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Cancer Epidemiology Biomarkers & Prevention

Year: 2009  |  Volume: 18  |  Issue: 6  |  Page No.: 1829 - 1840

Cytokine and Cytokine Receptor Single-Nucleotide Polymorphisms Predict Risk for Non-Small Cell Lung Cancer among Women

A. L Van Dyke, M. L Cote, A. S Wenzlaff, W Chen, J Abrams, S Land, C. N Giroux and A. G. Schwartz


Studies on the relationships between inflammatory pathway genes and lung cancer risk have not included African-Americans and have only included a handful of genes. In a population-based case-control study on 198 African-American and 744 Caucasian women, we examined the association between 70 cytokine and cytokine receptor single-nucleotide polymorphisms (SNPs) and risk of non–small cell lung cancer (NSCLC). Unconditional logistic regression was used to estimate odds ratios and 95% confidence intervals in a dominant model adjusting for major risk factors for lung cancer. Separate analyses were conducted by race and by smoking history and history of chronic obstructive pulmonary disease among Caucasians. Random forest analysis was conducted by race. On logistic regression analysis, IL6 (interleukin 6), IL7R, IL15, TNF (tumor necrosis factor), and IL10 SNP were associated with risk of non–small cell lung cancer among African-Americans; IL7R and IL10 SNPs were also associated with risk of lung cancer among Caucasians. Although random forest analysis showed IL7R and IL10 SNPs as being associated with risk for lung cancer among African-Americans, it also identified TNFRSF10A SNP as an important predictor. On random forest analysis, an IL1A SNP was identified as an important predictor of lung cancer among Caucasian women. Inflammatory SNPs differentially predicted risk for NSCLC according to race, as well as based on smoking history and history of chronic obstructive pulmonary disease among Caucasian women. Pathway analysis results are presented. Inflammatory pathway genotypes may serve to define a high risk group; further exploration of these genes in minority populations is warranted. (Cancer Epidemiol Biomarkers Prev 2009;18(6):1829–40)

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