Systems-level analysis of airway biology: Expression profiling, network biology, lung cancer, and retinoic acid

Study of gene expression patterns in cancer is used to aid in the discovery of marker genes and drug targets, as well as to provide insights to the nature of the disease. Paired normal and tumor samples from cancer patients were used to analyze the genes that are differentially regulated in squamous lung carcinoma. Herein, we have discovered a possible connection between cancer and protein interaction network: Genes that were differentially expressed have been identified, and mapped to the human protein interaction network to analyze the topological characteristics of the genes within these networks. Upregulated genes in squamous lung carcinoma are well connected to other genes in protein interaction network compared to the rest of the genes, whereas downregulated genes are not. To further test if this phenomenon exists in other types of cancer, meta-analysis of publicly available microarray data has been performed. In majority of the cases studied, the upregulated genes in cancer also tend to be highly connected, demonstrating that this relation is not limited to lung cancer. Given that highly connected genes are known to be essential in organisms such as yeast, our finding suggest that genes which confer cancer cells their survivable traits may also exhibit such feature in protein interaction network. Interpretation of gene expression profile using biological network data may potentially be a useful tool in cancer research. Retinoic acid is a potent stimulator of cellular differentiation. Response of primary human airway epithelial cell culture to retinoic acid has been studied using genome-scale DNA microarray over 96 hours. The experiment has identified 225 differentially expressed genes. To our knowledge, 155 of these genes have never been identified as retinoid target. The expression profiles over the timecourse indicate a coordinated expression of genes with similar functions over time, indicating the biological validity of the profiles. Many genes associated with inflammatory system are included in the list; if verified, it may lead to interesting theories. This list will serve as an important framework for future validation and detailed modeling of the process of cellular differentiation that occurs during the development and repair of human airway epithelium.