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Lung cancer is the leading cause of cancer deaths in the United States. While cigarette smoking is the principle causal agent of lung cancer, 10–15% of patients have no history of smoking, yet still manifest gene expression similar to smokers. Although microarrays have been applied widely to lung cancer, few studies have explored the specific expression differences between smokers and nonsmokers. The purpose of this study was to identify differentially expressed genes in lung cancer of nonsmokers by combining data from different microarray platforms using quantile transformation.Two statistical approaches were introduced in this study: the ordinal logistic regression and a new statistical test based on the DISCO Normal distribution. Results from these models were corroborated against the finding of the modified t-tests. The top reported genes were shown to play multiple differing roles in the cellular environment, including muscle maintenance, DNA damage repair mechanisms, cellular metabolism, proliferation and growth, and tumor progression. The results of this study give further insight to the genetic differences observed in lung cancer patients, as well as demonstrating the opportunity to combine data from different microarray platforms. |
