title: Pancreatic cancer serum detection using a lectin/glyco-antibody array method.
abstract: Pancreatic cancer is a formidable disease and early detection biomarkers are needed to make inroads into improving the outcomes in these patients. In this work, lectin antibody microarrays were utilized to detect unique glycosylation patterns of proteins from serum. Antibodies to four potential glycoprotein markers that were found in previous studies were printed on nitrocellulose coated glass slides and these microarrays were hybridized against patient serum to extract the target glycoproteins. Lectins were then used to detect different glycan structural units on the captured glycoproteins in a sandwich assay format. The biotinylated lectins used to assess differential glycosylation patterns were Aleuria aurentia lectin (AAL), Sambucus nigra bark lectin (SNA), Maackia amurensis lectin II (MAL), Lens culinaris agglutinin (LCA), and Concanavalin A (ConA). Captured glycoproteins were evaluated on the microarray in situ by on-plate digestion and direct analysis using MALDI QIT-TOF mass spectroscopy. Analysis was performed using serum from 89 normal controls, 35 chronic pancreatitis samples, 37 diabetic samples and 22 pancreatic cancer samples. We found that this method had excellent reproducibility as measured by the signal deviation of control blocks as on-slide standard and 41 pairs of pure technical replicates. It was possible to discriminate cancer from the other disease groups and normal samples with high sensitivity and specificity where the response of Alpha-1-beta glycoprotein to lectin SNA increased by 69% in the cancer sample compared to the other noncancer groups (95% confidence interval 53-86%). These data suggest that differential glycosylation patterns detected on high-throughput lectin glyco-antibody microarrays are a promising biomarker approach for the early detection of pancreatic cancer.
authors.affiliation: Department of Chemistry, The University of Michigan, Ann Arbor, Michigan 48109, USA.
authors.forename: Chen
authors.initials: C
authors.lastname: Li
authors.forename: Diane M
authors.initials: DM
authors.lastname: Simeone
authors.forename: Dean E
authors.initials: DE
authors.lastname: Brenner
authors.forename: Michelle A
authors.initials: MA
authors.lastname: Anderson
authors.forename: Kerby A
authors.initials: KA
authors.lastname: Shedden
authors.forename: Mack T
authors.initials: MT
authors.lastname: Ruffin
authors.forename: David M
authors.initials: DM
authors.lastname: Lubman
mesh_terms: D000818:Animals; D014408:Biomarkers, Tumor / Q000737:chemistry / Q000378:metabolism; D006023:Glycoproteins / Q000737:chemistry / Q000378:metabolism; D006031:Glycosylation; D006801:Humans; D037102:Lectins / Q000737:chemistry / Q000378:metabolism; D046228:Microarray Analysis / Q000295:instrumentation / Q000379:methods*; D010190:Pancreatic Neoplasms / Q000097:blood* / Q000737:chemistry / Q000175:diagnosis*; D012372:ROC Curve; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D019032:Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization / Q000379:methods
chemical_list: D014408:Biomarkers, Tumor; D006023:Glycoproteins; D037102:Lectins