Prima Dewi Sinawang, Mehmet O. Ozen, Shiqin Liu, En-Chi Hsu, Demir Akin, Emily Ding, Rosalie Nolley, James D. Brooks, Tanya Stoyanova, Utkan Demirci
{"title":"Extracellular Vesicles in Serum Carry Trop2 Protein as a Potential Molecular Indicator in Prostate Cancer","authors":"Prima Dewi Sinawang, Mehmet O. Ozen, Shiqin Liu, En-Chi Hsu, Demir Akin, Emily Ding, Rosalie Nolley, James D. Brooks, Tanya Stoyanova, Utkan Demirci","doi":"10.1002/jex2.70083","DOIUrl":null,"url":null,"abstract":"<p>Extracellular vesicles (EVs) are lipid nano-to-micro-sized vesicles increasingly studied for their role in intercellular communication and their potential as minimally invasive molecular indicators in various diseases. However, challenges remain in characterizing specific surface molecules on EVs due to cargo heterogeneity and the lack of convenient quantification methods. In this study, we show the isolation, characterization, detection, and quantification of Trop2-carrying EVs (EV-Trop2) in serum of prostate cancer patients. This work combines the unique advantages of our EV isolation method with ELISA to enable surface-protein-specific EV analysis directly from serum. This is, to our knowledge, the first demonstration to isolate and quantify EV-Trop2 from prostate cancer patient serum to study its expression patterns in relation to prostate cancer status. Analysis of serum samples from three patient groups: high-risk prostate cancer (<i>n</i> = 22), low-risk prostate cancer (<i>n</i> = 23), and cancer-free groups (<i>n</i> = 21), revealed significantly different levels of EV-Trop2 expression between the high-risk and low-risk patient groups (<i>p</i> = 0.0015) and between high-risk patient and cancer-free groups (<i>p</i> < 0.0001). Multivariate modeling further showed that EV-Trop2 contributed to improved classifier metrics across the three sample groups. These findings highlight a strategy for probing EV-associated surface targets and suggest broader applicability of this approach across multiple cancers.</p>","PeriodicalId":73747,"journal":{"name":"Journal of extracellular biology","volume":"4 9","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2025-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12456249/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of extracellular biology","FirstCategoryId":"1085","ListUrlMain":"https://isevjournals.onlinelibrary.wiley.com/doi/10.1002/jex2.70083","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Extracellular vesicles (EVs) are lipid nano-to-micro-sized vesicles increasingly studied for their role in intercellular communication and their potential as minimally invasive molecular indicators in various diseases. However, challenges remain in characterizing specific surface molecules on EVs due to cargo heterogeneity and the lack of convenient quantification methods. In this study, we show the isolation, characterization, detection, and quantification of Trop2-carrying EVs (EV-Trop2) in serum of prostate cancer patients. This work combines the unique advantages of our EV isolation method with ELISA to enable surface-protein-specific EV analysis directly from serum. This is, to our knowledge, the first demonstration to isolate and quantify EV-Trop2 from prostate cancer patient serum to study its expression patterns in relation to prostate cancer status. Analysis of serum samples from three patient groups: high-risk prostate cancer (n = 22), low-risk prostate cancer (n = 23), and cancer-free groups (n = 21), revealed significantly different levels of EV-Trop2 expression between the high-risk and low-risk patient groups (p = 0.0015) and between high-risk patient and cancer-free groups (p < 0.0001). Multivariate modeling further showed that EV-Trop2 contributed to improved classifier metrics across the three sample groups. These findings highlight a strategy for probing EV-associated surface targets and suggest broader applicability of this approach across multiple cancers.