Construction of protein profiling models for diagnosis of pancreatic carcinoma / 中华消化杂志

ABSTRACT

Objective To establish diagnostic models for pancreatic carcinoma(PC)and to find out the biomarkers related to PC.Methods Serum samples obtained from subjects including PC patients,pancreatic benign disease patients and normal controls were examined with strong anionic exchange chromatography(SAX2)chips for protein profiling using surface enhanced laser desorption/ionization-time of flight-mass spectrometry(SELDI-TOF-MS).The decision tree models and logistic regression models for evaluating the value of serum biomarkers were assessed.SELDI immunoassay and ELISA were used to identify the biomarker and its level in serum respectively.Results Twentysix mass peaks were different between PC patients and normal controls(P＜0.0 1)and 16 mass peaks were different between patients with PC and with pancreatic benign disease(P＜0.05).The decision tree model had a sensitivity of 83.3%and a specificity of 100.0%in differentiation of PC,which was better than that of CA19-9 by ROC curve.There were significant differences in 6 mass peaks among different stages of PC(P＜0.01).Logistic regression model showed a sensitivity of 81.6%and a specificity of 80.6%in diagnosis of early PC.The M/Z 28068 protein was identified as C14orf166 with a sensitivity of more than 82%and a specificity of more than 88%in diagnosis of PC.Conclusions The diagnostic models based on SELDI-TOF-MS were superior to CA19-9 in diagnosis of PC.The identified biomarker C14orf166 is expected to play a role in the diagnosis of PC.