Pulmonary neuroendocrine tumors vary dramatically in their malignant behavior. Their classification, based on histological examination, is often difficult. In search of molecular and prognostic markers for these tumors, we used cDNA microarray analysis of human transcripts against reference RNA from a well-characterized immortalized bronchial epithelial cell line, BEAS-2B. Tumor cells were isolated by laser-capture microdissection from primary tumors of 17 typical carcinoids, small cell lung cancers, and large cell neuroendocrine carcinomas. An unsupervised, hierarchical clustering algorithm resulted in a precise classification of each tumor subtype according to the proposed histological classification. Selection of genes, using supervised analysis, resulted in the identification of 198 statistically significant genes (P <.004) that also accurately discriminated between 3 predefined tumor subtypes. Two-by-two comparisons of these genes identified classifier genes that distinguished each tumor subtype from the others. Changes in expression of selected differentially expressed genes for each tumor subtype were internally validated by real-time reverse-transcription polymerase chain reaction. Expression of 2 potential classifier gene products, carboxypeptidase E (CPE) and gamma-glutamyl hydrolase (GGH), was validated by immunohistochemistry and cross-validated on additional archival samples of pulmonary neuroendocrine tumors. Kaplan-Meier survival analysis revealed that immunostaining for CPE was a statistically significant predictor of good prognosis, whereas GGH expression correlated with poor prognosis. Thus, cDNA microarray analysis led to the identification of 2 novel biomarkers that should facilitate molecular diagnosis and further study of pulmonary neuroendocrine tumors.