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This Article Full Text Full Text (PDF) Supplemental Data All Versions of this Article: clinchem.2007.087148v1 54/7/1166    most recent Alert me when this article is cited Alert me if a correction is posted Citation Map Services Email this article to a friend Similar articles in this journal Similar articles in Web of Science Similar articles in PubMed Alert me to new issues of the journal Download to citation manager Citing Articles Citing Articles via HighWire Citing Articles via Web of Science (8) Citing Articles via Google Scholar Google Scholar Articles by Kyselova, Z. Articles by Novotny, M. V. Search for Related Content PubMed PubMed Citation Articles by Kyselova, Z. Articles by Novotny, M. V. Related Collections Proteomics and Protein Markers

Breast Cancer Diagnosis and Prognosis through Quantitative Measurements of Serum Glycan Profiles

¹ National Center for Glycomics and Glycoproteomics, Department of Chemistry, Indiana University, Bloomington, IN; ² Department of Medicine, Indiana University School of Medicine, Indianapolis, IN; ³ Breast Cancer Center, Greater Baltimore Medical Center, Baltimore, MD; ⁴ Indiana University Cancer Center, Indianapolis, IN.

^aAddress correspondence to these authors at: Department of Chemistry, Indiana University, 800 E. Kirkwood Ave., Bloomington, IN 47405. Fax 812-855-8300; e-mail novotny{at}indiana.edu, ymechref{at}indiana.edu.

Background: Glycosylated proteins play important roles in cell-to-cell interactions, immunosurveillance, and a variety of receptor-mediated and specific protein functions through a highly complex repertoire of glycan structures. Aberrant glycosylation has been implicated in cancer for many years.

Methods: We performed specific MALDI mass spectrometry (MS)-based glycomic profile analyses of permethylated glycans in sera from breast cancer patients (12, stage I; 11, stage II; 9, stage III; and 50, stage IV) along with sera from 27 disease-free women. The serum glycoproteins were enzymatically deglycosylated, and the released glycans were purified and quantitatively permethylated before their MALDI-MS analyses. We applied various statistical analysis tools, including ANOVA and principal component analysis, to evaluate the MS profiles.

Results: Two statistical procedures implicated several sialylated and fucosylated N-glycan structures as highly probable biomarkers. Quantitative changes according to a cancer stage resulted when we categorized the glycans according to molecular size, number of oligomer branches, and abundance of sugar residues. Increases in sialylation and fucosylation of glycan structures appeared to be indicative of cancer progression. Different statistical evaluations confirmed independently that changes in the relative intensities of 8 N-glycans are characteristic of breast cancer (P < 0.001), whereas other glycan structures might contribute additionally to distinctions in the statistically recognizable patterns (different stages).

Conclusions: MS-based N-glycomic profiling of serum-derived constituents appears promising as a highly sensitive and informative approach for staging the progression of cancer.

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