[Proteomic analysis of prostate cancer using SELDI]
>>Zhonghua Yi Xue Za Zhi. 2005 Nov;85(45):3172-5.
[Proteomic analysis of prostate cancer using surface enhanced laser desorption/ionization mass spectrometry.]
[Article in Chinese]
Pan YZ, Xiao XY, Zhao D, Zhang L, Ji GY, Li Y, He DC, Zhao XJ, Yang BX.
Department of Pathophysiology, Basic Medical School, Jilin University, Changchun 130021, China.
OBJECTIVE: To identify the serum biomarkers of prostate cancer by using protein chip and bioinformatics. METHODS: Eighty three prostate cancer (PCA) patients and ninety five healthy people from mass screen in Changchun were detected by surface-enhanced laser desorption/ionization mass spectrometry (SELDI-MS). The data of spectra were analyzed by bioinformatics tools-Biomarker Wizard and Biomarker Pattern. RESULTS: Compared with the spectra of healthy people, there were 18 potential markers detected in the spectra of the PCA patients, the protein expression was high in 4 of which and low in the 10 of which. The softwares Biomarkerwizard and Biomarker Pattern automatically, under given conditions, selected 8 biomarker proteins to be used to establish a five layer decision tree differentiate to diagnose PCA and differentiate PCA from healthy people with a specificity of 92.632% and a sensitivity of 96.386%. CONCLUSION: New serum biomarkers of PCA have been identified, and this SELDI mass spectrometry coupled with decision tree classification algorithm will provide a highly accurate and innovative approach for the early diagnosis of PCA.<<
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