A gene expression database for the molecular pharmacology of cancer

We used cDNA microarrays to assess gene expression profiles in 60 human can cer cell lines used in a drug discovery screen by the National Cancer Insti tute. Using these data, we linked bioinformatics and chemoinformatics by co rrelating gene expression and drug activity patterns in the NCI60 lines. Cl ustering the cell lines on the basis of gene expression yielded relationshi ps very different from those obtained by clustering the cell lines on the b asis of their response to drugs. Gene-drug relationships for the clinical a gents 5-fluorouracil and L-asparaginase exemplify how variations in the tra nscript levels of particular genes relate to mechanisms of drug sensitivity and resistance. This is the first study to integrate large databases on ge ne expression and molecular pharmacology.