Computational and Experimental Biology Group, Chronic Diseases Research Centre (CEDOC), NOVA Medical School, Faculdade de Ciências Médicas, Universidade NOVA de Lisboa, 1169-056 Lisboa, Portugal.
Urology Department, Centro Hospitalar e Universitário de Lisboa Central, 1169-050 Lisbon, Portugal.
Int J Mol Sci. 2021 Dec 19;22(24):13605. doi: 10.3390/ijms222413605.
Molecular diagnostics based on discovery research holds the promise of improving screening methods for prostate cancer (PCa). Furthermore, the congregated information prompts the question whether the urinary extracellular vesicles (uEV) proteome has been thoroughly explored, especially at the proteome level. In fact, most extracellular vesicles (EV) based biomarker studies have mainly targeted plasma or serum. Therefore, in this study, we aim to inquire about possible strategies for urinary biomarker discovery particularly focused on the proteome of urine EVs. Proteomics data deposited in the PRIDE archive were reanalyzed to target identifications of potential PCa markers. Network analysis of the markers proposed by different prostate cancer studies revealed moderate overlap. The recent throughput improvements in mass spectrometry together with the network analysis performed in this study, suggest that a larger standardized cohort may provide potential biomarkers that are able to fully characterize the heterogeneity of PCa. According to our analysis PCa studies based on urinary EV proteome presents higher protein coverage compared to plasma, plasma EV, and voided urine proteome. This together with a direct interaction of the prostate gland and urethra makes uEVs an attractive option for protein biomarker studies. In addition, urinary proteome based PCa studies must also evaluate samples from bladder and renal cancers to assess specificity for PCa.
基于发现研究的分子诊断有望改善前列腺癌 (PCa) 的筛查方法。此外，汇集的信息引发了这样一个问题，即尿细胞外囊泡 (uEV) 蛋白质组是否已经得到充分探索，尤其是在蛋白质组水平上。事实上，大多数基于细胞外囊泡 (EV) 的生物标志物研究主要针对血浆或血清。因此，在这项研究中，我们旨在探讨尿液生物标志物发现的可能策略，特别是侧重于尿 EV 蛋白质组。重新分析了 PRIDE 档案中存储的蛋白质组学数据，以确定潜在的 PCa 标志物的鉴定。不同前列腺癌研究提出的标志物的网络分析显示出中等程度的重叠。最近质谱的高通量改进以及本研究中进行的网络分析表明，更大的标准化队列可能提供能够充分描述 PCa 异质性的潜在生物标志物。根据我们的分析，与血浆、血浆 EV 和尿液蛋白质组相比，基于尿 EV 蛋白质组的 PCa 研究具有更高的蛋白质覆盖率。这与前列腺和尿道的直接相互作用使 uEV 成为蛋白质生物标志物研究的一个有吸引力的选择。此外，基于尿蛋白质组的 PCa 研究还必须评估来自膀胱癌和肾癌的样本，以评估对 PCa 的特异性。
