Detecting Specific Tumor Markers In Urine Of Transitional Cell Carcinoma Of Bladder By Proteomics Methods

Objective: To detect the different protein expression in the urine of bladder transitional cell carcinoma (TCC), pick out new tumor markers, and explore the correlation between those proteins and the pathogenesis of TCC and the clinical application of proteomics methods for the early noninvasive diagnosis of TCC.Methods: Urine samples from 12 TCC patients and the control group (including 4 patients with TCC undergoing TUR-BT (transurethral resection of bladder tumor) or partial cystectomy previously, 4 healthy volunteers and 4 renal tumor patients) were analyzed using surface enhanced laser desorption/ionization-time of flight-mass spectrometry (SELDI-TOF-MS) ProteinChip technology. All experimental data were processed by computer to form the simulating maps and the contents of those different proteins would be statistically analyzed. Then the proteins which had been picked out would be identified in Swiss-Prot protein database.Results: Multiple protein changes were reproducibly detected in the urine samples of TCC group and Control group by IMAC-Cu-3 chip, including six potential novel TCC biomarkers and two protein clusters. Among those proteins, 2192Da, 3438Da, 4365Da, 5495Da and 8002Da were up-regulated in TCC group, while 4134Da protein and 3660Da-3830Da, 4310Da-5150Da protein clusters were up-regulated in Control group. Combination of the 343 8Da and 8002Da biomarkers increased significantly the sensitivity for detecting TCC to 83.3% with a specificity of 66.7%. The 3438Da biomarker had been identified as α-defensin, and the 4310Da-5150Da protein cluster was consistent with gp40 protein in the Swiss-Prot protein database.Conclusion: SELDI-TOF-MS ProteinChip technology is a quick, easy-handling and high-throughput analytic method. This technology can directly screen out relatively specific potential biomarkers from the urine of TCC patients, so it has a better clinical feasibility for early non-invasively diagnosing TCC and will provide some helpful information for predicting the prognosis and studying the pathogenesis of TCC.