Faculty of Medicine

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    Item type:Publication,
    Comparative Proteomics Analysis of Urine Reveals Down-Regulation of Acute Phase Response Signaling and LXR/RXR Activation Pathways in Prostate Cancer
    (MDPI AG, 2017-12-29)
    Davalieva, Katarina
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    Kiprijanovska, Sanja
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    Maleva Kostovska, Ivana
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    Detecting prostate cancer (PCa) using non-invasive diagnostic markers still remains a challenge. The aim of this study was the identification of urine proteins that are sufficiently sensitive and specific to detect PCa in the early stages. Comparative proteomics profiling of urine from patients with PCa, benign prostate hyperplasia, bladder cancer, and renal cancer, coupled with bioinformatics analysis, were performed. Statistically significant difference in abundance showed 20 and 85 proteins in the 2-D DIGE/MS and label-free LC-MS/MS experiments, respectively. In silico analysis indicated activation, binding, and cell movement of subset of immune cells as the top affected cellular functions in PCa, together with the down-regulation of Acute Phase Response Signaling and Liver X Receptor/ Retinoid X Receptor (LXR/RXR) activation pathways. The most promising biomarkers were 35, altered in PCa when compared to more than one group. Half of these have confirmed localization in normal or PCa tissues. Twenty proteins (CD14, AHSG, ENO1, ANXA1, CLU, COL6A1, C3, FGA, FGG, HPX, PTGDS, S100A9, LMAN2, ITIH4, ACTA2, GRN, HBB, PEBP1, CTSB, SPP1) are oncogenes, tumor suppressors, and multifunctional proteins with highly confirmed involvement in PCa, while 9 (AZU1, IGHG1, RNASE2, PZP, REG1A, AMY1A, AMY2A, ACTG2, COL18A1) have been associated with different cancers, but not with PCa so far, and may represent novel findings. LC-MS/MS data are available via ProteomeXchange with identifier PXD008407.
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    Item type:Publication,
    Rosuvastatin effects on the HDL proteome in hyperlipidemic patients
    (SCIENDO, 2023-09)
    Vavlukis, Ana
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    Davalieva, Katarina
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    The advancements in proteomics have provided a better understanding of the functionality of apolipoproteins and lipoprotein-associated proteins, with the HDL lipoprotein fraction being the most studied. The focus of this study was to evaluate the HDL proteome in dyslipidemic subjects without an established cardiovascular disease, as well as to test whether rosuvastatin treatment alters the HDL proteome. Patients with primary hypercholesterolemia or mixed dyslipidemia were assigned to 20 mg/day rosuvastatin and blood samples were drawn at study entry and after 12 weeks of treatment. A label-free LC-MS/MS protein profiling was conducted, coupled with bioinformatics analysis. Sixty-nine HDL proteins were identified, belonging to four main biological function clusters: lipid transport and metabolism; platelet activation, degranulation, and aggregation, wound response and wound healing; immune response; inflammatory and acute phase response. Five HDL proteins showed statistically significant differences in the abundance (Anova ≤ 0.05), before and after rosuvastatin treatment. Platelet factor 4 variant (PF4V1), Pregnancy-specific beta-1-glycoprotein 2 (PSG2), Profilin-1 (PFN1) and Keratin type II cytoskeletal 2 epidermal (KRT2) showed decreased expressions, while Integrin alpha-IIb (ITGA2B) showed an increased expression after treatment with rosuvastatin. The ELISA validation of PFN1 segregated the subjects into responders and non-responders, as PFN1 levels after rosuvastatin were shown to mostly depend on the subjects' inflammatory phenotype. Findings from this study introduce novel insights into the HDL proteome and statin pleiotropism.
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    Item type:Publication,
    Potential Role of Seven Proteomics Tissue Biomarkers for Diagnosis and Prognosis of Prostate Cancer in Urine
    (MDPI AG, 2022-12-16)
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    Rusevski, Aleksandar
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    Popov, Zivko
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    <jats:p>As the currently available tests for the clinical management of prostate cancer (PCa) are still far from providing precise diagnosis and risk stratification, the identification of new molecular marker(s) remains a pertinent clinical need. Candidate PCa biomarkers from the published proteomic comparative studies of prostate tissue (2002–2020) were collected and systematically evaluated. AZGP1, MDH2, FABP5, ENO1, GSTP1, GSTM2, and EZR were chosen for further evaluation in the urine of 85 PCa patients and controls using ELISA. Statistically significant differences in protein levels between PCa and BPH showed FABP5 (p = 0.019) and ENO1 (p = 0.015). A biomarker panel based on the combination of FABP5, ENO1, and PSA provided the highest accuracy (AUC = 0.795) for PCa detection. The combination of FABP5, EZR, AZGP1, and MDH2 showed AUC = 0.889 in PCa prognosis, with 85.29% of the samples correctly classified into low and high Gleason score (GS) groups. The addition of PSA to the panel slightly increased the AUC to 0.914. AZGP1, FABP5, and EZR showed significant correlation with GS, stage, and percentage of positive biopsy cores. Although validation using larger patient cohorts will be necessary to establish the credibility of the proposed biomarker panels in a clinical context, this study opens a way for the further testing of more high-quality proteomics biomarkers, which could ultimately add value to the clinical management of PCa.</jats:p>