Cytokine Polymorphisms and Cancer Related Pain

描述（由申请人提供）： 疼痛是肺癌患者最具破坏性、持续性和致残性的症状之一。预测重度疼痛风险的能力是早期症状干预的基础。我们正在为一项旨在确定肺癌患者疼痛严重程度的流行病学和遗传预测因子的研究寻求资金。疾病相关变量、临床健康状况和社会人口学特征的影响仅解释了症状中观察到的较小差异。动物和人类研究表明，细胞因子在疼痛生物学中的重要作用。具体而言，已经显示，脑中神经胶质细胞响应于体内促炎细胞因子的释放而重新合成促炎细胞因子可促进和调节疼痛。细胞因子是由癌细胞异常产生的。因此，我们假设免疫标记物（血浆细胞因子）的表达谱受细胞因子基因变体的调节，并且在重度疼痛患者与无重度疼痛患者之间存在差异。拟议的研究是建立在一个广泛的数据和标本库的原发性肺癌患者的所有阶段，年龄和组织学在MD。安德森癌症中心，来自NIH资助的研究（Margaret Spitz，PI），该研究收集了756例新诊断的、先前未经治疗的原发性肺癌白色高加索患者的生物样本。在所有情况下，在任何癌症治疗之前，在基线时收集关于疼痛的信息。我们的初步数据（n=514）支持我们的假设细胞因子基因（IL 8）对疼痛的严重程度的重要作用，最近已被接受出版。此外，一组关于炎症途径的基因分型数据已经通过父母资助获得。我们现在建议通过测量关键细胞因子（IL-1a，IL-1？，IL 1 RN，IL-2，IL-4，IL-6，IL-8，IL-10，TNF-α）的血浆水平，并将选定的基因型与细胞因子水平相关联，以评估多态性，细胞因子水平和疼痛严重程度之间的关联，从而建立这些令人信服的初步数据。具体目标是：1）评估9个关键细胞因子基因多态性的患病率（IL-1 α、IL-1 β、IL-1 RN、IL-2、IL-4、IL-6、IL-8、IL-10、TNF-α）并测定756例肺癌患者的相关细胞因子的血浆蛋白水平;并评估多态性、细胞因子水平和疼痛严重程度之间的关联;和3）使用先进的统计方法产生结合生物学数据的统计风险模型，用于预测肺癌患者的疼痛严重程度;并通过检查受试者工作特征曲线下的面积和执行三重交叉验证来评估模型的预测性能。长期目标是开发定量的多变量风险评估模型，以确定从早期疼痛干预中受益的患者亚组，并可能为癌症治疗方案提供信息。虽然近年来肺癌患者的生存率有所提高，但大多数患者仍然感到痛苦和痛苦。了解宿主对严重疼痛的遗传易感性对于减轻癌症负担及其治疗至关重要。这项研究的结果具有巨大的临床和公共卫生意义。

DESCRIPTION (provided by applicant): Pain is one of the most devastating, persistent and incapacitating symptoms in patients with lung cancer. The ability of predicting the risk for severe pain is fundamental for early symptom intervention. We seek funding for a study designed to identify epidemiologic and genetic predictors of pain severity in patients with lung cancer. The impact of disease-related variables, clinical health status and sociodemographic characteristics only account for a small variance observed in symptoms. Animal and human studies suggest an important role of cytokines in the biology of pain. Specifically, de novo synthesis of proinflammatory cytokines by glia in the brain in response to the release of proinflammatory cytokines in the body has been shown to facilitate and modulate pain. Cytokines are aberrantly produced by cancer cells. Accordingly, we hypothesize that expression profiles of immune markers (plasma cytokines) are modulated by variants in cytokine genes and will differ among patients with severe pain versus those without severe pain. The proposed study is built upon an extensive data and specimen repository of primary lung cancer patients of all stages, ages and histologies at M.D. Anderson Cancer Center, derived from an NIH-funded study (Margaret Spitz, PI) that has collected biologic samples on 756 White Caucasian patients with newly diagnosed, previously untreated primary lung cancer. In all cases, information on pain was collected at baseline, prior to any cancer treatment. Our preliminary data (n=514) supporting our hypothesis on the important role of cytokine genes (IL8) on pain severity have recently been accepted for publication. In addition, a panel of genotyping data on the inflammation pathway has become available through the parent grant. We now propose to build upon these compelling preliminary data by measuring plasma levels of key cytokines (IL-1a, IL-1¿, IL1RN, IL-2, IL4, IL-6, IL-8, IL-10, TNF-a) and correlating the select genotypes with cytokine levels to assess the association between polymorphisms, cytokine levels, and pain severity. The specific aims are: 1) To assess the prevalence of polymorphisms in 9 key cytokine genes (IL-1a, IL-1¿, IL-1RN, IL-2, IL4, IL-6, IL-8, IL-10, TNF-a) and to measure plasma protein levels of relevant cytokines in 756 patients of all histologies and stages of lung cancer; 2) To correlate genotype with cytokine levels; and assess the associations between polymorphisms, cytokine levels, and pain severity; and 3) To generate a statistical risk model incorporating biologic data for predicting the severity of pain in lung cancer patients using advanced statistical methods; and assess the predictive performance of the model by examining the areas under the receiver operating characteristic curves and performing three-fold cross validation. The long-term goal is to develop quantitative multivariate risk assessment models to identify patient subgroups that would benefit from early pain intervention and potentially inform cancer treatment options. Although improvements in the survival rates of patients with lung cancer have been observed in recent years, the majority of patients still experience distress and suffering. Understanding host genetic susceptibility to severe pain is critical to efforts in reducing the burden of cancer and its treatment. The results of this study have immense clinical and public health significance.