Molecular description of evolving paclitaxel resistance in the SKOV-3 human ovarian carcinoma cell line.

Ovarian cancer is currently the most lethal gynecological malignancy in the United States. Although effective therapies exist, the acquisition of multidrug resistance within persisting tumor cells renders curative therapies elusive for the majority of women with ovarian cancer. In an attempt to better define the evolution of paclitaxel resistance, three SKOV-3 sublines were selected during successive rounds of exposure to increasing paclitaxel concentrations. The sublines were selected to represent early (0.003 micro M), intermediate (0.03 micro M), and late (0.3 micro M) paclitaxel resistance. RNA from these cell lines, SKOV-3(0.003TR), SKOV-3(0.03TR), and SKOV-3(0.3TR), as well as the parent cell line SKOV-3, was analyzed by cDNA array to evaluate transcript expression profiles. Arrays were performed using Affymetrix HG-U95Av2 arrays, which contain probes for approximately 9600 known human genes. Signal intensities were calculated by Microarray Suite 5.0 (Affymetrix, Santa Clara, CA). Expression patterns were analyzed by Affymetrix Data Mining Tool 3.0 with filtering of expression patterns for fold change in expression (maximum divided by minimum expression value/gene) and for variation of expression (maximum minus minimum expression value/gene). This analysis dismissed approximately 11,000 of approximately 12,000 expression patterns. The remaining approximately 1000 expression patterns were normalized and segregated into 20 partitions of a self-organizing map (SOM). The resulting SOM discriminates between genes, which are differentially expressed in early versus intermediate versus late paclitaxel resistance. For example, multidrug resistance 1 transcript expression is not elevated in SKOV-3(0.003TR) as compared with parental SKOV-3 but demonstrates elevated expression in SKOV-3(0.03TR) and SKOV-3(0.3TR). In contrast, SOM analysis demonstrates early (SKOV-3(0.003TR)) transcriptional changes in a wide variety of genes, including gene families involved in cell growth/maintenance, cell structure, signal transduction, and inflammatory response. The use of array analysis with SOMs in sublines with progressive paclitaxel resistance can successfully define an evolution of resistance. Such an analysis may be useful at defining candidate gene families involved in the early-drug resistance phenotype.

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