Genome-wide association study: a useful tool to identify common genetic variants associated with drug toxicity and efficacy in cancer pharmacogenomics.
In recent years, the utilization of genome-wide association study (GWAS) has proved to be a beneficial method to identify novel common genetic variations not only for disease susceptibility but also for drug efficacy and drug-induced toxicity, creating a field of pharmacogenomics studies. In addition, the findings from GWAS also generate new biologic hypotheses that could improve the understanding of pathophysiology for disease or the mechanism of drug-induced toxicity. This review highlights the implications of GWAS that have been published to date and discusses the successes as well as challenges of using GWAS in cancer pharmacogenomics. The aim of pharmacogenomics is to realize the vision of personalized medicine; it is hoped that through GWAS, novel common genetic variations could be identified to predict clinical outcome and/or toxicity in cancer therapies that subsequently could be implemented to improve the quality of lives of patients with cancer. Nevertheless, given the complexity of cancer therapies, underpowered studies, and large heterogeneity of study designs, collaborative efforts are needed to validate these findings and overcome the limitations of GWA studies before clinical implementation. See all articles in this ccr focus section, "Progress in pharmacodynamic endpoints."
Authors' Affiliations: Laboratory for Statistical Analysis, Core for Genomic Medicine; Laboratory for Pharmacogenomics; and Laboratory for Genotyping Development, Core for Genomic Medicine, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan.
Siew-Kee
SK
Low
Authors' Affiliations: Laboratory for Statistical Analysis, Core for Genomic Medicine; Laboratory for Pharmacogenomics; and Laboratory for Genotyping Development, Core for Genomic Medicine, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan.
Atsushi
A
Takahashi
Authors' Affiliations: Laboratory for Statistical Analysis, Core for Genomic Medicine; Laboratory for Pharmacogenomics; and Laboratory for Genotyping Development, Core for Genomic Medicine, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan.
Taisei
T
Mushiroda
Authors' Affiliations: Laboratory for Statistical Analysis, Core for Genomic Medicine; Laboratory for Pharmacogenomics; and Laboratory for Genotyping Development, Core for Genomic Medicine, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan mkubo@src.riken.jp.
Michiaki
M
Kubo
D064420:Drug-Related Side Effects and Adverse Reactions / Q000235:genetics*; D014644:Genetic Variation; D055106:Genome-Wide Association Study / Q000379:methods* / Q000639:trends; D006801:Humans; D009369:Neoplasms / Q000188:drug therapy* / Q000235:genetics*; D010597:Pharmacogenetics / Q000379:methods / Q000639:trends; D057285:Precision Medicine / Q000379:methods / Q000639:trends; D015203:Reproducibility of Results; D016896:Treatment Outcome