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Pharmacogenomic characterization of gemcitabine response - A framework for data integration to enable personalized medicine

机译:吉西他滨反应的药物基因组学表征-用于实现个性化药物的数据集成框架

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OBJECTIVES: Response to the oncology drug gemcitabine may be variable in part due to genetic differences in the enzymes and transporters responsible for its metabolism and disposition. The aim of our in-silico study was to identify gene variants significantly associated with gemcitabine response that may help to personalize treatment in the clinic. METHODS: We analyzed two independent data sets: (a) genotype data from NCI-60 cell lines using the Affymetrix DMET 1.0 platform combined with gemcitabine cytotoxicity data in those cell lines, and (b) genome-wide association studies (GWAS) data from 351 pancreatic cancer patients treated on an NCI-sponsored phase III clinical trial. We also performed a subset analysis on the GWAS data set for 135 patients who were given gemcitabine+placebo. Statistical and systems biology analyses were performed on each individual data set to identify biomarkers significantly associated with gemcitabine response. RESULTS: Genetic variants in the ABC transporters (ABCC1, ABCC4) and the CYP4 family members CYP4F8 and CYP4F12, CHST3, and PPARD were found to be significant in both the NCI-60 and GWAS data sets. We report significant association between drug response and variants within members of the chondroitin sulfotransferase family (CHST) whose role in gemcitabine response is yet to be delineated. CONCLUSION: Biomarkers identified in this integrative analysis may contribute insights into gemcitabine response variability. As genotype data become more readily available, similar studies can be conducted to gain insights into drug response mechanisms and to facilitate clinical trial design and regulatory reviews.
机译:目的:对肿瘤药物吉西他滨的反应可能有所不同,部分原因是负责其代谢和处置的酶和转运蛋白的遗传差异。我们的计算机模拟研究的目的是鉴定与吉西他滨反应显着相关的基因变异,这可能有助于在临床上个性化治疗。方法:我们分析了两个独立的数据集:(a)使用Affymetrix DMET 1.0平台从NCI-60细胞系获得的基因型数据,结合吉西他滨在这些细胞系中的细胞毒性数据,以及(b)来自全基因组的关联研究(GWAS)数据351名接受NCI资助的III期临床试验治疗的胰腺癌患者。我们还对135名接受吉西他滨+安慰剂治疗的患者的GWAS数据集进行了子集分析。对每个单独的数据集进行统计和系统生物学分析,以鉴定与吉西他滨反应显着相关的生物标记。结果:在NCI-60和GWAS数据集中发现ABC转运蛋白(ABCC1,ABCC4)和CYP4家族成员CYP4F8和CYP4F12,CHST3和PPARD的遗传变异。我们报告药物反应与软骨素磺基转移酶家族(CHST)的成员之间的重大关联,其在吉西他滨反应中的作用尚未阐明。结论:本综合分析中鉴定的生物标志物可能有助于了解吉西他滨反应的变异性。随着基因型数据的获得越来越容易,可以进行类似的研究来深入了解药物反应机制并促进临床试验设计和法规审查。

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