aInnovation Center for Biomedical Informatics bLombardi Comprehensive Cancer Center, Developmental Therapeutics Program cDepartment of Neurology, Georgetown University Medical Center dDepartment of Mathematics and Statistics, Georgetown University, Washington, District of Columbia eESAC Inc., Rockville fUS Food and Drug Administration, Silver Spring, Maryland, USA.
Pharmacogenet Genomics. 2014 Feb;24(2):81-93. doi: 10.1097/FPC.0000000000000015.
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.
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.
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.
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.
肿瘤药物吉西他滨的反应可能存在差异，部分原因是负责其代谢和处置的酶和转运体存在遗传差异。我们的计算机研究旨在确定与吉西他滨反应显著相关的基因变异，这些变异可能有助于在临床上实现个体化治疗。
我们分析了两个独立的数据集：（a）使用 Affymetrix DMET 1.0 平台对 NCI-60 细胞系进行的基因型数据，以及这些细胞系中吉西他滨的细胞毒性数据，（b）来自 351 名接受 NCI 赞助的 III 期临床试验治疗的胰腺癌患者的全基因组关联研究（GWAS）数据。我们还对接受吉西他滨+安慰剂治疗的 135 名患者的 GWAS 数据集进行了亚组分析。对每个单独的数据集中进行了统计和系统生物学分析，以确定与吉西他滨反应显著相关的生物标志物。
在 NCI-60 和 GWAS 数据集中，ABC 转运体（ABCC1、ABCC4）和 CYP4 家族成员 CYP4F8 和 CYP4F12、CHST3 和 PPARD 的遗传变异被发现是显著的。我们报告了药物反应与软骨素硫酸转移酶家族（CHST）成员内的变异之间存在显著关联，其在吉西他滨反应中的作用尚待阐明。
本综合分析中确定的生物标志物可能有助于深入了解吉西他滨反应的变异性。随着基因型数据的更容易获得，类似的研究可以进行，以深入了解药物反应机制，并促进临床试验设计和监管审查。
