淋巴母细胞系的药物反应模型：来自药物基因组学模型的成功和经验

Title:Lymphoblastoid Cell Lines Models of Drug Response: Successes and Lessons from this Pharmacogenomic Model

Volume: 14 Issue: 7

Author(s): J. Jack, D. Rotroff and A. Motsinger-Reif

Affiliation:

关键词: 细胞毒素，基因关联映射，基因组广泛的关联分析，淋巴母细胞系，药物基因组学

摘要: A new standard for medicine is emerging that aims to improve individual drug responses through studying associations with genetic variations. This field, pharmacogenomics, is undergoing a rapid expansion due to a variety of technological advancements that are enabling higher throughput with reductions in cost. Here we review the advantages, limitations, and opportunities for using lymphoblastoid cell lines (LCL) as a model system for human pharmacogenomic studies.

There are a wide range of publicly available resources with genome-wide data available for LCLs from both related and unrelated populations, removing the cost of genotyping the data for drug response studies. Furthermore, in contrast to human clinical trials or in vivo model systems, with high-throughput in vitro screening technologies, pharmacogenomics studies can easily be scaled to accommodate large sample sizes.

An important component to leveraging genome-wide data in LCL models is association mapping. Several methods are discussed herein, and include multivariate concentration response modeling, issues with multiple testing, and successful examples of the ‘triangle model’ to identify candidate variants. Once candidate gene variants have been determined, their biological roles can be elucidated using pathway analyses and functionally confirmed using siRNA knockdown experiments.

The wealth of genomics data being produced using related and unrelated populations is creating many exciting opportunities leading to new insights into the genetic contribution and heritability of drug response.

Cite this article as:

Jack J., Rotroff D. and Motsinger-Reif A., Lymphoblastoid Cell Lines Models of Drug Response: Successes and Lessons from this Pharmacogenomic Model, Current Molecular Medicine 2014; 14 (7) . https://dx.doi.org/10.2174/1566524014666140811113946