A high- multiplexed phosphotyrosine profiling assay

描述（由申请人提供）：蛋白酪氨酸磷酸化在许多涉及肿瘤发生、进展和转移的生物学过程中起着重要作用，因此肿瘤细胞酪氨酸磷酸化的全局模式与其生物活性高度相关。因此，基于检测和表征肿瘤中酪氨酸磷酸化模式的分子诊断方法可能有助于分类和预后。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域紧密特异性结合，特别是Src同源性2 （SH2）结构域。我们最近描述了一种称为SH2分析的方法，其中使用一组SH2结构域探针来分析蛋白质样品的酪氨酸磷酸化的全局状态。在目前的提案中，我们将开发一种新的基于SH2结构域探针标记独特寡核苷酸标签的复用SH2分析格式。这种新颖的方法将导致定量分析分析，是快速，稳健，可重复性和敏感的临床标本的常规分析。在提案的R21阶段，我们将展示寡核苷酸标记多路复用（OTM）方法的可行性，并开发另外两种定量SH2分析格式，可用于验证OTM方法并建立该方法对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，以纳入人类基因组中约150个磷酸酪氨酸结合模块的整个补体，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来分析定量SH2结合数据和基于结合模式相似性的聚类样本，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。这些研究将提供一种基于酪氨酸磷酸化模式对肿瘤进行分类的新工具，这可能有助于预测疾病的进程和对治疗的反应。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，用于快速和敏感地分析临床样品。

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.