title: Novel blood biomarkers of pancreatic cancer-associated diabetes mellitus identified by peripheral blood-based gene expression profiles.
abstract: OBJECTIVE
  The prognosis of pancreatic cancer is still very poor, and the ability to detect pancreatic cancer in high-risk groups at an early stage is therefore essential for improving its long-term survival. The purpose of this study was to explore specific biomarkers that can differentiate pancreatic cancer-associated diabetes from type 2 diabetes, for the early detection of pancreatic cancer.
  
  
  METHODS
  From January 2006 to July 2008, 102 peripheral blood samples were collected from 25 patients diagnosed with pancreatic cancer and diabetes, 27 patients with pancreatic cancer without diabetes, 25 patients with diabetes mellitus >5 years, and 25 healthy controls. Thirty-two samples were used in microarray experiments to find differentially expressed genes specific for pancreatic cancer-associated diabetes. The results were further validated by quantitative real-time PCR for 101 blood samples. Protein expression of selected genes in serum and tissues was also detected.
  
  
  RESULTS
  Using microarray analysis, we found 58 genes to be unique in patients with pancreatic cancer-associated diabetes, including 23 upregulated genes and 35 downregulated genes. Eleven upregulated genes were further validated by RT-PCR, and two of these genes-vanin-1 (VNN1) and matrix metalloproteinase 9 (MMP9)-were selected for logistic regression analysis. The combination of VNN1 and MMP9 showed the best discrimination of pancreatic cancer-associated diabetes from type 2 diabetes. The protein expression of MMP9 and VNN1 was in accordance with the gene expression.
  
  
  CONCLUSIONS
  Our results indicate that the combination of VNN1 and MMP9 may be used as a novel blood biomarker panel for the discrimination of pancreatic cancer-associated diabetes from type 2 diabetes.
authors.affiliation: Department of Surgery, Second Affi liated Hospital, School of Medicine, Zhejiang University, 88 Jiefang Road, Hangzhou, Zhejiang 310009, China.
authors.forename: Hai
authors.initials: H
authors.lastname: Huang
authors.forename: Xin
authors.initials: X
authors.lastname: Dong
authors.forename: Mu Xing
authors.initials: MX
authors.lastname: Kang
authors.forename: Bin
authors.initials: B
authors.lastname: Xu
authors.forename: Ying
authors.initials: Y
authors.lastname: Chen
authors.forename: Bo
authors.initials: B
authors.lastname: Zhang
authors.forename: Jian
authors.initials: J
authors.lastname: Chen
authors.forename: Qiu Ping
authors.initials: QP
authors.lastname: Xie
authors.forename: Yu Lian
authors.initials: YL
authors.lastname: Wu
mesh_terms: D000328:Adult; D000368:Aged; D000581:Amidohydrolases / Q000097:blood* / Q000235:genetics*; D014408:Biomarkers, Tumor / Q000097:blood*; D015153:Blotting, Western; D016022:Case-Control Studies; D003924:Diabetes Mellitus, Type 2 / Q000097:blood* / Q000235:genetics*; D005260:Female; D058851:GPI-Linked Proteins; D020869:Gene Expression Profiling; D006801:Humans; D007124:Immunoenzyme Techniques; D016015:Logistic Models; D008297:Male; D020780:Matrix Metalloproteinase 9 / Q000097:blood* / Q000235:genetics*; D008875:Middle Aged; D010190:Pancreatic Neoplasms / Q000097:blood* / Q000235:genetics*; D040081:Protein Array Analysis; D012372:ROC Curve; D020133:Reverse Transcriptase Polymerase Chain Reaction; D018709:Statistics, Nonparametric
chemical_list: D014408:Biomarkers, Tumor; D058851:GPI-Linked Proteins; D020780:Matrix Metalloproteinase 9; D000581:Amidohydrolases; C022314:pantetheinase