Ribal Maria J, Mengual Lourdes, Lozano Juan J, Ingelmo-Torres Mercedes, Palou Joan, Rodríguez-Faba Oscar, Witjes Johannes A, Van der Heijden Antoine G, Medina Rafael, Conde Jose M, Marberger Michael, Schmidbauer Joerg, Fernández Pedro L, Alcaraz Antonio
Department and Laboratory of Urology, Hospital Clínic, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Universitat de Barcelona, Spain.
CIBERehd, Plataforma de Bioinformática, Centro de Investigación Biomédica en red de Enfermedades Hepáticas y Digestivas, Hospital Clínic, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Spain.
Eur J Cancer. 2016 Feb;54:131-138. doi: 10.1016/j.ejca.2015.11.003. Epub 2016 Jan 4.
This study aimed to validate, in a prospective, blinded, international and multicenter cohort, our previously reported four non-invasive tests for bladder cancer (BC) diagnosis based on the gene expression patterns of urine.
Consecutive voided urine samples from BC patients and controls were prospectively collected in five European centres (n=789). Finally, 525 samples were successfully analysed. Gene expression values were quantified using TaqMan Arrays and previously reported diagnostic algorithms were applied to gene expression data. Results from the most accurate gene signature for BC diagnosis were associated with clinical parameters using analysis of variance test.
High diagnostic accuracy for the four gene signatures was found in the independent validation set (area under curve [AUC]=0.903-0.918), with the signature composed of two genes (GS_D2) having the best performance (sensitivity: 81.48%; specificity: 91.26%; AUC: 0.918). The diagnostic accuracy of GS_D2 was not affected by the number of tumours (p=0.58) but was statistically associated with tumour size (p=0.008). Also, GS_D2 diagnostic accuracy increases with increasing BC tumour risk. We found no differences in the performance of the GS_D2 test among the populations and centres in detecting tumours (p=0.7) and controls (p=0.2).
Our GS_D2 test is non-invasive, non-observer dependent and non-labour-intensive, and has demonstrated diagnostic accuracy in an independent, international and multicenter study, equal or superior to the current gold standard (cystoscopy combined with cytology). Additionally, it has higher sensitivity than cytology while maintaining its specificity. Consequently, it meets the requirements for consideration as a molecular test applicable to clinical practice in the management of BC.
本研究旨在通过一项前瞻性、盲法、国际多中心队列研究,验证我们之前报道的基于尿液基因表达模式的四项膀胱癌(BC)诊断非侵入性检测方法。
在五个欧洲中心前瞻性收集BC患者和对照的连续排尿尿液样本(n = 789)。最终,成功分析了525个样本。使用TaqMan阵列定量基因表达值,并将先前报道的诊断算法应用于基因表达数据。使用方差分析检验将BC诊断最准确基因特征的结果与临床参数相关联。
在独立验证集中发现这四个基因特征具有较高的诊断准确性(曲线下面积[AUC]=0.903 - 0.918),由两个基因组成的特征(GS_D2)表现最佳(敏感性:81.48%;特异性:91.26%;AUC:0.918)。GS_D2的诊断准确性不受肿瘤数量影响(p = 0.58),但与肿瘤大小具有统计学关联(p = 0.008)。此外,GS_D2的诊断准确性随着BC肿瘤风险增加而提高。我们发现在检测肿瘤(p = 0.7)和对照(p = 0.2)方面,GS_D2检测在不同人群和中心之间的性能没有差异。
我们的GS_D2检测是非侵入性的,不依赖观察者,且劳动强度小,并且在一项独立的国际多中心研究中已证明其诊断准确性与当前金标准(膀胱镜检查联合细胞学检查)相当或更高。此外,它在保持特异性的同时比细胞学检查具有更高的敏感性。因此,它符合作为一种适用于BC管理临床实践的分子检测的考虑要求。