Discovery of Cancer Biomarkers Through Metabolic Engineering

描述（由申请方提供）：已知蛋白质粘蛋白型O-连接糖基化的变化与癌症相关。然而，与粘蛋白型糖基化相关的复杂性和可用于研究此类糖蛋白的有限工具严重限制了我们对其参与疾病的理解。生物标志物的寻找正成为基于质谱的蛋白质组学领域的主要焦点。然而，蛋白质表达水平的变化一直是该领域的主要焦点。最近，已经开发了代谢工程和质谱技术来研究聚糖结构。这些技术为糖生物学家研究与生物标志物相关的聚糖结构变化提供了希望。我们的初步研究表明，通过施陶丁格连接或“点击化学”捕获代谢掺入的O-连接叠氮糖提供了一种使用质谱法（MS）检测糖蛋白的方法。我们提出了一种基于质谱的方法来检测与培养细胞和小鼠肝癌模型中糖蛋白聚糖结构变化相关的癌症生物标志物。本课题的具体目标是：（1）建立一种从复杂裂解物中鉴定粘蛋白型糖基化的方法。(2)开发一种方法，通过稳定同位素标记和质谱法定量复杂裂解物中蛋白质和糖基化水平的变化。(3)分析小鼠肝癌模型中粘蛋白型糖基化水平的变化。通过代谢工程将叠氮糖转化为糖蛋白，然后通过“点击化学”与可切割的亲和标签进行选择性化学反应，这将为我们提供一种使用质谱法检测糖蛋白的方法，所述糖蛋白不一定是最丰富的蛋白质，而是以高通量产生的蛋白质。使用具有独特特征的稳定同位素标记的炔基标签将允许我们检测和定量糖基化和非糖基化肽，并比较来自培养细胞的健康和患病样品与鼠肝癌模型TRE-MYCxl 4-TTA小鼠之间的表达水平差异。该项目将有助于我们从基础科学的角度以及癌症生物标志物的发现来理解粘蛋白型O-连接糖基化。由于几乎所有哺乳动物细胞中的蛋白质都含有糖，因此几乎可以在任何类型的组织中找到癌症的生物标志物。发现早期检测疾病的可靠生物标志物无疑将提高诊断的准确性和患者的长期生存率，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.