{"title":"Leveraging Lymphoblastoid Cell Lines for Drug Response Modeling","authors":"A. Motsinger-Reif, Daniel M. Rotroff","doi":"10.4172/2153-0602.1000179","DOIUrl":null,"url":null,"abstract":"Lymphoblastoid cell lines (LCL) are becoming popular tools for modeling drug response. LCLs, and other in vitro assays, offer the ability to test many drugs, doses, and biological samples relatively quickly and inexpensively. In addition, a unique advantage to LCLs is that they are available from a large cohort of individuals, providing the capability to test for genetic variability on a scale not readily available in other in vitro systems. Since oftentimes the genotype data is publically available, the experimental costs can be limited to the cost of the drug response phenotyping. Here we describe several advantages and limitations of LCLs. In addition we review several important aspects of LCL experimental design and statistical analysis. Lastly, we present an example of LCLs being successfully used to identify candidate single nucleotide polymorphisms and genes for variability in response to a chemotherapeutic used to treat chronic myeloid leukemia.","PeriodicalId":15630,"journal":{"name":"Journal of Data Mining in Genomics & Proteomics","volume":"62 1","pages":"1-4"},"PeriodicalIF":0.0000,"publicationDate":"2015-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Data Mining in Genomics & Proteomics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4172/2153-0602.1000179","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Lymphoblastoid cell lines (LCL) are becoming popular tools for modeling drug response. LCLs, and other in vitro assays, offer the ability to test many drugs, doses, and biological samples relatively quickly and inexpensively. In addition, a unique advantage to LCLs is that they are available from a large cohort of individuals, providing the capability to test for genetic variability on a scale not readily available in other in vitro systems. Since oftentimes the genotype data is publically available, the experimental costs can be limited to the cost of the drug response phenotyping. Here we describe several advantages and limitations of LCLs. In addition we review several important aspects of LCL experimental design and statistical analysis. Lastly, we present an example of LCLs being successfully used to identify candidate single nucleotide polymorphisms and genes for variability in response to a chemotherapeutic used to treat chronic myeloid leukemia.