A high- multiplexed phosphotyrosine profiling assay

描述（由申请人提供）：蛋白质酪氨酸磷酸化在肿瘤发生、进展和转移中涉及的许多生物学过程中起重要作用，因此肿瘤细胞酪氨酸磷酸化的总体模式与其生物学活性高度相关。因此，基于肿瘤酪氨酸磷酸化模式的检测和表征的分子诊断方法可能对分类和预后有用。在细胞中，蛋白质上的大多数酪氨酸磷酸化位点与小的模块化蛋白质结合结构域，特别是Src同源2（SH2）结构域紧密且特异性地结合。我们最近描述了一种方法，称为SH2分析，其中电池的SH2结构域探针是用来配置文件的蛋白质样品的酪氨酸磷酸化的全局状态。在目前的建议中，我们将开发一种新的多重SH2分析格式的基础上标记的SH2结构域探针与独特的寡核苷酸标签。这种新的方法将导致定量分析测定，是快速的，稳健的，可重复的，足够灵敏的临床标本的常规分析。在该提案的R21阶段，我们将证明多路复用（OTM）方法的可行性，并开发其他两种定量SH2分析格式，可用于验证OTM方法，并建立该方法用于肿瘤样本分类的实用性。在R33阶段，我们将进一步开发和优化OTM方法，以整合人类基因组中约150个磷酸酪氨酸结合模块的完整补充，并评估不同定量方法的性能和成本效益。我们还将充分开发生物信息学工具，以分析定量SH2结合数据，并根据结合模式的相似性对样本进行聚类，并对临床样本进行试点研究，以评估这些数据对癌症分子诊断分类的有用性。这些研究将为基于酪氨酸磷酸化模式的肿瘤分类提供一种新的工具，这可能有助于预测疾病的病程和对治疗的反应。他们还将确定OTM方法作为一种更通用的蛋白质组学工具的可行性，用于快速和灵敏地分析临床样本。

DESCRIPTION (provided by applicant): Protein tyrosine phosphorylation plays an important role in many of the biological processes involved in tumorigenesis, progression, and metastasis, and thus the global pattern of tyrosine phosphorylation of a tumor cell is highly relevant to its biological activity. It is likely, therefore, that molecular diagnostic methods based on the detection and characterization of tyrosine phosphorylation patterns in tumors will be useful for classification and prognosis. In the cell, most tyrosine phosphorylated sites on proteins bind tightly and specifically to small modular protein binding domains, in particular Src Homology 2 (SH2) domains. We have recently described a method, termed SH2 profiling, in which a battery of SH2 domain probes is used to profile the global state of tyrosine phosphorylation of a protein sample. In the current proposal, we will develop a novel multiplexed SH2 profiling format based on the labeling of SH2 domain probes with unique oligonucleotide tags. This novel approach will result in a quantitative profiling assay that is rapid, robust, reproducible, and sensitive enough for routine analysis of clinical specimens. In the R21 phase of the proposal we will demonstrate the feasibility of the oligonucleotide-tagged multiplexed (OTM) method and also develop two other quantitative SH2 profiling formats that can be used to validate the OTM method and to establish the utility of the approach for classification of tumor samples. In the R33 phase we will further develop and optimize the OTM method to incorporate the entire complement of approximately 150 phosphotyrosine-binding modules in the human genome and evaluate the performance and cost-effectiveness of different methods of quantitation. We will also fully develop bioinformatic tools to analyze quantitative SH2 binding data and cluster samples based on similarities in binding patterns and perform pilot studies on clinical samples to assess the usefulness of such data for molecular diagnostic classification of cancer. These studies will provide a novel tool for classifying tumors based on tyrosine phosphorylation patterns, which is likely to be useful in predicting the course of disease and response to therapy. They will also establish the feasibility of the OTM approach as a more general proteomic tool for the rapid and sensitive profiling of clinical samples.