Single extracellular vesicle surface protein‐based blood assay identifies potential biomarkers for detection and screening of five cancers

癌症 液体活检 胞外囊泡 生物标志物 背景(考古学) 结直肠癌 曲线下面积 癌症生物标志物 医学 癌症研究 肿瘤科 生物 计算生物学 内科学 微泡 小RNA 基因 生物化学 古生物学
作者
Yuxin Min,Wenjiang Deng,Huangbo Yuan,Dongliang Zhu,Renjia Zhao,Pengyan Zhang,Jiangli Xue,Ziyu Yuan,Tiejun Zhang,Yanfeng Jiang,Kelin Xu,Di Wu,Y N Cai,Chen Suo,Xingdong Chen
出处
期刊:Molecular Oncology [Elsevier BV]
被引量:18
标识
DOI:10.1002/1878-0261.13586
摘要

Extracellular vesicles (EVs) and EV proteins are promising biomarkers for cancer liquid biopsy. Herein, we designed a case–control study involving 100 controls and 100 patients with esophageal, stomach, colorectal, liver, or lung cancer to identify common and type‐specific biomarkers of plasma‐derived EV surface proteins for the five cancers. EV surface proteins were profiled using a sequencing‐based proximity barcoding assay. In this study, five differentially expressed proteins (DEPs) and eight differentially expressed protein combinations (DEPCs) showed promising performance (area under curve, AUC > 0.900) in pan‐cancer identification [e.g., TENM2 (AUC = 0.982), CD36 (AUC = 0.974), and CD36‐ITGA1 (AUC = 0.971)]. Our classification model could properly discriminate between cancer patients and controls using DEPs (AUC = 0.981) or DEPCs (AUC = 0.965). When distinguishing one cancer from the other four, the accuracy of the classification model using DEPCs (85–92%) was higher than that using DEPs (78–84%). We validated the performance in an additional 14 cancer patients and 14 controls, and achieved an AUC value of 0.786 for DEPs and 0.622 for DEPCs, highlighting the necessity to recruit a larger cohort for further validation. When clustering EVs into subpopulations, we detected cluster‐specific proteins highly expressed in immune‐related tissues. In the context of colorectal cancer, we identified heterogeneous EV clusters enriched in cancer patients, correlating with tumor initiation and progression. These findings provide epidemiological and molecular evidence for the clinical application of EV proteins in cancer prediction, while also illuminating their functional roles in cancer physiopathology.
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