Early Warning System For Early Diagnosis, Classification And Recurrence Of Transitional Cell Carcinoma Of Bladder

ObjectiveTo Establish an early warning system of bladder transitional cell carcinoma(BTCC) for early diagnosis, classification of two-tie grading system and recurrence prediction, which may provide a guideline for clinical diagnostic and therapeutic targets. Elevating the survival rate and improving the prognostic of BTCC patient is the final objectives.Methods1Various conditions of2-DE for urine were optimized by comparative study, including sample preparation, volume of loading sample, composition of rehydration sample buffer, selection of IPG dry strip, program and parameters of electrophoresis. The2-DE gels were stained by using sliver dye and analyzed by ChemiDOC XRS and PDQuest8.02-DE analysis software.2The urine proteome derived from low malignant BTCC patients, aggressive BTCC patients and healthy donors were compared by2DE-mass spectrometry-bioinfomatics technique.2-DE and ELISA were used to confirm the difference of APO-AI content in urine. The Optimal Operating Point(OOP) of APO-A1for early diagnosis and classification of two-tie grading system of BTCC was determined by using the Receiver Operating Characteristic(ROC) curve. Clinical value and discriminatory power were evaluated.338urine samples, including12low malignant BTCC,12aggressive BTCC and14healthy donors, were tested by H4protein chip and surface enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS).The differentially expressed proteins peaks were analyzed by BioMarker Wizard Software, support vector machine(SVM) was applied to construct identify protein profiles which can distinguish BTCC from health,low malignant BTUC from aggressive BTCC. The differentially expressed proteins peaks were identified initially with bioinfomatics.4The clinical data of167patients with recurring transitional cell carcinoma of bladder were collected and analyzed retrospectively. Combined with protein expression of p53and FGFR3in their paraffin samples detected by immunohistochemistry. A multivariate analysis on recurrence type was performed by the binary logistic regression analysis and a analysis on relapse-free time-related factors was made by Cox’s proportional hazard model analysis.Results1Two-dimensional electrophoregrams with higher resolution and better reproducibility were obtained,872±18protein spots were detected, the match ratio was76.26%.2Five proteins that increased in urine of BTCC patients were identified through the database search, including fibrinogen, lactate dehydrogenase B, apoA1, clusterin and haptoglobin. The ROC curve indicate BTCC patients will be well discriminated from the controls by using18.22as an OPP. The sensitivity was90%and the specificity was81.25%. Patients with low malignant BTCC will be well discriminated from aggressive BTCC using29.85as an OPP. The sensitivity was87.5%and the specificity was75%.3We have established a3-peptide profile (7267.417,2339.642,1885.7951) which can separate patients with BTCC from the controls with the sensitivity of91.7%and the specificity of78.6%. Another4-peptide profile (4249.1776,2676.1477,2831.5038,5499.2115) which can separate patients with low malignant BTCC from aggressive BTCC with the sensitivity of83.3%and the specificity of75%.4Logistic regression analysis indicated recurrent type of BTCC patients is correlated with primary type, age and FGFR3. Cox regression analysis showed primary type, blood vessel infiltrate, multiple tumor and P53influenced the relapse-free time.Conclusions1A stable technical platform of2-DE for urine proteome was established.2An early warning system of BTCC for early diagnosis, classification of two-tie grading system was established3The identify protein profiles which combined SELDI-TOF-MS with SVM provides a new approach with high specificity and sensitivity for early diagnosis, classification of two-tie grading of BTCC.4Patients with aggressive BTCC, older than65and negative expression of FGFR3might have a high risk to aggressive BTCC as recurrence; Patients with aggressive BTCC, multiple tumors, without blood vessel infiltration and P53expression trend to recur in short time. Classification of two-tie grading system provides guidance for prediction of relapse-free time and recurrence type of BTCC.