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.
Journal of translational medicine. 2021 Apr 06*** epublish ***
Yosuke Hirasawa, Ian Pagano, Runpu Chen, Yijun Sun, Yunfeng Dai, Amit Gupta, Sergei Tikhonenkov, Steve Goodison, Charles J Rosser, Hideki Furuya
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., Department of Microbiology and Immunology, The State University of New York at Buffalo, Buffalo, NY, USA., Department of Epidemiology, University of Florida, Gainesville, FL, USA., Division of Urology, Cedars-Sinai Medical Center, Los Angeles, CA, USA., Translational and Clinical Program, University of Hawaii Cancer Center, Honolulu, HI, USA., Quantitative Health Sciences, Mayo Clinic Florida, Jacksonville, FL, USA., Cedars-Sinai Medical Center, Samuel Oschin Comprehensive Cancer Institute, Los Angeles, CA, USA. .