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The selective and in\u2010depth exploration of EV surface proteome (surfaceome) is highly compelling but remains technically challenging due to the unique physicochemical properties of surface proteins. These hurdles are further compounded by the inherent heterogeneity of EVs and the low abundance of surface targets in biofluids. Herein, we developed a chemical glycoproteomic strategy, EVscope (EV surface comprehensive one\u2010pot proteomic exploration), for comprehensively profiling the EV surfaceome. The hydrophilic and aromatic lipophilic group\u2010modified magnetic beads enable bias\u2010free EV isolation and in situ oxidation and labeling of cis\u2010diols on surface proteins. Subsequent on\u2010bead processes, including EV lysis, protein digestion, and surface glycopeptide enrichment, collectively maximize surfaceome coverage. Applied to urine samples from 368 individuals with prostate\u2010related diseases, EVscope identified 1,121 EV surface proteins, establishing the largest urine\u2010derived EV surfaceome dataset to date and identifying cathepsin L, integrin alpha 3, fibrinogen beta chain, and tetraspanin\u20101 as characteristic proteins with potential as noninvasive biomarkers for prostate cancer diagnosis and grading. In summary, this study establishes an innovative methodology for high\u2010resolution EV surfaceome analysis, facilitating noninvasive biomarker discovery and enabling direct detection in population\u2010scale screening.<\/jats:p>","DOI":"10.1002\/anie.202509399","type":"journal-article","created":{"date-parts":[[2025,9,23]],"date-time":"2025-09-23T13:14:13Z","timestamp":1758633253000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":15,"title":["A Chemical Glycoproteomic Approach Decrypts Urinary Extracellular Vesicle Surfaceome for Prostate Cancer Diagnosis and Grading"],"prefix":"10.1002","volume":"64","author":[{"given":"Yuhan","family":"Cai","sequence":"first","affiliation":[{"name":"Institute of Microphysiological Systems, State Key Laboratory of Digital Medical Engineering, School of Biological Science and Medical Engineering Southeast University  Nanjing Jiangsu 210096 P.R. 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