In order to identify and contrast global gene expression profiles defining the premalignant syndrome, Barrett's esophagus, as well as frank esophageal cancer, we utilized cDNA microarray technology in conjunction with bioinformatics tools. We hybridized microarrays, each containing 8000 cDNA clones, to RNAs extracted from 13 esophageal surgical or endoscopic biopsy specimens (seven Barrett's metaplasias and six esophageal carcinomas). Hierarchical cluster analysis was performed on these results and displayed using a color-coded graphic representation (Treeview). The esophageal samples clustered naturally into two principal groups, each possessing unique global gene expression profiles. After retrieving histologic reports for these tissues, we found that one main cluster contained all seven Barrett's samples, while the remaining principal cluster comprised the six esophageal cancers. The cancers also clustered according to histopathological subtype. Thus, squamous cell carcinomas (SCCAs) constituted one group, adenocarcinomas (ADCAs) clustered separately, and one signet-ring carcinoma was in its own cluster, distinct from the ADCA cluster. We conclude that cDNA microarrays and bioinformatics show promise in the classification of esophageal malignant and premalignant diseases, and that these methods can be applied to small biopsy samples.