Pharmacogenomic discovery using cell-based models

Marleen Welsh, Lara Mangravite, Marisa Wong Medina, Kelan Tantisira, Wei Zhang, R. Stephanie Huang, Howard McLeod, M. Eileen Dolan

Research output: Contribution to journalReview articlepeer-review

103 Scopus citations


Quantitative variation in response to drugs in human populations is multifactorial; genetic factors probably contribute to a significant extent. Identification of the genetic contribution to drug response typically comes from clinical observations and use of classic genetic tools. These clinical studies are limited by our inability to control environmental factors in vivo and the difficulty of manipulating the in vivo system to evaluate biological changes. Recent progress in dissecting genetic contribution to natural variation in drug response through the use of cell lines has been made and is the focus of this review. A general overview of current cell-based models used in pharmacogenomic discovery and validation is included. Discussion includes the current approach to translate findings generated from these cell-based models into the clinical arena and the use of cell lines for functional studies. Specific emphasis is given to recent advances emerging from cell line panels, including the International HapMap Project and the NCI60 cell panel. These panels provide a key resource of publicly available genotypic, expression, and phenotypic data while allowing researchers to generate their own data related to drug treatment to identify genetic variation of interest. Interindividual and interpopulation differences can be evaluated because human lymphoblastoid cell lines are available from major world populations of European, African, Chinese, and Japanese ancestry. The primary focus is recent progress in the pharmacogenomic discovery area through ex vivo models.

Original languageEnglish (US)
Pages (from-to)413-429
Number of pages17
JournalPharmacological Reviews
Issue number4
StatePublished - Dec 2009

ASJC Scopus subject areas

  • Molecular Medicine
  • Pharmacology


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