Gene copy number alterations and differential gene expression in the acquired resistance of ovarian cancer cells to taxanes

Abstract

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Ovarian cancer is the most common cause of death among women with gynecologic malignancies. Close to 75% of the patients have advanced-stage disease at diagnosis and are often characterized by rapid development of resistance to chemotherapy. In order to understand biological mechanisms underlying this behavior, we have developed a set of taxane-resistance models consisting of six parental ovarian cancer cell lines (A2780/1A9, ES-2, MES-OV, OVCA429, OVCA433 and OVCAR3) and 24 resistant variants exhibiting at least 10-fold resistance to either paclitaxel or docetaxel, selected with or without PSC, a modulator of P-glycoprotein. We hypothesized that the drug resistance phenotype depends on multiple changes in the transcriptional programs of resistant variants and the accumulation of numerous chromosomal alterations conferring selective advantages under drug pressure. High-resolution gene copy number and gene expression profiling were performed using a 42,000-element cDNA microarray platform. Parallel measures of gene copy number variation and gene expression were obtained for a total of 12,480 unique UniGene clusters. Gene copy number profiles were first transformed into regions of consistent gene copy number level using a recently developed circular binary segmentation algorithm (CBS) and deemed changed based on the reference distribution of multiple self-to-self hybridizations. The profiled cell lines exhibited numerous complex gene copy number aberrations, which is consistent with a high degree of aneuploidy in these tumors. The most common alterations include 1q, 3q, 8q, 17q and 20q. The global impact of gene copy number alterations on gene expression was first estimated using a linear regression model which indicated that at least 10% of all variation in gene expression among the analyzed cell lines is directly attributable to underlying variation in gene copy number. Since this relationship is likely to be much larger for a selected number of genes with higher biological importance, gene copy number and gene expression data were also integrated on a gene-by-gene level using signal-to-noise computation coupled with permutation testing. Gene expression profiles of 1,266 clones were found to be significantly associated with gene copy number alterations (q<0.05). These genes were then correlated with the taxane resistance phenotype using Significance Analysis of Microarrays (SAM), and 36 and 38 clones were found to be associated with P-gp and non-P-gp mediated drug resistance phenotypes, respectively (q<0.05). Finally, molecular interactions and potential functional relevance of identified genes were investigated using pathway analysis tools. Collectively, these observations provide a framework for future studies on the roles of genome instability and the accumulated genetic alterations in the development of chemoresistance.