Using a cell line breast cancer progression system to identify biomarker candidates.

Secreted and plasma membrane glycoproteins are considered excellent candidates for disease biomarkers. Herein we describe the identification of secreted and plasma membrane glycoproteins that are differentially expressed among a family of three breast cancer cell lines that models the progression of breast cancer. Using two-dimensional liquid chromatography-tandem mass spectrometry we identified more than 40 glycoproteins that were differentially expressed in either the premalignant (MCF10AT) or the fully malignant (MCF10CA1a) cell lines of this model system. Comparative analysis revealed that the differentially expressed breast cancer progression-associated glycoproteins were among the most highly expressed in the malignant (MCF10CA1a) breast cancer cell line; a subset of these was detected only in the malignant line; and others were detected in the malignant line at levels 25 to 50 times greater than in the benign (MCF10A) line. Using the results from this model cell system as a guide, we then carried out glycoproteomic analyses of normal and cancerous breast tissue lysates. Eleven of the glycoproteins differentially expressed in the breast cell lines were identified in the tissue lysates. Among these glycoproteins, collagen alpha-1 (XII) chain was expressed at dramatically higher (~10-fold) levels in breast cancer than in normal tissue. BIOLOGICAL SIGNIFICANCE: Identifying glycoproteins differentially expressed during cancer progression results in information on the biological processes and key pathways associated with cancer. In addition, new hypotheses and potential biomarkers result from these glycoproteomic studies. Our glycoproteomic analysis of this model of breast cancer provides a roadmap for future experimental interventions to further tease apart critical components of tumor progression.

Systemic alteration of cell-surface and secreted glycoprotein expression in malignant breast cancer cell lines.

Breast cancer cell lines express fewer transmembrane and secreted glycoproteins than nonmalignant ones. The objective of these experiments was to characterize the changes in the expression of several hundred glycoproteins quantitatively. Secreted and cell-surface glycoproteins were isolated using a glycoprotein capture protocol and then identified by tandem mass spectrometry. Glycoproteins expressed by a group of cell lines originating from malignant tumors of the breast were compared with those expressed by a nonmalignant set. The average number of spectral counts (proportional to relative protein abundance) and the total number of glycopeptides in the malignant samples were reduced to about two-thirds of the level in the nonmalignant samples. Most glycoproteins were expressed at a different level in the malignant samples, with nearly as many increasing as decreasing. The glycoproteins with reduced expression accounted for a larger change in spectral counts, and hence for the net loss of spectral counts in the malignant lines. Similar results were found when the glycoproteins were studied via identified glycosylation sites only, or through identified sites together with non-glycopeptides. The overall reduction is largely due to the loss of integrins, laminins and other proteins that form or interact with the basement membrane.

Overcoming challenges and opening new opportunities in glycoproteomics.

Glycoproteomics has emerged as a prime area of interest within the field of proteomics because glycoproteins have been shown to function as biomarkers for disease and as promising therapeutic targets. A significant challenge in the study of glycoproteins is the fact that they are expressed in relatively low abundance in cells. In response, various enrichment methods have been developed to improve the detection of glycoproteins. One such method involves their capture via oxidation of their glycan chains and covalent attachment with hydrazide resins which, when catalyzed by PNGase F, release N-linked glycans and convert the glycosite Asn to Asp; this conversion is identifiable with LC/ESI-MS/MS as a corresponding increase of 0.984 Da in molecular weight. The present study builds on this body of work, providing evidence of three additional strategies that improve glycoprotein identification: (1) use of a high resolution mass spectrometer-the Q Exactive MS-which delivers 2-3 times more glycoprotein identifications than a low resolution MS; (2) optimization of instrument settings and database search parameters to reduce misidentification of N-linked glycopeptides to ~1 percent; and (3) labeling glycopeptides with (18)O during PNGase F treatment to locate N-linked glycosites within peptides containing multiple N-linked sequons.