J Urol. 2013 Jul 2. pii: S0022-5347(13)04825-8. doi: 10.1016/j.juro.2013.06.083. [Epub ahead of print]
Validation study of a non-invasive urine test for diagnosis and prognosis assessment of bladder cancer. Evidence for improved models.
Laboratory and Department of Urology, Hospital Clínic. Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Universitat de Barcelona. Spain. Electronic address: firstname.lastname@example.org.
To validate the performance of our previously reported test for bladder cancer based on urine gene expression patterns, using an independent cohort, as well as to ascertain whether alternative models can achieve better accuracy.
MATERIALS AND METHODS:
Gene expression patterns of the previously reported 48 genes (including the 12+2 genes of the signature) were analyzed by TaqMan Arrays in an independent set of 207 urine samples. Afterwards, we pooled all samples analyzed to date to obtain a larger training set (n=404) and used it to search for putative improved new models.
Our 12+2 gene expression signature has an overall sensitivity of 80% with 86% specificity (AUC 0.914) in discriminating between bladder cancer and control samples and 75% sensitivity and 75% specificity (AUC 0.83) in predicting tumor aggressiveness in the validation set of urines. After grouping all samples, three new signatures (containing 2, 5, and 10 genes) for diagnosis and one (containing 6 genes) for prognosis were designed. Diagnostic performance for the 2, 5, 10, and 12 gene signatures was maintained or improved in the enlarged set of samples (AUC 0.913, 0.941, 0.949, 0.944, respectively). The performance for aggressiveness prediction was also improved in the 14 and six gene signatures (AUC 0.855 and 0.906, respectively).
This validation study confirms the accuracy of the 12+2 gene signature as a non-invasive tool in the assessment of bladder cancer. Improved models with a lower number of genes are presented that need to be validated in future studies.
Copyright © 2013 American Urological Association Education and Research, Inc. Published by Elsevier Inc. All rights reserved.
Biomarkers, bladder cancer, diagnosis and prognosis, gene expression signature, urine
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