Julia C. F. Quintanilha, Alessandro Racioppi, Jin Wang, Amy S. Etheridge, Stefanie Denning, Carol E. Peña, Andrew D. Skol, Daniel J. Crona, Danyu Lin, Federico Innocenti
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引用次数: 2
Abstract
No biomarkers are available to predict patients at risk of developing hypertension induced by VEGF-pathway inhibitors. This study aimed to identify predictive biomarkers of hypertension induced by these drugs using a discovery-replication approach. The discovery set included 140 sorafenib-treated patients (TARGET study) genotyped for 973 SNPs in 56 genes. The most statistically significant SNPs associated with grade ≥2 hypertension were tested for association with grade ≥2 hypertension in the replication set of a GWAS of 1039 bevacizumab-treated patients from four clinical trials (CALGB/Alliance). In the discovery set, rs444904 (G > A) in PIK3R5 was associated with an increased risk of sorafenib-induced hypertension (p = 0.006, OR = 3.88 95% CI 1.54–9.81). In the replication set, rs427554 (G > A) in PIK3R5 (in complete linkage disequilibrium with rs444904) was associated with an increased risk of bevacizumab-induced hypertension (p = 0.008, OR = 1.39, 95% CI 1.09–1.78). This study identified a predictive marker of drug-induced hypertension that should be evaluated for other VEGF-pathway inhibitors. ClinicalTrials.gov Identifier:NCT00073307 (TARGET).
期刊介绍:
The Pharmacogenomics Journal is a print and electronic journal, which is dedicated to the rapid publication of original research on pharmacogenomics and its clinical applications.
Key areas of coverage include:
Personalized medicine
Effects of genetic variability on drug toxicity and efficacy
Identification and functional characterization of polymorphisms relevant to drug action
Pharmacodynamic and pharmacokinetic variations and drug efficacy
Integration of new developments in the genome project and proteomics into clinical medicine, pharmacology, and therapeutics
Clinical applications of genomic science
Identification of novel genomic targets for drug development
Potential benefits of pharmacogenomics.