Screen For Specific Biomarkers In Serum Of Pancreatic Cancer By Using Of Proteomic Fingerprint Technology

IntroductionIn clinic the major of the patients with pancreatic cancer die in one year after final diagnosis,and the success rate of operation is only 10～20%.Only 3～4%of patients survive＞5 years after operation.Whereas 5-year survival after radical operation if the diameter≤2cm could increase 19～41%,and if the diameter≤1.0cm it could get 67%. The difference is remarkable.So early diagnosis may be the key way to increase the survival rate after pancreaticoduodenectomy and improve the prognosis of patients with pancreatic cancer.But the sensitivity and specificity of clinical diagnosis methods presently is low,which become the biggest obstacle for the effective diagnosis and treatment for patients with pancreatic cancer.In recent few years,it has become possible to find new tumor markers for diagnosing and monitoring the occurrence and development of tumors as the proteomics research develops.Surface-enhanced laser desorption and ionization time of fight mass spectrometry(SELDI-TOF-MS)is a new proteomics research technique developed in the recent few years.It is better than 2-DIMENSIONAL electrophoresis and other mass-spectrum analysis methods and has been extensively applied for the researches about tumor markers screening.This research is to screen a series of specific marker protein,to establish diagnostic cast about pancreatic cancer and to provide more sensitive and more reliable indexes about early precaution and early diagnosis for the pancreatic cancer by observing the finger printing of patients of pancreatic cancer and controls.ObjectiveTo Screen relatively specifically markers in serum from pancreatic cancer patients using surface-enhanced laser desorption and ionization time of fight mass spectrometry(SELDI-TOF-MS)and to establishment a serum protein pattern model for screening pancreatic cancer.Methods29 Serum samples from patients of pancreatic cancer,were collected before surgery and an additional 57 serum samples from age and sex matched individuals without cancer were used as controls,WCX magnetic beans and PBSⅡ-C protein chips reader (ciphergen Biosystems Ins),to detect the protein fingerprint expression of all the Serum samples and the resulting profiles between cancer and normal were analyzed with Biomarker Wizard system,establish the model using Biomarker Patterns system software.A double-blind test was used to determine the sensitivity and specificity of the classificated model.ResultsA group of four biomarkers(relative molecular weight are 5705Da,4935 Da,5318 Da,3243 Da)were selected to set up a decision trees as the classification model for screening pancreatic cancers effectively.The result yielded a sensitivity of is 100 %(20/20),specificity of 97.37%(37/38)and ROC curve is 99.72%.The double-blind test challenged the model with a sensitivity of 88.89%and a specificity of 89.49%.ConclusionsNew serum biomarkers of pancreatic cancer have been identified and the pattern of combined markers provides a powerful and reliable diagnostic method for pancreatic cancer with high sensitivity and specificity.