Hirasawa Yosuke, Pagano Ian, Chen Runpu, Sun Yijun, Dai Yunfeng, Gupta Amit, Tikhonenkov Sergei, Goodison Steve, Rosser Charles J, Furuya Hideki
Cedars-Sinai Medical Center, Samuel Oschin Comprehensive Cancer Institute, Los Angeles, CA, USA.
Cancer Prevention and Control Program, University of Hawaii Cancer Center, Honolulu, HI, USA.
J Transl Med. 2021 Apr 6;19(1):141. doi: 10.1186/s12967-021-02796-4.
Due to insufficient accuracy, urine-based assays currently have a limited role in the management of patients with bladder cancer. The identification of multiplex molecular signatures associated with disease has the potential to address this deficiency and to assist with accurate, non-invasive diagnosis and monitoring.
To evaluate the performance of Oncuria™, a multiplex immunoassay for bladder detection in voided urine samples. The test was evaluated in a multi-institutional cohort of 362 prospectively collected subjects presenting for bladder cancer evaluation. The parallel measurement of 10 biomarkers (A1AT, APOE, ANG, CA9, IL8, MMP9, MMP10, PAI1, SDC1 and VEGFA) was performed in an independent clinical laboratory. The ability of the test to identify patients harboring bladder cancer was assessed. Bladder cancer status was confirmed by cystoscopy and tissue biopsy. The association of biomarkers and demographic factors was evaluated using linear discriminant analysis (LDA) and predictive models were derived using supervised learning and cross-validation analyses. Diagnostic performance was assessed using ROC curves.
The combination of the 10 biomarkers provided an AUROC 0.93 [95% CI 0.87-0.98], outperforming any single biomarker. The addition of demographic data (age, sex, and race) into a hybrid signature improved the diagnostic performance AUROC 0.95 [95% CI 0.90-1.00]. The hybrid signature achieved an overall sensitivity of 0.93, specificity of 0.93, PPV of 0.65 and NPV of 0.99 for bladder cancer classification. Sensitivity values of the diagnostic panel for high-grade bladder cancer, low-grade bladder cancer, MIBC and NMIBC were 0.94, 0.89, 0.97 and 0.93, respectively.
Urinary levels of a biomarker panel enabled the accurate discrimination of bladder cancer patients and controls. The multiplex Oncuria™ test can achieve the efficient and accurate detection and monitoring of bladder cancer in a non-invasive patient setting.
由于准确性不足，目前基于尿液的检测在膀胱癌患者管理中的作用有限。识别与疾病相关的多重分子特征有可能弥补这一缺陷，并有助于进行准确的非侵入性诊断和监测。
为评估Oncuria™的性能，这是一种用于检测排尿尿液样本中膀胱癌的多重免疫分析方法。该测试在一个多机构队列中进行评估，该队列包含362名前瞻性收集的前来接受膀胱癌评估的受试者。在一个独立的临床实验室中对10种生物标志物（A1AT、APOE、ANG、CA9、IL8、MMP9、MMP10、PAI1、SDC1和VEGFA）进行平行检测。评估该测试识别膀胱癌患者的能力。通过膀胱镜检查和组织活检确认膀胱癌状态。使用线性判别分析（LDA）评估生物标志物与人口统计学因素的关联，并使用监督学习和交叉验证分析得出预测模型。使用ROC曲线评估诊断性能。
10种生物标志物的组合提供了0.93的曲线下面积（AUROC）[95%置信区间（CI）0.87 - 0.98]，优于任何单一生物标志物。将人口统计学数据（年龄、性别和种族）添加到混合特征中可提高诊断性能，AUROC为0.95[95%CI 0.90 - 1.00]。对于膀胱癌分类，混合特征的总体敏感性为0.93，特异性为0.93，阳性预测值（PPV）为0.65，阴性预测值（NPV）为0.99。诊断组对高级别膀胱癌、低级别膀胱癌、肌层浸润性膀胱癌（MIBC）和非肌层浸润性膀胱癌（NMIBC）的敏感性值分别为0.94、0.89、0.97和0.93。
生物标志物组合的尿液水平能够准确区分膀胱癌患者和对照。多重Oncuria™测试可以在非侵入性患者环境中实现对膀胱癌的高效准确检测和监测。
