Elucidation of N-Glycosites Within Human Plasma Glycoproteins for Cancer Biomarker Discovery

Abstract

Glycans are an important class of post-translational modifications that decorate a wide array of protein substrates. These cell-type specific molecules, which are modulated during developmental and disease processes, are attractive biomarker candidates as biology regarding altered glycosylation can be used to guide the experimental design. The mass spectrometry (MS)-based workflow described here incorporates chromatography on affinity matrices formed from lectins, proteins that bind specific glycan motifs. The goal was to design a relatively simple method for the rapid analysis of small plasma volumes (e.g., clinical specimens). As increases in sialylation and fucosylation are prominent among cancer-associated modifications, we focused on Sambucus nigra agglutinin and AAL, which bind sialic acid- and fucose-containing structures, respectively. Positive controls (fucosylated and sialylated human lactoferrin glycopeptides), and negative controls (high-mannose glycopeptides from Saccharomyces cerevisiae invertase) were used to monitor the specificity of lectin capture and optimize the workflow. Multiple Affinity Removal System 14-depleted, trypsin-digested human plasma from healthy donors served as the target analyte. Samples were loaded onto the lectin columns and separated by high performance liquid chromatography (HPLC) into flow through and bound fractions, which were treated with PNGase F, an amidase that removes N-linked glycans and marks the underlying asparagine glycosite by a +1 Da mass shift. The deglycosylated peptide fractions were interrogated by HPLC ESI-MS/MS on a quadrupole time-of-flight mass spectrometer. The method allowed identification of 122 human plasma glycoproteins containing 247 unique glycosites. Notably, glycoproteins that circulate at ng/mL levels (e.g., cadherin-5 at 0.3–4.9 ng/mL, and neutrophil gelatinase-associated lipocalin which is present at ∼2.5 ng/mL) were routinely observed, suggesting that this method enables the detection of low-abundance cancer-specific glycoproteins.