Journal
ANALYTICAL CHEMISTRY
Volume 83, Issue 7, Pages 2554-2561Publisher
AMER CHEMICAL SOC
DOI: 10.1021/ac102829b
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Funding
- University of Nebraska Medical Center and Ames Laboratory
- U.S. DOE
- Iowa State University [DE-AC02-07CH11358]
- Department of Defense [BC097421]
- National Institutes of Health [EDRN UO1 CA111294, RO1 CA131944]
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Pancreatic cancer (PC) is one of the most lethal malignancies. It has a 5-year survival rate of only 6%, owing in part to the lack of a reliable tumor marker for early diagnosis. Recent research has shown that the mucin protein MUC4 is aberrantly expressed in pancreatic adenocarcinoma cell lines and tissues but is undetectable in normal pancreas and chronic pancreatitis. Thus, the level of MUC4 in patient sera has the potential to function as a diagnostic and prognostic marker for PC. However, the measurement of MUC4 in sera using conventional test platforms (e.g., enzyme linked immunosorbent assay (ELISA) and radioimmunoassay (RIA)) has been unsuccessful. This has prevented the assessment of the utility of this protein as a possible PC marker in sera. In addressing this obstacle, the work herein examines the potential to create a simple diagnostic test for MUC4 through the development of a surface-enhanced Raman scattering (SERS)-based immunoassay, which was then used to demonstrate the first ever detection of MUC4 in cancer patient serum samples. Importantly, these measurements showed that sera from patients with PC produced a significantly higher SERS response for MUC4 compared to sera from healthy individuals and from patients with benign diseases. These results indicate that a SERS-based immunoassay can monitor MUC4 levels in patient sera, representing a much needed first step toward assessing the potential of this protein to serve as a serum marker for the early stage diagnosis of PC. This paper details these and other findings (i.e., the detection of the mucin protein CA19-9), which demonstrate that our SERS assay outperforms conventional assays (i.e., RIA and ELISA) with respect to limits of detection, readout time, and required sample volume.
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