Quercetin shows protective effects against hepatopulmonary syndrome (HPS), as demonstrated in a rat model. However, whether these effects involve pulmonary vascular angiogenesis in HPS remains unclear. Therefore, this study aimed to assess the effect of quercetin on pulmonary vascular angiogenesis and explore the underlying mechanisms. Male Sprague-Dawley rats weighing 200-250 g underwent sham operation or common bile duct ligation (CBDL). Two weeks after surgery, HIF-1α and NFκB levels were assessed in rat lung tissue by immunohistochemistry and western blot. Then, CBDL and sham-operated rats were further divided into 2 subgroups each to receive intraperitoneal administration of quercetin (50 mg/kg daily) or 0.2% Tween for two weeks: Sham (Sham+Tween; n=8), CBDL (CBDL+Tween; n=8), Q (Sham+quercetin; n=8), and CBDL+Q (CBDL+quercetin; n=8). After treatment, lung tissue specimens were assessed for protein (immunohistochemistry and western blot) and/or gene expression (quantitative real-time PCR) levels of relevant disease markers, including VEGFA, VEGFR2, Akt/p-Akt, HIF-1α, vWf, and IκB/p-IκB. Finally, arterial blood was analyzed for alveolar arterial oxygen pressure gradient (AaPO2). Two weeks after CBDL, HIF-1α expression in the lung decreased, but was gradually restored at four weeks. Treatment with quercetin did not significantly alter HIF-1α levels, but did reduce AaPO2 as well as lung tissue NF-κB activity, VEGFA gene and protein levels, Akt activity, and angiogenesis. Although hypoxia is an important feature in HPS, our findings suggest that HIF-1α was not the main cause for the VEGFA increase. Interestingly, quercetin inhibited pulmonary vascular angiogenesis in rats with HPS, with involvement of Akt/NF-κB and VEGFA/VEGFR-2 pathways.
Background:Pulmonary arterial hypertension with systemic sclerosis (SSc-PAH) is the main cause of death in patients with SSc. Early diagnosis and timely treatment are very important to reduce the mortality of patients with SSc-PAH1. At present, there are not many sensitive markers for the diagnosis of SSc-PAH. Therefore, it is necessary to mine more sensitive markers as more accurate and practical predictors, which is of great significance for the diagnosis and treatment of SSc-PAH.Objectives:To discover the differentially expressed genes (DEGs) and activated signaling pathways in SSc-PAH.Methods:Fifty-five samples (27 SSc-PAH v.s 28 normal controls) in GSE33463 chip data obtained from Gene Expression Omnibus (GEO) were included in this study. DEGs in SSc-PAH patients were screened by R, key pathways and hub genes were discoved by Metascape2, STRING3 and Cytoscape.Results:Total 431 genes with large differences were identified, including 238 up-regulated genes and 193 down-regulated genes, after standardizing the data (|logFC| > 1; P < 0.05). GO analysis showed that the upregulated genes were mainly involved in defense response to virus, hemoglobin complex, platelet alpha granule membrane and cytokine binding. The downregulated genes were mainly characterized by positive regulation of cell death, regulation of MAPK cascade, regulation of DNA-binding transcription factor activity and transcription factor AP-1 complex. Several significant enriched pathways obtained in the KEGG pathway analysis were Influenza A, Hepatitis C, IL-17 signaling pathway, MAPK signaling pathway, Toll-like receptor signaling pathway. Finally, after the selected differential genes were introduced into STRING online software, the data information of protein interaction network was derived, and 12 core genes in the network were identified, they were CXCL8, PPBP, LPAR1, FPR2, GNG11, CXCL10, LPAR5, JUN, C3AR1, CCR2, CCR3, IRF2.Conclusion:The genes and signal pathways related to SSc-PAH discovered by bioinformatics methods could not only provided new molecular markers for its diagnosis and treatment, but also provided new ideas for its related biological research.References:[1]Zheng JN, Li Y, Yan YM, et al. Identification and Validation of Key Genes Associated With Systemic Sclerosis-Related Pulmonary Hypertension. Front Genet 2020;11:816. doi: 10.3389/fgene.2020.00816 [published Online First: 2020/08/15].[2]Zhou Y, Zhou B, Pache L, et al. Metascape provides a biologist-oriented resource for the analysis of systems-level datasets. Nat Commun 2019;10(1):1523. doi: 10.1038/s41467-019-09234-6 [published Online First: 2019/04/05].[3]Szklarczyk D, Gable AL, Lyon D, et al. STRING v11: protein-protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets. Nucleic Acids Res 2019;47(D1):D607-D13. doi: 10.1093/nar/gky1131 [published Online First: 2018/11/27].Acknowledgements:This project was supported by National Science Foundation of China (82001740), Open Fund from the Key Laboratory of Cellular Physiology (Shanxi Medical University) (KLCP2019) and Innovation Plan for Postgraduate Education in Shanxi Province (2020BY078).Disclosure of Interests:None declared
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