Magnetic-Nanowaxberry-Based Simultaneous Detection of Exosome and Exosomal Proteins for the Intelligent Diagnosis of Cancer

外体 化学 适体 微泡 上皮细胞粘附分子 癌症生物标志物 癌症 表皮生长因子受体 纳米技术 分子生物学 生物化学 受体 细胞 小RNA 基因 生物 材料科学 遗传学
作者
Lei Ding,Lie Liu,Leiliang He,Clement Yaw Effah,Ruirui Yang,D. Ouyang,Ningge Jian,Xia Liu,Yongjun Wu,Lingbo Qu
出处
期刊:Analytical Chemistry [American Chemical Society]
卷期号:93 (45): 15200-15208 被引量:17
标识
DOI:10.1021/acs.analchem.1c03957
摘要

Exosome concentration and exosomal proteins are regarded as promising cancer biomarkers. Herein, a waxberry-like magnetic bead (magnetic-nanowaxberry) which has huge surface area and strong affinity was synthesized to couple with aptamer for exosome capture and recovery. Subsequently, we developed a fluorescent assay for the sensitive, accurate, and simultaneous quantification of exosome and cancer-related exosomal proteins [epidermal growth factor receptor (EGFR) and epithelial cell adhesion molecule (EpCAM)] by using triple-colored probes to recognize EGFR and EpCAM or spontaneously anchor to the lipid bilayer. In this design, the interference of soluble proteins can be avoided due to the dual recognition strategy. Moreover, the lipid-based quantification of exosome concentration can improve the accuracy. Besides, the simultaneous detection mode can save samples and simplify the operation steps. Consequently, the assay shows high sensitivity (the limits of detection are down to 0.96 pg/mL for EGFR, 0.19 pg/mL for EpCAM, and 2.4 × 104 particles/μL for exosome), high specificity, and satisfactory accuracy. More importantly, this technique is successfully used to analyze exosomes in plasma to distinguish cancer patients from healthy individuals. To improve the diagnostic efficacy, the deep learning was used to exploit the potential pattern hidden in data obtained by the proposed method. Also, the accuracy for the intelligent diagnosis of cancer can achieve 96.0%. This study provides a new avenue for developing new biosensors for exosome analysis and intelligent disease diagnosis.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
大幅提高文件上传限制,最高150M (2024-4-1)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
Jing发布了新的文献求助10
1秒前
wwq完成签到 ,获得积分10
2秒前
飘逸小笼包完成签到,获得积分20
3秒前
3秒前
提拉米草发布了新的文献求助10
4秒前
靓仔完成签到,获得积分10
4秒前
天峰完成签到,获得积分10
4秒前
YYT发布了新的文献求助10
5秒前
5秒前
汉堡包应助battery采纳,获得10
6秒前
6秒前
樱桃发布了新的文献求助10
8秒前
Yang发布了新的文献求助30
9秒前
11秒前
11秒前
晨晨发布了新的文献求助10
11秒前
Ld发布了新的文献求助10
11秒前
12秒前
高贵的乐儿完成签到,获得积分10
12秒前
13秒前
彭于晏应助研友_Lw4Ngn采纳,获得10
15秒前
丘比特应助铁盐君采纳,获得10
16秒前
Ryan完成签到,获得积分10
17秒前
18秒前
FashionBoy应助谨慎的咖啡豆采纳,获得10
18秒前
张泽崇应助谨慎的咖啡豆采纳,获得10
18秒前
18秒前
JamesPei应助大地鼠妈妈采纳,获得10
18秒前
脑洞疼应助谨慎的咖啡豆采纳,获得10
18秒前
18秒前
18秒前
Jasper应助谨慎的咖啡豆采纳,获得10
18秒前
Lucas应助谨慎的咖啡豆采纳,获得10
18秒前
bkagyin应助谨慎的咖啡豆采纳,获得10
18秒前
19秒前
SOLOMON举报Pink西求助涉嫌违规
20秒前
研友_X84O4Z发布了新的文献求助10
20秒前
搞怪的白竹完成签到,获得积分10
26秒前
ALITTLE完成签到,获得积分10
27秒前
yuuuue完成签到 ,获得积分10
28秒前
高分求助中
Teaching Social and Emotional Learning in Physical Education 900
Gymnastik für die Jugend 600
Chinese-English Translation Lexicon Version 3.0 500
Electronic Structure Calculations and Structure-Property Relationships on Aromatic Nitro Compounds 500
マンネンタケ科植物由来メロテルペノイド類の網羅的全合成/Collective Synthesis of Meroterpenoids Derived from Ganoderma Family 500
[Lambert-Eaton syndrome without calcium channel autoantibodies] 440
Plesiosaur extinction cycles; events that mark the beginning, middle and end of the Cretaceous 400
热门求助领域 (近24小时)
化学 材料科学 医学 生物 有机化学 工程类 生物化学 纳米技术 物理 内科学 计算机科学 化学工程 复合材料 遗传学 基因 物理化学 催化作用 电极 光电子学 量子力学
热门帖子
关注 科研通微信公众号,转发送积分 2385479
求助须知:如何正确求助?哪些是违规求助? 2092049
关于积分的说明 5262501
捐赠科研通 1819117
什么是DOI,文献DOI怎么找? 907282
版权声明 559134
科研通“疑难数据库(出版商)”最低求助积分说明 484620