One important purpose of conducting gene expression experiments is to understand the correlation of gene expression profiles to disease states. Based on the notion of emerging patterns and an entropy-oriented discretization method, we discover groups of genes that are correlated to disease states in a significant way. In each group, every member gene constrained by a specific expression interval, unanimously occurs only in one type of cells with a maximally large frequency, but never unanimously happens in the other types of cells. According to our studies on the colon tumor dataset, such gene groups (also called patterns) can reach a frequency of 90%, providing good insight into the correlation of gene expression profiles to disease states. The patterns can be used to correctly predict whether a new cell is normal or cancerous.