A candidate molecular biomarker panel for the detection of bladder cancer

Virginia Urquidi, Steven Goodison, Yunpeng Cai, Yijun Sun, Charles J. Rosser

Research output: Contribution to journalArticle

47 Citations (Scopus)

Abstract

Background: Bladder cancer is among the five most common malignancies worldwide, and due to high rates of recurrence, one of the most prevalent. Improvements in noninvasive urine-based assays to detect bladder cancer would benefit both patients and health care systems. In this study, the goal was to identify urothelial cell transcriptomic signatures associated with bladder cancer. Methods: Gene expression profiling (Affymetrix U133 Plus 2.0 arrays) was applied to exfoliated urothelia obtained from a cohort of 92 subjects with known bladder disease status. Computational analyses identified candidate biomarkers of bladder cancer and an optimal predictive model was derived. Selected targets from the profiling analyses were monitored in an independent cohort of 81 subjects using quantitative real-time PCR (RT-PCR). Results: Transcriptome profiling data analysis identified 52 genes associated with bladder cancer (P ≤ 0.001) and gene models that optimally predicted class label were derived. RT-PCR analysis of 48 selected targets in an independent cohort identified a 14-gene diagnostic signature that predicted the presence of bladder cancer with high accuracy. Conclusions: Exfoliated urothelia sampling provides a robust analyte for the evaluation of patients with suspected bladder cancer. The refinement and validation of the multigene urothelial cell signatures identified in this preliminary study may lead to accurate, noninvasive assays for the detection of bladder cancer. Impact: The development of an accurate, noninvasive bladder cancer detection assay would benefit both the patient and health care systems through better detection, monitoring, and control of disease.

Original languageEnglish (US)
Pages (from-to)2149-2158
Number of pages10
JournalCancer Epidemiology Biomarkers and Prevention
Volume21
Issue number12
DOIs
StatePublished - Dec 1 2012
Externally publishedYes

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Urinary Bladder Neoplasms
Biomarkers
Urothelium
Gene Expression Profiling
Real-Time Polymerase Chain Reaction
Patient Care
Urinary Bladder Diseases
Genes
Delivery of Health Care
Urine
Recurrence

ASJC Scopus subject areas

  • Epidemiology
  • Oncology

Cite this

A candidate molecular biomarker panel for the detection of bladder cancer. / Urquidi, Virginia; Goodison, Steven; Cai, Yunpeng; Sun, Yijun; Rosser, Charles J.

In: Cancer Epidemiology Biomarkers and Prevention, Vol. 21, No. 12, 01.12.2012, p. 2149-2158.

Research output: Contribution to journalArticle

Urquidi, Virginia ; Goodison, Steven ; Cai, Yunpeng ; Sun, Yijun ; Rosser, Charles J. / A candidate molecular biomarker panel for the detection of bladder cancer. In: Cancer Epidemiology Biomarkers and Prevention. 2012 ; Vol. 21, No. 12. pp. 2149-2158.
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