We have utilized serial analysis of gene expression (SAGE) to analyze the response of human coronary artery endothelial cells (HCAECs) to laminar shear stress (LSS). Primary cultures of HCAECs were exposed to 15 dyn/cm(2) LSS for 24 h in a parallel plate flow chamber and compared with identical same passage cells cultured under static conditions. The expression levels of a number of functional categories of genes were reduced by shear stress including those encoding proteins involved in cell proliferation (CDC10, CDC20, CDC23, CCND1, CCNB1), angiogenesis (ANGPTL4, CTGF, CYR61, ENG, EPAS1, EGFR, LGALS3, PGK1, and SPARC), extracellular matrix and cell-matrix adhesion (EFEMP1, LOXL2, P4HB, FBN1, FN1, ITGA5, ITGAE, ITGAV, ILK, LAMR1) and ATP synthesis (ATP5G3, ATP5J2, ATP5L, ATP5D). We also observed an increase in the LSS-responsive expression of genes encoding stress response proteins, including HMOX1, which is significant since HMOX1 may have anti-inflammatory and vasodilatory vascular effects. The autosomal dominant polycystic kidney disease (ADPKD) genes PKD1 and PKD2 were also elevated by LSS. ADPKD is associated with vascular malfunction, including the impairment of vasoreactive processes. To our knowledge, this is the first SAGE-based analysis of the shear stress-responsive endothelial cell transcriptome. These immortal data provide a resource for further analyses of the molecular mechanisms underlying the biological response to LSS and contribute to the expanding collection of publicly available SAGE data.

Comparative gene expression analysis of ovarian carcinoma and normal ovarian epithelium by serial analysis of gene expression.

Despite the poor prognosis of ovarian cancer and the importance of early diagnosis, there are no reliable noninvasive biomarkers for detection in the early stages of disease. Therefore, to identify novel ovarian cancer markers with potential utility in early-stage screening protocols, we have undertaken an unbiased and comprehensive analysis of gene expression in primary ovarian tumors and normal human ovarian surface epithelium (HOSE) using Serial Analysis of Gene Expression (SAGE). Specifically, we have generated SAGE libraries from three serous adenocarcinomas of the ovary and, using novel statistical tools, have compared these to SAGE data derived from two pools of normal HOSE. Significantly, in contrast to previous SAGE-based studies, our normal SAGE libraries are not derived from cultured cell lines. We have also compared our data with publicly available SAGE data obtained from primary tumors and "normal" HOSE-derived cell lines. We have thus identified several known and novel genes whose expressions are elevated in ovarian cancer. These include but are not limited to CLDN3, WFDC2, FOLR1, COL18A1, CCND1, and FLJ12988. Furthermore, we found marked differences in gene expression patterns in primary HOSE tissue compared with cultured HOSE. The use of HOSE tissue as a control for these experiments, along with hierarchical clustering analysis, identified several potentially novel biomarkers of ovarian cancer, including TACC3, CD9, GNAI2, AHCY, CCT3, and HMGA1. In summary, these data identify several genes whose elevated expressions have not been observed previously in ovarian cancer, confirm the validity of several existing markers, and provide a foundation for future studies in the understanding and management of this disease.