| 1. |
- Zhang, Yuan, et al.
(författare)
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Quantitative Proteomics of TRAMP Mice Combined with Bioinformatics Analysis Reveals That PDGF-B Regulatory Network Plays a Key Role in Prostate Cancer Progression
- 2018
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Ingår i: Journal of Proteome Research. - : American Chemical Society (ACS). - 1535-3893 .- 1535-3907. ; 17:7, s. 2401-2411
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Tidskriftsartikel (refereegranskat)abstract
- Transgenic adenocarcinoma of the mouse prostate (TRAMP) mice is a widely used transgenic animal model of prostate cancer (PCa). We performed a label-free quantitative proteomics analysis combined with a bioinformatics analysis on the entire prostate protein extraction from TRAMP mice and compared it with WT littermates. From 2379 total identified proteins, we presented a modest mice prostate reference proteome containing 919 proteins. 61 proteins presented a significant expression difference between two groups. The integrative bioinformatics analysis predicted the overexpression of platelet-derived growth factor B (PDGF-B) in tumor tissues and supports the hypothesis of the PDGF-B signaling network as a key upstream regulator in PCa progression. Furthermore, we demonstrated that Crenolanib, a novel PDGF receptor inhibitor, inhibited PCa cell proliferation in a dose-dependent manner. Finally, we revealed the importance of PDGF-B regulatory network in PCa progression, which will assist us in understanding the role and mechanisms of PDGF-B in promoting cancer growth and provide valuable knowledge for future research on anti-PDGF therapy.
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| 2. |
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| 3. |
- Liu, Zhengtao, et al.
(författare)
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Meta-Analysis of Adiponectin as a Biomarker for the Detection of Metabolic Syndrome
- 2018
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Ingår i: Frontiers in Physiology. - : Frontiers Media SA. - 1664-042X. ; 9:SEP
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Forskningsöversikt (refereegranskat)abstract
- Previous studies revealed the potential significance of circulating adiponectin levels with respect to the diagnosis and prediction of metabolic syndrome, but uncertainty has been noted across different cohorts. Systematic evaluation was performed for diagnostic accuracy and predictivity of adiponectin variation for metabolic syndrome in enrolled studies including 1,248 and 6,020 subjects, respectively. Adiponectin can identify metabolic syndrome with moderate accuracy (area under the curve = 0.81, 95% CI: 0.77-0.84). Heterogeneity analysis revealed that an increasing index of insulin resistance was independently associated with improving the performance of adiponectin upon metabolic syndrome diagnosis (ratio of diagnostic odds ratio = 3.89, 95% CI: 1.13-13.9). In addition, reductions in adiponectin were associated with increasing metabolic syndrome incidence in a linear dose-response manner. The risk of hypoadiponectinemia with metabolic syndrome was especially increased in men (P < 0.05). Further Mendelian randomization analysis identified that the amplified risk could be attributed to increased susceptibility (up to 7%) to insulin resistance compared with women. In conclusion, adiponectin measurement might have potential benefits in the detection of metabolic syndrome. Factors that affect insulin resistance should be considered for adjustment in future assessments.
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