Abstract 1679: Identification of pharmacogenomic markers associated with paclitaxel and carboplatin response in cancer: The cross-talk between agents
Authors: Eng Lawson , Ibrahim-zada Irada , Jarjanazi Hamdi , Savas Sevtap , Pritchard Kathleen I. , Ozcelik Hilmi 
Published: February 2011

Abstract
Introduction: Recent emerging results from various cancer trials have implicated the critical role of Paclitaxel and Carboplatin combination therapy. Paclitaxel stabilizes microtubules whereas Carboplatin cross-links with DNA; both leading to cellular damage and cell death. Genetic variability among patients has been shown to impact the outcome of chemotherapy, and forms the basis of our study. Here we applied a novel strategy developed by our group, where we have identified genes that may impact the therapeutic response to Paclitaxel and Carboplatin.
Materials and Methods: The GI50 response data on the NCI60 panel, available from DTP was obtained and resistant versus sensitive cell line categories were defined using a non-parametric kernel estimation on SAS 9.1. Using the Affymetrix 125k SNP Chip's genotype data for the cell lines, we carried out a genome-wide association study to identify SNPs associated with response to Paclitaxel and Carboplatin. After correction for multiple testing, significant SNPs were mapped to chromosomal regions using information from dbSNP. Genes with significant SNPs were also investigated for haplotypes using Haploview software and for mRNA expression differences using the Affymetrix U133A Chip data at BioGPS database. Using Ingenuity, we studied the biological associations and pathways between identified genes for both drugs.
Results: Our strategy identified 48 SNPs with 13 in protein-coding genes (KIAA0427, ROBO1, BTBD12, CCDC26, SLC2A9, DCT, SNTG1, SGCD, GRIK1, ZNF607, CFTR, LPHN2, PTPRD) for Paclitaxel and 20 SNPs with 7 in protein-coding genes (GRIN2A, CD86, KIAA1239, CTNND2, CMYA5, COL19A1, PTPRD) for Carboplatin. Interestingly, PTPRD was associated with both drugs suggesting some synchrony in their mechanisms. Ingenuity analyses have also shown common biological pathways involved in drug response mainly via β-catenin/p53, and microtubular interactions. Haplotype analyses revealed blocks around the significant SNPs for LPHN2, PTPRD, SLC2A9, GRIK1, ROBO1 and SGCD for Paclitaxel. Differential mRNA expression was found for SGCD and DCT for Paclitaxel. Haplotype and mRNA expression analysis for Carboplatin is still being conducted.
Conclusions: The common genes and pathways identified support the interaction of both drugs during combination therapy. As only 2 of the 13 genes for Paclitaxel showed significant changes in mRNA expression, this highlights the importance of looking for variants at the DNA level because mRNA expression alone would not have identified many of these genes. Furthermore, the 6 haplotypes identified so far can better predict of drug response than their respective SNPs, showing the role of SNP-SNP interactions. These genetic variants represent promising biomarkers that can one day be used to predict Paclitaxel and Carboplatin therapeutic response among cancer patients.
Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 1679.