Objective: To screen and build a diagnostic model of Uygur's
renal cancer in Xinjiang by surface-enhanced laser desorption/
ionization time of flight mass spectrometry (SELDI-TOF-MS).
Methods: SELDI-TOF-MS and CM10 protein chip were used to
detect the serum protein patterns in 45 Uygur patients with renal
cancer and 45 normal Uygur controls. The data was analyzed and the
diagnostic model was established by using ZUCI-protein chip data
analysis system software package. The data of spectra were analyzed
by support vector machine (SVM) to establish a diagnostic model
which was evaluated and validated by leave one cross validation.
Results: Nine protein markers were identified with the relative
molecular weights of 4296, 4305, 5914, 5935, 6116, 6887,
8085, 8142, and 8573. The differences of these protein markers
between renal cancer patients and controls were statistically
significant (P<0.05). The detective model could differentiate
renal cance from healthy controls with a sensitivity of 100.00%
(45/45) and specificity of 90.91% (41/45). The sensitivity and
specificity of double blind confirmation procedure were 93.33%
(28/30) and 85.00% (17/20), respectively.
Conclusions: The predictive models of Uygur's renal cancer in
Xinjiang was successful established by the differences of serum
protein fingerprint, which provides a highly specific and sensitive
diagnostic tool for renal cell carcinoma.