化学
前列腺癌
细胞外小泡
泌尿系统
仿形(计算机编程)
癌症
内科学
细胞生物学
计算机科学
医学
生物
操作系统
作者
Yuping Fan,Yuting Zhang,Guiyuan Zhang,Le Ma,Ying Lv,Jingyao Li,Yuxia Luan,Yanxi Zhang,Ya‐Ting Chen,Huiying Ren,Wei Liu,Menghan Li,Yuxuan Wu,Saisai Chen,Bing Han,Qiu‐Yi Tang,Lu-Hua Chen,Anke Wesselius,Wei-Chao Su,Maurice P. Zeegers
标识
DOI:10.1021/acs.analchem.5c01320
摘要
Distinguishing between prostate cancer (PCa) and prostatitis poses a challenge in clinical settings, often resulting in overdiagnosis and treatment. Large extracellular vesicles (lEVs) extracted from urine samples of patients may contain information about prostate pathology and are, therefore, potential biopsies for early PCa detection. This research endeavors to create a urinary lEV-centric proteomic approach for early PCa identification. An integrated workflow utilizing functionalized magnetic beads, centrifugation, and filter membranes optimizes and expedites the analysis of urinary lEVs. To validate the stability and significance of lEV proteomic markers, the study employed multiple reaction monitoring (MRM) to assess the identified differentially expressed proteins in lEVs (lEV-DEPs) within a validation group for precise quantification. Furthermore, cell-line experiments were conducted to compare the proteomic profiles of lEVs, small EVs (sEVs), and cell membranes (CM). In total, 3549 urinary lEV proteins were captured, revealing 17 lEV-DEPs, with 12 confirmed through MRM. Notably, this isolation method reduced contaminants compared to centrifugation, facilitating the extraction of relatively large EVs. Pathway enrichment analysis of lEV-DEPs underscored their role in transitioning from inflammation to cancer, with specific post-translational modifications (PTMs) influencing PCa progression. A panel integrating four potential lEV-DEPs and prostate-specific antigen (PSA) exhibited a distinguished accuracy of 0.875, emphasizing the importance of lEV-DEPs over PSA in distinguishing PCa from prostatitis. Additionally, lEVs demonstrated significant protein content and pathway similarity with CM compared to sEVs. In conclusion, this investigation establishes a comprehensive protocol for isolating and characterizing urinary lEV proteomics, showcasing its efficacy in discriminating PCa from prostatitis. These results enhance diagnostic precision and offer fresh insights into the biological mechanisms underlying PCa, paving the way for improved diagnostic and therapeutic approaches.
科研通智能强力驱动
Strongly Powered by AbleSci AI