Weaving a Biological Tale from Microarray Data

One of the difficult tasks of effectively using the rapidly evolving "-omics" technologies is interpreting the datasets within an interesting biological context. Our microarray studies have focused on lung adenocarcinoma (AC), the most frequently diagnosed form of human lung cancer. One animal model for lung AC is the A/J mouse after urethane injection, which resembles human AC with similar histological appearance and molecular changes. We collected the gene expression profiles of human and murine normal and AC lung tissues, and compared the two species' datasets after aligning ~7,500 orthologous genes. A list of 409 gene classifiers (p-value<0.0001) common to both species (joint classifiers) was generated which showed significant, positive correlation in expression levels between the two species. A number of previously reported expression changes in the published literature were recapitulated in both species, such as changes in glycolytic enzymes and cell cycle proteins. Unexpectedly, angiogenesis pathway joint classifiers were uniformly down-regulated in tumor tissues. These results demonstrate that the A/J mouse-urethane model reflects significant molecular details of human lung AC, and comparison of orthologous gene expression changes can provide novel insights into lung carcinogenesis.

We have extended these studies to examine the lung AC to identify and understand the complex cellular and signaling interactions present in the tumor microenvironment. Using a novel, though straightforward, microarray approach, we defined a unique gene expression signature from the tumor microenvironment in the murine A/J-urethane model. The tumor microenvironment is reflected by the composition of the cell types present and alterations in mRNA levels, resulting in a "Field Effect" around the tumor. The genes composing the Field Effect expression signature include proteases and their inhibitors, inflammation markers, and immune signaling molecules. By several criteria, the Field Effect expression signature was attributed to the macrophage lineage, in agreement with significant increases of tumor-associated macrophages (TAMs) observed in lung tumors. Using a variety of statistical measures, the Field Effect expression signature correctly classified the bronchoalveolar lavage (BAL) cells >94% of the time. Finally, the protein levels for several Field Effect genes were higher in cell-free BAL fluid, suggesting they are secreted by the TAMs. This work suggests that TAMs generate a unique gene expression signature within the tumor microenvironment and this signature could potentially be used for identifying lung cancer from BAL cells and/or fluid.