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Race and smoking status associated with paclitaxel drug response in patient-derived lymphoblastoid cell lines

机译:与患者衍生的淋巴母细胞系中紫杉醇药物反应相关的种族和吸烟状态

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The use of ex-vivo model systems to provide a level of forecasting for in-vivo characteristics remains an important need for cancer therapeutics. The use of lymphoblastoid cell lines (LCLs) is an attractive approach for pharmacogenomics and toxicogenomics, due to their scalability, efficiency, and cost-effectiveness. There is little data on the impact of demographic or clinical covariates on LCL response to chemotherapy. Paclitaxel sensitivity was determined in LCLs from 93 breast cancer patients from the University of North Carolina Lineberger Comprehensive Cancer Center Breast Cancer Database to test for potential associations and/or confounders in paclitaxel dose-response assays. Measures of paclitaxel cell viability were associated with patient data included treatment regimens, cancer status, demographic and environmental variables, and clinical outcomes. We used multivariate analysis of variance to identify the in-vivo variables associated with ex-vivo dose-response. In this unique dataset that includes both in-vivo and ex-vivo data from breast cancer patients, race (P = 0.0049) and smoking status (P = 0.0050) were found to be significantly associated with ex-vivo dose-response in LCLs. Racial differences in clinical dose-response have been previously described, but the smoking association has not been reported. Our results indicate that in-vivo smoking status can influence ex-vivo dose-response in LCLs, and more precise measures of covariates may allow for more precise forecasting of clinical effect. In addition, understanding the mechanism by which exposure to smoking in-vivo effects ex-vivo dose-response in LCLs may open up new avenues in the quest for better therapeutic prediction.
机译:使用体外模型系统为体内特征提供一定程度的预测仍然是癌症治疗学的重要需求。淋巴母细胞系(LCL)由于其可扩展性、效率和成本效益,在药物基因组学和毒理基因组学中是一种有吸引力的方法。关于人口统计学或临床协变量对LCL化疗反应的影响,目前几乎没有数据。从北卡罗来那大学LeNBER综合癌症中心乳腺癌数据库的93名乳腺癌患者中检测紫杉醇敏感性,以测试紫杉醇剂量-反应试验中潜在的关联和/或混杂因素。紫杉醇细胞活力的测量与患者数据相关,包括治疗方案、癌症状态、人口统计学和环境变量以及临床结果。我们使用多变量方差分析来确定与体外剂量反应相关的体内变量。在这个包含乳腺癌患者体内和体外数据的独特数据集中,发现种族(P=0.0049)和吸烟状态(P=0.0050)与LCL的体外剂量反应显著相关。临床剂量反应的种族差异之前已经被描述过,但吸烟相关性尚未被报道。我们的研究结果表明,体内吸烟状态可以影响LCL的体外剂量反应,更精确的协变量测量可以更精确地预测临床效果。此外,了解体内吸烟对LCL体外剂量反应的影响机制可能为寻求更好的治疗预测开辟新途径。

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