Discovery of Cancer Biomarkers Through Metabolic Engineering

描述(由申请人提供)：已知粘蛋白O型连接糖基化蛋白的变化与癌症有关。然而，与粘蛋白糖基化相关的复杂性和可用于研究此类糖蛋白的有限的工具严重限制了我们对它们与疾病的关系的了解。寻找生物标志物正成为基于质谱学的蛋白质组学领域的一个主要焦点。然而，蛋白质表达水平的变化一直是这一领域的主要焦点。最近，代谢工程和质谱学技术被用来研究多糖结构。这些技术为糖生物学家研究与生物标记物相关的糖链结构的变化带来了希望。我们的初步研究表明，通过Staudinger连接或“点击化学”捕获代谢结合的O-连接叠氮糖提供了一种使用质谱学(MS)检测糖蛋白的方法。我们提出了一种基于质谱学的方法来检测与培养细胞和小鼠肝癌模型中糖蛋白的糖结构变化相关的癌症生物标志物。该提案的具体目的是(1)开发一种从复杂的裂解物中鉴定粘蛋白型糖基化的方法。(2)建立一种通过稳定同位素标记和质谱学来量化复杂裂解产物中蛋白质和糖基化水平变化的方法。(3)分析小鼠肝癌模型中粘蛋白糖基化水平的变化。通过代谢工程将叠氮糖掺入糖蛋白中，然后通过带有可切割亲和标记的“点击化学反应”进行选择性化学反应，将为我们提供一种使用质谱学检测糖蛋白的方法，这些糖蛋白不一定是最丰富的蛋白质，但那些在高通量下产生的蛋白质。使用具有独特签名的稳定同位素标记的炔基标签将使我们能够检测和量化糖基化和非糖基化的多肽，并比较来自培养细胞和小鼠肝癌模型tre-MYCxLAP-TTA小鼠的健康和患病样本之间的表达水平差异。这项拟议的项目将有助于我们从基础科学的角度理解粘蛋白O-连接糖基化，以及癌症生物标志物的发现。与公众健康相关由于几乎所有哺乳动物细胞的蛋白质中都存在糖，因此在几乎任何类型的组织中都有可能找到癌症的生物标记物。发现可靠的早期发现疾病的生物标志物，无疑将提高诊断的准确性和患者的长期生存，并为药物开发提供治疗靶点。

DESCRIPTION (provided by applicant): Changes in mucin-type O-linked glycosylation of proteins are known to be linked to cancer. However, the complexity associated with mucin-type glycosylation and the limited tools available to study such glycoproteins has severely limited our understanding of their involvement in disease. The search for biomarkers is becoming a major focus in the field of mass spectrometry-based proteomics. However, changes in protein expression levels have been the main focus in this field. More recently, metabolic engineering and mass spectrometric techniques have been developed to study glycan structure. These techniques hold promise for glycobiologists studying changes to glycan structure related to biomarkers. Our preliminary studies have shown capture of metabolically incorporated O-linked azidosugars by Staudinger Ligation or "click chemistry" provides a method of detection for glycoproteins using mass spectrometry (MS). We propose a mass spectrometry-based method to detect biomarkers of cancer associated with changes to glycan structure of glycoproteins in cultured cells and a murine liver cancer model. Specific aims of the proposal are (1) Develop a method for identifying mucin-type glycosylation from complex lysates. (2) Develop a method to quantify changes in protein and glycosylation levels in complex lysates through stable isotope labeling and mass spectrometry. (3) Analyze changes in mucin-type glycosylation levels in a murine liver cancer model. Incorporating azidosugars into glycoproteins through metabolic engineering followed by a selective chemical reaction via "click chemistry" with a cleavable affinity tag will provide us with a method for the detection of glycoproteins using mass spectrometry that are not necessarily the most abundant proteins, but those that are produced at high flux. The use of a stable isotope labeled alkynyl tag with a unique signature will allow us to detect and quantify glycosylated and non-glycosylated peptides and compare differences in expression levels between healthy and diseased samples from cultured cells and a murine liver cancer model, the TRE-MYCxLAP-TTA mouse. The proposed project will contribute to our understanding of mucin-type O-linked glycosylation both from a basic science perspective as well as the discovery of cancer biomarkers. PUBLIC HEALTH RELEVANCE As sugars are found on proteins in nearly all mammalian cells, it is possible to find biomarkers of cancer in virtually any type of tissue. The discovery of reliable biomarkers for early detection of disease would undoubtedly improve the accuracy of diagnosis and long-term patient survival, and provide therapeutic targets for drug development.