Human lymphoblastoid cell line panels: novel tools for assessing shared drug pathways
Human lymphoblastoid cell line panels: novel tools for assessing shared drug pathways
复制标题
DOI：
10.2217/pgs.10.27
复制
发表时间：
2010-03-01
期刊：
影响因子：
2.1
通讯作者：
Gurwitz, David
中科院分区：
文献类型：
--
作者：
Morag, Ayelet;Kirchheiner, Julia;Gurwitz, David
目的：虽然出现了用于预测药物靶点和途径的强大的计算机工具，但缺乏用于评估此类预测的通用体外工具。我们提出了一种新的体外方法，用于区分共享与不同的药物途径的基础上比较细胞生长抑制概况跨一小组的人淋巴母细胞系（LCL）从个人捐助者。材料和方法：平行检查了来自无关健康供体的LCL的各种药物的生长抑制特征，包括抗抑郁药（帕罗西汀、氟西汀、氟伏沙明、西酞普兰、阿米替林和丙咪嗪）;抗癌药（5-氟尿嘧啶、6-巯基嘌呤、硫唑嘌呤、甲氨蝶呤和白藜芦醇）;类固醇药物（地塞米松、倍氯米松和泼尼松龙）;和抗精神病药（氟哌啶醇和氯氮平）。在药物暴露72小时后，通过比色2，3-双（2-甲氧基-4-硝基-5-磺基苯基）-5-[（苯基氨基）羰基]-2H-氢氧化四唑鎓方法评估细胞生长。结果如下：来自无关个体的LCL对给定药物的生长抑制表现出广泛的敏感性，这与基底细胞复制率无关。然而，每个细胞系对来自同一家族的多种药物表现出一致的敏感性。在比较具有相似途径的成对药物（例如抗抑郁药、类固醇药物、抗精神病药或6-巯基嘌呤与硫唑嘌呤相比）的生长抑制曲线的图中，一致观察到高拟合优度值（R-2 > 0.6），但对于具有不同途径的药物则没有观察到。该方法的实用性证明了观察扑尔敏，抗组胺药长期怀疑也具有抗抑郁药样的属性，表现出非常相似的抗抑郁药的生长抑制曲线。结论：将目标药物（或化合物）的生长抑制谱与具有已知途径的药物谱进行比较可能有助于药物途径分类。该方法可用于体外评估二氧化硅生成的药物途径预测，并用于区分目标化合物的共享途径与不同途径。表现出“边缘”敏感性的人淋巴母细胞系的比较转录组学分析随后可用于寻找用于个性化药物治疗的药物反应生物标志物。讨论了该方法的局限性和优点。
Aims: While powerful in silico tools are emerging for predicting drug targets and pathways, general in vitro tools for assessing such predictions are lacking. We present a novel in vitro method for distinguishing shared versus distinct drug pathways based on comparative cell growth inhibition profiles across a small panel of human lymphoblastoid cell lines (LCLs) from individual donors. Materials & methods: LCLs from unrelated healthy donors were examined in parallel for growth inhibition profiles of various drugs, including antidepressants (paroxetine, fluoxetine, fluvoxamine, citalopram, amitriptyline and imipramine); anticancer drugs (5-fluorouracil, 6-mercaptopurine, azathioprine, methotrexate and resveratrol); steroid drugs (dexamethasone, beclomethasone and prednisolone); and antipsychotic drugs (haloperidol and clozapine). Cell growth was assessed by the colorimetric 2,3-bis(2-methoxy-4-nitro-5-sulfophenly)-5-[(phenylamino) carbonyl]-2H-tetrazolium hydroxide method following 72 h of drug exposure. Results: LCLs from unrelated individuals exhibited a wide range of sensitivities to growth inhibition by a given drug, which were independent of basal cell replication rates. Yet, each individual cell line demonstrated a consistent sensitivity to multiple drugs from the same family. High goodness-of-fit values (R-2 > 0.6) were consistently observed for plots comparing the growth-inhibition profiles for paired drugs sharing a similar pathway, for example antidepressants, steroid drugs, antipsychotics, or 6-mercaptopurine compared with azathioprine, but not for drugs with different pathways. The method's utility is demonstrated by the observation that chlorpheniramine, an antihistamine drug long suspected to also possess antidepressant-like properties, exhibits a growth-inhibition profile very similar to antidepressants. Conclusion: Comparing the growth-inhibition profiles of drugs (or compounds) of interest with the profiles of drugs with known pathways may assist in drug pathway classification. The method is useful for in vitro assessment of in silica-generated drug pathway predictions and for distinguishing shared versus distinct pathways for compounds of interest. Comparative transcriptomics analysis of human lymphoblastoid cell lines exhibiting 'edge' sensitivities can subsequently be utilized in the search for drug response biomarkers for personalized pharmacotherapy. The limitations and advantages of the method are discussed.