Abstract
Abstract Racial differences in the incidence and mortality of lung cancer are well documented. Many factors are known to influence the risk and outcome of this most deadly disease, including exposure, behavior, access to health care, as well as inherent susceptibility. There is a paucity of data regarding the existence, if any, of biological differences among tumors that reflect inherent susceptibilities to known etiological factors and may contribute to some of the disparities observed among African Americans and Caucasians. Our laboratory employs a multipronged strategy to study the interaction of genetic, molecular, and etiological factors leading to lung cancer risk and survival, that encompasses mRNA and microRNA (miRNA) expression, DNA methylation, metabolomics, as well as genetic susceptibility in the form of Single Nucleotide Polymorphisms (SNPs). In this study, a cohort of sixty paired cancerous/non-cancerous lung tissues excised from stage I lung cancer patients (16 African Americans and 48 Caucasians) recruited through our longstanding Case-Control Study at University of Maryland, Baltimore, are being characterized by miRNA quantitation (Nanostring nCounter Human miRNA Expression Assay), mRNA expression profiling (Illumina HumanRef-8 v3 Expression Beadchip arrays), and methylation profiling (Illumina Infinium Human Methylation27 Beadchip arrays). When gene expression profiles on cancerous tissues from African Americans and Caucasians were compared, three genes were differentially expressed (FDR<10%), namely CRYBB2, PPIL3, and COMMD5. A similar comparison on non-cancerous tissues yielded 12 genes (FDR<10%), which included CRYBB2 and PPIL3. CRYBB2, Crystalline Beta B2, has previously been associated with prostate cancer in African Americans, and is upregulated in this sample cohort. We are currently analyzing and integrating these different data types with the purpose of finding biomarkers for lung cancer prognosis, associating DNA methylation, mRNA and miRNA abundance with clinical features of lung cancer (including race, gender, histology, and smoking), and correlating methylation, mRNA and miRNA patterns. Our goal is to delineate the most important transcriptional networks operational in lung cancer and specifically focus on those that may illuminate racial disparities associated with this disease. Citation Information: Cancer Epidemiol Biomarkers Prev 2011;20(10 Suppl):A4.
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