Kyselova Zuzana, Mechref Yehia, Kang Pilsoo, Goetz John A, Dobrolecki Lacey E, Sledge George W, Schnaper Lauren, Hickey Robert J, Malkas Linda H, Novotny Milos V
National Center for Glycomics and Glycoproteomics, Department of Chemistry, Indiana University, Bloomington, IN 47405, USA.
Clin Chem. 2008 Jul;54(7):1166-75. doi: 10.1373/clinchem.2007.087148. Epub 2008 May 16.
Glycosylated proteins play important roles in cell-to-cell interactions, immunosurveillance, and a variety of receptor-mediated and specific protein functions through a highly complex repertoire of glycan structures. Aberrant glycosylation has been implicated in cancer for many years.
We performed specific MALDI mass spectrometry (MS)-based glycomic profile analyses of permethylated glycans in sera from breast cancer patients (12, stage I; 11, stage II; 9, stage III; and 50, stage IV) along with sera from 27 disease-free women. The serum glycoproteins were enzymatically deglycosylated, and the released glycans were purified and quantitatively permethylated before their MALDI-MS analyses. We applied various statistical analysis tools, including ANOVA and principal component analysis, to evaluate the MS profiles.
Two statistical procedures implicated several sialylated and fucosylated N-glycan structures as highly probable biomarkers. Quantitative changes according to a cancer stage resulted when we categorized the glycans according to molecular size, number of oligomer branches, and abundance of sugar residues. Increases in sialylation and fucosylation of glycan structures appeared to be indicative of cancer progression. Different statistical evaluations confirmed independently that changes in the relative intensities of 8 N-glycans are characteristic of breast cancer (P < 0.001), whereas other glycan structures might contribute additionally to distinctions in the statistically recognizable patterns (different stages).
MS-based N-glycomic profiling of serum-derived constituents appears promising as a highly sensitive and informative approach for staging the progression of cancer.
糖基化蛋白通过高度复杂的聚糖结构库在细胞间相互作用、免疫监视以及各种受体介导的和特定的蛋白功能中发挥重要作用。异常糖基化与癌症的关联已有多年。
我们对乳腺癌患者（I期12例；II期11例；III期9例；IV期50例）以及27名无病女性的血清中经全甲基化的聚糖进行了基于基质辅助激光解吸电离质谱（MALDI-MS）的特定糖组分析。血清糖蛋白经酶法去糖基化，释放出的聚糖经纯化并在进行MALDI-MS分析前进行定量全甲基化。我们应用了包括方差分析和主成分分析在内的各种统计分析工具来评估质谱图。
两种统计程序表明几种唾液酸化和岩藻糖基化的N-聚糖结构极有可能是生物标志物。当我们根据分子大小、寡聚体分支数量和糖残基丰度对聚糖进行分类时，发现糖基化结构根据癌症分期存在定量变化。聚糖结构中唾液酸化和岩藻糖基化的增加似乎表明癌症进展。不同的统计评估独立证实，8种N-聚糖相对强度的变化是乳腺癌的特征（P < 0.001），而其他聚糖结构可能在统计学上可识别的模式（不同分期）差异中起到额外作用。
基于质谱的血清成分N-糖组分析作为一种对癌症进展进行分期的高度敏感且信息丰富的方法，似乎很有前景。
