We developed a novel method for the discovery of functional relationships between pairs of genes based on gene expression profiles generated from microarrays. This approach examines all possible pairs of genes and identifies those in which the relationship between the two genes changes in different diseases or conditions. In contrast to previous methods that have focused on differentially expressed genes, this method attempts to find changes in the correlation between genes. These changes may be indicative of the functional relationships related to a disease mechanism. We demonstrate the utility of this approach by applying it to an oral squamous cell carcinoma (OSCC) microarray data set. Our results suggest new directions for future experimental investigations.