Important progress continues to be made in the treatment of most common cancers, but therapeutic benefit remains difficult to predict and severe or fatal adverse events occur frequently. The Human Genome Project has fueled the notion that genetic information can produce effective and cost-efficient selection of therapies for individual patients, but validated genetic signatures that predict response to most chemotherapy regimens remain to be identified. Numerous genes potentially influence drug response, but current candidate-gene approaches are limited by the requirement of a priori knowledge about the genes involved and the moderate size of most clinical trials often limits the power of in vitro genome wide association studies (GWAS) for cancer pharmacogenomics discovery. In response to these limitations, we have undertaken a thorough, pharmacogenomic assessment of cytotoxic effect of the majority of FDA approved anti-cancer compounds using an ex vivo model system to determine the heritability of drug-induced cell killing to prioritize drugs for pharmacogenomic mapping. These results are an important first step, and while high heritability of a trait does not guarantee successful association mapping results, it represents an important first step and the results will be used to prioritize drugs with high heritabilities for genome-wide association mapping. In the current proposal, GWAS mapping of cytotoxic agents will be performed in a European American population, and then replication GWAS mapping will be performed in an East Asian population. In addition to discovering and validating genetic variants that predict drug response, the wealth of data collected will be used to dissect the underlying etiology of drug response traits, including assessing the relative contribution of genetic, environmental, and interaction components of variation. These results will provide crucial insight to prioritize genetic variants for follow-up in precious clinical population resources, and potentially reveal new insight into the overall etiology of drug responses.
We will build on our previous work to conduct ex vivo GWAS studies in two large, independent population cohorts on drug response phenotypes, and use cutting-edge statistical approaches to dissect the genetic etiology of these traits. Our overall goal is to identify high interest genes and characterize the trait etiology of these drug response outcomes so that they may be further investigated in future studies. This application leverages previously completed genome-wide genotyping for efficient association mapping, and will evaluate genetic associations in two independent cohorts.
|Jack, J; Rotroff, D; Motsinger-Reif, A (2014) Lymphoblastoid cell lines models of drug response: successes and lessons from this pharmacogenomic model. Curr Mol Med 14:833-40|
|Hariani, Gunjan D; Lam, Ernest T; Lam, Ernest J et al. (2014) Application of next generation sequencing to CEPH cell lines to discover variants associated with FDA approved chemotherapeutics. BMC Res Notes 7:360|
|Beam, Andrew; Motsinger-Reif, Alison (2014) Beyond IC50 s: Towards Robust Statistical Methods for in vitro Association Studies. J Pharmacogenomics Pharmacoproteomics 5:1000121|
|Brown, Chad C; Havener, Tammy M; Medina, Marisa W et al. (2014) Genome-wide association and pharmacological profiling of 29 anticancer agents using lymphoblastoid cell lines. Pharmacogenomics 15:137-46|
|McLeod, Howard L (2013) Cancer pharmacogenomics: early promise, but concerted effort needed. Science 339:1563-6|