Efficient Cancer Biomarker Screening and Multicancer Detection Enabled by a Multidimensional Serum Proteomic Strategy

IF 6.7 1区 化学 Q1 CHEMISTRY, ANALYTICAL Analytical Chemistry Pub Date : 2024-11-21 DOI:10.1021/acs.analchem.4c03006
Anqi Hu, Jiayi Zhang, Lei Zhang, Zhenxin Wang, Jiawei Dai, Ling Lin, Guoquan Yan, Fenglin Shen, Huali Shen
{"title":"Efficient Cancer Biomarker Screening and Multicancer Detection Enabled by a Multidimensional Serum Proteomic Strategy","authors":"Anqi Hu, Jiayi Zhang, Lei Zhang, Zhenxin Wang, Jiawei Dai, Ling Lin, Guoquan Yan, Fenglin Shen, Huali Shen","doi":"10.1021/acs.analchem.4c03006","DOIUrl":null,"url":null,"abstract":"Biomarker discovery and application are paramount for the early diagnosis, treatment, and prognosis assessment of diseases. Novel proteomic strategies have been developed for high-efficiency biomarker screening. However, evaluating various strategies and applying them for the in-depth mining of biomarkers from blood need to be elucidated. Herein, we systematically evaluated the technical characteristics of three representative biomarker discovery strategies, including the most popular DIA proteomics, and two promising strategies targeting the cancer-secreted proteome or extracellular vesicle proteome, and integrated them into one multidimensional serum proteomic strategy. The results showed that the three strategies each have unique characteristics in terms of sensitivity, reproducibility, and protein coverage and are highly complementary in biomarker discovery. The integrated multidimensional serum proteomic strategy achieves deep and comprehensive coverage of the serum proteome, discovers more cancer markers, and helps achieve a more accurate multicancer (breast, lung, stomach, liver, and colorectum) diagnosis with 87.5% localization accuracy.","PeriodicalId":27,"journal":{"name":"Analytical Chemistry","volume":"23 1","pages":""},"PeriodicalIF":6.7000,"publicationDate":"2024-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Analytical Chemistry","FirstCategoryId":"92","ListUrlMain":"https://doi.org/10.1021/acs.analchem.4c03006","RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CHEMISTRY, ANALYTICAL","Score":null,"Total":0}
引用次数: 0

Abstract

Biomarker discovery and application are paramount for the early diagnosis, treatment, and prognosis assessment of diseases. Novel proteomic strategies have been developed for high-efficiency biomarker screening. However, evaluating various strategies and applying them for the in-depth mining of biomarkers from blood need to be elucidated. Herein, we systematically evaluated the technical characteristics of three representative biomarker discovery strategies, including the most popular DIA proteomics, and two promising strategies targeting the cancer-secreted proteome or extracellular vesicle proteome, and integrated them into one multidimensional serum proteomic strategy. The results showed that the three strategies each have unique characteristics in terms of sensitivity, reproducibility, and protein coverage and are highly complementary in biomarker discovery. The integrated multidimensional serum proteomic strategy achieves deep and comprehensive coverage of the serum proteome, discovers more cancer markers, and helps achieve a more accurate multicancer (breast, lung, stomach, liver, and colorectum) diagnosis with 87.5% localization accuracy.

Abstract Image

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
通过多维血清蛋白质组策略实现高效的癌症生物标记物筛查和多发性癌症检测
生物标志物的发现和应用对于疾病的早期诊断、治疗和预后评估至关重要。为高效筛选生物标志物,人们开发了新的蛋白质组学策略。然而,评估各种策略并将其应用于深入挖掘血液中的生物标记物还有待进一步阐明。在本文中,我们系统评估了三种代表性生物标志物发现策略的技术特点,包括最流行的DIA蛋白质组学,以及两种针对癌症分泌蛋白质组或细胞外囊泡蛋白质组的有前途的策略,并将它们整合为一种多维血清蛋白质组学策略。结果表明,这三种策略在灵敏度、重现性和蛋白质覆盖率方面各有特点,在生物标记物发现方面具有很强的互补性。整合后的多维血清蛋白质组策略实现了对血清蛋白质组的深度和全面覆盖,发现了更多癌症标志物,有助于实现更准确的多癌症(乳腺癌、肺癌、胃癌、肝癌和结直肠癌)诊断,定位准确率达87.5%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Analytical Chemistry
Analytical Chemistry 化学-分析化学
CiteScore
12.10
自引率
12.20%
发文量
1949
审稿时长
1.4 months
期刊介绍: Analytical Chemistry, a peer-reviewed research journal, focuses on disseminating new and original knowledge across all branches of analytical chemistry. Fundamental articles may explore general principles of chemical measurement science and need not directly address existing or potential analytical methodology. They can be entirely theoretical or report experimental results. Contributions may cover various phases of analytical operations, including sampling, bioanalysis, electrochemistry, mass spectrometry, microscale and nanoscale systems, environmental analysis, separations, spectroscopy, chemical reactions and selectivity, instrumentation, imaging, surface analysis, and data processing. Papers discussing known analytical methods should present a significant, original application of the method, a notable improvement, or results on an important analyte.
期刊最新文献
Issue Editorial Masthead Issue Publication Information Measurement of Covalent Bond Formation in Light-Curing Hydrogels Predicts Physical Stability under Flow An Electrochemical Pipette for the Study of Drug Metabolite Determination of the pKa and Concentration of NMR-Invisible Molecules and Sites Using NMR Spectroscopy
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1