Abstract PL07-02: Whole genome approaches to identify pharmacogenomic markers of anticancer agents

Abstract

Abstract Preclinical and clinical genome-wide association studies (GWAS) in oncology provide an unprecedented opportunity for a comprehensive and unbiased assessment of the heritable factors associated with drug response. For chemotherapeutic drugs, there are many challenges with performing a clinical GWAS, including staggering costs because a homogenous population of patients treated with the same dosage regimen and minimal confounding variables is required. To get around these issues, we have developed preclinical cell-based models as a pharmacogenomic discovery tool but also a means to replicate or validate findings from clinical GWAS. Our model utilizes HapMap lymphoblastoid cell lines (LCLs) derived from individuals within different world populations (Caucasian, African, Asian, African American) that are evaluated for drug sensitivity to chemotherapeutic agents (platinating agents, antimetabolites, cyclophosphamide, paclitaxel). Evaluation of inter-ethnic differences revealed that LCLs from Africans tend to be more sensitive to antimetabolites and less sensitive to platinating agents than Caucasian derived LCLs. These LCLs are rich in genetic data as many are part of the International HapMap and the more recent 1000 Genome project. We utilized this data to identify disproportionately more expression quantitative trait loci (eQTLs, indicating that a SNP genotype is associated with the transcript abundance level of a gene) associated with pharmacologic traits than expected by chance based on minor allele frequency. We are attempting to unravel the functional consequence of top pharmacologic GWAS SNPs with local and distant regulatory roles in cellular resistance to chemotherapeutic agents. For example, we discovered a SNP (master regulator) that is local to PRPF39 and distant to more than 100 genes that is associated with cisplatin-induced cytotoxicity in LCLs derived from African populations. Our cell-based model provides potential targets for therapeutic intervention and provides us with a greater understanding of the genetic contribution to interethnic variation in chemotherapeutic sensitivity. Citation Information: Cancer Epidemiol Biomarkers Prev 2011;20(10 Suppl):PL07-02.