Literature DB >> 26761785

Gene expression test for the non-invasive diagnosis of bladder cancer: A prospective, blinded, international and multicenter validation study.

Maria J Ribal1, Lourdes Mengual2, Juan J Lozano3, Mercedes Ingelmo-Torres4, Joan Palou5, Oscar Rodríguez-Faba6, Johannes A Witjes7, Antoine G Van der Heijden8, Rafael Medina9, Jose M Conde10, Michael Marberger11, Joerg Schmidbauer12, Pedro L Fernández13, Antonio Alcaraz14.   

Abstract

OBJECTIVE: 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.
METHODS: 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.
RESULTS: 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).
CONCLUSIONS: 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.
Copyright © 2015 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Biomarkers; Bladder cancer; Gene expression; Molecular test; Non-invasive diagnosis; Sensitivity and specificity; Urine

Mesh:

Substances:

Year:  2016        PMID: 26761785     DOI: 10.1016/j.ejca.2015.11.003

Source DB:  PubMed          Journal:  Eur J Cancer        ISSN: 0959-8049            Impact factor:   9.162


  10 in total

1.  Deep Sequencing of Urinary RNAs for Bladder Cancer Molecular Diagnostics.

Authors:  Mandy L Y Sin; Kathleen E Mach; Rahul Sinha; Fan Wu; Dharati R Trivedi; Emanuela Altobelli; Kristin C Jensen; Debashis Sahoo; Ying Lu; Joseph C Liao
Journal:  Clin Cancer Res       Date:  2017-02-13       Impact factor: 12.531

2.  Significant lack of urine-based biomarkers to replace cystoscopy for the surveillance of non-muscle invasive bladder cancer.

Authors:  Makito Miyake; Takuya Owari; Shunta Hori; Kiyohide Fujimoto
Journal:  Transl Androl Urol       Date:  2019-07

3.  Urinary transcript quantitation of CK20 and IGF2 for the non-invasive bladder cancer detection.

Authors:  Karsten Salomo; Doreen Huebner; Manja U Boehme; Alexander Herr; Werner Brabetz; Ulrike Heberling; Oliver W Hakenberg; Daniela Jahn; Marc-Oliver Grimm; Daniel Steinbach; Marcus Horstmann; Michael Froehner; Manfred P Wirth; Susanne Fuessel
Journal:  J Cancer Res Clin Oncol       Date:  2017-05-08       Impact factor: 4.553

Review 4.  Current Use and Promise of Urinary Markers for Urothelial Cancer.

Authors:  William Tabayoyong; Ashish M Kamat
Journal:  Curr Urol Rep       Date:  2018-10-17       Impact factor: 3.092

5.  Urinary cell microRNA-based prognostic classifier for non-muscle invasive bladder cancer.

Authors:  Mercedes Ingelmo-Torres; Juan José Lozano; Laura Izquierdo; Albert Carrion; Meritxell Costa; Lidia Gómez; María José Ribal; Antonio Alcaraz; Lourdes Mengual
Journal:  Oncotarget       Date:  2017-03-14

6.  Urinary MicroRNAs as Potential Markers for Non-Invasive Diagnosis of Bladder Cancer.

Authors:  Kati Erdmann; Karsten Salomo; Anna Klimova; Ulrike Heberling; Andrea Lohse-Fischer; Romy Fuehrer; Christian Thomas; Ingo Roeder; Michael Froehner; Manfred P Wirth; Susanne Fuessel
Journal:  Int J Mol Sci       Date:  2020-05-27       Impact factor: 5.923

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

Authors:  Chengtao Han; Lourdes Mengual; Bin Kang; Juan José Lozano; Xiaoqun Yang; Cuizhu Zhang; Antonio Alcaraz; Ji Liang; Dingwei Ye
Journal:  J Cancer       Date:  2018-08-06       Impact factor: 4.207

8.  CD24 regulates cancer stem cell (CSC)-like traits and a panel of CSC-related molecules serves as a non-invasive urinary biomarker for the detection of bladder cancer.

Authors:  Akira Ooki; Christopher J VandenBussche; Max Kates; Noah M Hahn; Andres Matoso; David J McConkey; Trinity J Bivalacqua; Mohammad Obaidul Hoque
Journal:  Br J Cancer       Date:  2018-10-17       Impact factor: 7.640

Review 9.  The Role of Novel Bladder Cancer Diagnostic and Surveillance Biomarkers-What Should a Urologist Really Know?

Authors:  Rafaela Malinaric; Guglielmo Mantica; Lorenzo Lo Monaco; Federico Mariano; Rosario Leonardi; Alchiede Simonato; André Van der Merwe; Carlo Terrone
Journal:  Int J Environ Res Public Health       Date:  2022-08-05       Impact factor: 4.614

Review 10.  Review of non-invasive urinary biomarkers in bladder cancer.

Authors:  Hyung-Ho Lee; Sung Han Kim
Journal:  Transl Cancer Res       Date:  2020-10       Impact factor: 1.241

  10 in total

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