We profiled the expression of the 48 human nuclear receptors (NRs) by quantitative RT-PCR in 51 human cancer cell lines of the NCI60 collection derived from nine different tissues. NR mRNA expression accurately classified melanoma, colon, and renal cancers, whereas lung, breast, prostate, central nervous system, and leukemia cell lines exhibited heterogeneous receptor expression. Importantly, receptor mRNA levels faithfully predicted the growth-inhibitory qualities of receptor ligands in nonendocrine tumors. Correlation analysis using NR expression profiles and drug response information across the cell line panel uncovered a number of new potential receptor-drug interactions, suggesting that in these cases, individual receptor levels may predict response to chemotherapeutic interventions. Similarly, by cross-comparing receptor levels within our expression dataset and relating these profiles to existing microarray gene expression data, we defined interactions among receptors and between receptors and other genes that can now be mechanistically queried. This work supports the strategy of using NR expression profiling to classify various types of cancer, define NR-drug interactions and receptor-gene networks, predict cancer-drug sensitivity, and identify druggable targets that may be pharmacologically manipulated for potential therapeutic intervention.