Application of serum protein fingerprint in diagnosis of pancreatic cancer.
- Author:
Yang-wen ZHU
1
;
Yue-dong WANG
;
Zai-yuan YE
;
Xun HU
;
Jie-kai YU
Author Information
- Publication Type:Journal Article
- MeSH: Adult; Aged; Aged, 80 and over; Biomarkers, Tumor; blood; Blood Proteins; analysis; Female; Humans; Male; Middle Aged; Pancreatic Neoplasms; blood; diagnosis; Protein Array Analysis; methods; Sensitivity and Specificity; Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization; methods; Support Vector Machine
- From: Journal of Zhejiang University. Medical sciences 2012;41(3):289-297
- CountryChina
- Language:Chinese
-
Abstract:
OBJECTIVETo 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.
METHODSA 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.
RESULTSThe 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%.
CONCLUSIONSELDI-TOF-MS technique combined with bioinformatics can facilitate to identify biomarkers for pancreatic cancer.
