Literature DB >> 23831312

Validation study of a noninvasive urine test for diagnosis and prognosis assessment of bladder cancer: evidence for improved models.

Lourdes Mengual1, María José Ribal2, Juan José Lozano3, Mercedes Ingelmo-Torres2, Moisés Burset2, Pedro Luís Fernández4, Antonio Alcaraz2.   

Abstract

PURPOSE: We validated the performance of our previously reported test for bladder cancer based on urine gene expression patterns using an independent cohort. We also ascertained whether alternative models could 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. We pooled all samples analyzed to date to obtain a larger training set of 404 and used it to search for putative improved new models.
RESULTS: Our 12 + 2 gene expression signature had overall 80% sensitivity with 86% specificity (AUC 0.914) to discriminate between bladder cancer and control samples. It had 75% sensitivity and 75% specificity (AUC 0.83) to predict tumor aggressiveness in the validation set of urine samples. After grouping all samples 3 new signatures for diagnosis containing 2, 5 and 10 genes, respectively, and 1 containing 6 genes for prognosis were designed. Diagnostic performance of the 2, 5, 10 and 12-gene signatures was maintained or improved in the enlarged sample set (AUC 0.913, 0.941, 0.949 and 0.944, respectively). Performance to predict aggressiveness was also improved in the 14 and 6-gene signatures (AUC 0.855 and 0.906, respectively).
CONCLUSIONS: This validation study confirms the accuracy of the 12 + 2 gene signature as a noninvasive tool for assessing bladder cancer. We present improved models with fewer genes that must be validated in future studies.
Copyright © 2014 American Urological Association Education and Research, Inc. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  CIS; Cq; HG; LG; LOOCV; MIBC; NMIBC; PCR; SN; SP; UCC; biological markers; carcinoma; carcinoma in situ; cycle quantification; gene expression; high grade; leave-one-out cross validation; low grade; muscle invasive bladder cancer; nonMIBC; polymerase chain reaction; sensitivity; specificity; urinary bladder; urothelial cell carcinoma; urothelium

Mesh:

Substances:

Year:  2013        PMID: 23831312     DOI: 10.1016/j.juro.2013.06.083

Source DB:  PubMed          Journal:  J Urol        ISSN: 0022-5347            Impact factor:   7.450


  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

Review 3.  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

4.  Urinary protein biomarker panel for the detection of recurrent bladder cancer.

Authors:  Charles J Rosser; Myron Chang; Yunfeng Dai; Shanti Ross; Lourdes Mengual; Antonio Alcaraz; Steve Goodison
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2014-04-08       Impact factor: 4.254

5.  A Pilot Study on the Potential of RNA-Associated to Urinary Vesicles as a Suitable Non-Invasive Source for Diagnostic Purposes in Bladder Cancer.

Authors:  Amparo Perez; Ana Loizaga; Raquel Arceo; Isabel Lacasa; Ainara Rabade; Kerman Zorroza; David Mosen-Ansorena; Esperanza Gonzalez; Ana M Aransay; Juan M Falcon-Perez; Miguel Unda-Urzaiz; Felix Royo
Journal:  Cancers (Basel)       Date:  2014-01-22       Impact factor: 6.639

6.  Urinary mRNA biomarker panel for the detection of urothelial carcinoma.

Authors:  Virginia Urquidi; Mandy Netherton; Evan Gomes-Giacoia; Daniel Serie; Jeanette Eckel-Passow; Charles J Rosser; Steve Goodison
Journal:  Oncotarget       Date:  2016-06-21

7.  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

8.  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

9.  A Diagnostic Gene Expression Signature for Bladder Cancer Can Stratify Cases into Prescribed Molecular Subtypes and Predict Outcome.

Authors:  Runpu Chen; Ian Pagano; Yijun Sun; Kaoru Murakami; Steve Goodison; Ramanathan Vairavan; Malak Tahsin; Peter C Black; Charles J Rosser; Hideki Furuya
Journal:  Diagnostics (Basel)       Date:  2022-07-25

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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