{"title":"Identification of Colorectal Cancer-Associated Protein Signatures in Small Extracellular Vesicles Based on Proteomics","authors":"Xiaoqing Ding*, , , Xuan Huang, , , Junfeng Jiang, , , Shuang Han, , , Yanjun Zhou, , , Zhonghu Bai*, , and , Fang Gong*, ","doi":"10.1021/acs.jproteome.5c00509","DOIUrl":null,"url":null,"abstract":"<p >The clinical management of colorectal cancer (CRC) urgently requires more accurate serum protein biomarkers. While conventional proteomic approaches are hindered by the high abundance of resident blood proteins, this study utilized a highly sensitive four-dimensional label-free quantitative (4D-LFQ) proteomic strategy to analyze the protein cargo of small extracellular vesicles (sEVs). We purified sEVs via ultracentrifugation from pooled serum samples of 76 CRC patients and 40 healthy controls, alongside seven paired CRC tumors and adjacent normal tissues. A total of 1187 high-confidence proteins were identified in serum sEVs using 4D-LFQ analysis. Validation in an independent cohort using four-dimensional parallel reaction monitoring (4D-PRM) confirmed the significant elevation of six candidate proteins (ANXA11, ANXA5, CALR, KPNB1, OIT3, and OLFM4) in CRC sEVs. These candidates exhibited strong diagnostic performance (AUCs 0.769 – 0.869). Crucially, in early-stage CRC, the sEV candidate proteins were significantly elevated compared to controls (<i>p</i> < 0.001), whereas conventional markers CEA and CA19-9 failed to discriminate (<i>p</i> > 0.05). A logistic regression model combining the five available sEV proteins and two conventional markers demonstrated 78.26% sensitivity and 96.67% specificity for early detection (AUC = 0.961). Our findings nominate these sEV protein signatures as promising noninvasive biomarkers for CRC diagnosis.</p>","PeriodicalId":48,"journal":{"name":"Journal of Proteome Research","volume":"24 10","pages":"5127–5138"},"PeriodicalIF":3.6000,"publicationDate":"2025-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Proteome Research","FirstCategoryId":"99","ListUrlMain":"https://pubs.acs.org/doi/10.1021/acs.jproteome.5c00509","RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BIOCHEMICAL RESEARCH METHODS","Score":null,"Total":0}
引用次数: 0
Abstract
The clinical management of colorectal cancer (CRC) urgently requires more accurate serum protein biomarkers. While conventional proteomic approaches are hindered by the high abundance of resident blood proteins, this study utilized a highly sensitive four-dimensional label-free quantitative (4D-LFQ) proteomic strategy to analyze the protein cargo of small extracellular vesicles (sEVs). We purified sEVs via ultracentrifugation from pooled serum samples of 76 CRC patients and 40 healthy controls, alongside seven paired CRC tumors and adjacent normal tissues. A total of 1187 high-confidence proteins were identified in serum sEVs using 4D-LFQ analysis. Validation in an independent cohort using four-dimensional parallel reaction monitoring (4D-PRM) confirmed the significant elevation of six candidate proteins (ANXA11, ANXA5, CALR, KPNB1, OIT3, and OLFM4) in CRC sEVs. These candidates exhibited strong diagnostic performance (AUCs 0.769 – 0.869). Crucially, in early-stage CRC, the sEV candidate proteins were significantly elevated compared to controls (p < 0.001), whereas conventional markers CEA and CA19-9 failed to discriminate (p > 0.05). A logistic regression model combining the five available sEV proteins and two conventional markers demonstrated 78.26% sensitivity and 96.67% specificity for early detection (AUC = 0.961). Our findings nominate these sEV protein signatures as promising noninvasive biomarkers for CRC diagnosis.
期刊介绍:
Journal of Proteome Research publishes content encompassing all aspects of global protein analysis and function, including the dynamic aspects of genomics, spatio-temporal proteomics, metabonomics and metabolomics, clinical and agricultural proteomics, as well as advances in methodology including bioinformatics. The theme and emphasis is on a multidisciplinary approach to the life sciences through the synergy between the different types of "omics".