尿液蛋白质组综合分析确定了膀胱癌诊断和复发监测生物标记物

IF 3.8 2区 生物学 Q1 BIOCHEMICAL RESEARCH METHODS Journal of Proteome Research Pub Date : 2024-05-24 DOI:10.1021/acs.jproteome.4c00199
Qi Chang, Yongqiang Chen, Jianjian Yin, Tao Wang, Yuanheng Dai, Zixin Wu, Yufeng Guo, Lingang Wang, Yufen Zhao, Hang Yuan*, Dongkui Song* and Lirong Zhang*, 
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摘要

膀胱癌(BCa)是泌尿系统最主要的恶性肿瘤。在此,我们初步建立了一个全面的尿液蛋白质组特征,用于膀胱癌的无创诊断和复发监测。研究人员收集了 279 例病例(63 例原发性膀胱癌、87 例非肿瘤对照(NT)、73 例复发膀胱癌(BCR)和 56 例非复发膀胱癌(BCNR)),以筛选尿蛋白生物标志物。在两个发现集中,分别通过 DDA 和所有理论质谱的顺序窗口获取(SWATH-MS)分析对 4761 和 3668 个蛋白质进行了鉴定和定量。通过多反应监测(MRM)对两个独立的组合集中的上调蛋白进行了验证。使用多支持向量机-递归特征消除(mSVM-RFE)算法,在诊断测试集中,由 13 个蛋白质组成的模型在 BCa 和 NT 之间表现出良好的性能,AUC 为 0.821(95% CI:0.675-0.967),灵敏度为 90.9%(95% CI:72.7-100%),特异度为 73.3%(95% CI:53.3-93.3%)。同时,在复发监测测试组中,11 个标记物分类器能显著区分 BCR 和 BCNR,灵敏度为 75.0%(95% CI:50.0-100%),特异度为 81.8%(95% CI:54.5-100%),AUC 为 0.784(95% CI:0.609-0.959)。值得注意的是,24个标记物中有6个蛋白质(SPR、AK1、CD2AP、ADGRF1、GMPS和C8A)是新报道的。本文揭示了膀胱癌的新型尿蛋白生物标记物,为膀胱癌的发病机制提供了新的理论依据(数据标识符 PXD044896)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Comprehensive Urinary Proteome Profiling Analysis Identifies Diagnosis and Relapse Surveillance Biomarkers for Bladder Cancer

Bladder cancer (BCa) is the predominant malignancy of the urinary system. Herein, a comprehensive urine proteomic feature was initially established for the noninvasive diagnosis and recurrence monitoring of bladder cancer. 279 cases (63 primary BCa, 87 nontumor controls (NT), 73 relapsed BCa (BCR), and 56 nonrelapsed BCa (BCNR)) were collected to screen urinary protein biomarkers. 4761 and 3668 proteins were qualified and quantified by DDA and sequential window acquisition of all theoretical mass spectra (SWATH-MS) analysis in two discovery sets, respectively. Upregulated proteins were validated by multiple reaction monitoring (MRM) in two independent combined sets. Using the multi-support vector machine-recursive feature elimination (mSVM-RFE) algorithm, a model comprising 13 proteins exhibited good performance between BCa and NT with an AUC of 0.821 (95% CI: 0.675–0.967), 90.9% sensitivity (95% CI: 72.7–100%), and 73.3% specificity (95% CI: 53.3–93.3%) in the diagnosis test set. Meanwhile, an 11-marker classifier significantly distinguished BCR from BCNR with 75.0% sensitivity (95% CI: 50.0–100%), 81.8% specificity (95% CI: 54.5–100%), and an AUC of 0.784 (95% CI: 0.609–0.959) in the test cohort for relapse surveillance. Notably, six proteins (SPR, AK1, CD2AP, ADGRF1, GMPS, and C8A) of 24 markers were newly reported. This paper reveals novel urinary protein biomarkers for BCa and offers new theoretical insights into the pathogenesis of bladder cancer (data identifier PXD044896).

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来源期刊
Journal of Proteome Research
Journal of Proteome Research 生物-生化研究方法
CiteScore
9.00
自引率
4.50%
发文量
251
审稿时长
3 months
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".
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