Mucin domains are densely O-glycosylated modular protein domains found in a wide variety of cell surface and secreted proteins. Mucin-domain glycoproteins are key players in a host of human diseases, especially cancer, but the scope of the mucinome remains poorly defined. Recently, we characterized a bacterial mucinase, StcE, and demonstrated that an inactive point mutant retains binding selectivity for mucins. In this work, we leveraged inactive StcE to selectively enrich and identify mucins from complex samples like cell lysate and crude ovarian cancer patient ascites fluid. Our enrichment strategy was further aided by an algorithm to assign confidence to mucin-domain glycoprotein identifications. This mucinomics platform facilitated detection of hundreds of glycopeptides from mucin domains and highly overlapping populations of mucin-domain glycoproteins from ovarian cancer patients. Ultimately, we demonstrate our mucinomics approach can reveal key molecular signatures of cancer from in vitro and ex vivo sources.
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