4.5 Article

A multiplexed bead assay for profiling glycosylation patterns on serum protein biomarkers of pancreatic cancer

Journal

ELECTROPHORESIS
Volume 32, Issue 15, Pages 2028-2035

Publisher

WILEY
DOI: 10.1002/elps.201000693

Keywords

Antibody; Bead-based multiplexed assay; Biomarker; Cancer; Glycoproteins

Funding

  1. National Cancer Institute [R21CA124441]
  2. National Institute of Health [R01GM49500, K23 DK082097]

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A multiplexed bead-based immunoassay was developed to simultaneously profile glycosylation patterns of serum proteins to investigate their usefulness as biomarkers for pancreatic cancer. The multiplex assay utilized protein-specific capture antibodies chemically coupled individually to beads labeled with specific amounts of fluorescent dye. Captured proteins were detected based on the extent and specific type of glycosylation as determined by successive binding of fluorescent lectin probes. Advantages to this technique include the fact that antibodies coupled to the beads had minimal nonspecific binding to the lectins ConA/SNA, avoiding the step of chemically blocking the antibody glycans and the bead assays were performed in a 96-well filter plate enabling high-throughput screening applications with improved reproducibility. The assay was tested with ConA and SNA lectins to examine the glycosylation patterns of alpha-1-beta glycoprotein (A1BG) and serum amyloid p (SAP) component for use as potential biomarkers for the detection of pancreatic cancer based on the results from prior biomarker studies. The results showed that the SNA response on the captured A1BG protein could distinguish chronic pancreatitis samples from pancreatic cancer with a p-value of 0.035 and for the SAP protein with SNA, a p-value of 0.026 was found between the signal of normal controls and the pancreatic cancer samples. For the ConA response, a decline in the signal for both proteins in the serum samples was found to distinguish pancreatic cancer from normal controls and renal cell carnoma samples (A1BG, p<0.05; and SAP, p<0.0001).

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