[Proteomic analysis of prostate cancer using surface enhanced laser desorption/ionization mass spectrometry].
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%.


CONCLUSIONS
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.
Pan
Yu-zhuo
YZ
Department of Pathophysiology, Basic Medical School, Jilin University, Changchun 130021, China.
Xiao
Xue-yuan
XY
Zhao
Dan
D
Zhang
Ling
L
Ji
Guo-yi
GY
Li
Yang
Y
He
Da-cheng
DC
Zhao
Xue-jian
XJ
Yang
Bao-xue
BX
D000368:Aged; D014408:Biomarkers, Tumor / Q000097:blood*; D019295:Computational Biology; D006801:Humans; D008297:Male; D008875:Middle Aged; D011471:Prostatic Neoplasms / Q000097:blood / Q000175:diagnosis*; D040081:Protein Array Analysis; D040901:Proteomics / Q000379:methods*; D019032:Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization / Q000379:methods*
D014408:Biomarkers, Tumor