Tags

Type your tag names separated by a space and hit enter

Pancreatic cancer serum detection using a lectin/glyco-antibody array method.
J Proteome Res. 2009 Feb; 8(2):483-92.JP

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+Show Affiliations

Department of Chemistry, The University of Michigan, Ann Arbor, Michigan 48109, USA.No affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info available

Pub Type(s)

Evaluation Study
Journal Article
Research Support, N.I.H., Extramural

Language

eng

PubMed ID

19072160

Citation

Li, Chen, et al. "Pancreatic Cancer Serum Detection Using a Lectin/glyco-antibody Array Method." Journal of Proteome Research, vol. 8, no. 2, 2009, pp. 483-92.
Li C, Simeone DM, Brenner DE, et al. Pancreatic cancer serum detection using a lectin/glyco-antibody array method. J Proteome Res. 2009;8(2):483-92.
Li, C., Simeone, D. M., Brenner, D. E., Anderson, M. A., Shedden, K. A., Ruffin, M. T., & Lubman, D. M. (2009). Pancreatic cancer serum detection using a lectin/glyco-antibody array method. Journal of Proteome Research, 8(2), 483-92. https://doi.org/10.1021/pr8007013
Li C, et al. Pancreatic Cancer Serum Detection Using a Lectin/glyco-antibody Array Method. J Proteome Res. 2009;8(2):483-92. PubMed PMID: 19072160.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Pancreatic cancer serum detection using a lectin/glyco-antibody array method. AU - Li,Chen, AU - Simeone,Diane M, AU - Brenner,Dean E, AU - Anderson,Michelle A, AU - Shedden,Kerby A, AU - Ruffin,Mack T, AU - Lubman,David M, PY - 2008/12/17/entrez PY - 2008/12/17/pubmed PY - 2009/4/7/medline SP - 483 EP - 92 JF - Journal of proteome research JO - J. Proteome Res. VL - 8 IS - 2 N2 - 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. SN - 1535-3893 UR - https://www.unboundmedicine.com/medline/citation/19072160/Pancreatic_cancer_serum_detection_using_a_lectin/glyco_antibody_array_method_ L2 - https://dx.doi.org/10.1021/pr8007013 DB - PRIME DP - Unbound Medicine ER -