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A method to improve selection of molecular targets by circumventing the ADME pharmacokinetic system utilizing PharmArray DNA microarrays
Authors:Dooley Thomas P  Curto Ernest V  Reddy Shanker P  Davis Richard L  Lambert Glenna  Wilborn Teresa W
Institution:IntegriDerm Inc., 2800 Milan Court, Birmingham, AL 35211-6908, USA. dooley@intergriderm.com
Abstract:DNA microarrays may be used to identify potential molecular targets for drug discovery. Yet, DNA microarray experiments provide massive amounts of data. To limit the choice of potential molecular targets, it may be desirable to eliminate genes coincidentally up-regulated in tissues implicated in absorption, distribution, metabolism, and excretion (ADME) pharmacokinetics. DNA microarray experiments were performed to demonstrate a gene-exclusion approach using as an example RNA samples of neural origin, i.e., a human neuroblastoma cell line (SK-N-SH) and brain tissue, as the intended hypothetical site(s) of drug action. Biomarkers were identified using PharmArray DNA microarrays. The lists of neuroblastoma and neural biomarkers were constrained by limiting selection to the subset of genes that were not highly expressed in three transformed cell lines from liver, colon, and kidney (HepG2, Caco-2, and 786-O, respectively) that are routinely used as representatives of the ADME system during in vitro pharmacology and toxicology experiments. Principal component analysis methods with likelihood ratio-related bioinformatic tools were utilized to identify robust potential biomarker genes for the three ADME-related cell lines, neuroblastoma, and normal brain. Biomarkers of each sample were identified and selected genes were validated by qRT-PCR. Hundreds of biomarkers of the three ADME-related cell types, representing hepatocytes, kidney epithelium, and gastrointestinal tract, may now be used as a valuable database to restrict selection of biomarkers as potential molecular targets from the intended samples (e.g., neuroblastoma in this work). In addition to biomarker discovery per se, this demonstration suggests that our model method may be viable to help restrict gene lists during selection of potential molecular targets for subsequent drug discovery.
Keywords:DNA microarray  Biomarker  Molecular targets  Bioinformatics  Absorption distribution metabolism excretion  Brain  Neuroblastoma  HepG2  Caco-2  786-O
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