[Application of serum protein fingerprint in diagnosis of pancreatic cancer].
OBJECTIVE
To establish serum protein fingerprint model for early diagnosis of pancreatic cancer with surface enhanced laser desorption/ionization time of flight-mass spectrometry (SELDI-TOF-MS) and bioinformatics techniques.


METHODS
A total of 73 samples were analyzed in this study, including 31 cases of pancreatic cancers, 22 cases of pancreatitis and 20 healthy individuals. Samples were first analyzed by SELDI-TOF-MS and two patterns of differentiation model were constructed with support vector machine arithmetic method.


RESULTS
The pattern 1 model differentiating pancreatic cancer patients from healthy individuals had a specificity and a sensitivity of both 100.0%. The pattern 2 model differentiating pancreatic cancer from pancreatitis had a specificity of 95.5% and a sensitivity of 93.5%.


CONCLUSIONS
SELDI-TOF-MS technique combined with bioinformatics can facilitate to identify biomarkers for pancreatic cancer.
Department of General Surgery, Zhejiang Provincial People's Hospital, Hangzhou 310014, China. Zhuyw007@com.cn
Yang-wen
YW
Zhu
Yue-dong
YD
Wang
Zai-yuan
ZY
Ye
Xun
X
Hu
Jie-kai
JK
Yu
D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D014408:Biomarkers, Tumor / Q000097:blood; D001798:Blood Proteins / Q000032:analysis*; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D010190:Pancreatic Neoplasms / Q000097:blood / Q000175:diagnosis*; D040081:Protein Array Analysis / Q000379:methods*; D012680:Sensitivity and Specificity; D019032:Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization / Q000379:methods*; D060388:Support Vector Machine
D014408:Biomarkers, Tumor; D001798:Blood Proteins