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Department of OtolaryngologyHead and Neck Surgery, The Johns Hopkins School of Medicine, Baltimore, Maryland 21205 [M. O. H., J. L., K. Y., J. M. E., W. M. W., D. S.], and The James Buchanan Brady Urological Institute [M. S.] and Department of Pathology [S. B., W. M. W.], Johns Hopkins Medical Institutions, Baltimore, Maryland 21205
The detection of urothelial malignancies remains challenging. The majority of patients diagnosed with bladder cancer require life-long surveillance for disease recurrence. Monitoring strategies rely predominantly on invasive endoscopic techniques, which are inconvenient and uncomfortable. Multiple in vitro diagnostic technologies have been developed to supplant the contemporary standard of care. The U.S. Food and Drug Administration has approved several assays, but [because of inferior performance characteristics (low sensitivity and specificity)] these tests have not made a significant impact on practice, to date. We sought to develop a test for bladder cancer with better performance characterization detection based on a novel molecular approach.
Matched urine and peripheral blood lymphocyte samples were obtained before surgery from 31 patients with bladder cancer (10 pTa, 4 pT1, and 17 pT2
). DNA from these samples was subjected to allelic imbalance analysis using HuSNP chips and was validated in parallel with microsatellite analysis for loss of heterozygosity and microsatellite instability. Peripheral blood lymphocyte and urine DNA obtained from 14 individuals without clinical evidence of genitourinary malignancy served as controls.
Thirty-one of 31 (100%) urine DNA samples from patients with bladder tumors were found to have 24 or more single-nucleotide polymorphism (SNP) DNA alterations. In general, SNP alterations were more common in urine samples from pT2
tumors than pTa or pT1 tumors. SNP alterations were not identified in nine normal control subjects and in four of five patients with hematuria.
These data support the noninvasive HuSNP chip assay in urine DNA as a valuable tool for the detection of bladder cancer (on a high-throughput-automated platform).
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