[Tree analysis pattern of mass spectral urine profiles in differential diagnosis of bladder transitional cell carcinoma].
OBJECTIVE
To develope a tree analysis pattern of mass spectral urine profiles to discriminate bladder transitional cell carcinoma (TCC) from non-cancer lesions using surface-enhanced laser desorption and ionization time-of-flight mass spectrometry (SELDI-TOF-MS) technology.


METHODS
Urine samples from 61 bladder transitional cell carcinoma (TCCs) patients, 53 healthy volunteers and 42 patients with other urogenital diseases were analyzed using IMAC-Cu-3 ProteinChip. Proteomic spectra were generated by SELDI-TOF- MS. A preliminary "training" set of spectra derived from analysis of urine from 46 TCC patients, 32 patients with benign urogenital diseases (BUD), and 40 age-matched unaffected healthy men were used to train and develop a decision tree classification algorithm which identified a fine-protein mass pattern that discriminated cancers from non-cancers effectively. A blinded test set including 38 cases was used to determine the sensitivity and specificity of the classification system.


RESULTS
The algorithm identified a cluster pattern that, in the training set, segregated cancer from non-cancer with a sensitivity of 84.8% and specificity of 91.7%. The discriminatory pattern was correctly identified. A sensitivity of 93.3% and a specificity of 87% for the blinded test were obtained when compared the TCC versus non-cancers.


CONCLUSIONS
SELDI-TOF-MS technology is a rapid, convenient and high-throughput analyzing method. The urine tree analysis proteomic pattern as a screening tool is effective for differential diagnosis of bladder cancer. More detailed studies are needed to further evaluate the clinical value of this pattern.
Wu
Deng-long
DL
Department of Urology, Shanghai 6th People's Hospital, Shanghai Jiatong University, Shanghai 200233, China. wudenglong@163.com
Zhang
Yuan-fang
YF
Guan
Ming
M
Liu
Wei-wei
WW
Xu
Yue-min
YM
Jin
San-bao
SB
Zhang
Jiong
J
Jin
Chong-rui
CR
Lü
Yuan
Y
D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D002295:Carcinoma, Transitional Cell / Q000175:diagnosis / Q000652:urine*; D003556:Cystitis / Q000175:diagnosis / Q000652:urine; D003663:Decision Trees; D003937:Diagnosis, Differential; D006801:Humans; D008297:Male; D008875:Middle Aged; D011470:Prostatic Hyperplasia / Q000175:diagnosis / Q000652:urine; D040081:Protein Array Analysis; D040901:Proteomics / Q000379:methods; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D019032:Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization / Q000379:methods; D001749:Urinary Bladder Neoplasms / Q000175:diagnosis / Q000652:urine*