Whole-genome approach implicates CD44 in cellular resistance to carboplatin

Abstract

Carboplatin is a chemotherapeutic agent used in the management of many cancers, yet treatment is limited by resistance and toxicities. To achieve a better understanding of the genetic contribution to carboplatin resistance or toxicities, lymphoblastoid cell lines from 34 large Centre d'Etude du Polymorphisme Humain pedigrees were utilised to evaluate interindividual variation in carboplatin cytotoxicity. Significant heritability, ranging from 0.17-0.36 (p = 1 × 10-7 to 9 × 10-4), was found for cell growth inhibition following 72-hour treatment at each carboplatin concentration (10, 20, 40 and 80 μM) and IC50 (concentration for 50 per cent cell growth inhibition). Linkage analysis revealed 11 regions with logarithm of odds (LOD) scores greater than 1.5. The highest LOD score on chromosome 11 (LOD = 3.36, p = 4.2 × 10-5) encompasses 65 genes within the 1 LOD confidence interval for the carboplatin IC50. We further analysed the IC50 phenotype with a linkage-directed association analysis using 71 unrelated HapMap and Perlegen cell lines and identified 18 single nucleotide polymorphisms within eight genes that were significantly associated with the carboplatin IC50 (p < 3.6 × 10-5; false discovery rate < 5 per cent). Next, we performed linear regression on the baseline expression and carboplatin IC50 values of the eight associated genes, which identified the most significant correlation between CD44 expression and IC50 (r2 = 0.20; p = 6 × 10-4). The quantitative real-time polymerase chain reaction further confirmed a statistically significant difference in CD44 expression levels between carboplatin-resistant and -sensitive cell lines (p = 5.9 × 10-3). Knockdown of CD44 expression through small interfering RNA resulted in increased cellular sensitivity to carboplatin (p < 0.01). Our whole-genome approach using molecular experiments identified CD44 as being important in conferring cellular resistance to carboplatin.

Pharmacogenomic Discovery Using Cell-Based Models

“…There is ample evidence for reasonable LOD scores from linkage analysis of chemotherapeutic-induced cytotoxicity (Dolan et al, 2004;Duan et al, 2007;Shukla et al, 2008Shukla et al, , 2009Bleibel et al, 2009); however, linkage peaks typically cover a large genomic region that contains many genes that require follow-up analysis. Using linkage-directed association studies or evaluating multiple phenotypes for a given drug may narrow the gene list to a reasonable number for follow-up studies.…”

“…Even though a LOD score greater than 3 is considered genome-wide significant, drug sensitivity traits are likely multigenic; therefore, peaks with LOD scores above 1.5 were thought to be suggestive of regions harboring genes that contributed to the trait (Dolan et al, 2004;Watters et al, 2004;Duan et al, 2007;Shukla et al, 2008;Bleibel et al, 2009;Shukla et al, 2009). It is noteworthy that in several of these studies there was an inverse relationship between the height of the peak and the concentration of drug used to obtain the phenotype (cell growth inhibition) indicative that some regions of the genome harbor genes that are involved in the delicate balance between cell survival and cell death (low drug concentrations) while others may be involved in cellular apoptosis (higher concentrations of drug).…”

“…In addition, 5-FU and docetaxel shared linkage to chromosome 9q13-q22 (Watters et al, 2004). Some analyses included follow-up association studies under the suggestive linkage peaks (Dolan et al, 2004;Duan et al, 2007;Shukla et al, 2009), resulting in identification of novel candidate pharmacogenes, such as INPP4B on chromosome 4 and CDH13 on chromosome 16 contributing to daunorubicin cytotoxicity (Duan et al, 2007).…”

A Combined-Cross Analysis Reveals Genes With Drug-Specific and Background-Dependent Effects on Drug Sensitivity in Saccharomyces cerevisiae

“…Consequently, understanding the genetic basis of variable drug responses is important to both mitigating adverse drug reactions and developing new or improved pharmacological therapies. Although many pharmacogenetic variants have been identified from surveys of candidate genes and pathways (Katz and Bhathena 2009), there have been only a few studies that have conducted genomewide mapping (Dolan et al 2004;Watters et al 2004;Perlstein et al 2006;Duan et al 2007;Huang et al 2007;Kim and Fay 2007;Perlstein et al 2007;Bleibel et al 2009;Shukla et al 2009), and many of these have focused on chemotherapy-induced cytotoxicity in human lymphoblastoid cell lines, which in some instances may be susceptible to false-positive associations due to low repeatability (Choy et al 2008). Furthermore, identification of individual genes and their causal variants in human cell lines is a significant challenge.…”

Leveraging Lymphoblastoid Cell Lines for Drug Response Modeling

“…Several studies have used LCL models to functionally validate findings using knock-down experiments [15][16][17] and the advantages offered by these techniques are described in greater detail below.…”