Diagnosis of Renal Cancer by Molecular Urinalysis
Open Access
- 1 December 1999
- journal article
- research article
- Published by Oxford University Press (OUP) in JNCI Journal of the National Cancer Institute
- Vol. 91 (23), 2028-2032
- https://doi.org/10.1093/jnci/91.23.2028
Abstract
BACKGROUND: Organ-confined renal malignancies can be cured in the majority of patients, whereas more extensive lesions have a poor prognosis. We sought to develop a noninvasive test for renal cancer detection based on a novel molecular approach. METHODS: Matched urine and serum DNA samples were obtained before surgery from 30 patients with clinically organ-confined solid renal masses (25 with malignant tumors and five with tumors of low malignant potential) and were subjected to microsatellite analysis. Serum samples and urine samples obtained from 16 individuals without clinical evidence of genitourinary malignancy served as controls. RESULTS: Nineteen (76%) of the 25 patients with malignant tumors were found to have one or more microsatellite DNA alterations in their urine specimen, and 15 (60%) were found to have alterations in their serum DNA by microsatellite analysis. In every case, the microsatellite changes in urine or serum were identical to those found in the primary tumor. Three of five patients with tumors of low malignant potential were found to have DNA alterations in their urine, but none displayed alterations in their serum. Moreover, microsatellite alterations were not identified in either the urine or the serum samples from normal control subjects and patients with hematuria due to nephrolithiasis (renal stones). CONCLUSION: These data suggest that microsatellite DNA analysis of urine specimens provides a potentially valuable tool for the early detection of resectable kidney cancer. Furthermore, microsatellite analysis of serum samples reveals evidence of circulating tumor-specific DNA in approximately half of these patients and may reflect the propensity of these tumors to spread to distant sites at an early stage.Keywords
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