Mathematical model relating gene expression to glycoform structure

描述(申请人提供)：葡聚糖是高度可变和结构多样化的糖链，当连接到膜蛋白和脂类时，是哺乳动物细胞表面的主要特征。在包括癌症在内的许多疾病中，糖链结构的分布往往与正常细胞不同，这导致了疾病特有的糖链结构及其功能可以用于诊断和治疗的诱人可能性。然而，由于难以分析细胞上发现的数以千计的寡糖结构，基于多糖的临床程序的开发一直受到阻碍，这些结构通常以微量存在，这使得结构表征成为一个艰巨的挑战。与蛋白质结构相反，糖链结构不是直接在基因组中编码的，因此没有允许PCR型扩增的模板，这一事实使这些困难变得更加复杂。相反，多糖的结构是由许多糖基化酶与蛋白质和其他代谢物的复杂相互作用决定的。该项目的目标是开发数学建模技术，以预测糖基化基因表达的变化如何影响细胞上发现的高度多样化的糖链结构。以这种方式将糖链结构分布与遗传修饰或容易获得的基因表达数据联系起来，将极大地促进基于糖链的诊断标记或治疗干预的开发；该项目的目标是开发一种计算机模型来预测特定疾病的糖链，并使这项技术可供医学研究人员商业使用。该项目将主要利用公开可用的关于酶性质、糖基因表达水平和糖链图谱的实验数据来源来开发和完善数学模型。除文献资源外，还将充分利用这些数据的网上汇编。该项目还将与约翰霍普金斯大学正在进行的实验糖生物学计划合作，以互动地评估原型实施用于研究指导的使用。该技术包括定性和定量两个方面。定性方面包括预测可能由给定的起始结构和给定的糖基化酶列表产生的糖链结构。例如，一个(或少量)新出现的结构是某些癌症恶性程度的有力指标。定量方面将产生的各种糖链结构的丰度与糖基化酶的一组表达水平联系起来；这种复杂程度将对评估条件很有价值，例如Pron病，在这些疾病中，数十个或数百个结构丰度的细微差异可能与致病性有关。该项目的最终产品将是一个软件系统，以商业软件包的形式向公众提供，以绘制基因表达和糖链结构之间的关系。该项目的结果将提供一个计算机工具系统，帮助研究人员确定癌症等严重疾病的新诊断方法，并开发治疗这些疾病的新疗法。这些工具将在基本的细胞过程和细胞表面显示的化学结构之间建立联系，这些化学结构控制着正常和恶性细胞之间的相互作用。该项目的最终产品将是一个软件系统，其中包含定性和定量工具，以绘制基因表达和糖链结构之间的关系图。该系统将以商业软件包的形式向公众提供。

DESCRIPTION (provided by applicant): Glycans are highly variable and structurally diverse sugar chains that, when attached to membrane proteins and lipids, are the dominant feature of the mammalian cell surface. In many diseases, including cancer, the distribution of glycan structures often differs from normal cells leading to the enticing possibility that disease- specific glycan structures and their functions can be used diagnostically and therapeutically. Development of glycan-based clinical procedures, however, has been hindered by the difficulty of analyzing the thousands of oligosaccharide structures found on cells, which are usually present in minute quantities that make structural characterization a formidable challenge. These difficulties are compounded by the fact that, in contrast to protein structures, glycan structures are not directly encoded in the genome and no template is therefore available that would allow PCR-type amplification. Instead, the structure of glycans is determined by a complex interaction of many glycosylation enzymes with proteins and other metabolites. The objective of this project is to develop mathematical modeling technology to predict how changes in the expression of glycosylation genes - now readily obtained through DNA microarray experiments - affect the highly diverse repertoire of glycan structures found on cells. Linking glycan structure distributions to genetic modifications or easily obtained gene expression data in this manner will greatly facilitate development of glycan-based diagnostic markers or therapeutic interventions; the goal of this project is to develop a computer model to predict disease-specific glycans and to make this technology commercially available to medical researchers. The project will primarily utilize publicly available experimental data sources on enzyme properties, glycogene expression levels and glycan profiles to develop and refine the mathematical model. Full advantage will be taken of web based compilations of these data in addition to literature resources. The project will also collaborate with ongoing experimental glycobiology programs at Johns Hopkins in order to evaluate the use of a prototype implementation interactively for research guidance. The technology includes both a qualitative and quantitative aspect. The qualitative aspect involves predicting the possible glycan structures that can result from a given starting structure and a given list of glycosylation enzymes. For example, the de novo appearance of one (or a small number) of structures is a powerful indicator of the malignant status of certain cancers. The quantitative aspect relates the abundances of the various glycan structures produced to the set of expression levels of the glycosylation enzymes; this level of sophistication will be valuable for assessing conditions such as prion disease where subtle differences in the abundances of dozens, or hundreds, of structures may be related to pathogenicity. The final product of the project would be a software system, made available to the public as a commercial software package to map the relationship between gene expression and glycan structure in either direction. The results of this project will provide a system of computer tools to help researchers determine new diagnostic methods for serious diseases, such as cancer, and develop new therapies for treating these diseases. The tools will make a link between fundamental cellular processes and the chemical structures displayed on cell surfaces, which control, for example, interactions between normal and malignant cells. The final product of the project would be a software system that contains both qualitative and quantitative tools to map the relationship between gene expression and glycan structure in either direction. The system would be made available to the public as a commercial software package.