Molecular Signatures to Improve Diagnosis and Outcome Pr

描述(由申请人提供)： 定义非霍奇金淋巴瘤(NHL)常见类别的基因表达特征已经被识别，包括一些以前没有识别的独特的亚型。对这些NHL的分子预测也进行了描述。我们最近开发了一种具有2500多个特征的DNA微阵列，包括所有已知的NHL诊断和预后参数。我们建议使用这个数组来研究2400个新的案例，以验证和改进当前以及随着研究的进展新发现的签名和算法。这一目标的实现将为准确的诊断和预后应用提供一个强大的、成本效益高的系统。还将开发一种可应用于石蜡包埋组织的替代的定量(Q)RT-PCR平台。它将纳入来自微阵列平台的基本信息，并允许评估并非专门为微阵列分析收集的样本的关键参数，从而极大地扩大信息的用途。有证据表明，遗传数据可能会为目前的基因表达衍生的预后指标提供额外的预后信息。我们建议获得弥漫性大B细胞淋巴瘤的全面、高分辨率的分子遗传学数据，以检查遗传参数和基因表达参数的组合是否会改善当前的预后模型。由于现有的预测指标是在抗CD20治疗可用之前对档案病例的研究得出的，因此将在接受当前治疗方案的患者中重新评估这些预测指标。将进行修改，以保持预测者的准确性。这项研究不仅将验证先前定义的诊断和预后特征，而且将进一步改进特征和算法，以获得更高的准确性和稳健性。通过将信息改编到Q-RT-PCR平台上，扩大了应用范围。通过纳入遗传数据将增强预测者，并通过重新评估接受当前治疗方案治疗的患者队列来更新预测者。

DESCRIPTION (provided by applicant): Gene expression signatures that define the common categories of non-Hodgkin's lymphoma (NHL) have been identified, including some unique subtypes not recognized previously. Molecular prognosticators for these NHLs have also been described. We have recently developed a DNA microarray with over 2500 features, including all known diagnostic and prognostic parameters for NHL. We propose to use this array to study 2400 new cases to validate and refine current as well as newly discovered signatures and algorithms as the study progresses. Completion of this aim will provide a robust, cost-effective system for accurate diagnostic and prognostic applications. An alternative, quantitive(Q) RT-PCR based platform that can be applied to paraffin-embedded tissue will also be developed. It will incorporate the essential information from of the microarray platform and allow the assessment of critical parameters in specimens not specifically collected for microarray analysis, hence greatly expanding the utility of the information. There is evidence that genetic data may provide additional prognostic information to the current gene expression-derived prognosticators. We propose to obtain comprehensive, high-resolution molecular genetic data on diffuse large B-cell lymphoma to examine if the combination of genetic and gene expression parameters will improve the current prognostic model. Since existing prognosticators were derived from the study of archival cases prior to the availablility of anti-CD20 therapy, they will be re-evaluated in patients treated with current therapeutic regimens. Modifications will be made to maintain the accuracy of the prognosticators. This study will not only validate previously-defined diagnostic and prognostic signatures, but will further refine the signatures and algorithms for higher accuracy and robustness. The range of application will be expanded by adapting the information to a Q-RT-PCR platform. Prognosticators will be enhanced by the incorporation of genetic data, and updated by a re-evaluation of cohorts of patients treated with current therapeutic regimens.