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。存活率最近才开始提高，目前的5年存活率为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，它们单独和共同预测滤泡性淋巴瘤(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总体NHL存活率相关。我们建议复制和推广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相关性是否独立于肿瘤分子标志物，以及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。这项研究的总体目标是确定预测无事件和总体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的病理生理学，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修复基因的多态性与FL和DLBCL的无事件和总生存期的关系；2)评估肿瘤分子标志物与FL和DLBCL的无事件和总生存期的关系；以及3)建立结合标准人口学和临床特征、治疗、宿主遗传变异(目标1)和肿瘤分子标志物(目标2)的FL和DLBCL的多变量预测模型，以预测无事件和总的生存期。在第二个目标中，我们将评估诊断前的生活方式因素在非霍奇金淋巴瘤无事件和总存活率中的作用。为了实现这些目标，我们将使用淋巴瘤分子流行病学资源，这是一项持续的、前瞻性的预后队列研究，研究对象是2002年启动的梅奥诊所和爱荷华大学的新诊断病例。该资源具有多种方法优势，包括大样本量(2200例)、中央病理回顾和分类、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体存活率。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(S)。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确认为可靠的预后预测因子，这可能会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变化。宿主遗传学还可能导致对NHL病理生理学的更好理解，从而可能导致新的方法来提高NHL患者的存活率。

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.