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Multilectin Affinity Chromatography for Characterization of Multiple Glycoprotein Biomarker Candidates in Serum from Breast Cancer Patients

¹ Barnett Institute and Department of Chemistry and Chemical Biology, Northeastern University, Boston, MA.
² Dana-Farber Cancer Institute, Boston, MA.
³ Renal Unit, Department of Medicine, Massachusetts General Hospital, Harvard University, Cambridge, MA.

^aAddress correspondence to this author at: Barnett Institute and Department of Chemistry and Chemical Biology, Northeastern University, Boston, MA 02115. Fax 617-373-2855; e-mail wi.hancock{at}neu.edu.

Background: Glycoproteins are often associated with cancer and are important in serum studies, for which glycosylation is a common posttranslational modification.

Methods: We used multilectin affinity chromatography (M-LAC) to isolate glycoproteins from the sera of breast cancer patients and controls. The proteins were identified by HPLC–tandem mass spectrometry (MS/MS) analysis of the corresponding tryptic digests. We used the FuncAssociate Gene Ontology program for association analysis of the identified proteins. Biomarker candidates in these groups were comparatively quantitated by use of peak area measurements, with inclusion of an internal standard. We analyzed data for concordance within the ontology association groups for vector of change with the development of breast cancer.

Results: Detection of the known low-concentration biomarker HER-2 (8–24 µg/L) enabled us to establish a dynamic range of 10⁶, relative to the amount of albumin, for the depletion step. We then used ELISA to confirm this range. Proteins associated with lipid transport and metabolism, cell growth and maintenance, ion homeostasis, and protease inhibition were found to be differentially regulated in serum from women with breast cancer compared with serum from women without breast cancer.

Conclusions: M-LAC for isolation of the serum glycoproteome, coupled with liquid chromatography–MS/MS and the use of gene ontology associations, can be used to characterize large panels of candidate markers, which can then be evaluated in a particular patient population.

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