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）的常见类别的基因表达特征已被确定，包括一些以前未识别的独特亚型。也已经描述了这些NHL的分子生物学。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个新案例，以验证和完善当前以及新发现的签名和算法。这一目标的完成将为准确的诊断和预后应用提供一个强大的，具有成本效益的系统。还将开发一种可应用于石蜡包埋组织的替代定量（Q）RT-PCR平台。它将整合来自微阵列平台的基本信息，并允许评估未专门收集用于微阵列分析的样本中的关键参数，从而极大地扩展了信息的实用性。有证据表明，遗传数据可以提供额外的预后信息，目前的基因表达衍生的预测。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，以检查遗传和基因表达参数的组合是否会改善目前的预后模型。由于现有的促分化因子来源于抗CD 20治疗可用之前的存档病例研究，因此将在接受当前治疗方案治疗的患者中对其进行重新评价。将进行修改，以保持计量器的准确性。这项研究不仅将验证先前定义的诊断和预后特征，还将进一步完善特征和算法，以提高准确性和鲁棒性。通过使信息适应Q-RT-PCR平台，将扩大应用范围。通过纳入遗传学数据，将增强预后指标，并通过重新评估接受当前治疗方案治疗的患者队列进行更新。

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.