UC Davis Cancer Center , Sacramento, California 95817, United States.
Department of Chemistry, University of California , Davis, California 95616, United States.
J Proteome Res. 2018 Jan 5;17(1):222-233. doi: 10.1021/acs.jproteome.7b00541. Epub 2017 Dec 19.
Protein glycosylation fingerprints are widely recognized as potential markers for disease states, and indeed differential glycosylation has been identified in multiple types of autoimmune diseases and several types of cancer. However, releasing the glycans leave the glycoproteins unknown; therefore, there exists a need for high-throughput methods that allow quantification of site- and protein-specific glycosylation patterns from complex biological mixtures. In this study, a targeted multiple reaction monitoring (MRM)-based method for the protein- and site-specific quantitation involving serum proteins immunoglobulins A, G and M, alpha-1-antitrypsin, transferrin, alpha-2-macroglobulin, haptoglobin, alpha-1-acid glycoprotein and complement C3 was developed. The method is based on tryptic digestion of serum glycoproteins, followed by immediate reverse phase UPLC-QQQ-MS analysis of glycopeptides. To quantitate protein glycosylation independent of the protein serum concentration, a nonglycosylated peptide was also monitored. Using this strategy, 178 glycopeptides and 18 peptides from serum glycoproteins are analyzed with good repeatability (interday CVs of 3.65-21-92%) in a single 17 min run. To assess the potential of the method, protein glycosylation was analyzed in serum samples from ovarian cancer patients and controls. A training set consisting of 40 cases and 40 controls was analyzed, and differential analyses were performed to identify aberrant glycopeptide levels. All findings were validated in an independent test set (n = 44 cases and n = 44 controls). In addition to the differential glycosylation on the immunoglobulins, which was reported previously, aberrant glycosylation was also observed on each of the glycoproteins, which could be corroborated in the test set. This report shows the development of a method for targeted protein- and site-specific glycosylation analysis and the potential of such methods in biomarker development.
蛋白质糖基化指纹广泛被认为是疾病状态的潜在标志物，事实上，在多种自身免疫性疾病和几种类型的癌症中已经鉴定出了差异糖基化。然而，释放聚糖会使糖蛋白未知；因此，需要高通量的方法来允许从复杂的生物混合物中定量测定位点和蛋白质特异性糖基化模式。在这项研究中，开发了一种基于靶向多重反应监测（MRM）的方法，用于定量涉及血清蛋白免疫球蛋白 A、G 和 M、α-1-抗胰蛋白酶、转铁蛋白、α-2-巨球蛋白、触珠蛋白、α-1-酸性糖蛋白和补体 C3 的蛋白质和位点特异性糖基化模式。该方法基于血清糖蛋白的胰蛋白酶消化，然后立即进行反向相 UPLC-QQQ-MS 对糖肽进行分析。为了独立于血清蛋白浓度定量蛋白质糖基化，还监测了一种非糖基化肽。使用这种策略，在单个 17 分钟运行中，从血清糖蛋白中分析了 178 个糖肽和 18 个肽，具有良好的重复性（日内 CV 值为 3.65-21-92%）。为了评估该方法的潜力，分析了卵巢癌患者和对照者的血清样本中的蛋白质糖基化。分析了由 40 例病例和 40 例对照组成的训练集，并进行了差异分析以确定异常糖肽水平。所有发现均在独立测试集（n = 44 例和 n = 44 例对照）中进行了验证。除了先前报道的免疫球蛋白的差异糖基化外，还观察到每种糖蛋白上的异常糖基化，在测试集中也得到了证实。本报告展示了一种用于靶向蛋白质和位点特异性糖基化分析的方法的开发，以及此类方法在生物标志物开发中的潜力。
