Identification of serum biomarkers for pancreatic adenocarcinoma by proteomic analysis

Diagnosis of pancreatic adenocarcinoma (PaCa) at an early stage is important for successful treatment and improving the prognosis of patients. Serum samples were applied to strong anionic exchange chromatography (SAX) protein chips for protein profiling by surface enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS) to distinguish PaCa from noncancer. The Wilcoxon rank-sum test, decision tree algorithm, and logistic regression were used to statistically analyze the multiple protein peaks. Sixty-one protein peaks between 2000 and 30,000 m/z ratios were detected to establish multiple decision classification trees for differentiating the known disease states. A sensitivity of 0.833 and a specificity of 1.000 were obtained in distinguishing PaCa from healthy controls and benign pancreatic diseases. Six protein biomarkers related to different PaCa TNM stages were detected (P < 0.01). One protein biomarker (m/z 4016) rich in PaCa had a down-regulated trend when preoperative and postoperative samples (P < 0.05) were compared. Three protein biomarkers (m/z 4155, 4791, and 28,068) were detected in the differential diagnosis of the three test groups (P < 0.05). A peak m/z 28 068 was identified as C14orf16 using ProteinChip immunoassay. C14orf166 levels were significantly higher in the serum of patients with PaCa compared with the control group using a sandwich immunoenzymatic system. Immunolabeling of tissue sections revealed that the C14orf166 protein was strongly expressed in tumor cells. The results suggest that SELDI-TOF-MS serum profiling is helpful for the diagnostic, prognostic or therapeutic effects of PaCa, which is superior to CA 19-9. The identified protein biomarker C14orf166 is a potential biomarker of PaCa.