Epigenomic determinants of clinical outcomes in MCL patients treated on E1405

描述(申请人提供)：套细胞淋巴瘤(MCL)是一种侵袭性的非霍奇金淋巴瘤，其发病机制尚不清楚。大多数患者复发并最终死于这种疾病，迫切需要新的治疗方案来治疗复发的MCL。来自我们实验室和其他实验室的数据表明，DNA甲基化在整个MCL基因组中的分布发生了深刻的变化。受甲基化改变影响的基因涉及关键的细胞内过程，如转录、细胞周期和细胞生存。对全基因组甲基化和表达的综合分析可以产生生物学见解，并识别仅凭基因表达不明显的患者亚群。此外，使用基于数组的技术的甲基化特征可以预测患者的预后。与基于微阵列的方法相比，大规模并行测序(MPS)方法具有更大的动态范围、更灵敏、更全面地捕捉基因组信息。我们假设，对DNA甲基化和基因表达的高分辨率综合分析可以确定原发性MCL临床结局的关键表观基因组决定因素。因此，我们建议使用RNA-seq和Help标记的深度测序来分析来自三组MCL患者的预处理肿瘤样本中的全基因组RNA表达和甲基化，这些患者包括：(A)接受ECOG 1405治疗的患者，这是一项针对MCL的VCR-CVAD加维持性利妥昔单抗的多中心II期临床试验；(B)由威斯康星大学网络治疗的MCL患者；以及(C)在哈肯萨克大学医学中心接受治疗的MCL患者。我们将确定与预后相关的差异甲基化/表达基因，然后建立一个预测临床结果的多变量模型。我们的相关研究利用这些高分辨率平台和库标本提供的独特机会，以(1)改善对可能从化疗中受益的MCL患者的选择(2)识别仅通过基因表达谱不明显的临床相关患者亚组，以及(3)了解MCL临床结果不同的生物学基础。

DESCRIPTION (provided by applicant): Mantle cell lymphoma (MCL) is an aggressive form of Non-Hodgkin's lymphoma whose pathogenesis is not clearly understood. Most patients relapse and eventually die of this disease, and new treatment options for relapsed MCL are urgently needed. Data from our lab and others suggests that there are profound changes in distribution of DNA methylation across the MCL genome. The genes affected by changes in methylation involve critical intracellular processes like transcription, cell cycle and cell survival. Integratve analysis of genome-wide methylation and expression can yield biological insights and identify patient subgroups that are not apparent by gene expression alone. Moreover, methylation signatures using array-based techniques can be prognostic and predictive for patient outcomes. Measurement of DNA methylation and RNA transcript abundance by massively parallel sequencing (MPS) has a greater dynamic range, is more sensitive, and captures genomic information more completely than microarray based approaches. We hypothesize that integrative high-resolution analysis of DNA methylation and gene expression can identify the key epigenomic determinants of clinical outcomes in primary MCL. We therefore propose to use RNA-seq and HELP-tagged deep sequencing to assay genome-wide RNA expression and methylation, in pretreatment tumor samples from three cohorts of MCL patients (a) Patients treated on ECOG 1405, a multicenter Phase II clinical trial of VcR-CVAD with maintenance Rituximab for MCL (b) MCL patients treated by the University of Wisconsin Network and (c) MCL patients treated at Hackensack University Medical Center. We will identify the differentially methylated/expressed genes associated with prognosis and then build a multi-variable model predictive for clinical outcomes. Our correlative studies leverage the unique opportunity provided by these high resolution platforms and banked specimens towards (1) improving selection of MCL patients likely to benefit most from chemotherapy (2) identifying clinically relevant patient sub-groups not apparent by gene expression profiling alone and (3) understanding the biological basis for heterogeneous clinical outcomes in MCL.