Molecular Medicine Research Center, Chang Gung University, Taoyuan 333, Taiwan.
J Proteomics. 2012 Jun 27;75(12):3529-45. doi: 10.1016/j.jprot.2011.12.031. Epub 2012 Jan 3.
Three common urological diseases are bladder cancer, urinary tract infection, and hematuria. Seventeen bladder cancer biomarkers were previously discovered using iTRAQ - these findings were verified by MRM-MS in this current study. Urine samples from 156 patients with hernia (n=57, control), bladder cancer (n=76), or urinary tract infection/hematuria (n=23) were collected and subjected to multiplexed LC-MRM/MS to determine the concentrations of 63 proteins that are normally considered to be plasma proteins, but which include proteins found in our earlier iTRAQ study. Sixty-five stable isotope-labeled standard proteotypic peptides were used as internal standards for 63 targeted proteins. Twelve proteins showed higher concentrations in the bladder cancer group than in the hernia and the urinary tract infection/hematuria groups, and thus represent potential urinary biomarkers for detection of bladder cancer. Prothrombin had the highest AUC (0.796), with 71.1% sensitivity and 75.0% specificity for differentiating bladder cancer (n=76) from non-cancerous (n=80) patients. The multiplexed MRM-MS data was used to generate a six-peptide marker panel. This six-peptide panel (afamin, adiponectin, complement C4 gamma chain, apolipoprotein A-II precursor, ceruloplasmin, and prothrombin) can discriminate bladder cancer subjects from non-cancerous subjects with an AUC of 0.814, with a 76.3% positive predictive value, and a 77.5% negative predictive value. This article is part of a Special Section entitled: Understanding genome regulation and genetic diversity by mass spectrometry.
三种常见的泌尿科疾病是膀胱癌、尿路感染和血尿。此前使用 iTRAQ 发现了 17 种膀胱癌生物标志物-本研究通过 MRM-MS 对这些发现进行了验证。收集了 156 名疝(n=57,对照)、膀胱癌(n=76)或尿路感染/血尿(n=23)患者的尿样,并用多重 LC-MRM/MS 测定 63 种通常被认为是血浆蛋白的蛋白质浓度,但其中包括我们之前 iTRAQ 研究中发现的蛋白质。65 种稳定同位素标记的标准肽作为 63 种靶向蛋白的内标。12 种蛋白质在膀胱癌组中的浓度高于疝组和尿路感染/血尿组,因此代表了膀胱癌检测的潜在尿生物标志物。凝血酶原的 AUC 最高(0.796),对区分膀胱癌(n=76)和非癌(n=80)患者的灵敏度为 71.1%,特异性为 75.0%。多重 MRM-MS 数据用于生成六肽标记物组。该六肽组(转铁蛋白、脂联素、补体 C4 γ 链、载脂蛋白 A-II 前体、铜蓝蛋白和凝血酶原)可以区分膀胱癌患者和非癌症患者,AUC 为 0.814,阳性预测值为 76.3%,阴性预测值为 77.5%。本文是一个特刊的一部分,标题为:通过质谱法了解基因组调控和遗传多样性。