SH2 PROFILING

本子项目是利用由NIH/NCRR资助的中心赠款提供的资源的众多研究子项目之一。子项目和研究者（PI）可能已经从另一个NIH来源获得了主要资金，因此可以在其他CRISP条目中表示。列出的机构是中心的，不一定是研究者的机构。我们需要一种分子诊断工具，使肿瘤的分类超越目前使用标准技术所能做到的。理想情况下，将确定具有预后价值的标志物（例如，与特定治疗的反应相关）。使用cDNA微阵列的表达谱分析目前正在为此目的进行测试，但目前是繁琐的，昂贵的，并且不太可能提供有关肿瘤细胞分子缺陷的任何信息。我们正在开发一种新的分子诊断技术，该技术基于肿瘤样本中与某些已知在信号转导中起重要作用的蛋白质结构域结合的蛋白质谱。在初步实验中，该技术可以在相似的肿瘤类型中识别不同的结合谱，这表明它可能是一种有价值的分子诊断工具。所得到的谱也可以提供关于特定肿瘤分子缺陷的信息。我们建议在康涅狄格大学健康中心提供的造血恶性肿瘤样本上测试这项技术，以确定在更大规模实施的可行性。最终，如果技术足够稳健和可重复性，我们将把分析数据与患者信息联系起来，以确定相互作用分析是否提供具有预后价值的信息。

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. There is a need for molecular diagnostic tools that will allow the classification of tumors beyond what is currently possible using standard techniques. Ideally, markers will be identified that will have prognostic value (correlate with response to particular treatments, for example). Expression profiling using cDNA microarrays is now being tested for this purpose, but is at present cumbersome, costly, and is unlikely to give any information about the molecular defects in the tumor cell. We are developing a novel molecular diagnostic technique based on the profile of proteins in a tumor sample that bind to certain protein domains known to play an important role in signal transduction. In preliminary experiments this technique can identify different binding profiles in similar tumor types, suggesting it may be a valuable molecular diagnostic tool. The resulting profiles may also be informative about the molecular defects in a particular tumor. We propose to test this technique on samples from hematopoietic malignancies available at the UConn Health Center to establish the feasibility of implementation on a larger scale. Ultimately, if the technique is sufficiently robust and reproducible, we will correlate profiling data with patient information to determine whether the interaction profiling provides information with prognostic value.