J Cancer 2018; 9(17):3208-3215. doi:10.7150/jca.24506

Research Paper

Validation of Urine-based Gene Classifiers for Detecting Bladder Cancer in a Chinese Study

Chengtao Han1,2*, Lourdes Mengual3*, Bin Kang4,5, Juan José Lozano6, Xiaoqun Yang7, Cuizhu Zhang1,2, Antonio Alcaraz3✉, Ji Liang4,5✉, Dingwei Ye1,2✉

1. Department of Urology, Fudan University Shanghai Cancer Center, Shanghai, P.R. China
2. Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, P.R. China
3. Department and Laboratory of Urology, Hospital Clínic, Institut d'Investigacions Biomèdiques August Pi iSunyer, Universitat de Barcelona, Barcelona, Spain
4. Fudan University Shanghai Cancer Center - Institut Merieux Laboratory, Cancer Institute,Fudan University Shanghai Cancer Center, Shanghai, P.R. China.
5. bioMerieux (Shanghai) Company Limited, Shanghai, P.R. China.
6. CIBERehd. Plataforma de Bioinformática. IDIBAPS
7. Department of Pathology, Rui Jin Hospital, School of Medicine, Shanghai Jiao-Tong University, Shanghai, P.R. China.
* Both authors have contributed equally to this work

This is an open access article distributed under the terms of the Creative Commons Attribution (CC BY-NC) license (https://creativecommons.org/licenses/by-nc/4.0/). See http://ivyspring.com/terms for full terms and conditions.
Han C, Mengual L, Kang B, Lozano JJ, Yang X, Zhang C, Alcaraz A, Liang J, Ye D. Validation of Urine-based Gene Classifiers for Detecting Bladder Cancer in a Chinese Study. J Cancer 2018; 9(17):3208-3215. doi:10.7150/jca.24506. Available from http://www.jcancer.org/v09p3208.htm

File import instruction


Background: Current standard methods used to detect and monitor bladder cancer (BC) are invasive or have low sensitivity. We have previously reported in an international European study four non-invasive tests for BC diagnosis based on the gene expression patterns of urine.

Objective: to validate the tests in an independent Asian cohort.

Design, setting and participants: Prospective blinded study in which consecutive voided urine samples from BC patients and controls (n=520) were collected in the Fudan University Shanghai Cancer Center from 2014-2016. Gene expression values were quantified using TaqMan Arrays. The same cut-off as previously reported for discrimination between tumours and controls was used in this validation study.

Results and limitations: Finally, a total of 257 tumour and 132 control urine samples were analysed. We found a high accuracy for the four gene classifiers in this independent Asian set, the classifiers composed of 5 and 10 genes achieved the best sensitivity (80.54% and 81.32%, respectively) maintaining a high specificity (91.67% and 85.61%, respectively). Sensitivity of 5-gene (GS_D5) and 10-gene (GS_D10) expression classifiers in recurrent BC cases (78 and 79%, respectively) is comparable to that of primary BC cases (82%). Cytology and NMP22 identified 67% and 40%, respectively, of tumours that have been diagnosed with our tests. In addition, influence of each studied gene was analyzed and showed similar gene rank between Chinese and Caucasian population.

Conclusions: Our study proves that our non-invasive diagnostic BC tests can be reproduced in independent cohorts and in an external laboratory. All the four gene classifiers have shown equal or superior performance to the current gold standard in the present and previously reported validation studies. Consequently, they may be taken for consideration as molecular tests applicable to clinical practice in the management of BC.

Patient summary: Our gene classifiers achieve sensitivities up to 90% in HR NMIBC and MIBC patients, while this achievement is comparatively lower in LR NMIBC ones.

Keywords: Bladder cancer, Biomarkers, Gene expression, Gene classifiers, Non-invasive, Chinese