Molecular Epidemiology of non-Hodgkin Lymphoma Survival

2008年，美国将有超过66,000人被诊断为非霍奇金淋巴瘤（NHL），超过19,000人将死于这种癌症。生存率最近才开始改善，目前的5年生存率为66%。我们已经确定了一些候选宿主（遗传）免疫基因和DNA修复基因，这些基因单独和总体上预测滤泡性淋巴瘤（FL）和弥漫性大b细胞淋巴瘤（DLBCL）的生存，超出了经典的临床和人口统计学预后因素。我们还发现，诊断前吸烟和肥胖与较差的NHL总生存率相关。我们建议复制和扩展这些具有挑衅性的发现。此外，在这些发现的基础上，我们将评估宿主遗传学的关联是否独立于肿瘤分子标记，并开始探索是否存在影响疾病进展和生存的宿主-肿瘤相互作用。本研究的总体目标是确定预测无事件生存和总生存的宿主遗传和肿瘤分子标记，以改善预后，更好地了解NHL病理生理，并最终帮助确定提高NHL患者生存的方法。我们的具体目标是：1)评估免疫和DNA修复基因多态性与FL和DLBCL无事件生存和总生存的关系；2)评价肿瘤分子标志物与FL和DLBCL无事件生存期和总生存期的关系；3)建立FL和DLBCL的多变量预测模型，将标准人口统计学和临床特征、治疗、宿主遗传变异（Aim 1）和肿瘤分子标记（Aim 2）结合起来，预测无事件生存期和总生存期。在次要目的中，我们将评估诊断前生活方式因素在非hl无事件生存和总生存中的作用。为了实现这些目标，我们将使用淋巴瘤分子流行病学资源，这是一项正在进行的，来自梅奥诊所和爱荷华大学于2002年启动的新诊断病例的前瞻性预后队列研究。该资源有几个方学优势，包括大样本量（约2200例）、中心病理回顾和分类、肿瘤组织的可用性、详细的基线临床预后数据、初始和后续治疗，以及在免疫化疗（利妥昔单抗）时代接受治疗的大量患者。我们系统地收集了详细的结果数据，这将使我们能够评估无事件和总生存期。我们还将能够在确定的人口统计学和临床预后因素以及所有治疗的背景下评估宿主遗传和肿瘤分子预后因素。在完成这些目标后，我们将同时评估宿主遗传变异和分子肿瘤标志物在FL和DLBCL预后中的作用。如果宿主遗传因素被证实是预后的可靠预测因素，这可能导致通过将宿主基因型纳入预后模型来评估患者预后的方式发生根本性转变。宿主遗传学也可能导致对NHL病理生理学的更好理解，从而可能导致提高NHL患者生存率的新方法。

In 2008, over 66,000 people in the US will be diagnosed with Non-Hodgkin lymphoma (NHL), and over 19,000 will die of this cancer. Survival rates have only recently begun to improve, and the current 5-year survival rate is 66%. We have identified a number of candidate host (inherited) immune genes and DNA repair genes that individually and in aggregate predict survival for follicular lymphoma (FL) and diffuse large B-cell lymphoma (DLBCL) beyond classic clinical and demographic prognostic factors. We have also found that pre-diagnosis smoking and obesity are associated with poorer overall NHL survival. We propose to replicate and extend these provocative findings. Furthermore, building off these findings, we will evaluate whether the association of host genetics is independent of tumor molecular markers, as well as begin to explore whether there are host–tumor interactions that impact disease progression and survival. The overall goal of this study is to identify host genetic and tumor molecular markers that predict event-free and overall survival in order to improve prognostication, better understand NHL pathophysiology, and ultimately help identify approaches to improve the survival of NHL patients. Our specific aims are: 1) To evaluate the association of polymorphisms in immune and DNA repair genes with event-free and overall survival from FL and DLBCL; 2) To evaluate the association of tumor molecular markers with event-free and overall survival from FL and DLBCL; and 3) To develop multivariate prediction models for FL and DLBCL that integrate standard demographic and clinical characteristics, treatment, host genetic variation (Aim 1) and tumor molecular markers (Aim 2) to predict eventfree and overall survival. In a secondary aim, we will evaluate the role of pre-diagnosis lifestyle factors with event-free and overall survival from NHL. To achieve these aims, we will use the Lymphoma Molecular Epidemiology Resource, an ongoing, prospective prognostic cohort study of newly diagnosed cases from the Mayo Clinic and the University of Iowa initiated in 2002. This resource has several methodologic strengths, including large sample size (>2200cases), central pathology review and classification, availability of tumor tissue, detailed baseline clinical prognostic data, initial and subsequent treatments, and a large patient population treated in the immunochemotherapy (rituximab) era. We have systematically collected detailed outcome data, which will allow us to evaluate both event-free and overall survival. We will also be able to evaluate host genetic and tumor molecular prognostic factors in the context of established demographic and clinical prognostic factors, as well as all treatment(s). Upon completion of these aims, we will have simultaneously evaluated the role of host genetic variation and molecular tumor markers in the prognosis of FL and DLBCL. If host genetic factors are confirmed as robust predictors of outcome, this could lead to a fundamental shift in how patient prognosis is evaluated by incorporating host genotype into prognostic models. Host genetics may also lead to a better understanding of NHL pathophysiology that could lead to new approaches to improve the survival of NHL patients.