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Cancer Control Research

Abstract

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.