Detection of urothelial bladder cancer cells in voided urine can be improved by a combination of cytology and standardized microsatellite analysis.

PURPOSE: To evaluate molecular and immunohistochemical markers to develop a molecular grading of urothelial bladder cancer and to test these markers in voided urine samples. EXPERIMENTAL
DESIGN: 255 consecutive biopsies from primary bladder cancer patients were evaluated on a tissue microarray. The clinical parameters gender, age, adjacent carcinoma in situ, and multifocality were collected. UroVysion fluorescence in situ hybridization (FISH) was done. Expression of cytokeratin 20, MIB1, and TP53 was analyzed by immunohistochemistry. Fibroblast growth factor receptor 3 (FGFR3) status was studied by SNaPshot mutation detection. Results were correlated with clinical outcome by Cox regression analysis. To assess the predictive power of different predictor subsets to detect high grade and tumor invasion, logistic regression models were learned. Additionally, voided urine samples of 119 patients were investigated. After cytologic examination, urine samples were matched with their biopsies and analyzed for loss of heterozygosity (LOH), FGFR3 mutation, polysomy, and p16 deletion using UroVysion FISH. Receiver operator characteristic curves for various predictor subsets were plotted.
RESULTS: In biopsies, high grade and solid growth pattern were independent prognostic factors for overall survival. A model consisting of UroVysion FISH and FGFR3 status (FISH + FGFR3) predicted high grade significantly better compared with a recently proposed molecular grade (MIB1 + FGFR3). In voided urine, the combination of cytology with LOH analysis (CYTO + LOH) reached the highest diagnostic accuracy for the detection of bladder cancer cells and performed better than cytology alone (sensitivity of 88.2% and specificity of 97.1%).
CONCLUSIONS: The combination of cytology with LOH analysis could reduce unpleasant cystoscopies for bladder cancer patients.