Davalieva Katarina, Kiprijanovska Sanja, Maleva Kostovska Ivana, Stavridis Sotir, Stankov Oliver, Komina Selim, Petrusevska Gordana, Polenakovic Momir
Research Centre for Genetic Engineering and Biotechnology "Georgi D Efremov", Macedonian Academy of Sciences and Arts, Skopje, Krste Misirkov 2, 1000 Skopje, Macedonia.
University Clinic for Urology, University Clinical Centre "Mother Theresa", 1000 Skopje, Macedonia.
Proteomes. 2017 Dec 29;6(1):1. doi: 10.3390/proteomes6010001.
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.
利用非侵入性诊断标志物检测前列腺癌(PCa)仍然是一项挑战。本研究的目的是鉴定出对早期PCa检测具有足够敏感性和特异性的尿液蛋白质。我们对PCa、良性前列腺增生、膀胱癌和肾癌患者的尿液进行了比较蛋白质组学分析,并结合生物信息学分析。二维差异凝胶电泳/质谱(2-D DIGE/MS)和无标记液相色谱-质谱/质谱(label-free LC-MS/MS)实验分别显示,丰度上有统计学显著差异的蛋白质有20种和85种。计算机分析表明,免疫细胞亚群的激活、结合和细胞运动是PCa中受影响最显著的细胞功能,同时急性期反应信号通路和肝脏X受体/视黄醇X受体(LXR/RXR)激活通路下调。最有前景的生物标志物有35种,与多个组相比,在PCa中发生了改变。其中一半已在正常或PCa组织中证实了其定位。20种蛋白质(CD14、AHSG、ENO1、ANXA1、CLU、COL6A1、C3、FGA、FGG、HPX、PTGDS、S100A9、LMAN2、ITIH4、ACTA2、GRN、HBB、PEBP1、CTSB、SPP1)是癌基因、肿瘤抑制因子和多功能蛋白质,已高度证实与PCa有关,而9种蛋白质(AZU1、IGHG1、RNASE2、PZP、REG1A、AMY1A、AMY2A、ACTG2、COL18A1)与不同癌症有关,但迄今为止与PCa无关,可能代表新发现。LC-MS/MS数据可通过ProteomeXchange获得,标识符为PXD008407。