Hematological Malignancies Program and Department of Pharmaceutical Sciences, St Jude Children's Research Hospital, Memphis, Tennessee 38105, USA.
Curr Opin Pediatr. 2010 Dec;22(6):703-10. doi: 10.1097/MOP.0b013e32833fde85.
The therapeutic index of many medications, especially in children, is very narrow with substantial risk for toxicity at doses required for therapeutic effects. This is particularly relevant to cancer chemotherapy, when the risk of toxicity must be balanced against potential suboptimal (low) systemic exposure that can be less effective in patients with higher rates of drug clearance. The purpose of this review is to discuss genetic factors that lead to interpatient differences in the pharmacokinetics and pharmacodynamics of these medications.
Genome-wide agonistic studies of pediatric patient populations are revealing genome variations that may affect susceptibility to specific diseases and that influence the pharmacokinetic and pharmacodynamic characteristics of medications. Several genetic factors with relatively small effect may be combined in the determination of a pharmacogenomic phenotype and considering these polygenic models may be mandatory in order to predict the related drug response phenotypes. These findings have potential to yield new insights into disease pathogenesis, and lead to molecular diagnostics that can be used to optimize the treatment of childhood cancers.
Advances in genome technology, and their comprehensive and systematic deployment to elucidate the genomic basis of interpatient differences in drug response and disease risk, hold great promise to ultimately enhance the efficacy and reduce the toxicity of drug therapy in children.
目的综述:许多药物,尤其是儿童用药,其治疗指数很窄,在需要治疗效果的剂量下,存在很大的毒性风险。这在癌症化疗中尤为重要,因为毒性风险必须与潜在的不理想(低)全身暴露相平衡,而在清除率较高的患者中,这种暴露可能效果不佳。本文的目的是讨论导致这些药物药代动力学和药效动力学个体间差异的遗传因素。
最新发现:针对儿科患者群体的全基因组激动性研究揭示了可能影响特定疾病易感性的基因组变异,以及影响药物药代动力学和药效动力学特征的因素。几个具有相对较小影响的遗传因素可能会组合在一起,决定药物基因组表型,并且考虑这些多基因模型可能是预测相关药物反应表型的必要条件。这些发现有可能深入了解疾病的发病机制,并产生可用于优化儿童癌症治疗的分子诊断。
总结:基因组技术的进步,以及它们对阐明药物反应和疾病风险个体间差异的基因组基础的全面系统应用,有望最终提高儿童药物治疗的疗效,降低毒性。