{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Wu Y"],"funding":["Natural Science Foundation of Beijing Municipality","National Natural Science Foundation of China","National Key Research and Development Program of China"],"pagination":["278"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC11974170"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["23(1)"],"pubmed_abstract":["<h4>Background</h4>Ovarian cancer (OC) is diagnosed at advanced stages, resulting in limited treatment options for patients. While early detection of OC has been investigated, the invasiveness of approaches, high sample requirements, or false-positive rates undermined its benefits. Here, we present a \"one-step\" high-throughput microfluidic platform for epithelial ovarian cancer (EOC) detection that integrates small extracellular vesicle (sEV) capture, in situ lysis, and protein biomarker detection.<h4>Results</h4>We identified 1,818 differentially expressed proteins (DEPs) through proteomic analysis of sEVs from patients' serum, combined with cell lines. Through multi-step screening of DEPs, we identified EOC biomarkers to customize the microfluidic platform. We used the microfluidic platf"],"journal":["Journal of nanobiotechnology"],"pubmed_title":["Small extracellular vesicle-based one-step high-throughput microfluidic platform for epithelial ovarian cancer diagnosis."],"pmcid":["PMC11974170"],"funding_grant_id":["Z220011","2023YFB3210400","T2225006"],"pubmed_authors":["Liu Z","Wang P","Guo Y","Han L","Wang C","Zhang Y","Guo H","Zhang X","Zhu X","Yue W","Wu Y","Li M"],"additional_accession":[]},"is_claimable":false,"name":"Small extracellular vesicle-based one-step high-throughput microfluidic platform for epithelial ovarian cancer diagnosis.","description":"<h4>Background</h4>Ovarian cancer (OC) is diagnosed at advanced stages, resulting in limited treatment options for patients. While early detection of OC has been investigated, the invasiveness of approaches, high sample requirements, or false-positive rates undermined its benefits. Here, we present a \"one-step\" high-throughput microfluidic platform for epithelial ovarian cancer (EOC) detection that integrates small extracellular vesicle (sEV) capture, in situ lysis, and protein biomarker detection.<h4>Results</h4>We identified 1,818 differentially expressed proteins (DEPs) through proteomic analysis of sEVs from patients' serum, combined with cell lines. Through multi-step screening of DEPs, we identified EOC biomarkers to customize the microfluidic platform. We used the microfluidic platf","dates":{"release":"2025-01-01T00:00:00Z","publication":"2025 Apr","modification":"2025-07-13T03:05:12.732Z","creation":"2025-07-13T03:05:12.732Z"},"accession":"S-EPMC11974170","cross_references":{"pubmed":["40189497"],"doi":["10.1186/s12951-025-03348-4"]}}