Abstract
We used cDNA microarrays to assess gene expression profiles in 60 human cancer cell lines used in a drug discovery screen by the National Cancer Institute. Using these data, we linked bioinformatics and chemoinformatics by correlating gene expression and drug activity patterns in the NCI60 lines. Clustering the cell lines on the basis of gene expression yielded relationships very different from those obtained by clustering the cell lines on the basis of their response to drugs. Gene-drug relationships for the clinical agents 5-fluorouracil and L-asparaginase exemplify how variations in the transcript levels of particular genes relate to mechanisms of drug sensitivity and resistance. This is the first study to integrate large databases on gene expression and molecular pharmacology.
Publication types
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Comparative Study
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Research Support, Non-U.S. Gov't
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Research Support, U.S. Gov't, P.H.S.
MeSH terms
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Antineoplastic Agents / classification
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Antineoplastic Agents / pharmacology*
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Cluster Analysis
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DNA, Complementary / genetics*
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DNA, Neoplasm / genetics
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Databases, Factual*
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Drug Resistance, Neoplasm / genetics
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Gene Expression Profiling*
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Gene Expression Regulation, Neoplastic* / drug effects
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Humans
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Neoplasm Proteins / biosynthesis
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Neoplasm Proteins / genetics
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Neoplasms / drug therapy
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Neoplasms / genetics*
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Neoplasms / metabolism
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Neoplasms / pathology
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Oligonucleotide Array Sequence Analysis*
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Organ Specificity
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Tumor Cells, Cultured / classification
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Tumor Cells, Cultured / metabolism*
Substances
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Antineoplastic Agents
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DNA, Complementary
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DNA, Neoplasm
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Neoplasm Proteins