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.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2802425 | PMC |
http://dx.doi.org/10.1124/pr.109.001461 | DOI Listing |
Clin Pharmacol Ther
January 2025
Department of Pharmacology, Center for Pharmacogenomics, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA.
Clopidogrel, an anti-platelet drug, is used to prevent thrombosis after percutaneous coronary intervention. Clopidogrel resistance results in recurring ischemic events, with African Americans (AA) suffering disproportionately. The aim of this study was to discover novel biomarkers of clopidogrel resistance in African Americans using genome and transcriptome data.
View Article and Find Full Text PDFGenes (Basel)
January 2025
Department of Stroke and Cerebrovascular Diseases, University of Tsukuba Hospital, Tsukuba 305-8576, Japan.
Background/objectives: Recent advances in stroke genetics have substantially enhanced our understanding of the complex genetic architecture underlying cerebral infarction and other stroke subtypes. As knowledge in this field expands, healthcare providers must remain informed about these latest developments. This review aims to provide a comprehensive overview of recent advances in stroke genetics, with a focus on cerebral infarction, and discuss their potential impact on patient care and future research directions.
View Article and Find Full Text PDFAnnu Rev Pharmacol Toxicol
January 2025
Clinical and Translational Science Institute, Colleges of Medicine and Pharmacy, The Ohio State University, Columbus, Ohio, USA.
Pharmacogenetic variation is common and an established driver of response for many drugs. There has been tremendous progress in pharmacogenetics knowledge over the last 30 years and in clinical implementation of that knowledge over the last 15 years. But there have also been many examples where translation has stalled because of the lack of available data sets for discovery or validation research.
View Article and Find Full Text PDFGenome Med
January 2025
Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, 181 Longwood Avenue, Boston, MA, 02115, USA.
Background: Large-scale pharmacogenomic resources, such as the Connectivity Map (CMap), have greatly assisted computational drug discovery. However, despite their widespread use, CMap-based methods have thus far been agnostic to the biological activity of drugs as well as to the genomic effects of drugs in multiple disease contexts. Here, we present a network-based statistical approach, Pathopticon, that uses CMap to build cell type-specific gene-drug perturbation networks and integrates these networks with cheminformatic data and diverse disease phenotypes to prioritize drugs in a cell type-dependent manner.
View Article and Find Full Text PDFFront Pharmacol
January 2025
Institute of Molecular Pathology Biomarkers, Universidad de Extremadura, Cáceres, Spain.
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!